From e6142d37fee619e3390cad6ebbac3e4260da2d76 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Angel=20Mart=C3=ADnez?= <76793458+AFMartinezF@users.noreply.github.com> Date: Tue, 15 Oct 2024 23:42:21 +0000 Subject: [PATCH 1/9] Fixed requirements.txt dependences --- requirements.txt | 7 +++++-- 1 file changed, 5 insertions(+), 2 deletions(-) diff --git a/requirements.txt b/requirements.txt index d1f71c12..30ba043f 100644 --- a/requirements.txt +++ b/requirements.txt @@ -1,2 +1,5 @@ -pandas==2.18.4 -sklearn==1.3.4 +#pandas==2.18.4 +#sklearn==1.3.4 +pandas==2.1.4 +scikit-learn==1.3.0 +flask==2.3.3 From 7693e77464d9e274204ad4b2784417d2df111c6f Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Angel=20Mart=C3=ADnez?= <76793458+AFMartinezF@users.noreply.github.com> Date: Wed, 16 Oct 2024 00:01:09 +0000 Subject: [PATCH 2/9] Added documentation, include confusion matrix visualization --- app.py | 30 +++++++- .../modelgeneration_27092023_ricalanis.ipynb | 71 +++++++++++-------- 2 files changed, 70 insertions(+), 31 deletions(-) diff --git a/app.py b/app.py index c27bed07..b9339fd8 100644 --- a/app.py +++ b/app.py @@ -4,15 +4,28 @@ import pandas as pd +# Cargar las características, el modelo y las equivalencias de columnas desde archivos creados con la libreria pickle FEATURES = pickle.load(open("churn/models/features.pk", "rb")) - model = pickle.load(open("churn/models/model.pk", "rb")) column_equivalence = pickle.load(open("churn/models/column_equivalence.pk", "rb")) -# create the Flask app + app = Flask(__name__) def convert_numerical(features): + """ + Función para convertir características en formato numérico. + + Si una característica es categórica, se reemplaza por su código numérico + utilizando el diccionario 'column_equivalence'. Si no es categórica, + se intenta convertir a valor numérico con pandas. Si falla, se coloca un 0. + + Parámetros: + features (list): Lista de características a convertir. + + Retorna: + list: Lista de características convertidas a formato numérico. + """ output = [] for i, feat in enumerate(features): if i in column_equivalence: @@ -26,6 +39,17 @@ def convert_numerical(features): @app.route('/query') def query_example(): + """ + Endpoint que recibe características en la URL, las convierte a formato numérico + y devuelve la predicción del modelo en formato JSON. + + Parámetros (GET): + feats: Cadena de características separadas por comas. + + Retorna: + JSON: Respuesta con la predicción del modelo. + """ + features = convert_numerical(request.args.get('feats').split(',')) response = { 'response': [int(x) for x in model.predict([features])] @@ -33,5 +57,5 @@ def query_example(): return json.dumps(response) if __name__ == '__main__': - # run app in debug mode on port 3001 + # Ejecutamos la aplicación Flask en modo debug en el puerto 3001 app.run(debug=True, port=3001) \ No newline at end of file diff --git a/notebooks/modelgeneration_27092023_ricalanis.ipynb b/notebooks/modelgeneration_27092023_ricalanis.ipynb index 78b5eed4..02072763 100644 --- a/notebooks/modelgeneration_27092023_ricalanis.ipynb +++ b/notebooks/modelgeneration_27092023_ricalanis.ipynb @@ -2,7 +2,7 @@ "cells": [ { "cell_type": "code", - "execution_count": 19, + "execution_count": 1, "id": "9de64c0d-889e-483d-9921-25cbe60cedf4", "metadata": {}, "outputs": [], @@ -24,7 +24,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": 3, "id": "45a2377a-c148-44d4-b936-800d57362bcb", "metadata": {}, "outputs": [], @@ -35,7 +35,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 4, "id": "e6e35832-17f4-43b3-adcc-5de303725f8d", "metadata": {}, "outputs": [ @@ -189,7 +189,7 @@ "4 79084.10 0 " ] }, - "execution_count": 21, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -200,7 +200,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 5, "id": "3da27622-b70d-45bb-9efb-bd94bd4fb0a7", "metadata": {}, "outputs": [], @@ -211,7 +211,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 6, "id": "c6519a08-642b-4ce3-8800-bfd80be89989", "metadata": {}, "outputs": [], @@ -219,20 +219,23 @@ "# Convertimos los datos en formato categorico, para más info: shorturl.at/y0269\n", "column_equivalence = {}\n", "features = list(data.columns)\n", + "# Iteramos sobre los tipos de datos de cada columna, convirtiéndolos a string para poder compararlos\n", "for i, column in enumerate(list([str(d) for d in data.dtypes])):\n", + " # Si la columna es de tipo 'object' (categoría o texto)\n", " if column == \"object\":\n", - " data[data.columns[i]] = data[data.columns[i]].fillna(data[data.columns[i]].mode())\n", - " categorical_column = data[data.columns[i]].astype(\"category\")\n", - " current_column_equivalence = dict(enumerate(categorical_column.cat.categories))\n", - " column_equivalence[i] = dict((v,k) for k,v in current_column_equivalence.items())\n", - " data[data.columns[i]] = categorical_column.cat.codes\n", + " data[data.columns[i]] = data[data.columns[i]].fillna(data[data.columns[i]].mode()) # Rellenamos valores nulos con el valor más frecuente (moda)\n", + " categorical_column = data[data.columns[i]].astype(\"category\") # Convertimos la columna a tipo 'category' (categoría de pandas)\n", + " current_column_equivalence = dict(enumerate(categorical_column.cat.categories)) # Diccionario que asocia índices numéricos a cada categoría\n", + " column_equivalence[i] = dict((v,k) for k,v in current_column_equivalence.items()) # Invertimos el diccionario\n", + " data[data.columns[i]] = categorical_column.cat.codes # Reemplazamos las categorías por sus códigos numéricos en la columna\n", + " # Si la columna no es de tipo 'object' (numérica u otro)\n", " else:\n", - " data[data.columns[i]] = data[data.columns[i]].fillna(data[data.columns[i]].median())" + " data[data.columns[i]] = data[data.columns[i]].fillna(data[data.columns[i]].median()) # Rellenamos valores nulos con la mediana de la columna" ] }, { "cell_type": "code", - "execution_count": 33, + "execution_count": 7, "id": "1d48b3b8-f48c-4340-8d77-93e35054ecaf", "metadata": {}, "outputs": [ @@ -242,7 +245,7 @@ "{1: {'France': 0, 'Germany': 1, 'Spain': 2}, 2: {'Female': 0, 'Male': 1}}" ] }, - "execution_count": 33, + "execution_count": 7, "metadata": {}, "output_type": "execute_result" } @@ -253,7 +256,7 @@ }, { "cell_type": "code", - "execution_count": 27, + "execution_count": 8, "id": "21e4ba90-1206-4ce6-bdc8-6986e6b93ef5", "metadata": {}, "outputs": [], @@ -265,7 +268,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 22, "id": "f45f3df3-bcbe-45f3-820c-82867e36d012", "metadata": {}, "outputs": [], @@ -277,7 +280,7 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 24, "id": "8a6ee78f-7c8b-4810-a763-c8b20155ec28", "metadata": {}, "outputs": [], @@ -288,48 +291,60 @@ }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 25, "id": "409f0391-4500-41fd-85a9-e501ecdd9329", "metadata": {}, "outputs": [], "source": [ "# Crear el modelo y entrenarlo\n", - "clf_lin = LogisticRegression(random_state=0, solver='lbfgs', multi_class='multinomial').fit(X, y)\n" + "clf_lin = LogisticRegression(random_state=0, solver='lbfgs', multi_class='multinomial').fit(X, y)" ] }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 30, "id": "753ab797-0b07-4e27-a497-9518034451a9", "metadata": {}, "outputs": [ { "data": { + "image/png": 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", "text/plain": [ - "array([[2599, 58],\n", - " [ 597, 46]])" + "
" ] }, - "execution_count": 31, "metadata": {}, - "output_type": "execute_result" + "output_type": "display_data" } ], "source": [ - "# Medir los resultados obtenidos\n", + "# Medir los resultados obtenidos usando una matriz de confusión\n", + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", "from sklearn.metrics import confusion_matrix\n", - "confusion_matrix(y_test, clf_lin.predict(X_test))\n" + "cm = confusion_matrix(y_test, clf_lin.predict(X_test))\n", + "\n", + "#Visualizar la matriz de confusión\n", + "plt.figure(figsize=(9,9))\n", + "plt.title('Confusion matrix')\n", + "sns.heatmap(cm, annot=True, fmt='g', linewidths=.5, square=True, cmap='coolwarm')\n", + "plt.ylabel('Actual label')\n", + "plt.xlabel('Predicted label')\n", + "plt.show()" ] }, { "cell_type": "code", - "execution_count": 32, + "execution_count": 31, "id": "20f25624-4ba7-4c0d-a79a-590d1884b7d0", "metadata": {}, "outputs": [], "source": [ "# Generar el binario del modelo para reutilizarlo, equivalencia de variables categoricas y caracteristicas del modelo\n", "import pickle\n", + "#Tener en cuenta esta nota de la documentación de Python\n", + "#\"Warning: The pickle module is not secure. Only unpickle data you trust.\"\n", + "\n", "pickle.dump(clf_lin, open(\"churn/models/model.pk\", \"wb\"))\n", "pickle.dump(column_equivalence, open(\"churn/models/column_equivalence.pk\", \"wb\"))\n", "pickle.dump(features, open(\"churn/models/features.pk\", \"wb\"))" @@ -352,7 +367,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.7.3" + "version": "3.12.1" } }, "nbformat": 4, From 85a13881d0b231856d8c87eb7da372e977ce9e98 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Angel=20Mart=C3=ADnez?= <76793458+AFMartinezF@users.noreply.github.com> Date: Wed, 16 Oct 2024 01:08:30 +0000 Subject: [PATCH 3/9] Added new metrics to evaluate the model --- .../modelgeneration_27092023_ricalanis.ipynb | 78 +++++++++++++++++-- 1 file changed, 73 insertions(+), 5 deletions(-) diff --git a/notebooks/modelgeneration_27092023_ricalanis.ipynb b/notebooks/modelgeneration_27092023_ricalanis.ipynb index 02072763..bbffdcd9 100644 --- a/notebooks/modelgeneration_27092023_ricalanis.ipynb +++ b/notebooks/modelgeneration_27092023_ricalanis.ipynb @@ -1,5 +1,13 @@ { "cells": [ + { + "cell_type": "markdown", + "id": "3dbce2b2", + "metadata": {}, + "source": [ + "## Análisis exploratorio de datos (EDA)" + ] + }, { "cell_type": "code", "execution_count": 1, @@ -254,6 +262,14 @@ "column_equivalence" ] }, + { + "cell_type": "markdown", + "id": "106c84df", + "metadata": {}, + "source": [ + "## Entrenamiento del modelo" + ] + }, { "cell_type": "code", "execution_count": 8, @@ -268,7 +284,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 9, "id": "f45f3df3-bcbe-45f3-820c-82867e36d012", "metadata": {}, "outputs": [], @@ -280,7 +296,7 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 10, "id": "8a6ee78f-7c8b-4810-a763-c8b20155ec28", "metadata": {}, "outputs": [], @@ -291,7 +307,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 11, "id": "409f0391-4500-41fd-85a9-e501ecdd9329", "metadata": {}, "outputs": [], @@ -300,9 +316,17 @@ "clf_lin = LogisticRegression(random_state=0, solver='lbfgs', multi_class='multinomial').fit(X, y)" ] }, + { + "cell_type": "markdown", + "id": "9dc2f9e7", + "metadata": {}, + "source": [ + "## Evaluación del modelo" + ] + }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 12, "id": "753ab797-0b07-4e27-a497-9518034451a9", "metadata": {}, "outputs": [ @@ -335,7 +359,51 @@ }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 21, + "id": "1e21c8b3", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Accuracy model: 0.802\n", + "Exited Churn='NO': 0.978\n", + "Exited Churn='YES': 0.072\n", + "F1 Score: 0.123\n" + ] + } + ], + "source": [ + "# Metricas de éxito propuestas para evaluar el modelo, en todas se busca un valor cercano a 1\n", + "from sklearn.metrics import accuracy_score, recall_score, f1_score\n", + "\n", + "# Predecir resultados con los datos de prueba\n", + "prediction_test = clf_lin.predict(X_test)\n", + "\n", + "# Exactitud: proporción de predicciones correctas.\n", + "print(f\"Accuracy model: {accuracy_score(y_test, prediction_test):.3f}\")\n", + "\n", + "# Sensibilidad: capacidad del modelo de identificar todas las muestras positivas para un label.\n", + "print(f\"Exited Churn='NO': {recall_score(y_test, prediction_test, pos_label=0):.3f}\")\n", + "print(f\"Exited Churn='YES': {recall_score(y_test, prediction_test, pos_label=1):.3f}\")\n", + "\n", + "# F1 Score: media armónica entre precisión y sensibilidad, nos da una mejor idea de que tan bien se comporta el modelo de forma global.\n", + "print(f\"F1 Score: {f1_score(y_test, prediction_test):.3f}\")\n", + "# En ocasiones, esta última metrica se usa en competiciones (Kaggle, DataDriven) para comparar modelos.\n" + ] + }, + { + "cell_type": "markdown", + "id": "8f3fabc9", + "metadata": {}, + "source": [ + "## Exportación con pickle" + ] + }, + { + "cell_type": "code", + "execution_count": 14, "id": "20f25624-4ba7-4c0d-a79a-590d1884b7d0", "metadata": {}, "outputs": [], From 03a0c12be910f7fa1d3695f5bbbd056acfde84ab Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Angel=20Mart=C3=ADnez?= <76793458+AFMartinezF@users.noreply.github.com> Date: Sun, 20 Oct 2024 16:50:42 +0000 Subject: [PATCH 4/9] Reordered files to follow cookiecutter data driven structure --- .gitignore | 172 + Makefile | 68 + app.py | 6 +- churn/.DS_Store | Bin 6148 -> 0 bytes churn/models/column_equivalence.pk | Bin 95 -> 0 bytes churn/models/features.pk | Bin 184 -> 0 bytes churn/models/model.pk | Bin 934 -> 0 bytes data/.DS_Store | Bin 6148 -> 0 bytes data/churn.csv | 10001 ---------------- docs/.gitkeep | 0 models/column_equivalence.pk | Bin 0 -> 81 bytes models/features.pk | Bin 0 -> 148 bytes models/model.pk | Bin 0 -> 1006 bytes ...ration_27092023_ricalanis-checkpoint.ipynb | 360 - .../modelgeneration_27092023_ricalanis.ipynb | 10 +- references/.gitkeep | 0 reports/.gitkeep | 0 reports/figures/.gitkeep | 0 18 files changed, 248 insertions(+), 10369 deletions(-) create mode 100644 .gitignore create mode 100644 Makefile delete mode 100644 churn/.DS_Store delete mode 100644 churn/models/column_equivalence.pk delete mode 100644 churn/models/features.pk delete mode 100644 churn/models/model.pk delete mode 100644 data/.DS_Store delete mode 100644 data/churn.csv create mode 100644 docs/.gitkeep create mode 100644 models/column_equivalence.pk create mode 100644 models/features.pk create mode 100644 models/model.pk delete mode 100644 notebooks/.ipynb_checkpoints/modelgeneration_27092023_ricalanis-checkpoint.ipynb create mode 100644 references/.gitkeep create mode 100644 reports/.gitkeep create mode 100644 reports/figures/.gitkeep diff --git a/.gitignore b/.gitignore new file mode 100644 index 00000000..a5df42ba --- /dev/null +++ b/.gitignore @@ -0,0 +1,172 @@ +# Data +/data/ + +# Mac OS-specific storage files +.DS_Store + +# vim +*.swp +*.swo + +## https://github.com/github/gitignore/blob/4488915eec0b3a45b5c63ead28f286819c0917de/Python.gitignore + +# Byte-compiled / optimized / DLL files +__pycache__/ +*.py[cod] +*$py.class + +# C extensions +*.so + +# Distribution / packaging +.Python +build/ +develop-eggs/ +dist/ +downloads/ +eggs/ +.eggs/ +lib/ +lib64/ +parts/ +sdist/ +var/ +wheels/ +share/python-wheels/ +*.egg-info/ +.installed.cfg +*.egg +MANIFEST + +# PyInstaller +# Usually these files are written by a python script from a template +# before PyInstaller builds the exe, so as to inject date/other infos into it. +*.manifest +*.spec + +# Installer logs +pip-log.txt +pip-delete-this-directory.txt + +# Unit test / coverage reports +htmlcov/ +.tox/ +.nox/ +.coverage +.coverage.* +.cache +nosetests.xml +coverage.xml +*.cover +*.py,cover +.hypothesis/ +.pytest_cache/ +cover/ + +# Translations +*.mo +*.pot + +# Django stuff: +*.log +local_settings.py +db.sqlite3 +db.sqlite3-journal + +# Flask stuff: +instance/ +.webassets-cache + +# Scrapy stuff: +.scrapy + +# MkDocs documentation +docs/site/ + +# PyBuilder +.pybuilder/ +target/ + +# Jupyter Notebook +.ipynb_checkpoints + +# IPython +profile_default/ +ipython_config.py + +# pyenv +# For a library or package, you might want to ignore these files since the code is +# intended to run in multiple environments; otherwise, check them in: +# .python-version + +# pipenv +# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control. +# However, in case of collaboration, if having platform-specific dependencies or dependencies +# having no cross-platform support, pipenv may install dependencies that don't work, or not +# install all needed dependencies. +#Pipfile.lock + +# poetry +# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control. +# This is especially recommended for binary packages to ensure reproducibility, and is more +# commonly ignored for libraries. +# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control +#poetry.lock + +# pdm +# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control. +#pdm.lock +# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it +# in version control. +# https://pdm.fming.dev/#use-with-ide +.pdm.toml + +# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm +__pypackages__/ + +# Celery stuff +celerybeat-schedule +celerybeat.pid + +# SageMath parsed files +*.sage.py + +# Environments +.env +.venv +env/ +venv/ +ENV/ +env.bak/ +venv.bak/ + +# Spyder project settings +.spyderproject +.spyproject + +# Rope project settings +.ropeproject + +# mkdocs documentation +/site + +# mypy +.mypy_cache/ +.dmypy.json +dmypy.json + +# Pyre type checker +.pyre/ + +# pytype static type analyzer +.pytype/ + +# Cython debug symbols +cython_debug/ + +# PyCharm +# JetBrains specific template is maintained in a separate JetBrains.gitignore that can +# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore +# and can be added to the global gitignore or merged into this file. For a more nuclear +# option (not recommended) you can uncomment the following to ignore the entire idea folder. +#.idea/ diff --git a/Makefile b/Makefile new file mode 100644 index 00000000..1a298e01 --- /dev/null +++ b/Makefile @@ -0,0 +1,68 @@ +################################################################################# +# GLOBALS # +################################################################################# + +PROJECT_NAME = Lab-ML-platzi +PYTHON_VERSION = 3.10 +PYTHON_INTERPRETER = python + +################################################################################# +# COMMANDS # +################################################################################# + + +## Install Python Dependencies +.PHONY: requirements +requirements: + $(PYTHON_INTERPRETER) -m pip install -U pip + $(PYTHON_INTERPRETER) -m pip install -r requirements.txt + + + + +## Delete all compiled Python files +.PHONY: clean +clean: + find . -type f -name "*.py[co]" -delete + find . -type d -name "__pycache__" -delete + +## Lint using flake8 and black (use `make format` to do formatting) +.PHONY: lint +lint: + flake8 logistic_regression + isort --check --diff --profile black logistic_regression + black --check --config pyproject.toml logistic_regression + +## Format source code with black +.PHONY: format +format: + black --config pyproject.toml logistic_regression + + + + + + +################################################################################# +# PROJECT RULES # +################################################################################# + + + +################################################################################# +# Self Documenting Commands # +################################################################################# + +.DEFAULT_GOAL := help + +define PRINT_HELP_PYSCRIPT +import re, sys; \ +lines = '\n'.join([line for line in sys.stdin]); \ +matches = re.findall(r'\n## (.*)\n[\s\S]+?\n([a-zA-Z_-]+):', lines); \ +print('Available rules:\n'); \ +print('\n'.join(['{:25}{}'.format(*reversed(match)) for match in matches])) +endef +export PRINT_HELP_PYSCRIPT + +help: + @$(PYTHON_INTERPRETER) -c "${PRINT_HELP_PYSCRIPT}" < $(MAKEFILE_LIST) diff --git a/app.py b/app.py index b9339fd8..56a669cb 100644 --- a/app.py +++ b/app.py @@ -5,9 +5,9 @@ # Cargar las características, el modelo y las equivalencias de columnas desde archivos creados con la libreria pickle -FEATURES = pickle.load(open("churn/models/features.pk", "rb")) -model = pickle.load(open("churn/models/model.pk", "rb")) -column_equivalence = pickle.load(open("churn/models/column_equivalence.pk", "rb")) +FEATURES = pickle.load(open("models/features.pk", "rb")) +model = pickle.load(open("models/model.pk", "rb")) +column_equivalence = pickle.load(open("models/column_equivalence.pk", "rb")) app = Flask(__name__) diff --git a/churn/.DS_Store b/churn/.DS_Store deleted file mode 100644 index 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-RowNumber,CustomerId,Surname,CreditScore,Geography,Gender,Age,Tenure,Balance,NumOfProducts,HasCrCard,IsActiveMember,EstimatedSalary,Exited -1,15634602,Hargrave,619,France,Female,42,2,0,1,1,1,101348.88,1 -2,15647311,Hill,608,Spain,Female,41,1,83807.86,1,0,1,112542.58,0 -3,15619304,Onio,502,France,Female,42,8,159660.8,3,1,0,113931.57,1 -4,15701354,Boni,699,France,Female,39,1,0,2,0,0,93826.63,0 -5,15737888,Mitchell,850,Spain,Female,43,2,125510.82,1,1,1,79084.1,0 -6,15574012,Chu,645,Spain,Male,44,8,113755.78,2,1,0,149756.71,1 -7,15592531,Bartlett,822,France,Male,50,7,0,2,1,1,10062.8,0 -8,15656148,Obinna,376,Germany,Female,29,4,115046.74,4,1,0,119346.88,1 -9,15792365,He,501,France,Male,44,4,142051.07,2,0,1,74940.5,0 -10,15592389,H?,684,France,Male,27,2,134603.88,1,1,1,71725.73,0 -11,15767821,Bearce,528,France,Male,31,6,102016.72,2,0,0,80181.12,0 -12,15737173,Andrews,497,Spain,Male,24,3,0,2,1,0,76390.01,0 -13,15632264,Kay,476,France,Female,34,10,0,2,1,0,26260.98,0 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-43,15687946,Osborne,556,France,Female,61,2,117419.35,1,1,1,94153.83,0 -44,15755196,Lavine,834,France,Female,49,2,131394.56,1,0,0,194365.76,1 -45,15684171,Bianchi,660,Spain,Female,61,5,155931.11,1,1,1,158338.39,0 -46,15754849,Tyler,776,Germany,Female,32,4,109421.13,2,1,1,126517.46,0 -47,15602280,Martin,829,Germany,Female,27,9,112045.67,1,1,1,119708.21,1 -48,15771573,Okagbue,637,Germany,Female,39,9,137843.8,1,1,1,117622.8,1 -49,15766205,Yin,550,Germany,Male,38,2,103391.38,1,0,1,90878.13,0 -50,15771873,Buccho,776,Germany,Female,37,2,103769.22,2,1,0,194099.12,0 -51,15616550,Chidiebele,698,Germany,Male,44,10,116363.37,2,1,0,198059.16,0 -52,15768193,Trevisani,585,Germany,Male,36,5,146050.97,2,0,0,86424.57,0 -53,15683553,O'Brien,788,France,Female,33,5,0,2,0,0,116978.19,0 -54,15702298,Parkhill,655,Germany,Male,41,8,125561.97,1,0,0,164040.94,1 -55,15569590,Yoo,601,Germany,Male,42,1,98495.72,1,1,0,40014.76,1 -56,15760861,Phillipps,619,France,Male,43,1,125211.92,1,1,1,113410.49,0 -57,15630053,Tsao,656,France,Male,45,5,127864.4,1,1,0,87107.57,0 -58,15647091,Endrizzi,725,Germany,Male,19,0,75888.2,1,0,0,45613.75,0 -59,15623944,T'ien,511,Spain,Female,66,4,0,1,1,0,1643.11,1 -60,15804771,Velazquez,614,France,Male,51,4,40685.92,1,1,1,46775.28,0 -61,15651280,Hunter,742,Germany,Male,35,5,136857,1,0,0,84509.57,0 -62,15773469,Clark,687,Germany,Female,27,9,152328.88,2,0,0,126494.82,0 -63,15702014,Jeffrey,555,Spain,Male,33,1,56084.69,2,0,0,178798.13,0 -64,15751208,Pirozzi,684,Spain,Male,56,8,78707.16,1,1,1,99398.36,0 -65,15592461,Jackson,603,Germany,Male,26,4,109166.37,1,1,1,92840.67,0 -66,15789484,Hammond,751,Germany,Female,36,6,169831.46,2,1,1,27758.36,0 -67,15696061,Brownless,581,Germany,Female,34,1,101633.04,1,1,0,110431.51,0 -68,15641582,Chibugo,735,Germany,Male,43,10,123180.01,2,1,1,196673.28,0 -69,15638424,Glauert,661,Germany,Female,35,5,150725.53,2,0,1,113656.85,0 -70,15755648,Pisano,675,France,Female,21,8,98373.26,1,1,0,18203,0 -71,15703793,Konovalova,738,Germany,Male,58,2,133745.44,4,1,0,28373.86,1 -72,15620344,McKee,813,France,Male,29,6,0,1,1,0,33953.87,0 -73,15812518,Palermo,657,Spain,Female,37,0,163607.18,1,0,1,44203.55,0 -74,15779052,Ballard,604,Germany,Female,25,5,157780.84,2,1,1,58426.81,0 -75,15770811,Wallace,519,France,Male,36,9,0,2,0,1,145562.4,0 -76,15780961,Cavenagh,735,France,Female,21,1,178718.19,2,1,0,22388,0 -77,15614049,Hu,664,France,Male,55,8,0,2,1,1,139161.64,0 -78,15662085,Read,678,France,Female,32,9,0,1,1,1,148210.64,0 -79,15575185,Bushell,757,Spain,Male,33,5,77253.22,1,0,1,194239.63,0 -80,15803136,Postle,416,Germany,Female,41,10,122189.66,2,1,0,98301.61,0 -81,15706021,Buley,665,France,Female,34,1,96645.54,2,0,0,171413.66,0 -82,15663706,Leonard,777,France,Female,32,2,0,1,1,0,136458.19,1 -83,15641732,Mills,543,France,Female,36,3,0,2,0,0,26019.59,0 -84,15701164,Onyeorulu,506,France,Female,34,4,90307.62,1,1,1,159235.29,0 -85,15738751,Beit,493,France,Female,46,4,0,2,1,0,1907.66,0 -86,15805254,Ndukaku,652,Spain,Female,75,10,0,2,1,1,114675.75,0 -87,15762418,Gant,750,Spain,Male,22,3,121681.82,1,1,0,128643.35,1 -88,15625759,Rowley,729,France,Male,30,9,0,2,1,0,151869.35,0 -89,15622897,Sharpe,646,France,Female,46,4,0,3,1,0,93251.42,1 -90,15767954,Osborne,635,Germany,Female,28,3,81623.67,2,1,1,156791.36,0 -91,15757535,Heap,647,Spain,Female,44,5,0,3,1,1,174205.22,1 -92,15731511,Ritchie,808,France,Male,45,7,118626.55,2,1,0,147132.46,0 -93,15809248,Cole,524,France,Female,36,10,0,2,1,0,109614.57,0 -94,15640635,Capon,769,France,Male,29,8,0,2,1,1,172290.61,0 -95,15676966,Capon,730,Spain,Male,42,4,0,2,0,1,85982.47,0 -96,15699461,Fiorentini,515,Spain,Male,35,10,176273.95,1,0,1,121277.78,0 -97,15738721,Graham,773,Spain,Male,41,9,102827.44,1,0,1,64595.25,0 -98,15693683,Yuille,814,Germany,Male,29,8,97086.4,2,1,1,197276.13,0 -99,15604348,Allard,710,Spain,Male,22,8,0,2,0,0,99645.04,0 -100,15633059,Fanucci,413,France,Male,34,9,0,2,0,0,6534.18,0 -101,15808582,Fu,665,France,Female,40,6,0,1,1,1,161848.03,0 -102,15743192,Hung,623,France,Female,44,6,0,2,0,0,167162.43,0 -103,15580146,Hung,738,France,Male,31,9,82674.15,1,1,0,41970.72,0 -104,15776605,Bradley,528,Spain,Male,36,7,0,2,1,0,60536.56,0 -105,15804919,Dunbabin,670,Spain,Female,65,1,0,1,1,1,177655.68,1 -106,15613854,Mauldon,622,Spain,Female,46,4,107073.27,2,1,1,30984.59,1 -107,15599195,Stiger,582,Germany,Male,32,1,88938.62,1,1,1,10054.53,0 -108,15812878,Parsons,785,Germany,Female,36,2,99806.85,1,0,1,36976.52,0 -109,15602312,Walkom,605,Spain,Male,33,5,150092.8,1,0,0,71862.79,0 -110,15744689,T'ang,479,Germany,Male,35,9,92833.89,1,1,0,99449.86,1 -111,15803526,Eremenko,685,Germany,Male,30,3,90536.81,1,0,1,63082.88,0 -112,15665790,Rowntree,538,Germany,Male,39,7,108055.1,2,1,0,27231.26,0 -113,15715951,Thorpe,562,France,Male,42,2,100238.35,1,0,0,86797.41,0 -114,15591100,Chiemela,675,Spain,Male,36,9,106190.55,1,0,1,22994.32,0 -115,15609618,Fanucci,721,Germany,Male,28,9,154475.54,2,0,1,101300.94,1 -116,15675522,Ko,628,Germany,Female,30,9,132351.29,2,1,1,74169.13,0 -117,15705512,Welch,668,Germany,Female,37,6,167864.4,1,1,0,115638.29,0 -118,15698028,Duncan,506,France,Female,41,1,0,2,1,0,31766.3,0 -119,15661670,Chidozie,524,Germany,Female,31,8,107818.63,1,1,0,199725.39,1 -120,15600781,Wu,699,Germany,Male,34,4,185173.81,2,1,0,120834.48,0 -121,15682472,Culbreth,828,France,Male,34,8,129433.34,2,0,0,38131.77,0 -122,15580203,Kennedy,674,Spain,Male,39,6,120193.42,1,0,0,100130.95,0 -123,15690673,Cameron,656,France,Female,39,6,0,2,1,0,141069.88,0 -124,15760085,Calabresi,684,Germany,Female,48,10,126384.42,1,1,1,198129.36,0 -125,15779659,Zetticci,625,France,Female,28,3,0,1,0,0,183646.41,0 -126,15627360,Fuller,432,France,Male,42,9,152603.45,1,1,0,110265.24,1 -127,15671137,MacDonald,549,France,Female,52,1,0,1,0,1,8636.05,1 -128,15782688,Piccio,625,Germany,Male,56,0,148507.24,1,1,0,46824.08,1 -129,15575492,Kennedy,828,France,Female,41,7,0,2,1,0,171378.77,0 -130,15591607,Fernie,770,France,Male,24,9,101827.07,1,1,0,167256.35,0 -131,15740404,He,758,France,Female,34,3,0,2,1,1,124226.16,0 -132,15718369,Kaodilinakachukwu,795,Germany,Female,33,9,130862.43,1,1,1,114935.21,0 -133,15677871,Cocci,687,France,Male,38,9,122570.87,1,1,1,35608.88,0 -134,15642004,Alekseeva,686,France,Male,25,1,0,2,0,1,16459.37,0 -135,15712543,Chinweike,789,Germany,Male,39,7,124828.46,2,1,1,124411.08,0 -136,15584518,Arthur,589,Germany,Female,50,5,144895.05,2,1,1,34941.23,0 -137,15802381,Li,461,Germany,Female,34,5,63663.93,1,0,1,167784.28,0 -138,15610156,Ma,637,France,Male,40,2,133463.1,1,0,1,93165.34,0 -139,15594408,Chia,584,Spain,Female,48,2,213146.2,1,1,0,75161.25,1 -140,15640905,Vasin,579,Spain,Female,35,1,129490.36,2,0,1,8590.83,1 -141,15698932,Groves,756,Germany,Male,44,10,137452.09,1,1,0,189543.9,0 -142,15724944,Tien,663,France,Male,34,7,0,2,1,1,180427.24,0 -143,15628145,Forwood,682,France,Female,43,5,125851.93,1,1,1,193318.33,0 -144,15713483,Greeves,793,Spain,Male,52,2,0,1,1,0,159123.82,1 -145,15612350,Taylor,691,France,Female,31,5,40915.55,1,1,0,126213.84,1 -146,15800703,Madukwe,485,Spain,Female,21,5,113157.22,1,1,1,54141.5,0 -147,15705707,Bennelong,635,Spain,Female,29,8,138296.94,2,1,0,141075.51,0 -148,15754105,Olisanugo,650,France,Male,37,5,106967.18,1,0,0,24495.03,0 -149,15703264,Chukwufumnanya,735,France,Male,44,9,120681.63,1,1,0,74836.34,0 -150,15794413,Harris,416,France,Male,32,0,0,2,0,1,878.87,0 -151,15650237,Morgan,754,Spain,Female,32,7,0,2,1,0,89520.75,0 -152,15759618,Alexeeva,535,France,Female,48,9,0,1,1,0,149892.79,1 -153,15811589,Metcalfe,716,Spain,Male,42,8,0,2,1,0,180800.42,0 -154,15689044,Humphries,539,France,Male,37,2,127609.59,1,1,0,98646.22,0 -155,15709368,Milne,614,France,Female,43,6,0,2,1,1,109041.53,0 -156,15679145,Chou,706,Spain,Male,57,7,0,1,1,0,17941.16,1 -157,15655007,Li,758,France,Female,33,7,0,2,0,0,82996.47,0 -158,15623595,Clayton,586,Spain,Female,28,2,0,2,1,1,92067.35,0 -159,15589975,Maclean,646,France,Female,73,6,97259.25,1,0,1,104719.66,0 -160,15804017,Chigolum,631,Germany,Female,33,4,123246.7,1,0,0,112687.57,0 -161,15692132,Wilkinson,717,Spain,Female,22,6,101060.25,1,0,1,84699.56,0 -162,15641122,Wei,684,France,Male,30,2,0,2,1,0,83473.82,0 -163,15630910,Treacy,800,France,Female,49,7,108007.36,1,0,0,47125.11,0 -164,15680772,Hu,721,Spain,Female,36,2,0,2,1,1,106977.8,0 -165,15658929,Taverner,683,Spain,Male,29,0,133702.89,1,1,0,55582.54,1 -166,15585388,Sherman,660,Germany,Male,31,9,125189.75,2,1,1,139874.43,0 -167,15724623,Taubman,704,Germany,Female,24,7,113034.22,1,1,0,162503.48,1 -168,15588537,Robinson,615,Spain,Female,41,9,109013.23,1,1,0,196499.96,0 -169,15574692,Pinto,667,Spain,Female,39,2,0,2,1,0,40721.24,1 -170,15611325,Wood,682,Germany,Male,24,9,57929.81,2,0,0,53134.3,0 -171,15587562,Hawkins,484,France,Female,29,4,130114.39,1,1,0,164017.89,0 -172,15613172,Sun,628,Germany,Male,27,5,95826.49,2,1,0,155996.96,0 -173,15651022,Yost,480,Germany,Male,44,10,129608.57,1,1,0,5472.7,1 -174,15586310,Ting,578,France,Male,30,4,169462.09,1,1,0,112187.11,0 -175,15625524,Rowe,512,France,Male,40,5,0,2,1,1,146457.83,0 -176,15755209,Fu,484,Spain,Female,35,7,133868.21,1,1,1,27286.1,0 -177,15645248,Ho,510,France,Female,30,0,0,2,1,1,130553.47,0 -178,15790355,Okechukwu,606,Germany,Male,36,5,190479.48,2,0,0,179351.89,0 -179,15762615,Campbell,597,Spain,Female,40,8,101993.12,1,0,1,94774.12,0 -180,15625426,Ashbolt,754,Germany,Female,55,3,161608.81,1,1,0,8080.85,1 -181,15716334,Rozier,850,Spain,Female,45,2,122311.21,1,1,1,19482.5,0 -182,15789669,Hsia,510,France,Male,65,2,0,2,1,1,48071.61,0 -183,15621075,Ogbonnaya,778,Germany,Female,45,1,162150.42,2,1,0,174531.27,0 -184,15810845,T'ang,636,France,Male,42,2,0,2,1,1,55470.78,0 -185,15719377,Cocci,804,France,Female,50,4,0,1,1,1,8546.87,1 -186,15654506,Chang,514,France,Male,32,8,0,2,1,0,95857.18,0 -187,15771977,T'ao,730,France,Female,39,1,99010.67,1,1,0,194945.8,0 -188,15708710,Ford,525,Spain,Female,37,0,0,1,0,1,131521.72,0 -189,15726676,Marshall,616,Spain,Male,30,5,0,2,0,1,196108.51,0 -190,15587421,Tsai,687,Germany,Female,34,7,111388.18,2,1,0,148564.76,0 -191,15726931,Onwumelu,715,France,Female,41,8,56214.85,2,0,0,92982.61,1 -192,15771086,Graham,512,France,Female,36,3,84327.77,2,1,0,17675.36,0 -193,15756850,Golovanov,479,France,Male,40,1,0,2,0,0,114996.43,0 -194,15702741,Potts,601,France,Male,32,8,93012.89,1,1,0,86957.42,0 -195,15679200,Crawford,580,Spain,Male,29,9,61710.44,2,1,0,128077.8,0 -196,15594815,Aleshire,807,France,Male,35,3,174790.15,1,1,1,600.36,0 -197,15635905,Moran,616,Spain,Female,32,6,0,2,1,1,43001.46,0 -198,15777892,Samsonova,721,Germany,Male,37,3,107720.64,1,1,1,158591.12,0 -199,15656176,Jenkins,501,France,Male,57,10,0,2,1,1,47847.19,0 -200,15811127,Volkov,521,France,Male,35,6,96423.84,1,1,0,10488.44,0 -201,15604482,Chiemezie,850,Spain,Male,30,2,141040.01,1,1,1,5978.2,0 -202,15622911,Jude,759,France,Male,42,4,105420.18,1,0,1,121409.06,0 -203,15600974,He,516,Spain,Male,50,5,0,1,0,1,146145.93,1 -204,15727868,Onuora,711,France,Female,38,2,129022.06,2,1,1,14374.86,1 -205,15627801,Ginikanwa,512,Spain,Male,33,3,176666.62,1,1,0,94670.77,0 -206,15773039,Ku,550,France,Male,37,3,0,1,1,1,179670.31,0 -207,15755262,McDonald,608,Spain,Female,41,3,89763.84,1,0,0,199304.74,1 -208,15679531,Collins,618,France,Male,34,5,134954.53,1,1,1,151954.39,0 -209,15684181,Hackett,643,France,Male,45,5,0,1,1,0,142513.5,1 -210,15612087,Dike,671,France,Male,45,2,106376.85,1,0,1,158264.62,0 -211,15752047,Trevisano,689,Germany,Male,33,2,161814.64,2,1,0,169381.9,0 -212,15624592,Tan,603,France,Male,31,8,0,2,1,1,169915.02,0 -213,15573152,Glassman,620,France,Female,41,9,0,2,0,0,88852.47,0 -214,15594917,Miller,676,France,Female,34,1,63095.01,1,1,1,40645.81,0 -215,15785542,Kornilova,572,Germany,Male,26,4,118287.01,2,0,0,60427.3,0 -216,15723488,Watson,668,Germany,Male,47,7,106854.21,1,0,1,157959.02,1 -217,15680920,Marchesi,695,France,Male,46,7,49512.55,1,1,0,133007.34,0 -218,15786308,Millar,730,Spain,Female,33,9,0,2,0,0,176576.62,0 -219,15659366,Shih,807,France,Male,43,1,105799.32,2,1,0,34888.04,1 -220,15774854,Fuller,592,France,Male,54,8,0,1,1,1,28737.71,1 -221,15725311,Hay,726,France,Female,31,9,114722.05,2,1,1,98178.57,0 -222,15787155,Yang,514,Spain,Male,30,7,0,1,0,1,125010.24,0 -223,15727829,McIntyre,567,France,Male,42,2,0,2,1,1,167984.61,0 -224,15733247,Stevenson,850,France,Male,33,10,0,1,1,0,4861.72,1 -225,15568748,Poole,671,Germany,Male,45,6,99564.22,1,1,1,108872.45,1 -226,15699029,Bagley,670,France,Male,37,4,170557.91,2,1,0,198252.88,0 -227,15774393,Ch'ien,694,France,Female,30,9,0,2,1,1,26960.31,0 -228,15676895,Cattaneo,547,Germany,Female,39,6,74596.15,3,1,1,85746.52,1 -229,15637753,O'Sullivan,751,Germany,Male,50,2,96888.39,1,1,0,77206.25,1 -230,15605461,Lucas,594,Germany,Female,29,3,130830.22,1,1,0,61048.53,0 -231,15808473,Ringrose,673,France,Male,72,1,0,2,0,1,111981.19,0 -232,15627000,Freeman,610,France,Male,40,0,0,2,1,0,62232.6,0 -233,15787174,Sergeyev,512,France,Female,37,1,0,2,0,1,156105.03,0 -234,15723886,Fiore,767,Germany,Male,20,3,119714.25,2,0,1,150135.38,0 -235,15704769,Smith,585,France,Female,67,5,113978.97,2,0,1,93146.11,0 -236,15772896,Dumetochukwu,763,Germany,Male,42,6,100160.75,1,1,0,33462.94,1 -237,15711540,Pacheco,712,France,Female,29,2,0,1,1,1,144375,0 -238,15764866,Synnot,539,Germany,Female,43,3,116220.5,3,1,0,55803.96,1 -239,15794056,Johnston,668,France,Female,46,2,0,3,1,0,89048.46,1 -240,15795149,Stevens,703,France,Male,28,2,81173.83,2,0,1,162812.16,0 -241,15812009,Grant,662,Spain,Male,38,4,0,2,1,0,136259.65,0 -242,15651001,Tsao,725,Germany,Female,39,5,116803.8,1,1,0,124052.97,0 -243,15813844,Barnes,703,France,Male,37,8,105961.68,2,0,1,74158.8,0 -244,15596175,McIntosh,659,Germany,Male,67,6,117411.6,1,1,1,45071.09,1 -245,15576269,Madison,523,Spain,Male,34,7,0,2,1,0,62030.06,0 -246,15797219,Ifesinachi,635,France,Female,40,10,123497.58,1,1,0,131953.23,1 -247,15685500,Glazkov,772,Germany,Male,26,7,152400.51,2,1,0,79414,0 -248,15599792,Dimauro,545,France,Female,26,1,0,2,1,1,199638.56,0 -249,15657566,Wieck,634,Germany,Male,24,8,103097.85,1,1,1,157577.29,0 -250,15772423,Liao,739,Germany,Male,54,8,126418.14,1,1,0,134420.75,1 -251,15628112,Hughes,771,Germany,Female,36,5,77846.9,1,0,0,99805.99,0 -252,15753754,Morrison,587,Spain,Female,34,1,0,2,1,1,97932.68,0 -253,15793726,Matveyeva,681,France,Female,79,0,0,2,0,1,170968.99,0 -254,15694717,Ku,544,Germany,Male,37,2,79731.91,1,1,1,57558.95,0 -255,15665834,Cheatham,696,Spain,Male,28,8,0,1,0,0,176713.47,0 -256,15765297,Yao,766,Spain,Male,41,0,0,2,0,1,34283.23,0 -257,15636684,Kirkland,727,France,Male,34,10,0,2,1,1,198637.34,0 -258,15592979,Rose,671,Germany,Female,34,6,37266.67,2,0,0,156917.12,0 -259,15750803,Jess,693,France,Female,30,6,127992.25,1,1,1,50457.2,0 -260,15607178,Welch,850,Germany,Male,38,3,54901.01,1,1,1,140075.55,0 -261,15713853,Ifeajuna,732,Germany,Male,42,9,108748.08,2,1,1,65323.11,0 -262,15673481,Morton,726,Spain,Female,48,6,99906.19,1,1,0,64323.24,0 -263,15686776,Rossi,557,France,Female,32,6,184686.41,2,1,0,14956.44,0 -264,15673693,Reppert,682,France,Female,26,0,110654.02,1,0,1,111879.21,0 -265,15700696,Kang,738,Spain,Male,31,9,79019.8,1,1,1,18606.23,0 -266,15813163,Ch'iu,531,Spain,Female,36,9,99240.51,1,1,0,123137.01,0 -267,15653857,Wallis,498,France,Male,34,2,0,2,1,1,148528.24,0 -268,15777076,Clark,651,France,Male,36,7,0,2,1,0,13898.31,0 -269,15717398,Fielding,549,Spain,Female,39,7,0,1,0,0,81259.25,1 -270,15799217,Zetticci,791,Germany,Female,35,7,52436.2,1,1,0,161051.75,0 -271,15787071,Dulhunty,650,Spain,Male,41,9,0,2,0,1,191599.67,0 -272,15619955,Bevington,733,Germany,Male,34,3,100337.96,3,1,0,48559.19,1 -273,15796505,Boyle,811,Germany,Female,34,1,149297.19,2,1,1,186339.74,0 -274,15725166,Newton,707,France,Male,30,8,0,2,1,0,33159.37,0 -275,15800116,Bowman,712,Germany,Male,28,4,145605.44,1,0,1,93883.53,0 -276,15758685,Dubinina,706,Spain,Female,37,7,0,2,1,1,110899.3,0 -277,15694456,Toscani,756,France,Male,62,3,0,1,1,1,11199.04,1 -278,15767339,Chiazagomekpere,777,France,Female,53,10,0,2,1,0,189992.97,0 -279,15683562,Allen,646,France,Male,35,6,84026.86,1,0,1,164255.69,0 -280,15782210,K'ung,714,France,Male,46,1,0,1,1,0,152167.79,1 -281,15668893,Wilsmore,782,France,Male,39,8,0,2,1,1,33949.67,0 -282,15669169,Hargreaves,775,Spain,Male,29,10,0,2,1,1,68143.93,0 -283,15643024,Huang,479,Germany,Male,35,4,138718.92,1,1,1,47251.79,1 -284,15699389,Ch'ien,807,France,Male,42,7,118274.71,1,1,1,25885.72,0 -285,15708608,Wallwork,799,France,Female,22,8,174185.98,2,0,1,192633.85,0 -286,15626144,Chu,675,France,Male,40,7,113208.86,2,1,0,34577.36,0 -287,15573112,Kang,602,Spain,Male,29,5,103907.28,1,1,0,161229.84,0 -288,15790678,Davidson,475,France,Female,32,8,119023.28,1,1,0,100816.29,0 -289,15727556,O'Donnell,744,Spain,Female,26,5,166297.89,1,1,1,181694.44,0 -290,15697307,Nnachetam,588,Spain,Male,34,10,0,2,1,0,79078.91,0 -291,15652266,Chidiebele,703,Germany,Male,42,9,63227,1,0,1,137316.32,0 -292,15607098,Ahmed,747,Spain,Female,41,5,94521.17,2,1,0,194926.86,0 -293,15655774,Booth,583,France,Male,27,7,0,2,1,0,51285.49,0 -294,15590241,Chuang,750,Spain,Female,34,9,112822.26,1,0,0,150401.53,1 -295,15785819,Shao,681,France,Male,38,3,0,2,1,1,112491.96,0 -296,15723654,Tsao,773,France,Male,25,2,135903.33,1,1,0,73656.38,0 -297,15774510,Tien,714,France,Female,31,4,125169.26,1,1,1,106636.89,0 -298,15684173,Chang,687,Spain,Female,44,7,0,3,1,0,155853.52,1 -299,15650068,Johnson,511,France,Male,58,0,149117.31,1,1,1,162599.51,0 -300,15811490,French,627,France,Male,33,5,0,2,1,1,103737.82,0 -301,15803976,Efremov,694,France,Female,31,10,0,2,1,0,160990.27,0 -302,15682541,Hartley,616,Spain,Female,36,6,132311.71,1,0,0,15462.84,0 -303,15695699,Calabrese,687,France,Male,35,8,0,2,1,0,10334.05,0 -304,15624188,Chiu,712,France,Female,33,6,0,2,1,1,190686.16,0 -305,15812191,Brennan,553,France,Male,33,4,118082.89,1,0,0,94440.45,0 -306,15636673,Onwuatuegwu,667,France,Male,31,1,119266.69,1,1,1,28257.63,0 -307,15594898,Hewitt,731,France,Male,43,2,0,1,1,1,170034.95,1 -308,15660211,Shih,629,Germany,Male,35,7,156847.29,2,1,0,31824.29,0 -309,15773972,Balashov,614,France,Male,50,4,137104.47,1,1,0,127166.49,1 -310,15746726,Doyle,438,Germany,Male,31,8,78398.69,1,1,0,44937.01,0 -311,15712287,Pokrovskii,652,France,Female,80,4,0,2,1,1,188603.07,0 -312,15702919,Collins,729,Germany,Male,30,6,63669.42,1,1,0,145111.37,0 -313,15674398,Russo,642,France,Male,38,3,0,2,0,0,171463.83,0 -314,15797960,Skinner,806,Germany,Female,59,0,135296.33,1,1,0,182822.5,0 -315,15631868,Robertson,744,Spain,Male,36,2,153804.44,1,1,1,87213.33,0 -316,15581539,Atkinson,474,Spain,Male,37,3,0,2,0,0,57175.32,0 -317,15662736,Doyle,559,France,Male,49,2,147069.78,1,1,0,120540.83,1 -318,15666252,Ritchie,706,Spain,Male,42,9,0,2,1,1,28714.34,0 -319,15677512,McEncroe,628,Spain,Female,22,3,0,1,1,0,85426.28,0 -320,15626114,Pearson,429,France,Male,24,4,95741.75,1,1,0,46170.75,0 -321,15810834,Gordon,525,Spain,Female,57,2,145965.33,1,1,1,64448.36,0 -322,15678910,Ts'ai,680,France,Female,30,8,141441.75,1,1,1,16278.97,0 -323,15694408,Lung,749,France,Male,40,1,139290.41,1,1,0,182855.42,1 -324,15585215,Yuan,763,France,Female,31,4,0,2,0,0,50404.72,0 -325,15682757,Pardey,734,France,Male,30,3,0,2,1,0,107640.25,0 -326,15736601,Tai,716,France,Male,35,4,144428.87,1,1,0,134132.65,0 -327,15601848,Scott,594,France,Male,35,2,0,2,1,0,103480.69,0 -328,15736008,Hunter,644,France,Female,46,9,95441.27,1,1,0,108761.05,1 -329,15669064,Mazzanti,671,Germany,Male,35,1,144848.74,1,1,1,179012.3,0 -330,15624528,L?,664,Germany,Male,26,7,116244.14,2,1,1,95145.14,0 -331,15598493,Beach,656,France,Male,50,7,0,2,0,1,72143.44,0 -332,15601274,Hsieh,667,Spain,Female,40,1,146502.07,1,1,0,19162.89,0 -333,15702669,Faulkner,663,Germany,Male,44,2,117028.6,2,0,1,144680.18,0 -334,15728669,Knowles,584,Germany,Female,30,8,112013.81,1,1,0,177772.03,1 -335,15742668,Day,626,Spain,Female,37,6,108269.37,1,1,0,5597.94,0 -336,15697441,Hsueh,485,France,Male,29,7,182123.79,1,1,0,116828.51,1 -337,15740476,Tsao,659,Germany,Female,32,3,150923.74,2,0,1,174652.51,0 -338,15648064,Kennedy,649,France,Male,33,2,0,2,1,0,2010.98,0 -339,15636624,Nwabugwu,805,Spain,Female,39,5,165272.13,1,1,0,14109.85,1 -340,15807923,Young,716,Germany,Female,39,10,115301.31,1,1,0,43527.4,1 -341,15745844,Kerr,642,Germany,Female,40,6,129502.49,2,0,1,86099.23,1 -342,15786170,Tien,659,France,Male,31,4,118342.26,1,0,0,161574.19,0 -343,15681081,Marrero,545,Spain,Female,47,5,0,2,1,1,38970.14,0 -344,15684484,White,543,France,Male,22,8,0,2,0,0,127587.22,0 -345,15785869,Pisano,718,France,Female,25,7,0,2,1,0,30380.12,0 -346,15763859,Brown,840,France,Female,43,7,0,2,1,0,90908.95,0 -347,15658935,Freeman,630,Germany,Female,34,9,106937.05,2,1,0,138275.01,0 -348,15747358,Russell,643,Germany,Male,59,3,170331.37,1,1,1,32171.79,0 -349,15735203,Seleznyov,654,Germany,Female,32,1,114510.85,1,1,1,126143.23,0 -350,15576256,Yusupova,582,France,Male,39,5,0,2,1,1,129892.93,0 -351,15659420,Foley,659,Spain,Male,32,3,107594.11,2,1,1,102416.84,0 -352,15593365,Shih,762,Spain,Male,39,2,81273.13,1,1,1,18719.67,0 -353,15777352,Ikedinachukwu,568,Spain,Female,32,7,169399.6,1,1,0,61936.22,0 -354,15812007,Power,670,Spain,Male,25,6,0,2,1,1,78358.94,0 -355,15625461,Amos,613,France,Female,45,1,187841.99,2,1,1,147224.27,0 -356,15739438,Reed,539,France,Male,30,0,0,2,1,0,160979.66,0 -357,15611759,Simmons,850,Spain,Female,57,8,126776.3,2,1,1,132298.49,0 -358,15661629,Ricci,522,Spain,Male,34,9,126436.29,1,1,0,174248.52,1 -359,15633950,Yen,737,France,Male,41,1,101960.74,1,1,1,123547.28,0 -360,15592386,Campbell,520,France,Male,58,3,0,2,0,1,32790.02,0 -361,15803716,West,706,Spain,Male,28,3,0,2,0,1,181543.67,0 -362,15696674,Robinson,643,Germany,Female,45,2,150842.93,1,0,1,2319.96,1 -363,15706365,Bianchi,648,France,Female,50,9,102535.57,1,1,1,189543.19,0 -364,15745088,Chen,443,Germany,Female,29,9,99027.61,2,1,0,10940.4,0 -365,15676715,Madukaego,640,France,Male,68,9,0,2,1,1,199493.38,0 -366,15613085,Ibrahimova,628,Spain,Female,33,3,0,1,1,1,188193.25,0 -367,15633537,Nolan,540,Germany,Female,42,9,87271.41,2,1,0,172572.64,0 -368,15594720,Scott,460,Germany,Female,35,8,102742.91,2,1,1,189339.6,0 -369,15684042,Blair,636,Germany,Male,34,2,40105.51,2,0,1,53512.16,0 -370,15583303,Monaldo,593,France,Female,29,2,152265.43,1,1,0,34004.44,0 -371,15611579,Sutherland,801,Spain,Male,42,4,141947.67,1,1,1,10598.29,0 -372,15774696,Cole,640,Germany,Female,75,1,106307.91,2,0,1,113428.77,0 -373,15694506,Briggs,611,Germany,Male,31,0,107884.81,2,1,1,183487.98,0 -374,15688074,Gregory,802,Germany,Male,31,1,125013.72,1,1,1,187658.09,0 -375,15759537,Bianchi,717,Germany,Male,35,7,58469.37,2,1,1,172459.39,0 -376,15758449,Angelo,769,France,Female,39,8,0,1,0,1,21016,0 -377,15583456,Gardiner,745,Germany,Male,45,10,117231.63,3,1,1,122381.02,1 -378,15667871,Kerr,572,Spain,Male,35,4,152390.26,1,1,0,128123.66,0 -379,15677371,Ko,629,Spain,Female,30,2,34013.63,1,1,0,19570.63,0 -380,15629677,Distefano,687,Spain,Female,39,2,0,3,0,0,188150.6,1 -381,15713578,Farrell,483,France,Female,50,9,0,2,1,1,111020.24,0 -382,15591509,Milano,690,France,Male,36,7,101583.11,2,1,0,123775.15,0 -383,15568240,Ting,492,Germany,Female,30,10,77168.87,2,0,1,146700.22,0 -384,15622993,Boyd,709,Germany,Male,28,8,124695.72,2,1,0,145251.35,0 -385,15689294,Onyemaechi,705,Germany,Male,44,3,105934.96,1,1,0,82463.69,0 -386,15720910,Black,560,France,Female,66,9,0,1,1,1,15928.49,0 -387,15721181,Oliver,611,Spain,Male,46,6,0,2,1,0,45886.33,0 -388,15776433,Greco,730,Spain,Male,62,2,0,2,1,1,186489.95,0 -389,15748936,Whitehead,709,Spain,Female,45,2,0,2,0,1,162922.65,0 -390,15717225,Ikemefuna,544,France,Female,21,10,161525.96,2,1,0,9262.77,0 -391,15685226,Morrison,712,Germany,Female,29,7,147199.07,1,1,1,84932.4,0 -392,15785611,Onyeoruru,752,Germany,Male,38,3,183102.29,1,1,1,71557.12,0 -393,15573456,Cunningham,648,Spain,Male,46,9,127209,2,1,0,77405.95,1 -394,15684548,Demidov,556,Spain,Male,38,8,0,2,0,0,417.41,1 -395,15620505,Celis,594,Spain,Female,24,0,97378.54,1,1,1,71405.17,0 -396,15807432,Cheng,645,Germany,Female,37,2,136925.09,2,0,1,153400.24,0 -397,15584766,Knight,557,France,Male,33,3,54503.55,1,1,1,371.05,0 -398,15612187,Morin,547,Germany,Male,32,8,155726.85,1,1,0,67789.99,0 -399,15762218,Mills,701,France,Female,39,9,0,2,0,1,145894.9,0 -400,15646372,Outhwaite,616,France,Female,66,1,135842.41,1,1,0,183840.51,1 -401,15690452,Tung,605,France,Male,52,1,63349.75,1,1,0,108887.44,0 -402,15747795,Pai,593,Germany,Female,38,4,129499.42,1,1,1,154071.27,0 -403,15781589,Carpenter,751,Spain,Male,52,8,0,2,0,1,179291.85,0 -404,15732674,Fennell,443,Spain,Male,36,6,70438.01,2,0,1,56937.43,0 -405,15642291,Fontaine,685,France,Male,23,8,0,2,1,1,112239.03,0 -406,15692761,Pratt,718,France,Male,36,9,0,1,1,0,45909.87,0 -407,15578045,Mitchell,538,Spain,Female,49,9,141434.04,1,0,0,173779.25,1 -408,15745354,Franklin,611,Spain,Female,37,4,0,2,1,0,125696.26,0 -409,15701376,K'ung,668,Germany,Male,37,10,152958.29,2,1,1,159585.61,0 -410,15691625,Ko,537,Germany,Female,41,3,138306.34,1,1,0,106761.47,0 -411,15566594,McKenzie,709,Spain,Male,23,10,0,2,0,0,129590.18,0 -412,15760431,Pino,850,France,Male,38,1,0,2,1,1,80006.65,0 -413,15686302,Fisk,745,Spain,Female,31,3,124328.84,1,1,1,140451.52,0 -414,15801559,Chiang,693,Germany,Female,41,9,181461.48,3,1,1,187929.43,1 -415,15810432,Moseley,795,Spain,Male,35,8,0,2,1,0,167155.36,0 -416,15809616,Hsiung,626,Spain,Male,26,8,0,2,0,0,191420.71,0 -417,15720559,Heath,487,Germany,Female,61,5,110368.03,1,0,0,11384.45,1 -418,15695632,Dellucci,556,France,Female,39,9,89588.35,1,1,1,94898.1,0 -419,15659843,Li,643,France,Female,46,6,0,2,0,0,106781.59,0 -420,15615624,De Salis,605,France,Female,28,6,0,2,0,0,159508.52,0 -421,15810418,T'ang,756,Germany,Female,60,3,115924.89,1,1,0,93524.19,1 -422,15716186,Richardson,586,France,Female,38,2,0,2,1,0,87168.46,0 -423,15674551,Fitch,535,Germany,Male,40,7,111756.5,1,1,0,8128.32,1 -424,15622834,Stevenson,678,France,Female,35,4,0,1,1,0,125518.32,0 -425,15566111,Estes,596,France,Male,39,9,0,1,1,0,48963.59,0 -426,15784597,Lattimore,648,France,Male,26,9,162923.85,1,1,0,98368.24,0 -427,15652883,Chung,492,Germany,Male,39,10,124576.65,2,1,0,148584.61,0 -428,15806964,Utz,702,France,Male,45,0,80793.58,1,1,1,27474.81,0 -429,15576313,Wei,486,Germany,Female,40,9,71340.09,1,1,0,76192.21,0 -430,15806467,Boyle,568,Germany,Male,40,1,99282.63,1,0,0,134600.94,1 -431,15597602,Nwachinemelu,619,Germany,Male,57,3,137946.39,1,1,1,72467.99,1 -432,15743040,Kuznetsova,724,Germany,Male,41,2,127892.57,2,0,1,199645.45,0 -433,15705521,Pisani,548,Germany,Female,33,0,101084.36,1,1,0,42749.85,0 -434,15595039,Manna,545,Germany,Female,37,8,114754.08,1,1,0,136050.44,1 -435,15799384,Collier,683,France,Male,33,8,0,1,0,0,73564.44,0 -436,15581197,Ricci,762,France,Female,51,3,99286.98,1,0,1,85578.63,0 -437,15693737,Carr,627,Germany,Female,30,4,79871.02,2,1,0,129826.89,0 -438,15624623,Hs?,516,France,Male,35,10,104088.59,2,0,0,119666,0 -439,15783501,Findlay,800,France,Female,38,2,168190.33,2,1,0,68052.08,0 -440,15690134,Hughes,464,Germany,Female,42,3,85679.25,1,1,1,164104.74,0 -441,15782735,Chukwuemeka,626,France,Female,35,3,0,1,0,0,80190.36,0 -442,15611088,Genovese,790,France,Female,31,9,0,2,1,0,84126.75,0 -443,15672145,Swift,534,France,Female,34,7,121551.58,2,1,1,70179,0 -444,15732628,Ugoji,745,France,Male,46,2,122220.19,1,1,1,118024.1,0 -445,15787470,Parkinson,553,Spain,Male,47,3,116528.15,1,0,0,145704.19,1 -446,15803406,Ross,748,France,Female,26,1,77780.29,1,0,1,183049.41,0 -447,15730460,Oleary,722,France,Male,37,2,0,1,0,0,120906.83,0 -448,15644572,Turnbull,501,France,Male,40,4,125832.2,1,1,1,100433.83,0 -449,15694860,Uspensky,675,France,Female,38,6,68065.8,1,0,0,138777,1 -450,15658169,Cook,778,Spain,Female,47,6,127299.34,2,1,0,124694.99,0 -451,15794396,Newbold,494,Germany,Female,38,7,174937.64,1,1,0,40084.32,0 -452,15785798,Uchechukwu,850,France,Male,40,9,0,2,0,1,119232.33,0 -453,15710825,Ch'en,592,Spain,Male,31,7,110071.1,1,0,0,43921.36,0 -454,15668444,He,590,Spain,Female,44,3,139432.37,1,1,0,62222.81,0 -455,15726631,Hilton,758,France,Female,39,6,127357.76,1,0,1,56577,0 -456,15733797,Sal,506,France,Male,36,5,0,2,1,0,164253.35,0 -457,15747960,Eluemuno,733,France,Male,33,3,0,1,1,1,7666.73,0 -458,15634632,Titus,711,France,Male,38,3,0,2,1,0,68487.51,0 -459,15707362,Yin,514,Germany,Male,43,1,95556.31,1,0,1,199273.98,1 -460,15662976,Lettiere,637,Spain,Male,37,8,0,1,1,1,186062.36,0 -461,15732778,Templeman,468,Germany,Male,29,1,111681.98,2,1,1,195711.16,0 -462,15718443,Chibuzo,539,France,Male,39,3,0,2,1,0,36692.17,0 -463,15670039,Sun,509,Spain,Female,25,3,108738.71,2,1,0,106920.57,0 -464,15773792,Evans,662,France,Female,32,4,133950.37,1,1,1,48725.68,1 -465,15613786,Ogbonnaya,818,Spain,Male,26,4,0,2,1,1,167036.94,0 -466,15726032,Enyinnaya,608,France,Male,33,9,89968.69,1,1,0,68777.26,0 -467,15663252,Olisanugo,850,Spain,Female,32,9,0,2,1,1,18924.92,0 -468,15593782,Brookes,816,Germany,Female,38,5,130878.75,3,1,0,71905.77,1 -469,15633283,Padovano,536,France,Male,35,8,0,2,1,0,64833.28,0 -470,15749167,Fisk,753,France,Male,35,3,0,2,1,1,184843.77,0 -471,15759298,Shih,631,Spain,Male,27,10,134169.62,1,1,1,176730.02,0 -472,15683625,Hare,703,France,Male,37,1,149762.08,1,1,0,20629.4,1 -473,15635367,Muir,774,France,Male,26,2,93844.69,1,1,0,28415.36,0 -474,15681705,Fanucci,785,France,Male,28,8,0,2,1,0,77231.27,0 -475,15603156,Elewechi,571,France,Female,33,1,0,2,1,0,102750.7,0 -476,15591986,Johnston,621,Germany,Male,46,6,141078.37,1,0,0,34580.8,1 -477,15798888,Pisano,605,Germany,Female,31,1,117992.59,1,1,1,183598.77,0 -478,15809722,Ankudinov,611,France,Female,40,8,100812.33,2,1,0,147358.27,0 -479,15677538,Nwokike,569,France,Male,38,7,0,1,1,1,108469.2,0 -480,15797736,Smith,658,France,Male,29,4,80262.6,1,1,1,20612.82,0 -481,15695585,Atkins,788,Spain,Male,34,6,156478.62,1,0,1,181196.76,0 -482,15744398,Burns,525,France,Female,23,5,0,2,1,0,160249.1,0 -483,15750658,Obiuto,798,France,Male,37,8,0,3,0,0,110783.28,0 -484,15578186,Pirozzi,486,Germany,Male,37,9,115217.99,2,1,0,144995.33,0 -485,15676519,George,615,Spain,Male,61,9,0,2,1,0,150227.85,1 -486,15637954,Lewis,730,France,Female,35,0,155470.55,1,1,1,53718.28,0 -487,15758639,Moran,641,France,Male,37,7,0,2,1,0,75248.3,0 -488,15613772,Dalrymple,542,France,Male,39,3,135096.77,1,1,1,14353.43,1 -489,15731744,Carslaw,692,France,Male,30,2,0,2,0,1,130486.57,0 -490,15807709,Kirby,714,Germany,Female,55,9,180075.22,1,1,1,100127.71,0 -491,15714689,Houghton,591,Spain,Male,29,1,97541.24,1,1,1,196356.17,0 -492,15699005,Martin,710,France,Female,41,2,156067.05,1,1,1,9983.88,0 -493,15624170,Tan,639,France,Female,38,4,81550.94,2,0,1,118974.77,0 -494,15725679,Hsia,531,France,Female,47,6,0,1,0,0,194998.34,1 -495,15585865,Westerberg,673,France,Female,38,2,170061.92,2,0,0,134901.34,1 -496,15804256,Hale,765,Germany,Male,36,8,92310.54,2,1,1,72924.56,0 -497,15662403,Kryukova,622,France,Female,32,6,169089.38,2,1,0,101057.95,0 -498,15733616,Sopuluchukwu,806,France,Male,40,5,80613.93,1,1,1,142838.64,0 -499,15591995,Barry,757,Germany,Male,26,8,121581.56,2,1,1,127059.04,0 -500,15677020,Selezneva,570,France,Female,58,8,0,1,0,1,116503.92,1 -501,15727688,Chizuoke,555,Spain,Male,32,4,0,2,1,1,54405.79,0 -502,15715941,Lueck,692,France,Male,54,5,0,2,1,1,88721.84,0 -503,15714485,Udinese,774,France,Male,60,5,85891.55,1,1,0,74135.48,1 -504,15730059,Udobata,638,Spain,Male,44,9,77637.35,2,1,1,111346.22,0 -505,15715527,Freeman,543,Spain,Female,41,4,0,1,0,0,194902.16,0 -506,15576623,Outlaw,584,France,Male,31,5,0,2,1,0,31474.27,0 -507,15805565,Obiuto,691,Germany,Male,30,7,116927.89,1,1,0,21198.39,0 -508,15677307,Lo,684,Germany,Female,40,6,137326.65,1,1,0,186976.6,0 -509,15773890,Okechukwu,733,France,Male,22,5,0,2,1,1,117202.19,0 -510,15598883,King,599,Spain,Female,37,2,0,2,1,1,143739.29,0 -511,15568506,Forbes,524,Germany,Female,31,10,67238.98,2,1,1,161811.23,0 -512,15761043,Macleod,632,Germany,Female,38,6,86569.76,2,1,0,98090.91,0 -513,15782236,Gibbs,735,Spain,Male,34,5,0,2,0,0,71095.41,0 -514,15593601,Isayev,734,France,Male,34,6,133598.4,1,1,1,13107.24,0 -515,15682048,Pisano,605,France,Female,51,3,136188.78,1,1,1,67110.59,1 -516,15746902,Belstead,793,Spain,Male,38,9,0,2,1,0,88225.02,0 -517,15752081,Vassiliev,468,France,Female,56,10,0,3,0,1,62256.87,1 -518,15781307,Schneider,779,Germany,Male,37,7,120092.52,2,1,0,135925.72,0 -519,15775912,Mazzanti,698,France,Male,48,4,101238.24,2,0,1,177815.87,1 -520,15745417,Knipe,707,France,Male,58,6,89685.92,1,0,1,126471.13,0 -521,15671256,Macartney,850,France,Female,35,1,211774.31,1,1,0,188574.12,1 -522,15653547,Madukwe,850,France,Male,56,7,131317.48,1,1,1,119175.45,0 -523,15595766,Watts,527,Spain,Male,37,5,93722.73,2,1,1,139093.73,0 -524,15742358,Humphreys,696,Germany,Male,32,8,101160.99,1,1,1,115916.55,0 -525,15763274,Wu,661,France,Male,48,3,120320.54,1,0,0,96463.25,0 -526,15786063,Chin,776,France,Female,31,2,0,2,1,1,112349.51,0 -527,15600258,Chesnokova,701,France,Male,43,2,0,2,1,1,165303.79,0 -528,15573318,Kung,610,France,Male,26,8,0,2,1,0,166031.08,0 -529,15653849,Lu,572,Germany,Female,48,3,152827.99,1,1,0,38411.79,1 -530,15694272,Nkemakolam,673,France,Male,30,1,64097.75,1,1,1,77783.35,0 -531,15736112,Walton,519,Spain,Female,57,2,119035.35,2,1,1,29871.79,0 -532,15749851,Brookes,702,Spain,Female,26,4,135219.57,1,0,1,59747.63,0 -533,15663478,Baldwin,729,France,Male,32,6,93694.42,1,1,1,79919.13,0 -534,15592300,Mai,543,Spain,Male,35,10,59408.63,1,1,0,76773.53,0 -535,15567832,Shih,550,France,Female,40,7,114354.95,1,1,0,54018.93,0 -536,15776780,He,608,France,Male,59,1,0,1,1,0,70649.64,1 -537,15592846,Fiorentini,639,Germany,Male,35,10,128173.9,2,1,0,59093.39,0 -538,15739803,Lucciano,686,Spain,Male,34,9,0,2,1,0,127569.8,0 -539,15794142,Ferreira,564,Germany,Female,62,5,114931.35,3,0,1,18260.98,1 -540,15762729,Ukaegbunam,745,Germany,Female,28,1,111071.36,1,1,0,73275.96,1 -541,15667896,De Luca,833,France,Male,37,8,151226.18,2,1,1,136129.49,0 -542,15626578,Milne,622,France,Male,26,9,0,2,1,1,153237.59,0 -543,15776223,Davide,597,France,Female,42,4,64740.12,1,1,1,106841.12,0 -544,15705953,Kodilinyechukwu,721,Spain,Male,51,0,169312.13,1,1,0,109078.35,1 -545,15802593,Little,504,France,Female,49,7,0,3,0,1,87822.14,1 -546,15615457,Burns,842,Spain,Female,44,2,112652.08,2,1,0,126644.98,0 -547,15708916,Paterson,587,France,Male,38,0,0,2,1,0,47414.15,0 -548,15720187,Han,479,Germany,Female,30,7,143964.36,2,1,0,41879.99,0 -549,15595440,Kryukova,508,France,Male,49,7,122451.46,2,1,1,75808.1,0 -550,15600651,Ijendu,749,France,Male,24,1,0,3,1,1,47911.03,0 -551,15750141,Reichard,721,Germany,Female,36,3,65253.07,2,1,0,28737.78,0 -552,15657284,Day,674,Germany,Male,47,6,106901.94,1,1,1,2079.2,1 -553,15763063,Price,685,Spain,Female,25,10,128509.63,1,1,0,121562.33,0 -554,15709324,Bruce,417,France,Male,34,7,0,2,1,0,55003.79,0 -555,15711309,Sumrall,574,Germany,Male,33,3,129834.67,1,1,0,193131.42,0 -556,15775318,Lu,590,Spain,Female,51,3,154962.99,3,0,1,191932.27,1 -557,15705515,Lazarev,587,Germany,Male,40,5,138241.9,2,1,0,159418.1,0 -558,15634844,Miller,598,Germany,Male,41,3,91536.93,1,1,0,191468.78,1 -559,15717046,Wentworth-Shields,741,Spain,Male,53,3,0,2,1,1,38913.68,0 -560,15571816,Ritchie,850,Spain,Female,70,5,0,1,1,1,705.18,0 -561,15670080,Mackenzie,584,Germany,Female,29,7,105204.01,1,0,1,138490.03,0 -562,15800440,Power,650,Spain,Male,61,1,152968.73,1,0,1,82970.69,0 -563,15665678,Tan,607,Spain,Male,36,8,158261.68,1,1,1,76744.72,0 -564,15665956,Pendergrass,509,France,Female,46,1,0,1,1,0,71244.59,1 -565,15788126,Evans,689,Spain,Female,38,6,121021.05,1,1,1,12182.15,0 -566,15811773,Hsia,543,France,Male,36,4,0,2,1,1,141210.5,0 -567,15651674,Billson,438,Spain,Female,54,2,0,1,0,0,191763.07,1 -568,15689614,Teng,687,Spain,Female,63,1,137715.66,1,1,1,37938.74,0 -569,15795564,Moretti,737,Germany,Male,31,5,121192.22,2,1,1,74890.58,0 -570,15706647,Jordan,761,France,Male,31,7,0,3,1,1,166698.18,0 -571,15728505,Ts'ao,601,France,Male,44,1,100486.18,2,1,1,62678.53,0 -572,15730076,Osborne,651,France,Male,45,1,0,1,1,0,67740.08,1 -573,15622003,Carslaw,745,France,Male,35,9,92566.53,2,1,0,161519.77,0 -574,15607312,Ch'ang,648,Spain,Female,49,10,0,2,1,1,159835.78,1 -575,15644753,Hung,848,Spain,Male,40,3,110929.96,1,1,1,30876.84,0 -576,15653620,Gordon,546,France,Female,27,8,0,2,1,1,14858.1,0 -577,15761986,Obialo,439,Spain,Female,32,3,138901.61,1,1,0,75685.97,0 -578,15633922,Gray,755,France,Male,30,4,123217.66,2,0,1,144183.1,0 -579,15734674,Lin,593,France,Female,41,6,0,1,1,0,65170.66,0 -580,15658032,Hopkins,701,France,Male,39,2,0,2,1,1,82526.92,0 -581,15692671,Dobson,701,Spain,Male,36,8,0,2,1,0,169161.46,0 -582,15737741,McKay,607,Spain,Female,33,2,108431.87,2,0,1,109291.39,1 -583,15576352,Revell,586,Spain,Female,57,3,0,2,0,1,6057.81,0 -584,15753719,Rickards,547,Germany,Female,30,9,72392.41,1,1,0,77077.14,0 -585,15803689,Begum,647,Germany,Female,51,1,119741.77,2,0,0,54954.51,1 -586,15718057,Onyinyechukwuka,760,France,Female,51,2,100946.71,1,0,0,179614.8,1 -587,15722010,Zuyev,621,Spain,Male,53,9,170491.84,1,1,0,35588.07,1 -588,15680998,Nwankwo,725,France,Male,44,5,0,1,1,1,117356.14,0 -589,15614782,Hao,526,France,Male,36,1,0,1,1,0,160696.72,0 -590,15591047,Ma,519,Spain,Female,47,6,157296.02,2,0,0,147278.43,1 -591,15788291,Okwuadigbo,713,Germany,Female,38,7,144606.22,1,1,1,56594.36,1 -592,15604044,Mitchell,700,France,Male,38,8,134811.3,1,1,0,1299.75,0 -593,15679587,Chan,666,France,Female,34,9,115897.12,1,1,1,25095.03,0 -594,15775153,Buchi,630,Spain,Male,32,4,82034,1,0,0,146326.45,0 -595,15603925,Greco,779,Spain,Female,26,4,174318.13,2,0,1,38296.21,0 -596,15680970,Lombardi,611,Germany,Female,41,2,114206.84,1,1,0,164061.6,0 -597,15697183,Uchenna,685,Spain,Male,43,9,0,2,1,0,107811.28,0 -598,15567446,Coffman,646,Germany,Male,39,9,111574.41,1,1,1,30838.51,0 -599,15637476,Alexandrova,683,Germany,Female,57,5,162448.69,1,0,0,9221.78,1 -600,15714939,Fallaci,484,Germany,Female,34,4,148249.54,1,0,1,33738.27,0 -601,15683503,Hudson,601,France,Female,43,8,0,3,0,1,110916.15,1 -602,15645569,Mai,762,Spain,Female,26,7,123709.46,2,1,1,169654.57,0 -603,15782569,Stout,687,France,Female,72,9,0,1,0,1,69829.4,0 -604,15592387,Burke,566,France,Male,30,5,0,1,1,0,54926.51,1 -605,15609286,Chadwick,702,France,Male,37,10,150525.8,1,1,1,94728.49,0 -606,15814035,Lawrence,601,France,Male,29,9,0,1,1,1,80393.27,0 -607,15661249,Bellucci,699,France,Male,53,4,0,2,0,1,111307.98,0 -608,15629117,Harper,584,France,Male,28,10,0,2,1,0,19834.32,0 -609,15607170,Boyle,699,France,Male,35,5,0,2,1,1,78397.24,0 -610,15586585,Duncan,698,Germany,Female,51,2,111018.98,1,1,0,86410.28,0 -611,15686611,Moss,495,France,Male,30,10,129755.99,1,0,0,172749.65,0 -612,15603203,Avdeyeva,650,France,Female,27,6,0,2,1,0,1002.39,0 -613,15619857,Crawford,605,France,Female,64,2,129555.7,1,1,1,13601.79,0 -614,15805062,Lynton,667,Spain,Male,38,1,87202.38,1,1,1,77866.91,0 -615,15660271,Duncan,688,Germany,Male,26,8,146133.39,1,1,1,175296.76,0 -616,15745295,Gether,727,Spain,Female,31,0,0,1,1,0,121751.04,1 -617,15719352,Davidson,754,Spain,Male,39,6,170184.99,2,1,0,89593.26,0 -618,15766575,Larionova,612,Germany,Female,62,8,140745.33,1,1,0,193437.89,1 -619,15594594,Loggia,546,Spain,Male,42,7,139070.51,1,1,1,86945,0 -620,15646161,Steinhoff,673,Spain,Female,37,8,0,2,1,1,183318.79,0 -621,15682585,Guerra,593,France,Male,35,9,114193.24,1,1,0,71154.1,0 -622,15603134,Pai,656,Spain,Female,40,10,167878.5,1,0,1,151887.16,0 -623,15636444,Craig,535,Germany,Female,53,5,141616.55,2,1,1,75888.65,0 -624,15773456,Lazareva,678,Germany,Male,36,3,145747.67,2,0,1,89566.74,0 -625,15745307,Ch'iu,477,Spain,Female,48,2,129120.64,1,0,1,26475.79,0 -626,15604119,Alderete,850,Spain,Male,35,7,110349.82,1,0,0,126355.8,0 -627,15626900,Kung,427,France,Male,29,1,141325.56,1,1,1,93839.3,0 -628,15605447,Palermo,752,France,Male,49,2,78653.84,1,1,0,7698.6,0 -629,15589030,Ts'ai,649,France,Male,47,1,0,2,1,1,145593.85,0 -630,15692463,Rahman,799,Spain,Female,28,3,142253.65,1,1,0,45042.56,0 -631,15712403,McMillan,589,France,Female,61,1,0,1,1,0,61108.56,1 -632,15811762,Pickering,583,Germany,Female,54,6,115988.86,1,1,0,57553.98,1 -633,15718673,Mirams,839,Spain,Female,33,10,75592.43,1,1,0,62674.42,0 -634,15724282,Tsao,540,Germany,Male,44,3,164113.04,2,1,1,12120.79,0 -635,15738181,Douglas,850,France,Male,31,6,67996.23,2,0,0,50129.87,1 -636,15633648,Jideofor,696,Spain,Female,51,5,0,2,1,0,55022.43,0 -637,15603323,Bell,660,Spain,Female,33,1,0,2,0,0,117834.91,0 -638,15583725,Mairinger,682,France,Male,48,1,138778.15,1,0,1,168840.23,0 -639,15588350,McIntyre,744,France,Female,43,10,147832.15,1,0,1,24234.11,0 -640,15798398,Pagnotto,785,France,Female,36,4,135438.4,1,0,0,190627.01,0 -641,15784844,K'ung,752,Spain,Male,48,5,116060.08,1,1,0,156618.38,1 -642,15580684,Feng,706,France,Female,29,5,112564.62,1,1,0,42334.38,0 -643,15809663,Donaldson,583,France,Female,27,1,125406.58,1,1,1,110784.42,0 -644,15640078,Chambers,660,Germany,Female,39,5,135134.99,1,1,0,173683,1 -645,15698786,Marcelo,819,France,Female,39,9,133102.92,1,1,0,27046.46,1 -646,15569807,Ejimofor,673,France,Female,34,8,42157.08,1,1,0,20598.59,1 -647,15730830,Dale,752,France,Female,30,3,0,2,1,1,104991.28,0 -648,15805112,Pokrovsky,578,France,Male,38,7,82259.29,1,1,0,8996.97,0 -649,15633064,Stonebraker,438,France,Female,36,4,0,2,1,0,64420.5,0 -650,15703119,Liang,652,France,Male,38,6,0,2,1,1,145700.22,0 -651,15730447,Anderson,629,France,Female,49,4,0,2,1,1,196335.48,0 -652,15813850,Christian,720,France,Male,52,7,0,1,1,1,14781.12,0 -653,15711889,Mao,668,France,Male,42,3,150461.07,1,1,0,108139.23,0 -654,15664610,Campbell,459,Germany,Male,48,4,133994.52,1,1,1,19287.06,1 -655,15751710,Ginikanwa,729,Spain,Male,31,8,164870.81,2,1,1,9567.39,0 -656,15692926,Toscani,498,Germany,Male,25,8,121702.73,1,1,1,132210.49,0 -657,15813741,Nnachetam,549,Spain,Male,25,6,193858.2,1,0,1,21600.11,0 -658,15698474,Sagese,601,Germany,Female,54,1,131039.97,2,1,1,199661.5,0 -659,15568595,Fleming,544,France,Male,64,9,113829.45,1,1,1,124341.49,0 -660,15603065,Grubb,751,France,Female,30,6,0,2,1,0,15766.1,0 -661,15592937,Napolitani,632,Germany,Female,41,3,81877.38,1,1,1,33642.21,0 -662,15699637,Anenechi,694,Spain,Male,57,8,116326.07,1,1,1,117704.65,0 -663,15667215,Chandler,678,France,Male,31,2,0,2,1,1,58803.28,0 -664,15788659,Howells,695,France,Male,46,4,0,2,1,1,137537.22,0 -665,15763218,Akeroyd,661,France,Female,41,1,0,2,0,1,131300.68,0 -666,15645772,Onwumelu,661,France,Male,33,9,0,2,1,1,84174.81,0 -667,15725511,Wallace,559,France,Female,31,3,127070.73,1,0,1,160941.78,0 -668,15575024,Uwaezuoke,503,France,Male,29,3,0,2,1,1,143954.99,0 -669,15640825,Loyau,695,Spain,Male,46,3,122549.64,1,1,1,56297.85,0 -670,15662397,Small,640,France,Female,42,5,176099.13,1,1,1,8404.73,0 -671,15576368,Bledsoe,624,Germany,Female,48,3,122388.38,2,0,0,30020.09,0 -672,15674991,Kao,667,France,Male,42,9,0,2,0,1,58137.42,0 -673,15721024,Wickens,642,France,Male,26,0,0,1,0,0,47472.68,0 -674,15745621,Wertheim,640,Spain,Female,32,6,118879.35,2,1,1,19131.71,0 -675,15642394,He,529,Spain,Male,35,5,0,2,1,1,187288.5,0 -676,15754605,Jarvis,563,France,Female,39,5,0,2,1,1,17603.81,0 -677,15607040,P'an,593,Spain,Female,38,4,88736.44,2,1,0,67020.03,0 -678,15715142,Repina,739,Germany,Male,45,7,102703.62,1,0,1,147802.94,1 -679,15810978,Pugliesi,788,Spain,Female,70,1,0,2,1,1,41610.62,0 -680,15668886,Blakey,684,Spain,Female,38,3,0,2,1,0,44255.65,0 -681,15780804,Nucci,482,France,Male,55,5,97318.25,1,0,1,78416.14,0 -682,15613880,Higinbotham,591,Spain,Male,58,5,128468.69,1,0,1,137254.55,0 -683,15775238,Achebe,651,Germany,Female,41,4,133432.59,1,0,1,151303.48,0 -684,15786905,Russo,749,Germany,Female,40,8,141782.57,2,0,0,86333.63,0 -685,15747867,Trevisani,583,France,Male,24,9,135125.28,1,0,0,89801.9,0 -686,15600337,Dobie,661,Spain,Male,42,2,178820.91,1,0,0,29358.57,1 -687,15801277,Maccallum,715,France,Female,31,2,112212.14,2,1,1,181600.72,0 -688,15579334,Watkins,769,Germany,Female,45,5,126674.81,1,1,0,124118.71,1 -689,15802741,Mitchel,625,France,Female,51,7,136294.97,1,1,0,38867.46,1 -690,15720649,Ferdinand,641,France,Female,36,5,66392.64,1,1,0,31106.67,0 -691,15589493,Otitodilinna,716,Germany,Male,27,1,122552.34,2,1,0,67611.36,0 -692,15688251,Mamelu,767,France,Male,43,1,76408.85,2,1,0,77837.63,0 -693,15665238,Beneventi,745,Germany,Male,36,8,145071.24,1,0,0,6078.46,0 -694,15740900,Perrodin,589,France,Male,34,6,0,2,1,1,177896.92,0 -695,15681068,Chinagorom,796,France,Female,45,2,109730.22,1,1,1,123882.73,0 -696,15748625,Napolitano,664,France,Male,57,6,0,2,1,1,15304.08,0 -697,15727299,Edgar,445,Spain,Male,62,1,64119.38,1,1,1,76569.64,1 -698,15620204,Walker,543,Germany,Female,57,1,106138.33,2,1,1,120657.32,1 -699,15669516,Steele,746,Spain,Male,36,2,0,2,1,1,16436.56,0 -700,15736534,Elkins,742,Germany,Male,33,0,181656.51,1,1,1,107667.91,0 -701,15803457,Hao,750,France,Female,32,5,0,2,1,0,95611.47,0 -702,15659098,Toscano,669,France,Male,30,7,95128.86,1,0,0,19799.26,0 -703,15603436,Savage,594,Spain,Female,49,2,126615.94,2,0,1,123214.74,0 -704,15566292,Okwuadigbo,574,Spain,Male,36,1,0,2,0,1,71709.12,0 -705,15808621,Mordvinova,659,Germany,Male,36,2,76190.48,2,1,1,149066.14,0 -706,15580148,Welch,750,Germany,Male,40,5,168286.81,3,1,0,20451.99,1 -707,15776231,Kent,626,Germany,Male,35,4,88109.81,1,1,1,32825.5,0 -708,15773809,Campbell,620,France,Male,42,4,0,2,1,0,6232.31,0 -709,15649423,Cooper,580,France,Female,35,8,0,2,0,1,10357.03,0 -710,15734886,Mazzi,686,France,Female,34,3,123971.51,2,1,0,147794.63,0 -711,15722548,Fisher,540,France,Male,48,0,148116.48,1,0,0,116973.48,0 -712,15650288,Summers,634,Germany,Male,35,6,116269.01,1,1,0,129964.94,0 -713,15629448,Brady,632,Spain,Male,38,1,120599.21,1,1,0,92816.86,0 -714,15716164,Nicholls,501,France,Female,41,3,144260.5,1,1,0,172114.67,0 -715,15807609,Yuan,650,Spain,Female,25,3,86605.5,3,1,0,16649.31,1 -716,15578977,Robinson,786,France,Male,34,9,0,2,1,0,144517.19,0 -717,15677369,Golubov,554,Germany,Female,37,4,58629.97,1,0,0,182038.6,0 -718,15804072,Chen,701,Spain,Female,42,5,0,2,0,0,24210.56,0 -719,15696859,Oldham,474,France,Male,45,10,0,2,0,0,172175.9,0 -720,15653780,Kambinachi,621,France,Female,43,5,0,1,1,1,47578.45,0 -721,15721658,Fleming,672,Spain,Female,56,2,209767.31,2,1,1,150694.42,1 -722,15578761,Cunningham,459,Spain,Female,42,6,129634.25,2,1,1,177683.02,1 -723,15736879,Obinna,669,France,Male,23,1,0,2,0,0,66088.83,0 -724,15571973,Chinwemma,776,France,Female,38,2,169824.46,1,1,0,169291.7,0 -725,15626742,Carpenter,694,France,Male,36,3,97530.25,1,1,1,117140.41,0 -726,15672692,Yin,787,France,Female,42,10,145988.65,2,1,1,79510.37,0 -727,15673570,Olsen,580,France,Male,37,9,0,2,0,1,77108.66,0 -728,15767432,Ts'ai,711,France,Female,25,7,0,3,1,1,9679.28,0 -729,15654238,Jen,673,France,Female,40,5,137494.28,1,1,0,81753.92,0 -730,15612525,Preston,499,France,Female,57,1,0,1,0,0,131372.38,1 -731,15812750,Ozioma,591,France,Male,24,6,147360,1,1,1,25310.82,0 -732,15790757,Cody,769,France,Female,25,10,0,2,0,0,187925.75,0 -733,15723873,Ponomarev,657,Spain,Male,31,3,125167.02,1,0,0,98820.39,0 -734,15744607,Martin,738,Germany,Male,43,9,121152.05,2,1,0,64166.7,1 -735,15612966,Milani,545,Germany,Female,60,7,128981.07,1,0,1,176924.21,1 -736,15784209,Tang,497,France,Male,47,6,0,1,1,1,90055.08,0 -737,15794278,Romani,816,Spain,Male,67,6,151858.98,1,1,1,72814.31,0 -738,15766741,McIntyre,525,France,Male,36,2,114628.4,1,0,1,168290.06,0 -739,15661036,Davis,725,France,Male,46,6,0,2,1,0,161767.38,0 -740,15705639,Onyemauchechukwu,692,France,Female,28,8,95059.02,2,1,0,44420.18,0 -741,15637414,Gell,618,France,Female,24,7,128736.39,1,0,1,37147.61,0 -742,15716835,Rossi,546,France,Male,24,8,156325.38,1,1,1,125381.02,0 -743,15696231,Chiwetelu,635,France,Male,29,7,105405.97,1,1,1,149853.89,0 -744,15641675,Kirillova,611,France,Female,49,2,88915.37,3,0,0,161435.02,1 -745,15670755,Shaw,650,France,Male,60,8,0,2,1,1,102925.76,0 -746,15640059,Smith,606,France,Male,40,5,0,2,1,1,70899.27,0 -747,15787619,Hsieh,844,France,Male,18,2,160980.03,1,0,0,145936.28,0 -748,15587535,Onyemauchechukwu,450,Spain,Female,46,5,177619.71,1,1,0,54227.06,0 -749,15813034,Martin,727,Spain,Male,38,2,62276.99,1,1,1,59280.79,0 -750,15698839,Okwudilichukwu,460,Germany,Male,46,4,127559.97,2,1,1,126952.5,0 -751,15790314,Onuoha,649,France,Male,41,0,0,2,0,1,130567.02,0 -752,15634245,Muecke,758,Germany,Female,47,9,95523.16,1,1,0,73294.48,0 -753,15677305,Hsieh,490,France,Female,35,7,107749.03,1,1,1,3937.37,0 -754,15661526,Anderson,815,Germany,Male,37,2,110777.26,2,1,0,2383.59,0 -755,15685997,Azubuike,838,Spain,Female,39,5,166733.92,2,1,0,14279.44,0 -756,15660101,Nnonso,803,France,Male,31,9,157120.86,2,1,0,141300.53,0 -757,15637979,Fuller,664,Germany,Female,36,2,127160.78,2,1,0,78140.75,0 -758,15815364,Ashley,736,Spain,Female,28,2,0,2,1,1,117431.1,0 -759,15647099,Ts'ui,633,France,Female,37,9,156091.97,1,1,0,72008.61,0 -760,15625944,Buccho,664,France,Male,58,5,98668.18,1,1,1,60887.58,0 -761,15583212,Chidozie,600,France,Female,43,5,134022.06,1,1,0,194764.83,0 -762,15582741,Maclean,693,France,Female,35,5,124151.09,1,1,0,88705.14,1 -763,15637876,Burns,663,Germany,Female,36,6,77253.5,1,0,0,35817.97,1 -764,15622750,Chu,742,Germany,Female,21,1,114292.48,1,1,0,31520.4,0 -765,15672056,Kenenna,710,Germany,Male,43,2,140080.32,3,1,1,157908.19,1 -766,15812351,Beluchi,710,Spain,Female,27,2,135277.96,1,1,0,142200.15,0 -767,15810864,Williamson,700,France,Female,82,2,0,2,0,1,182055.36,0 -768,15677921,Bobrov,720,Germany,Male,60,9,115920.62,2,0,0,157552.08,1 -769,15724296,Kerr,684,Spain,Male,41,2,119782.72,2,0,0,120284.67,0 -770,15685329,McKenzie,531,France,Female,63,1,114715.71,1,0,1,24506.95,1 -771,15584091,Pitts,742,Germany,Female,36,2,129748.54,2,0,0,47271.61,1 -772,15640442,Standish,717,France,Male,31,4,129722.57,1,0,0,41176.6,0 -773,15639314,Cartwright,589,France,Male,32,2,0,2,0,1,9468.64,0 -774,15685320,Johnstone,767,France,Male,36,3,139180.2,1,0,0,123880.19,0 -775,15789158,Nikitina,636,Germany,Male,49,6,113599.74,2,1,0,158887.09,1 -776,15752137,McElroy,648,France,Male,33,7,134944,1,1,1,117036.38,0 -777,15712551,Shen,622,Germany,Female,58,7,116922.25,1,1,0,120415.61,1 -778,15628936,Archer,692,Spain,Male,28,9,118945.09,1,0,0,16064.25,1 -779,15797227,Otutodilinna,754,France,Male,28,8,0,2,1,1,52615.62,0 -780,15769974,Shih,679,Spain,Female,35,8,119182.73,1,0,0,121210.09,0 -781,15737051,Denisov,639,France,Male,27,8,0,2,1,0,192247.35,0 -782,15585595,Owens,774,France,Female,28,1,71264.02,2,0,1,68759.57,0 -783,15654060,P'eng,517,France,Male,41,2,0,2,0,1,75937.47,0 -784,15745196,Verco,571,France,Female,35,8,0,2,0,0,84569.13,0 -785,15571221,Bergamaschi,747,Germany,Male,58,7,116313.57,1,1,1,190696.35,1 -786,15660155,Lorenzo,792,Spain,Male,36,5,92140.15,1,0,1,67468.67,0 -787,15605284,Outtrim,688,France,Male,26,1,0,2,1,1,104435.94,0 -788,15694366,Hou,714,Germany,Male,42,2,177640.09,1,0,1,47166.55,0 -789,15600739,Galkin,562,Spain,Female,35,0,0,2,1,0,119899.52,0 -790,15653253,Pagnotto,704,Spain,Male,48,8,167997.6,1,1,1,173498.45,0 -791,15763431,Echezonachukwu,698,France,Male,36,2,82275.35,2,1,1,93249.26,0 -792,15643696,Young,611,France,Male,49,3,0,2,1,1,142917.54,0 -793,15707473,Summers,850,Germany,Female,48,6,111962.99,1,1,0,111755.8,0 -794,15769504,Munro,743,Germany,Female,34,1,131736.88,1,1,1,108543.21,0 -795,15776807,Brennan,654,France,Male,29,1,0,1,1,0,180345.44,0 -796,15686870,Ball,761,Germany,Male,36,8,108239.11,2,0,0,99444.02,0 -797,15668747,Virgo,702,France,Female,46,9,98444.19,1,0,1,109563.28,0 -798,15766908,Trevisani,488,Germany,Male,32,3,114540.38,1,1,0,92568.07,0 -799,15570134,Padovano,683,France,Female,35,6,187530.66,2,1,1,37976.36,0 -800,15567367,Tao,601,Germany,Female,42,9,133636.16,1,0,1,103315.74,0 -801,15747542,Perez,605,France,Male,52,7,0,2,1,1,173952.5,0 -802,15762238,Fraser,671,Germany,Female,44,0,84745.03,2,0,1,34673.98,0 -803,15681554,Alley,614,Germany,Female,31,7,120599.38,2,1,1,46163.44,0 -804,15712825,Howells,511,Spain,Female,29,9,0,2,0,1,140676.98,0 -805,15640280,Cameron,850,France,Male,39,4,127771.35,2,0,1,151738.54,0 -806,15756026,Hooper,790,Spain,Female,46,9,0,1,0,0,14679.81,1 -807,15613319,Rice,793,France,Female,33,0,0,1,0,0,175544.02,0 -808,15798906,Cox,628,France,Male,69,5,0,2,1,1,181964.6,0 -809,15708917,Martin,598,Germany,Male,53,10,167772.96,1,1,1,136886.86,0 -810,15778463,Ikenna,657,France,Female,37,6,95845.6,1,1,0,122218.23,0 -811,15699430,Davide,618,France,Female,35,10,0,2,1,0,180439.75,0 -812,15649992,Alexander,681,Spain,Male,65,7,134714.7,2,0,1,190419.81,0 -813,15578980,Piazza,516,Spain,Female,33,3,0,2,1,1,58685.59,0 -814,15775306,Ni,421,Germany,Male,28,8,122384.22,3,1,1,89017.38,1 -815,15641655,Black,700,France,Female,26,2,0,2,0,0,50051.42,0 -816,15619708,Harker,745,France,Male,25,5,157993.15,2,1,0,146041.45,0 -817,15734565,Hughes,696,France,Male,29,8,0,2,1,0,191166.09,0 -818,15806438,Chiabuotu,580,Germany,Female,42,2,123331.36,1,0,0,103516.08,1 -819,15591969,Kuo,497,Spain,Male,27,9,75263.16,1,1,1,164825.04,0 -820,15747807,Gallagher,720,France,Female,43,6,137824.03,2,1,0,172557.77,0 -821,15596939,Calabresi,659,Germany,Male,36,4,132578.92,2,1,0,84320.94,0 -822,15716155,Shaw,841,France,Female,36,5,156021.31,1,0,0,122662.98,0 -823,15765311,Zhirov,642,Spain,Male,34,8,0,1,1,0,72085.1,0 -824,15757811,Lloyd,732,Spain,Female,69,9,137453.43,1,0,1,110932.24,1 -825,15603830,Palmer,600,Spain,Male,36,4,0,2,1,0,143635.36,0 -826,15660602,Ch'eng,464,Germany,Male,33,8,164284.72,2,1,1,3710.34,0 -827,15660535,Avent,680,France,Female,47,5,0,2,1,1,179843.33,0 -828,15666633,Huang,758,Spain,Male,56,1,0,2,1,1,10643.38,0 -829,15596914,Shaw,630,Germany,Female,31,2,112373.49,2,1,1,131167.98,0 -830,15639788,Yuan,577,France,Female,39,10,0,2,1,0,10553.31,0 -831,15695846,Hawkins,684,France,Female,34,6,0,2,1,1,130928.22,0 -832,15726234,Trentini,708,Spain,Female,41,5,0,1,0,1,157003.99,0 -833,15797964,Cameron,732,Germany,Female,29,1,154333.82,1,1,1,138527.56,0 -834,15625881,Koehler,634,Germany,Male,37,3,111432.77,2,1,1,167032.49,0 -835,15780628,Wu,633,France,Female,30,6,0,2,0,0,41642.29,0 -836,15575883,Manna,559,France,Male,34,2,137390.11,2,1,0,9677,0 -837,15585036,Okoli,694,Spain,Female,37,3,0,2,1,1,147012.22,0 -838,15589488,Ch'eng,686,Germany,Female,56,5,111642.08,1,1,1,80553.87,0 -839,15585888,Nwokezuike,553,Spain,Female,48,3,0,1,0,1,30730.95,1 -840,15727915,Artemiev,507,France,Male,36,4,83543.37,1,0,0,140134.43,0 -841,15707567,Esposito,732,Germany,Male,50,6,145338.76,1,0,0,91936.1,1 -842,15737792,Abbie,818,France,Female,31,1,186796.37,1,0,0,178252.63,0 -843,15599433,Fanucci,660,Germany,Male,35,8,58641.43,1,0,1,198674.08,0 -844,15672012,Jen,773,Spain,Female,41,5,0,1,1,0,28266.9,1 -845,15806983,Moss,640,France,Male,44,3,137148.68,1,1,0,92381.01,0 -846,15592222,Lo,505,France,Male,49,7,80001.23,1,0,0,135180.11,0 -847,15608968,Averyanov,714,Germany,Male,21,6,86402.52,2,0,0,27330.59,0 -848,15586959,Unaipon,468,France,Female,42,5,0,2,1,0,125305.34,0 -849,15646558,Clamp,611,Spain,Male,51,1,122874.74,1,1,1,149648.45,0 -850,15725811,Lim,705,France,Male,25,0,97544.29,1,0,1,59887.15,0 -851,15572265,Wu,646,Germany,Male,46,1,170826.55,2,1,0,45041.32,0 -852,15794048,Wan,667,Germany,Female,48,1,97133.92,2,0,0,113316.77,1 -853,15677610,Chambers,511,Germany,Female,41,8,153895.65,1,1,1,39087.42,0 -854,15745012,Pettit,653,France,Female,43,6,0,2,1,1,7330.59,0 -855,15601589,Baresi,675,France,Female,57,8,0,2,0,1,95463.29,0 -856,15686436,Newbery,523,Spain,Male,32,4,0,2,1,0,167848.02,0 -857,15693864,Iheanacho,567,Germany,Female,49,5,134956.02,1,1,0,93953.84,1 -858,15760550,Duncan,741,Spain,Male,39,7,143637.58,2,0,1,174227.66,0 -859,15686137,Barry,456,Spain,Male,32,9,147506.25,1,1,1,135399.21,0 -860,15809087,Landry,598,France,Male,64,1,0,2,1,0,195635.3,1 -861,15807663,McGregor,667,France,Male,43,8,190227.46,1,1,0,97508.04,1 -862,15809100,Nucci,548,France,Female,32,2,172448.77,1,1,0,188083.77,1 -863,15794916,Pirogov,725,France,Male,41,7,113980.21,1,1,1,116704.25,0 -864,15614215,Oguejiofor,717,France,Male,53,6,0,2,0,1,97614.87,0 -865,15805449,Ugochukwu,594,France,Male,38,4,0,2,0,0,186884.04,0 -866,15686983,Rohu,678,Germany,Female,25,10,76968.12,2,0,1,131501.72,0 -867,15808017,Cary,545,France,Male,38,1,88293.13,2,1,1,24302.95,0 -868,15756804,O'Loghlen,636,France,Female,48,1,170833.46,1,1,0,110510.28,1 -869,15646810,Quinn,603,Germany,Male,44,6,108122.39,2,1,0,108488.33,1 -870,15710424,Page,435,France,Male,36,4,0,1,1,1,197015.2,0 -871,15799422,Evans,535,France,Female,40,8,0,1,1,1,27689.77,0 -872,15692750,McGregor,629,Germany,Female,45,7,129818.39,3,1,0,9217.55,1 -873,15794549,Andrews,722,France,Female,35,2,163943.89,2,1,1,15068.18,0 -874,15803764,Stanley,561,France,Male,28,7,0,2,1,0,7797.01,0 -875,15674840,Chiazagomekpere,645,France,Female,38,5,101430.3,2,0,1,4400.32,0 -876,15653762,Chidiebele,501,France,Female,39,9,117301.66,1,0,0,182025.95,0 -877,15581229,Gregory,502,Germany,Female,32,1,173340.83,1,0,1,122763.95,0 -878,15800228,Bednall,652,Spain,Female,42,4,0,2,1,1,38152.01,0 -879,15656333,Jen,574,France,Female,33,3,134348.57,1,1,0,63163.99,0 -880,15697497,She,518,France,Female,45,9,105525.65,2,1,1,73418.29,0 -881,15585362,Simmons,749,France,Female,60,6,0,1,1,0,17978.68,1 -882,15571928,Fraser,679,France,Female,43,4,0,3,1,0,115136.51,1 -883,15785519,May,565,France,Male,36,6,106192.1,1,1,0,149575.59,0 -884,15743007,Seabrook,643,France,Female,45,4,45144.43,1,1,0,60917.24,1 -885,15777211,Herrera,515,France,Male,65,7,92113.61,1,1,1,142548.33,0 -886,15721935,Kincaid,521,France,Male,25,7,0,2,1,1,157878.67,0 -887,15591711,Sleeman,739,Spain,Male,38,0,128366.44,1,1,0,12796.43,0 -888,15625021,Hung,585,France,Male,42,2,0,2,1,1,18657.77,0 -889,15702968,Artemieva,733,Germany,Male,74,3,106545.53,1,1,1,134589.58,0 -890,15600462,Barwell,542,France,Female,43,8,145618.37,1,0,1,10350.74,0 -891,15768104,Wright,788,Spain,Male,37,8,141541.25,1,0,0,66013.27,0 -892,15780140,Bellucci,435,Germany,Male,32,2,57017.06,2,1,1,5907.11,0 -893,15585255,Moore,577,France,Male,42,9,0,1,1,0,74077.91,0 -894,15772781,Ball,703,France,Female,51,3,0,3,1,1,77294.56,1 -895,15669987,Sung,728,Germany,Female,35,8,125884.95,2,1,0,54359.02,1 -896,15697000,Mello,728,Germany,Male,32,5,61825.5,1,1,1,156124.93,0 -897,15733119,Mistry,718,France,Male,35,8,0,2,1,0,94820.85,0 -898,15782390,T'ien,621,France,Female,40,6,0,1,1,0,155155.25,0 -899,15654700,Fallaci,523,France,Female,40,2,102967.41,1,1,0,128702.1,1 -900,15632210,Hill,657,Germany,Male,25,2,171770.55,1,1,0,22745.5,0 -901,15642041,Burns,727,Germany,Male,40,1,93051.64,2,1,0,71865.31,1 -902,15709737,Hunter,643,France,Male,36,7,161064.64,2,0,1,84294.82,0 -903,15792388,Li,645,France,Female,48,7,90612.34,1,1,1,149139.13,0 -904,15786014,Ku,568,France,Male,28,5,145105.64,2,1,0,185489.11,0 -905,15794580,Ch'en,599,France,Male,58,4,0,1,0,0,176407.15,1 -906,15675964,Chukwukadibia,672,France,Female,45,9,0,1,1,1,92027.69,1 -907,15814275,Zikoranachidimma,685,France,Male,33,6,174912.72,1,1,1,43932.54,0 -908,15724848,Oluchukwu,516,France,Female,46,1,104947.72,1,1,0,115789.25,1 -909,15754713,Rivera,685,Spain,Male,31,10,135213.71,1,1,1,125777.28,0 -910,15693814,Niu,806,Spain,Male,25,7,0,2,1,0,18461.9,0 -911,15599660,Bennett,604,France,Male,36,6,116229.85,2,1,1,79633.38,0 -912,15746490,Wollstonecraft,648,Spain,Female,53,6,111201.41,1,1,1,121542.29,0 -913,15566091,Thomsen,545,Spain,Female,32,4,0,1,1,0,94739.2,0 -914,15655961,Palermo,756,Germany,Male,27,1,131899,1,1,0,93302.29,0 -915,15710404,Chinwendu,569,France,Male,35,10,124525.52,1,1,1,193793.78,0 -916,15775625,McKenzie,596,France,Male,47,6,0,1,1,0,74835.65,0 -917,15792328,James,475,France,Male,39,6,0,1,1,1,56999.9,1 -918,15719856,Lamb,646,France,Female,45,3,47134.75,1,1,1,57236.44,0 -919,15593773,Olejuru,784,Spain,Male,35,3,0,2,0,0,81483.64,0 -920,15733114,Hay,552,Spain,Male,45,9,0,2,1,0,26752.56,0 -921,15797748,Lu,729,France,Male,44,5,0,2,0,1,9200.54,0 -922,15743411,Chiawuotu,609,Spain,Male,61,1,0,1,1,0,22447.85,1 -923,15753337,Yeates,555,France,Male,51,5,0,3,1,0,189122.89,1 -924,15601026,Gallagher,572,Germany,Female,19,1,138657.08,1,1,1,16161.82,0 -925,15658485,Heath,785,France,Female,34,9,70302.48,1,1,1,68600.36,0 -926,15636731,Ts'ai,714,Germany,Female,36,1,101609.01,2,1,1,447.73,0 -927,15628303,Thurgood,738,Spain,Male,35,3,0,1,1,1,15650.73,0 -928,15633461,Pai,639,Germany,Male,38,5,130170.82,1,1,1,149599.62,0 -929,15677135,Lorenzo,520,Germany,Male,61,8,133802.29,2,1,1,90304.01,0 -930,15590876,Knupp,764,France,Female,24,7,106234.02,1,0,0,115676.38,0 -931,15790782,Baryshnikov,661,Spain,Male,39,6,132628.98,1,0,0,38812.67,0 -932,15700476,Azubuike,564,Germany,Male,41,9,103522.75,2,1,1,34338.21,0 -933,15634141,Shephard,708,Germany,Female,42,8,192390.52,2,1,0,823.36,0 -934,15737795,Scott,512,Spain,Male,36,1,0,1,0,1,135482.26,1 -935,15790299,Williamson,592,Spain,Male,37,9,0,3,1,1,10656.89,0 -936,15675316,Avdeeva,619,France,Female,38,3,0,2,0,1,116467.35,0 -937,15613630,Tang,775,France,Male,52,8,109922.61,1,1,1,96823.32,1 -938,15662100,Hsu,850,Germany,Female,44,5,128605.32,1,0,1,171096.2,0 -939,15668032,Buchanan,577,France,Female,37,4,0,1,1,1,79881.39,0 -940,15599289,Yeh,724,France,Female,37,10,68598.56,1,1,0,157862.82,0 -941,15754084,Palazzi,710,Spain,Male,35,1,106518.52,1,1,1,127951.81,0 -942,15676521,Y?an,696,France,Female,31,8,0,2,0,0,191074.11,0 -943,15804586,Lin,376,France,Female,46,6,0,1,1,0,157333.69,1 -944,15781465,Schofield,675,Germany,Female,29,8,121326.42,1,1,0,133457.52,0 -945,15729362,Lombardi,745,France,Male,36,8,67226.37,1,1,0,130789.6,0 -946,15709295,Wall,697,Spain,Female,25,5,82931.85,2,1,1,128373.88,0 -947,15745324,Milani,599,Spain,Female,39,4,0,1,1,0,194273.2,1 -948,15741336,Ejimofor,715,France,Female,38,5,118590.41,1,1,1,5684.17,1 -949,15783659,Blackburn,659,France,Male,67,4,145981.87,1,1,1,131043.2,0 -950,15620981,Wickham,684,France,Female,48,3,73309.38,1,0,0,21228.34,1 -951,15630328,Bird,635,France,Female,48,8,130796.33,2,1,1,43250.3,0 -952,15785899,Ch'en,789,Germany,Male,33,8,151607.56,1,1,0,4389.4,0 -953,15606149,Wood,571,Germany,Female,66,9,111577.01,1,0,1,189271.9,0 -954,15671139,Brizendine,694,Spain,Male,39,0,107042.74,1,1,1,102284.2,0 -955,15660429,Ch'in,665,Spain,Female,42,2,156371.61,2,0,1,156774.94,1 -956,15571002,Yusupov,706,France,Female,44,4,129605.99,1,0,0,69865.49,0 -957,15631681,Jibunoh,807,Spain,Female,43,0,0,2,0,1,85523.24,0 -958,15731522,Ts'ui,771,Spain,Female,67,8,0,2,1,1,51219.8,0 -959,15619529,Ndukaku,531,Spain,Male,27,8,132576.25,1,0,0,7222.92,0 -960,15628034,Wilder,629,France,Female,37,6,129101.3,1,1,1,23971.33,0 -961,15686164,Maclean,850,Germany,Female,31,1,108822.4,1,1,1,132173.31,0 -962,15582797,Ch'iu,685,Spain,Male,35,4,137948.51,1,1,0,113639.64,0 -963,15753831,Cox,642,Spain,Male,32,7,100433.8,1,1,1,39768.59,0 -964,15731815,Nepean,529,Spain,Male,63,4,96134.11,3,1,0,108732.96,1 -965,15580956,McNess,683,Germany,Female,43,4,115888.04,1,1,1,117349.19,1 -966,15602084,Coles,663,France,Female,42,5,124626.07,1,1,1,78004.5,0 -967,15589805,Benson,563,France,Female,34,6,139810.34,1,1,1,152417.79,0 -968,15720893,Gilbert,637,Spain,Female,34,9,0,2,0,0,26057.08,0 -969,15641009,Wilhelm,544,France,Male,37,3,84496.71,1,0,0,79972.09,0 -970,15605926,Sinclair,649,Germany,Male,70,9,116854.71,2,0,1,107125.79,0 -971,15805955,L?,638,France,Female,48,10,138333.03,1,1,1,47679.14,0 -972,15801488,Buckner,723,France,Male,25,3,0,2,1,1,134509.47,0 -973,15605918,Padovesi,635,Germany,Male,43,5,78992.75,2,0,0,153265.31,0 -974,15779711,Gray,750,Spain,Female,38,7,97257.41,2,0,1,179883.04,0 -975,15705620,Lu,730,France,Male,34,5,122453.37,2,1,0,138882.98,0 -976,15685357,Wright,750,Spain,Female,36,8,112940.07,1,0,1,9855.81,0 -977,15570060,Palerma,586,France,Female,43,8,132558.26,1,1,0,67046.83,1 -978,15582616,Y?an,520,France,Female,38,4,0,2,1,0,56388.63,0 -979,15799515,Wei,652,France,Female,48,8,133297.24,1,1,0,77764.37,0 -980,15642937,Padovesi,550,France,Female,46,7,0,2,1,0,130590.35,0 -981,15624729,Tsao,594,France,Male,27,0,197041.8,1,0,0,151912.49,0 -982,15566156,Franklin,749,Germany,Female,44,0,71497.79,2,0,0,151083.8,0 -983,15792360,Clark,668,France,Male,32,7,0,2,1,1,777.37,0 -984,15807008,McGregor,614,Germany,Female,35,6,128100.28,1,0,0,69454.24,1 -985,15704770,Pan,773,France,Male,25,1,124532.78,2,0,1,11723.57,0 -986,15756475,Kenniff,551,Germany,Male,31,9,82293.82,2,1,1,91565.25,0 -987,15655339,Spencer,566,France,Male,36,1,142120.91,1,1,0,79616.37,0 -988,15613749,Lees,569,Spain,Male,34,0,151839.26,1,1,0,102299.81,1 -989,15664521,David,659,Spain,Male,31,7,149620.88,2,1,1,104533.51,0 -990,15681206,Hsing,722,France,Female,49,3,168197.66,1,1,0,140765.57,1 -991,15745527,Burke,655,France,Male,37,5,93147,2,1,0,66214.13,0 -992,15806926,Watson,615,France,Female,35,2,97440.02,2,1,1,139816.1,0 -993,15724563,Hawkins,752,Germany,Female,42,3,65046.08,2,0,1,140139.28,0 -994,15782899,Ginn,661,Spain,Female,28,7,95357.49,1,0,0,102297.15,0 -995,15623521,Sozonov,838,Spain,Male,43,9,123105.88,2,1,0,145765.83,0 -996,15810218,Sun,610,Spain,Male,29,9,0,3,0,1,83912.24,0 -997,15645621,Hunter,811,Spain,Male,44,3,0,2,0,1,78439.73,0 -998,15608114,Manfrin,587,Spain,Male,62,7,121286.27,1,0,1,6776.92,0 -999,15659557,Artamonova,811,Germany,Female,28,4,167738.82,2,1,1,9903.42,0 -1000,15787772,Hansen,759,France,Female,38,1,104091.29,1,0,0,91561.91,0 -1001,15691111,Pai,648,Germany,Female,42,8,121980.56,2,1,0,4027.02,0 -1002,15592089,Larsen,788,France,Female,43,10,0,2,1,1,116111.51,0 -1003,15633897,Owen,725,Germany,Male,39,1,50880.98,2,1,1,184023.54,0 -1004,15701301,Murphy,646,France,Female,42,3,175159.9,2,0,0,67124.48,1 -1005,15723685,Ekechukwu,601,Germany,Female,26,7,105514.69,2,1,0,50070.59,0 -1006,15701602,Ayers,521,Germany,Male,52,5,116497.31,3,0,0,53793.1,1 -1007,15739189,Johnson,561,Spain,Female,33,6,0,2,1,0,45261.47,0 -1008,15573086,Millar,564,France,Male,42,7,99824.45,1,1,1,36721.4,0 -1009,15569050,Farrell,444,France,Male,45,6,0,1,1,0,130009.85,1 -1010,15750765,Sanders,650,Spain,Male,71,0,0,1,1,1,175380.77,0 -1011,15799811,Herrera,724,France,Male,40,10,0,1,1,0,127847.25,1 -1012,15698442,Eberechukwu,719,Spain,Male,35,3,122964.88,1,1,1,138231.7,0 -1013,15655274,Bardin,548,France,Female,29,4,0,2,0,1,48673.18,0 -1014,15603594,Nwankwo,635,Spain,Male,24,4,0,2,1,1,70668.77,0 -1015,15585961,Talbot,496,Spain,Female,43,3,0,2,0,1,199505.53,0 -1016,15686936,McGregor,676,France,Female,37,5,89634.69,1,1,1,169583.18,1 -1017,15770424,Onyeorulu,541,Germany,Male,40,7,95710.11,2,1,0,49063.42,0 -1018,15587451,Goold,778,Germany,Male,41,7,139706.31,1,1,0,63337.19,0 -1019,15602010,Zikoranaudodimma,850,Germany,Female,45,5,103909.86,1,1,0,60083.11,1 -1020,15600583,Garner,633,France,Male,31,1,0,1,1,0,48606.71,0 -1021,15654673,Onyinyechukwuka,625,France,Male,49,6,173434.9,1,1,0,165580.93,1 -1022,15717164,Genovese,485,Spain,Male,32,6,102238.01,2,1,1,194010.12,0 -1023,15765014,Mai,547,France,Female,48,1,179380.74,2,0,1,69263.1,0 -1024,15682639,Marshall,642,France,Male,32,3,0,2,1,1,88698.83,0 -1025,15729279,Naylor,718,France,Female,25,4,108691.95,1,1,0,63030.97,0 -1026,15759805,Pinto,582,France,Female,32,4,0,2,1,0,59668.81,0 -1027,15767864,Fulton,628,France,Male,33,6,0,2,0,0,184230.23,0 -1028,15769948,Palerma,737,Germany,Male,35,0,133377.8,1,0,1,64050.19,0 -1029,15686345,McCaffrey,828,Spain,Male,34,9,0,2,1,1,81853.98,0 -1030,15688071,Collins,609,Spain,Male,53,10,0,1,1,1,154642.91,0 -1031,15681174,Zuev,730,France,Male,39,1,116537.6,1,0,0,145679.6,0 -1032,15667521,Crawford,631,France,Female,22,3,0,2,0,0,30781.77,0 -1033,15750243,Genovese,830,Spain,Male,40,4,0,2,0,1,81622.52,0 -1034,15695475,Maclean,645,France,Male,29,1,130131.08,2,0,1,196474.35,0 -1035,15689176,Fabro,663,France,Male,46,3,0,2,0,1,176276.1,0 -1036,15652955,Price,678,Spain,Male,30,0,0,1,1,0,35113.08,0 -1037,15668958,Chatfield,521,France,Male,30,2,107316.09,1,1,0,64299.82,0 -1038,15631054,Volkova,625,France,Female,24,1,0,2,1,1,180969.55,0 -1039,15581479,Archer,523,France,Male,30,1,83181.29,1,1,1,138176.78,0 -1040,15577478,Ch'iu,714,France,Female,72,3,0,1,1,1,86733.61,0 -1041,15780870,McKay,580,Spain,Male,67,3,153946.14,1,1,1,7418.92,0 -1042,15692317,Craig,722,France,Male,30,5,0,2,1,0,166376.54,0 -1043,15593969,Abramovich,630,Spain,Female,39,7,135483.17,1,1,0,140881.2,1 -1044,15570417,Chien,579,France,Male,35,1,0,2,1,0,4460.2,0 -1045,15779059,Timms,670,France,Female,38,4,119624.54,2,1,1,110472.12,0 -1046,15785980,Williford,588,Spain,Male,34,6,121132.26,2,1,0,86460.28,0 -1047,15644200,Hamilton,807,Spain,Female,42,1,0,1,1,0,16500.66,1 -1048,15793949,Cheng,726,France,Female,48,4,0,1,1,0,114020.06,1 -1049,15645103,Su,812,Germany,Male,25,5,54817.55,1,1,0,131660.31,0 -1050,15705860,McKenzie,631,Germany,Male,40,3,107949.45,1,1,0,52449.62,1 -1051,15623828,Akobundu,682,France,Male,30,4,0,1,0,1,161465.31,0 -1052,15715003,Ko,625,Spain,Female,49,2,80816.45,1,1,1,20018.79,0 -1053,15623471,Marcelo,607,Germany,Male,38,3,98205.77,1,1,0,176318.27,0 -1054,15798348,Chukwuebuka,600,Spain,Female,50,6,94684.27,1,1,1,50488.91,0 -1055,15743016,MacDonald,602,Spain,Female,22,7,141604.76,1,1,0,30379.6,0 -1056,15769499,Lampungmeiua,545,Spain,Female,74,3,0,2,1,1,161326.73,0 -1057,15798521,Tai,675,Spain,Male,33,3,0,2,1,0,45348.08,0 -1058,15706534,Enyinnaya,581,France,Female,47,1,122949.14,1,0,0,180251.68,1 -1059,15706186,McKenzie,640,Germany,Male,33,8,81677.22,2,0,0,34925.56,0 -1060,15812197,Kline,850,France,Male,38,7,80293.98,1,0,0,126555.74,0 -1061,15650933,Ma,490,Spain,Female,48,8,155413.06,1,1,0,187921.3,0 -1062,15692991,Wood,710,Spain,Female,38,4,0,2,1,1,136390.88,0 -1063,15631189,Riggs,613,Germany,Male,38,9,67111.65,1,1,0,78566.64,1 -1064,15762198,Capon,812,France,Male,34,5,103818.43,1,1,1,166038.27,0 -1065,15699598,Smith,723,France,Female,20,4,0,2,1,1,140385.33,0 -1066,15692744,Davison,512,France,Male,36,4,152169.12,2,0,0,38629.3,1 -1067,15688963,Ingram,731,France,Female,52,10,0,1,1,1,24998.75,1 -1068,15599131,Dilke,650,Germany,Male,26,4,214346.96,2,1,0,128815.33,0 -1069,15680303,Gibson,594,France,Male,57,6,0,1,1,0,19376.56,1 -1070,15628674,Iadanza,844,France,Male,40,7,113348.14,1,1,0,31904.31,1 -1071,15648075,Hebert,686,Germany,Female,47,5,170935.94,1,1,0,173179.79,1 -1072,15586970,Pinto,695,Germany,Male,52,8,103023.26,1,1,1,22485.64,0 -1073,15625698,Dumetochukwu,624,Spain,Female,23,6,0,2,0,1,196668.51,0 -1074,15790497,Ross,503,Spain,Male,37,6,0,2,0,0,136506.86,0 -1075,15682618,Jamieson,535,France,Female,31,7,111855.04,2,1,1,36278.89,0 -1076,15762937,Chiganu,743,Germany,Female,32,6,140348.56,2,1,1,163254.39,0 -1077,15750929,Burgess,702,Spain,Male,39,8,0,2,1,0,99654.13,0 -1078,15729832,Cheng,658,France,Male,29,3,145512.84,1,1,0,20207.02,0 -1079,15633650,Woods,677,Germany,Female,41,8,146720.98,2,1,1,4195.84,0 -1080,15748856,Liang,664,France,Male,32,10,107209.73,1,1,1,112340.2,0 -1081,15589195,Bluett,766,Germany,Female,38,7,130933.74,1,0,1,2035.94,0 -1082,15699911,Chapman,461,Spain,Female,35,8,0,1,1,0,132295.95,0 -1083,15663438,Andrejew,688,Spain,Male,36,0,89772.3,1,1,0,177383.68,1 -1084,15692583,Udobata,678,France,Female,32,5,0,2,1,0,90284.47,0 -1085,15591257,Ejimofor,796,France,Male,24,8,0,2,1,0,61349.37,0 -1086,15646513,Spyer,803,France,Male,42,5,0,1,1,0,196466.83,1 -1087,15708063,Walker,712,France,Male,36,2,100749.5,3,0,0,70758.37,1 -1088,15696098,Palermo,498,France,Female,31,10,0,2,1,0,13892.57,0 -1089,15645517,Philip,850,Spain,Male,22,2,0,2,1,1,9684.52,0 -1090,15649744,Fallaci,628,France,Female,51,3,123981.31,2,1,1,40546.15,0 -1091,15604304,Perry,539,Germany,Female,34,4,91622.42,1,1,1,136603.42,0 -1092,15784092,Henderson,732,France,Male,36,7,126195.81,1,1,1,133172.48,0 -1093,15585198,Bergamaschi,715,France,Male,41,4,94267.9,1,0,1,152821.12,1 -1094,15624347,Fokine,651,France,Male,40,4,0,2,1,1,147715.83,0 -1095,15621687,Mackay,813,France,Male,34,0,0,2,1,0,43169.15,0 -1096,15689081,Wu,692,France,Male,29,4,0,1,1,0,76755.99,1 -1097,15813168,Maslova,756,Germany,Female,39,3,100717.85,3,1,1,73406.04,1 -1098,15604295,Wei,543,France,Male,36,6,0,2,1,0,176728.28,0 -1099,15724127,McLean,790,France,Female,26,4,141581.71,2,0,0,98309.27,0 -1100,15673055,Sung,494,Spain,Male,38,7,0,2,1,1,6203.66,0 -1101,15768201,Paterson,850,France,Female,39,2,148586.64,1,1,1,176791.27,0 -1102,15782219,Fanucci,703,Spain,Male,29,9,0,2,1,0,50679.48,0 -1103,15746410,Thompson,432,Spain,Male,38,7,0,2,1,0,150580.88,0 -1104,15780144,Tisdall,512,Germany,Female,32,2,123403.85,2,1,0,80120.19,0 -1105,15590476,Onochie,589,France,Male,28,7,0,2,1,0,151645.96,0 -1106,15624293,Mironova,514,France,Female,46,3,106511.85,1,1,0,55072.32,0 -1107,15618182,Ndubueze,678,France,Female,38,2,0,2,0,0,115068.99,0 -1108,15660316,Stephenson,420,Germany,Female,34,1,135549.9,1,0,0,149471.13,1 -1109,15678886,Golubev,679,Germany,Male,38,7,110555.37,2,1,0,46522.68,0 -1110,15616330,Liao,595,France,Male,31,4,0,2,1,0,189995.86,0 -1111,15592229,Mullan,713,France,Female,52,0,185891.54,1,1,1,46369.57,1 -1112,15798424,Glover,833,Germany,Male,59,1,130854.59,1,1,1,30722.52,1 -1113,15714750,Northey,690,France,Female,42,3,92578.14,2,0,0,70810.6,0 -1114,15648800,Paterson,731,Germany,Female,21,8,132312.06,1,1,0,106663.46,1 -1115,15626147,Maclean,608,France,Female,62,8,144976.5,1,0,0,175836.03,1 -1116,15626608,Howarde,479,Spain,Male,48,5,87070.23,1,0,1,85646.41,0 -1117,15723250,Teng,519,France,Male,42,8,0,2,1,1,101485.72,0 -1118,15592583,Colman,731,France,Female,47,1,115414.19,3,0,0,191734.67,1 -1119,15759381,Johnson,617,Spain,Male,61,7,91070.43,1,1,1,101839.77,0 -1120,15585241,Butcher,756,Spain,Male,29,2,117412.19,2,1,0,4888.91,0 -1121,15589358,Stanley,848,Germany,Male,31,4,90018.45,2,1,0,193132.98,0 -1122,15672704,Jackson,809,France,Female,24,4,0,2,1,0,193518.76,0 -1123,15789955,Hu,698,Germany,Male,56,1,112414.81,2,0,0,93982.02,1 -1124,15596800,Hill,779,Germany,Male,33,1,158456.76,1,1,1,197000.92,1 -1125,15627305,Pan,606,Spain,Male,35,7,0,1,1,0,106837.06,1 -1126,15645316,Han,612,Germany,Female,58,1,149641.53,1,1,1,115161.28,0 -1127,15593973,Wilkie,663,Spain,Female,33,8,122528.18,1,1,0,196260.3,0 -1128,15647301,Bray,549,Germany,Female,45,3,143734.01,2,1,1,96404.38,0 -1129,15750258,Ann,675,France,Female,32,2,155663.31,1,1,0,97658.66,0 -1130,15685309,Souter,669,France,Female,35,7,0,1,1,1,49108.23,1 -1131,15628205,Greco,571,Germany,Female,34,1,101736.66,1,0,1,195651.66,0 -1132,15733974,Mao,500,Spain,Male,37,9,125822.21,1,1,0,111698,0 -1133,15762110,Anderson,628,France,Male,37,0,0,2,1,1,171707.93,0 -1134,15706899,Ma,559,France,Male,34,4,0,2,1,1,66721.98,0 -1135,15732660,Black,769,France,Female,27,2,0,1,1,1,57876.05,0 -1136,15656121,Medvedeva,733,Germany,Male,31,6,157791.07,2,0,0,177994.81,0 -1137,15614220,Benson,750,France,Male,22,5,0,2,0,1,105125.65,0 -1138,15645269,Duncan,583,France,Female,42,4,0,2,1,0,17439.66,0 -1139,15698510,Onwudiwe,468,Germany,Male,42,9,181627.14,2,1,0,172668.39,0 -1140,15569247,Mitchell,727,Spain,Female,57,1,109679.72,1,0,1,753.37,0 -1141,15566251,Ferrari,618,France,Female,37,5,96652.86,1,1,0,98686.4,1 -1142,15716134,Russo,617,France,Male,40,5,190008.32,2,1,1,107047.92,0 -1143,15763625,Hazon,793,Spain,Male,41,9,0,2,1,0,152153.74,0 -1144,15605965,Henderson,630,France,Male,43,9,0,2,1,1,34338.04,0 -1145,15694821,Hardy,765,Germany,Male,43,4,148962.76,1,0,1,173878.87,1 -1146,15601688,Piccio,546,France,Male,28,8,0,1,1,0,159254.29,0 -1147,15575581,Dickson,614,Germany,Female,30,3,131344.52,2,1,0,54776.64,0 -1148,15671209,Holden,593,Germany,Female,29,5,101713.84,3,1,0,134594.99,0 -1149,15616529,Hsieh,613,Spain,Male,34,3,0,1,1,1,41724.72,0 -1150,15773906,Doherty,655,France,Male,38,4,0,2,0,0,110527.71,0 -1151,15722993,Page,700,France,Female,27,6,137963.07,1,0,0,8996.79,0 -1152,15752463,Samuel,826,Spain,Female,29,4,129938.07,1,0,1,190200.53,0 -1153,15589754,Malloy,652,Germany,Male,45,2,151421.44,1,0,1,115333.43,0 -1154,15669899,Fitts,755,Germany,Female,45,7,135643,1,0,0,143619.52,1 -1155,15766887,Iadanza,538,Spain,Male,39,2,122773.5,2,1,1,58467.08,0 -1156,15768006,Wu,729,France,Male,34,3,152303.8,1,1,0,12128.69,0 -1157,15741295,Yefimova,615,France,Male,49,3,0,2,1,1,49872.33,0 -1158,15811327,Pan,700,Spain,Male,54,1,79415.67,1,0,1,139735.54,0 -1159,15690007,Ts'ui,434,Germany,Female,58,9,125801.03,2,1,0,60891.8,1 -1160,15690664,Liang,729,Spain,Male,37,10,0,2,1,0,100862.54,0 -1161,15719348,Tsao,513,France,Male,35,8,0,1,1,0,76640.29,1 -1162,15781802,Abramov,755,France,Male,41,6,104817.41,1,1,0,126013.58,1 -1163,15752731,Millar,615,France,Female,30,9,0,1,1,0,87347.82,0 -1164,15600997,Demuth,747,Germany,Female,32,5,67495.04,2,0,1,77370.37,0 -1165,15750776,Genovese,850,France,Female,36,0,164850.54,1,1,1,62722.44,0 -1166,15723907,Lawless,712,Germany,Female,49,5,154776.42,2,0,0,196257.68,0 -1167,15633419,Brooks,622,Germany,Female,28,1,143124.63,2,1,0,81723.8,0 -1168,15702430,Ignatyeva,548,France,Female,35,10,0,1,1,1,31299.71,0 -1169,15710456,Balmain,607,France,Female,27,2,0,2,1,0,63495.86,0 -1170,15650351,Millar,653,France,Female,38,8,102133.38,1,1,1,166520.96,0 -1171,15590820,Ecuyer,699,Spain,Male,26,6,79932.41,1,0,0,150242.44,0 -1172,15640454,Parkhill,693,Germany,Male,40,0,120711.73,1,0,0,27345.18,1 -1173,15697789,Li Fonti,647,Germany,Female,43,3,122717.53,2,1,1,87000.39,0 -1174,15808182,Beneventi,478,Spain,Female,36,3,92363.3,2,1,0,44912.7,0 -1175,15588670,Despeissis,705,Spain,Female,40,5,203715.15,1,1,0,179978.68,1 -1176,15721292,Atkins,719,Spain,Male,39,5,0,2,1,0,145759.7,0 -1177,15604217,Williams,726,France,Male,34,9,0,2,0,0,14121.61,0 -1178,15651369,Wright,626,France,Male,21,1,0,2,1,0,66232.23,0 -1179,15782454,Hancock,552,France,Male,49,4,0,1,1,1,190296.76,1 -1180,15814032,Hsieh,807,Germany,Female,31,1,93460.47,2,0,0,172782.69,0 -1181,15570326,Wilkins,621,France,Male,34,6,0,2,1,1,99128.13,0 -1182,15624428,Longo,651,Germany,Female,24,7,40224.7,1,1,1,178341.33,0 -1183,15755638,Mancini,673,France,Female,43,5,168069.73,1,1,1,146992.24,1 -1184,15600992,Madukaego,652,France,Male,36,1,0,2,1,1,151314.98,0 -1185,15755649,Winter-Irving,584,Germany,Male,47,7,130538.77,1,1,0,92915.84,0 -1186,15795228,Stewart,756,France,Male,37,3,132623.6,1,1,1,58974,0 -1187,15589257,Grant,670,France,Female,35,3,103465.02,2,1,1,174627.06,0 -1188,15719302,Brennan,765,France,Female,50,9,126547.8,1,1,1,79579.94,1 -1189,15639882,She,528,France,Male,30,2,128262.72,2,1,0,50771.16,0 -1190,15791279,Murray,701,France,Male,40,5,169742.64,1,1,1,153537.55,1 -1191,15636935,Rischbieth,797,France,Female,29,1,0,2,1,1,132975.39,0 -1192,15686909,Lung,639,Germany,Male,27,3,150795.81,1,0,1,85208.93,0 -1193,15589572,Otutodilichukwu,785,Spain,Female,61,4,129855.72,2,1,0,170214.82,1 -1194,15779947,Thomas,363,Spain,Female,28,6,146098.43,3,1,0,100615.14,1 -1195,15573769,Fiorentini,764,France,Female,24,7,0,2,1,0,186105.99,0 -1196,15578866,Hughes,676,France,Female,43,2,0,1,1,1,55119.53,0 -1197,15739131,Whitworth,718,Germany,Male,28,4,65643.3,1,1,0,28760.99,0 -1198,15813444,McIntosh,590,Spain,Female,34,6,0,2,1,0,171021.44,0 -1199,15678058,Ayers,584,France,Male,38,9,104584.16,1,1,0,176678.72,0 -1200,15769169,Trentino,645,France,Male,41,7,0,1,0,1,28667.56,0 -1201,15804602,Boyd,772,Germany,Male,30,6,99785.28,2,0,0,197238.03,0 -1202,15651052,McMasters,399,Germany,Male,46,2,127655.22,1,1,0,139994.68,1 -1203,15724334,Alekseyeva,529,France,Male,22,5,0,1,1,0,151169.83,0 -1204,15569451,Miller,463,France,Male,35,2,101257.16,1,1,1,118113.64,0 -1205,15650098,Baranova,630,France,Female,40,7,0,2,1,1,34453.17,0 -1206,15724307,Mitchell,780,France,Male,76,10,121313.88,1,0,1,64872.33,0 -1207,15599268,Yobachi,584,Spain,Male,32,5,0,2,1,0,10956.82,0 -1208,15594864,Huang,752,Germany,Male,30,4,81523.38,1,1,1,36885.85,0 -1209,15616451,Genovese,697,France,Female,47,6,128252.66,1,1,1,168053.4,0 -1210,15715667,Sorokina,850,France,Female,32,7,0,2,0,0,155227,0 -1211,15658969,Gray,711,France,Male,51,7,0,3,1,0,38409.79,1 -1212,15738174,Ervin,452,France,Female,32,5,0,2,0,1,75279.39,0 -1213,15813590,Vance,610,Spain,Male,42,6,0,2,1,0,158302.59,1 -1214,15624229,Noble,694,France,Female,22,4,0,2,1,1,11525.72,0 -1215,15674148,Milanesi,579,Spain,Male,33,6,0,1,1,0,94993.04,1 -1216,15625080,Parkin,745,Spain,Female,54,8,0,1,1,0,173912.29,1 -1217,15682528,Cremonesi,572,France,Male,33,5,0,1,0,1,41139.05,0 -1218,15696900,Burns,505,Germany,Male,29,3,145541.56,2,1,1,58019.95,0 -1219,15730038,Docherty,706,France,Female,23,5,0,1,0,0,164128.41,1 -1220,15812272,Ugonna,693,Germany,Male,44,5,124601.58,2,1,1,46998.13,1 -1221,15654654,L?,725,Germany,Female,33,7,115182.84,2,1,1,177279.41,0 -1222,15697625,Bevan,791,France,Male,37,2,163789.49,2,1,0,75832.53,0 -1223,15616280,Hsia,536,France,Male,46,1,65733.41,1,1,0,61094.53,0 -1224,15654229,O'Neill,699,Spain,Male,47,1,0,2,0,1,30117.44,0 -1225,15628298,Johnstone,500,Spain,Female,47,8,128486.11,1,1,0,179227.12,0 -1226,15733387,Pham,707,Spain,Female,53,6,109663.47,1,1,1,52110.45,0 -1227,15775572,Bergamaschi,531,Germany,Female,42,6,88324.31,2,1,0,75248.75,0 -1228,15613844,Murphy,557,France,Female,28,7,146445.24,2,1,0,184317.74,0 -1229,15578515,Osinachi,659,France,Female,38,3,0,2,1,0,158553.1,0 -1230,15607598,Muravyov,575,Spain,Female,31,6,0,2,1,1,95686.42,0 -1231,15742480,Igwebuike,775,Germany,Male,36,2,109949.05,2,0,1,71682.54,0 -1232,15749482,Zack,772,Spain,Male,30,4,78653.05,1,1,0,1790.48,0 -1233,15607537,Crawford,587,Germany,Male,46,9,107850.82,1,1,0,139431,1 -1234,15575410,Chidiegwu,667,Germany,Female,39,4,83765.35,2,1,0,118358.54,0 -1235,15684865,Lucchesi,771,France,Female,66,7,143773.07,1,1,1,130827.88,0 -1236,15600700,Pan,523,Germany,Male,63,6,116227.27,1,1,1,119404.63,0 -1237,15774155,Trevisani,662,Germany,Male,33,0,103471.52,1,1,1,162703,0 -1238,15634267,Yudin,717,France,Male,42,5,0,2,1,0,172665.21,0 -1239,15619626,Wade,746,France,Male,24,3,137492.35,2,0,1,170142.09,0 -1240,15660422,Chung,569,France,Male,28,7,0,2,1,0,73977.23,0 -1241,15617934,Septimus,579,France,Male,36,9,129829.59,1,1,1,60906.12,0 -1242,15760774,Hargraves,519,France,Female,21,1,146329.57,2,1,1,194867.27,0 -1243,15813132,Chukwukadibia,696,Germany,Male,30,4,114027.7,1,1,1,193716.56,0 -1244,15593331,Sidorov,693,Germany,Male,25,6,146580.69,1,0,1,14633.35,0 -1245,15616709,Bunton,587,Germany,Female,38,0,132122.42,2,0,0,31730.32,0 -1246,15658052,Cameron,626,France,Female,44,10,81553.93,1,1,0,20063.63,1 -1247,15721189,Kung,666,France,Female,66,7,0,2,1,1,99792.82,0 -1248,15711288,Hay,512,France,Male,24,6,0,2,1,0,37654.31,0 -1249,15770030,Conti,689,Spain,Female,28,3,0,2,1,1,192449.02,0 -1250,15803681,Sims,803,France,Female,26,4,0,2,1,1,181208.47,0 -1251,15702789,Carter,548,Germany,Male,32,5,175214.71,1,1,1,155165.61,0 -1252,15814930,McGregor,588,Germany,Female,40,10,125534.51,1,1,0,121504.18,1 -1253,15658306,Lo,693,France,Male,68,4,97705.99,1,1,1,61569.07,0 -1254,15699523,Chu,499,Germany,Female,55,4,126817.65,2,1,0,123269.71,0 -1255,15610383,Dumetolisa,628,France,Female,46,1,46870.43,4,1,0,31272.14,1 -1256,15615032,Peng,624,Spain,Male,46,3,0,2,1,1,62825.03,0 -1257,15781989,Drake-Brockman,733,France,Male,42,9,120094.93,1,1,0,184056.45,0 -1258,15647402,Wan,628,France,Female,38,3,0,2,1,1,48924.73,0 -1259,15740494,Cameron,633,France,Female,33,3,0,2,1,0,191111.02,0 -1260,15701265,Tretiakov,559,Germany,Female,36,1,104356.94,2,0,1,54184.06,0 -1261,15743532,Ball,704,Germany,Male,27,5,147004.34,1,1,0,64381.33,1 -1262,15794870,Sal,744,Germany,Male,38,6,73023.17,2,1,0,78770.86,0 -1263,15747591,Chung,665,Spain,Female,40,1,173432.55,1,0,1,116766.79,0 -1264,15726557,Lai,638,France,Female,42,7,165679.92,1,0,0,32916.29,0 -1265,15732199,Gether,837,Spain,Male,31,9,104678.62,1,0,1,50972.6,0 -1266,15662291,Davidson,534,France,Female,55,8,116973.26,3,1,0,122066.5,1 -1267,15749050,Justice,548,France,Female,36,3,0,1,1,0,65996.9,0 -1268,15781586,Osonduagwuike,837,Germany,Male,38,2,126732.85,1,1,1,79577.38,0 -1269,15617078,Ewing,658,France,Female,44,6,148481.09,1,1,0,130529.13,0 -1270,15723339,Chin,554,France,Female,38,4,137654.05,2,1,1,172629.67,0 -1271,15671322,Chiang,724,Germany,Male,30,7,115315.04,1,1,0,15216.53,0 -1272,15793854,Ahmed,723,France,Male,42,2,99095.73,1,1,1,17512.53,0 -1273,15756539,Marshall,585,Germany,Female,39,7,165610.41,2,0,0,131852.01,0 -1274,15612064,Tsou,474,France,Male,33,5,0,2,1,0,181945.52,1 -1275,15625916,Chien,562,Spain,Male,32,6,161628.66,1,1,0,91482.5,0 -1276,15683195,Ubanwa,719,France,Male,32,9,146605.27,1,1,1,77119.45,0 -1277,15690182,Kapustin,635,Germany,Male,37,5,113488.68,1,1,0,95611.74,1 -1278,15721719,Calabresi,743,France,Male,42,7,77002.2,2,1,1,80428.42,0 -1279,15641690,Hsiao,681,Spain,Male,67,7,0,2,0,1,163714.92,0 -1280,15634896,Grant,521,France,Female,39,6,0,2,0,1,27375.15,0 -1281,15671590,H?,741,Spain,Male,25,4,0,2,1,1,73873.65,0 -1282,15779182,Chia,790,Spain,Male,46,8,182364.53,1,0,0,139266.48,1 -1283,15778287,Ugoji,622,France,Male,35,8,0,2,1,1,131772.51,0 -1284,15609510,Gregory,669,France,Male,45,7,149364.58,1,0,1,173454.07,0 -1285,15742229,Mackay,583,France,Male,59,7,127450.14,1,0,1,67552.71,0 -1286,15658532,Nnamutaezinwa,520,Spain,Female,63,5,162278.32,1,1,1,34765.33,0 -1287,15590993,Findlay,579,Spain,Male,37,5,152212.88,2,0,0,120219.14,0 -1288,15565701,Ferri,698,Spain,Female,39,9,161993.89,1,0,0,90212.38,0 -1289,15597239,Ku,548,Spain,Male,39,7,131468.44,1,1,0,164975.82,0 -1290,15688880,Amechi,672,Germany,Male,40,10,102980.44,1,1,0,1285.81,1 -1291,15813917,Kirk,653,Germany,Male,31,9,143321.97,1,1,0,83679.46,0 -1292,15679611,Andrews,734,Spain,Female,37,2,130404.92,1,0,0,34548.74,0 -1293,15636589,Murray,794,France,Female,41,7,0,2,1,1,74275.08,0 -1294,15687752,Griffin,641,France,Male,30,2,87505.47,2,0,1,7278.57,0 -1295,15584363,Longstaff,824,France,Male,30,0,133634.02,1,1,1,162053.92,0 -1296,15737748,McWilliam,534,Spain,Female,33,3,151233.62,1,0,0,199336.63,0 -1297,15803365,Coffee,653,Spain,Male,55,2,70263.83,1,0,1,62347.71,0 -1298,15793247,Hancock,498,France,Male,34,5,0,2,1,1,91711.66,0 -1299,15572360,Clark,683,France,Male,30,10,57657.49,1,0,0,79240.9,0 -1300,15795166,Creswell,618,Germany,Male,42,8,153572.31,2,1,1,76679.6,0 -1301,15724620,Dodds,538,France,Male,37,1,134752.08,1,1,0,162511.55,0 -1302,15800856,Ewen,643,Spain,Male,34,3,83132.09,1,1,1,21360.88,0 -1303,15671097,Carter,428,France,Female,31,2,0,2,1,0,54487.43,0 -1304,15683930,Ch'iu,593,Germany,Female,32,9,134096.53,2,1,0,53931.05,1 -1305,15749004,Tsao,718,France,Female,31,0,118100.59,2,1,0,103165.15,0 -1306,15800434,Burgess,811,Germany,Male,52,10,76915.4,1,0,0,146359.81,1 -1307,15709117,Fanucci,823,Spain,Female,46,3,81576.75,1,1,1,28370.95,1 -1308,15638806,Blackburn,645,Spain,Male,49,2,0,2,0,0,10023.15,0 -1309,15662294,Bennett,710,France,Male,33,10,118327.17,2,1,1,192928.82,0 -1310,15690079,Boniwell,591,Spain,Male,30,8,124857.69,2,0,0,50485.7,0 -1311,15759317,Vasilieva,748,Germany,Female,27,2,90971.85,1,1,1,131662.47,0 -1312,15750497,Longo,850,France,Female,37,7,153147.75,1,1,1,152235.3,0 -1313,15596181,Kwemto,542,France,Male,38,8,65942.26,1,1,1,68093.23,1 -1314,15576602,Lawrence,809,France,Male,38,3,0,2,1,1,80061.31,0 -1315,15644833,Duncan,675,France,Male,54,2,0,1,1,0,149583.67,1 -1316,15734634,Bocharova,607,Spain,Female,27,5,100912.19,1,0,0,7631.27,0 -1317,15808689,Morres,850,France,Female,31,4,0,2,1,1,33082.81,0 -1318,15720702,Shih,789,France,Male,37,3,0,1,1,0,121883.87,1 -1319,15665077,Vogel,598,France,Female,43,5,0,3,1,1,100722.72,1 -1320,15763612,T'an,756,Germany,Male,41,2,124439.49,2,0,1,47093.11,0 -1321,15596493,Wisdom,687,France,Female,47,7,0,2,1,1,177624.01,0 -1322,15704483,Lorenzo,724,France,Male,40,6,0,2,0,0,106149.48,0 -1323,15598846,Shahan,700,France,Female,44,2,58781.76,1,1,0,16874.92,0 -1324,15629244,Bryant,635,Spain,Male,50,7,159453.64,2,0,0,54560.79,1 -1325,15765537,Liang,687,Germany,Male,26,2,142721.52,1,1,1,153605.75,0 -1326,15729975,Chidozie,613,France,Female,46,8,167795.6,1,0,1,44390.38,0 -1327,15682773,Hayward,781,France,Female,38,3,128345.69,2,1,0,63218.85,0 -1328,15688007,Liu,703,Spain,Male,20,3,165260.98,1,1,1,41626.78,0 -1329,15574331,Alexeeva,593,Germany,Female,62,3,118233.81,1,0,1,24765.53,1 -1330,15645572,Calabresi,743,France,Female,40,6,0,1,1,0,28280.8,1 -1331,15742854,Lettiere,640,Spain,Female,46,8,0,2,1,0,89043.19,0 -1332,15575417,Chou,849,Germany,Male,37,7,143452.74,2,1,1,17294.12,0 -1333,15796721,Nnamutaezinwa,778,France,Male,38,3,145018.49,2,1,1,126702.41,0 -1334,15734942,Nnamutaezinwa,539,Germany,Female,38,8,82407.51,1,1,0,13123.41,0 -1335,15664772,Greece,489,Germany,Male,28,1,79460.98,2,1,1,167973.63,0 -1336,15576683,Yin,568,Spain,Female,43,9,0,1,1,0,125870.79,1 -1337,15682563,Larionova,618,Spain,Male,38,5,126473.99,1,1,0,91972.49,0 -1338,15650889,Golubev,710,Germany,Female,30,10,133537.1,2,1,0,155593.74,0 -1339,15612108,Norman,625,France,Male,52,5,164978.01,1,1,1,67788.49,0 -1340,15761132,Capon,682,Spain,Male,46,7,128029.72,1,1,1,62615.35,0 -1341,15645511,Chukwudi,727,Spain,Male,43,2,97403.18,1,1,1,107415.02,1 -1342,15609824,Fedorov,794,France,Female,41,7,176845.41,3,1,0,166526.26,1 -1343,15640268,Avdeeva,652,Spain,Male,71,4,0,1,1,1,120107.1,0 -1344,15645778,Reid,670,Spain,Male,42,3,81589.04,1,1,0,188227.8,0 -1345,15691104,Kennedy,460,Germany,Female,40,6,119507.58,2,1,0,91560.63,1 -1346,15714567,Chan,568,Spain,Female,26,6,0,2,0,0,166495.2,0 -1347,15777826,Wofford,643,France,Male,30,5,94443.77,1,1,1,165614.4,0 -1348,15668445,Mai,521,France,Male,37,2,0,2,1,1,86372.24,0 -1349,15576162,King,615,France,Male,32,7,92199.84,1,1,1,2755.53,0 -1350,15778135,T'ao,575,Spain,Male,43,3,0,1,1,0,83594.51,0 -1351,15613141,Hsu,717,France,Female,41,3,135756.96,1,1,1,103706.41,0 -1352,15635435,White,648,France,Female,54,9,120633.42,1,0,0,5924.38,1 -1353,15596552,Stephens,535,Germany,Male,48,5,134542.73,1,1,1,58203.67,1 -1354,15623644,Frolov,626,Spain,Male,29,7,0,2,1,0,49361.84,0 -1355,15683403,Lombardi,611,Spain,Male,52,7,0,1,0,1,73585.18,1 -1356,15615029,Munro,734,Spain,Male,39,6,0,1,1,1,95135.27,0 -1357,15769005,Hayward,709,France,Male,49,4,154344.49,2,1,1,38794.57,0 -1358,15746326,Fields,591,France,Male,43,3,0,2,0,1,198926.36,0 -1359,15722364,Onwumelu,664,France,Male,43,9,189026.53,2,1,1,56099.86,0 -1360,15704954,Suffolk,431,France,Male,37,0,120764.08,1,1,1,117023.08,0 -1361,15694409,Tsao,647,Germany,Female,22,3,97975.82,2,0,1,62083,0 -1362,15754068,Judd,578,France,Male,32,4,0,2,1,1,141822.8,0 -1363,15683841,Hamilton,555,Germany,Male,41,10,113270.2,2,1,1,185387.14,0 -1364,15789095,T'ang,775,Spain,Male,30,4,0,2,0,1,57461.13,0 -1365,15719958,Degtyarev,850,Germany,Male,39,3,124548.99,2,1,1,120380.12,0 -1366,15689514,Kang,625,France,Male,43,8,201696.07,1,1,0,133020.9,1 -1367,15621353,Hudson,645,Spain,Female,37,7,0,2,1,0,13589.93,0 -1368,15627232,Jibunoh,608,Germany,Male,44,7,114203.47,1,1,1,77830.36,1 -1369,15745843,Kinlaw,689,Spain,Female,31,4,0,2,1,1,136610.02,0 -1370,15722902,Chizuoke,652,Germany,Male,50,8,125437.64,1,1,1,17160.94,1 -1371,15791767,Lucciano,769,France,Female,26,7,0,2,1,0,176843.53,0 -1372,15792722,Omeokachie,611,France,Female,43,8,64897.75,1,1,0,114996.33,0 -1373,15723006,Gorbunova,489,France,Male,38,8,0,2,0,1,196990.79,0 -1374,15771942,Tikhonov,528,Germany,Female,46,9,135555.66,1,1,0,133146.03,1 -1375,15774738,Campa,632,France,Male,44,3,107764.75,1,1,0,185667.72,0 -1376,15574004,Mancini,429,France,Female,27,6,117307.44,2,1,1,24020.49,0 -1377,15587233,Donoghue,457,France,Male,41,8,73700.12,3,1,1,185750.02,1 -1378,15808228,Tuan,768,Spain,Female,44,6,60603.4,1,1,1,178045.97,0 -1379,15682834,Johnstone,715,Spain,Female,35,4,40169.88,2,1,1,199857.47,0 -1380,15571752,Romani,668,Germany,Female,32,10,92041.87,1,1,1,43595.9,0 -1381,15743067,Fuller,625,Germany,Male,26,3,130483.95,1,1,0,122810.53,0 -1382,15714466,Baxter,846,France,Female,41,5,0,3,1,0,3440.47,1 -1383,15617982,Pirozzi,661,Spain,Female,42,3,0,2,1,0,35989.41,0 -1384,15696637,Sung,571,France,Female,23,10,151097.28,1,0,1,17163.75,0 -1385,15690647,Rogers,582,Spain,Female,46,8,67563.31,1,1,0,44506.09,1 -1386,15672756,Mills,716,France,Female,35,8,112808.18,1,0,1,17848.3,0 -1387,15704586,Osonduagwuike,758,France,Female,42,7,0,2,0,1,76209.56,0 -1388,15674526,Byrne,725,France,Male,66,4,86459.8,1,1,1,141476.56,0 -1389,15775295,McIntyre,630,France,Female,40,0,118633.08,1,0,1,60032.46,1 -1390,15684196,Aitken,627,France,Female,55,2,159441.27,1,1,0,100686.11,1 -1391,15727281,Macintyre,653,France,Female,27,9,0,2,1,0,96429.29,0 -1392,15787835,Simpson,775,Germany,Female,38,4,125212.65,2,1,1,15795.88,1 -1393,15730540,Simpson,794,Spain,Male,45,8,88656.37,2,1,0,116547.31,0 -1394,15646276,Metcalfe,831,France,Female,32,2,146033.62,1,1,0,191260.74,0 -1395,15582180,Lees,561,France,Male,29,9,120268.13,1,1,1,173870.39,0 -1396,15697095,Zetticci,705,Spain,Male,46,7,0,2,1,0,117273.35,0 -1397,15748797,Dale,636,Spain,Female,33,0,0,1,1,0,92277.47,1 -1398,15754796,Byrne,487,Germany,Female,46,4,135070.58,2,1,1,44244.49,1 -1399,15628947,Praed,693,France,Female,38,3,0,2,0,0,78133.48,1 -1400,15775546,Laurens,517,Spain,Female,29,5,0,2,1,0,103402.88,0 -1401,15670481,Woods,684,France,Female,27,9,122550.05,2,0,1,137835.82,0 -1402,15619029,Bykov,620,Spain,Female,43,2,0,2,1,0,20670.1,0 -1403,15613282,Vorobyova,757,France,Male,29,8,130306.49,1,1,0,77469.38,0 -1404,15721487,Pirogova,739,France,Female,27,6,0,1,1,1,57572.38,0 -1405,15797276,Sturt,662,Spain,Female,41,4,90350.77,1,1,0,75884.65,1 -1406,15612494,Panicucci,359,France,Female,44,6,128747.69,1,1,0,146955.71,1 -1407,15629617,Cook,572,Spain,Male,23,2,126873.52,1,0,1,67040.12,0 -1408,15600821,Hardy,721,France,Male,69,2,108424.19,1,1,1,178418.35,0 -1409,15579062,Chu,707,France,Male,32,9,0,2,0,0,30807.02,0 -1410,15814268,Franklin,444,France,Female,40,5,84350.07,1,1,0,143835.76,0 -1411,15710164,P'eng,523,France,Female,73,7,0,2,0,0,130883.9,1 -1412,15693904,Chiang,685,Germany,Female,30,4,84958.6,2,0,1,194343.72,0 -1413,15588986,Grant,673,Germany,Female,29,4,99097.36,1,1,1,9796.69,0 -1414,15797733,Udobata,503,Germany,Male,30,10,136622.55,2,0,0,47310.24,0 -1415,15620507,Siciliani,485,Germany,Female,30,5,156771.68,1,1,1,141148.21,0 -1416,15685150,Evans,799,Germany,Male,28,7,167658.33,2,1,1,111138.25,0 -1417,15667651,Young,585,Spain,Female,33,8,0,2,1,0,114182.07,0 -1418,15774166,Mitchell,607,Germany,Female,24,2,109483.54,2,0,1,127560.77,0 -1419,15649280,Lucchese,521,Germany,Female,40,9,134504.78,1,1,0,18082.06,0 -1420,15705657,Hewitt,535,France,Female,44,2,114427.86,1,1,1,136330.26,0 -1421,15753969,K'ung,724,Spain,Male,45,5,83888.54,1,0,1,34121.81,0 -1422,15742378,Swaim,520,Germany,Male,32,5,110029.77,1,1,0,56246.69,0 -1423,15794874,Quinones,696,Spain,Male,41,9,127523.75,1,0,1,191417.42,0 -1424,15589221,Kennedy,657,Germany,Male,30,1,139762.13,2,1,1,23317.88,0 -1425,15596671,Endrizzi,603,Spain,Female,42,8,91611.12,1,0,0,144675.3,1 -1426,15583668,Ludowici,726,France,Female,42,2,109471.79,1,0,1,175161.05,0 -1427,15710206,Larson,591,France,Female,39,4,150500.64,1,1,0,14928.8,0 -1428,15799966,Chigolum,792,Germany,Female,59,9,101609.77,1,0,0,161479.19,1 -1429,15794560,Maclean,550,France,Male,57,5,0,1,1,1,133501.94,0 -1430,15626485,Lu,601,France,Female,26,8,78892.23,1,1,1,23703.52,0 -1431,15703143,Tuan,820,France,Female,29,3,82344.84,1,0,1,115985.38,0 -1432,15809772,Glover,667,France,Male,48,2,0,1,1,0,43229.2,0 -1433,15687959,Landman,573,Spain,Female,44,4,0,1,1,1,94862.93,0 -1434,15585282,Trevisano,755,France,Male,62,1,127706.33,2,0,1,142377.69,0 -1435,15714993,Longo,552,France,Female,41,9,124349.34,1,1,0,135635.25,0 -1436,15596021,K?,598,Spain,Male,44,8,0,2,1,0,148487.9,0 -1437,15646615,Muir,576,Germany,Male,28,1,119336.29,2,0,1,58976.85,0 -1438,15742632,Alexeyeva,670,France,Female,31,9,0,1,0,1,76254.83,0 -1439,15574068,Norman,504,Germany,Male,56,9,104217.3,1,0,0,55857.48,1 -1440,15806967,Simmons,778,France,Female,65,7,0,1,1,1,77867.23,0 -1441,15796334,Chukwualuka,558,Germany,Male,39,10,144757.02,1,1,0,22878.16,1 -1442,15688713,McCall,627,Spain,Male,44,6,0,1,1,1,114469.55,0 -1443,15796179,Moore,683,France,Male,43,8,0,1,1,0,96754.8,0 -1444,15598751,Ingram,556,France,Female,43,6,0,3,0,0,125154.57,1 -1445,15703019,Okeke,583,France,Female,38,10,0,2,0,1,113597.64,0 -1446,15646302,Shao,705,France,Female,24,7,100169.51,1,1,0,121408.55,0 -1447,15680855,Iloabuchi,637,France,Male,33,2,145731.83,1,0,1,109219.43,0 -1448,15697311,Nebechukwu,697,Spain,Male,56,5,110802.03,1,1,1,50230.31,1 -1449,15585367,Diribe,555,Germany,Female,46,4,120392.99,1,1,0,177719.88,1 -1450,15726556,Macgroarty,594,Germany,Female,26,6,135067.52,2,0,0,131211.86,0 -1451,15676242,Artemova,632,Spain,Male,31,3,136556.44,1,1,0,82152.83,1 -1452,15684198,McDonald,551,France,Female,38,10,0,2,1,1,216.27,0 -1453,15774882,Mazzanti,687,France,Female,35,3,99587.43,1,1,1,1713.1,1 -1454,15714227,Kelly,672,France,Female,53,7,0,1,1,1,136910.18,0 -1455,15608653,Davison,521,Spain,Female,34,7,70731.07,1,1,1,20243.97,1 -1456,15784280,Reilly,686,Germany,Male,35,2,109342.82,2,0,1,86043.27,0 -1457,15789546,Ojiofor,639,Spain,Male,28,8,0,2,1,0,126561.07,0 -1458,15590320,Shelton,850,France,Male,66,4,0,2,0,1,64350.8,0 -1459,15678385,Lange,465,France,Male,25,2,78247.31,2,1,1,10472.31,0 -1460,15571778,Trentini,817,France,Female,55,10,117561.49,1,1,0,95941.55,1 -1461,15657085,Gardiner,578,France,Male,23,10,88980.32,1,1,1,125222.36,0 -1462,15640627,Wan,611,Spain,Male,34,4,0,2,1,0,170950.58,0 -1463,15566211,Hsu,616,Germany,Female,41,1,103560.57,1,1,0,236.45,1 -1464,15669293,Hovell,517,France,Male,37,5,113308.84,1,0,1,31517.16,0 -1465,15595067,Zhirov,637,Spain,Female,40,6,0,2,1,1,181610.6,0 -1466,15753566,Espinosa,806,France,Female,32,3,63763.49,1,1,0,156593.09,0 -1467,15650391,Wallace,633,France,Female,29,7,169988.35,1,1,0,4272,0 -1468,15681843,Barbour,624,Germany,Female,35,0,180303.24,2,1,0,163587.9,0 -1469,15814846,Ozerova,691,France,Male,52,3,0,1,1,0,175843.68,1 -1470,15670374,Wright,819,Germany,Female,49,1,120656.86,4,0,0,166164.3,1 -1471,15762332,Ulyanova,568,Germany,Female,31,1,61592.14,2,1,1,61796.64,0 -1472,15700223,Steiner,806,France,Male,48,4,164701.68,1,1,1,21439.49,0 -1473,15729956,Akabueze,726,Spain,Female,26,1,80780.16,1,1,1,19225.85,0 -1474,15594862,Aleksandrova,552,France,Male,36,8,0,2,0,0,132547.02,0 -1475,15598782,Pinto,755,Germany,Female,30,6,154221.37,2,0,1,62688.55,0 -1476,15745080,Griffiths,634,France,Male,26,8,0,1,1,0,21760.96,0 -1477,15703399,McNeil,756,France,Female,26,5,101641.14,2,0,1,154460.68,0 -1478,15732175,Bruno,776,France,Male,37,2,0,1,0,1,8065,0 -1479,15630725,Johnson,649,France,Female,45,5,92786.66,1,1,0,173365.9,1 -1480,15640260,Okorie,595,Germany,Male,32,8,131081.66,2,1,1,69428.79,0 -1481,15716822,Moen,646,France,Male,30,5,98014.74,1,1,1,12757.14,0 -1482,15583748,McGuigan,592,Spain,Male,38,8,0,2,1,0,180426.2,0 -1483,15605968,Fancher,574,France,Male,26,8,97460.1,1,1,1,43093.67,0 -1484,15790683,Matthews,850,France,Male,36,1,104077.19,2,0,1,68594,0 -1485,15607713,Kaeppel,850,Spain,Female,29,1,0,2,1,1,197996.65,0 -1486,15700212,Shih,475,France,Female,46,10,0,2,0,0,122953,1 -1487,15626710,Yudina,642,France,Female,39,4,0,1,1,1,76821.24,0 -1488,15716491,Akabueze,710,Spain,Female,51,4,93656.95,1,0,1,141400.51,1 -1489,15625824,Kornilova,596,Spain,Male,30,6,121345.88,4,1,0,41921.75,1 -1490,15617705,Ozioma,609,France,Female,39,8,141675.23,1,0,1,175664.25,0 -1491,15761976,Su,797,Spain,Female,31,8,0,2,1,0,117916.63,0 -1492,15634891,Jamison,504,Germany,Female,43,7,102365.49,1,1,0,194690.77,1 -1493,15744517,Esposito,735,Spain,Male,50,9,0,1,0,0,166677.35,1 -1494,15686963,Hardiman,680,Spain,Female,30,3,0,1,1,0,160131.58,0 -1495,15808189,Woodard,449,France,Male,52,6,0,2,0,1,123622,0 -1496,15580845,Chienezie,685,Germany,Male,57,7,101868.51,1,0,1,113483.96,0 -1497,15799156,Okwuadigbo,569,Spain,Male,38,8,0,2,0,0,79618.79,0 -1498,15694296,Chineze,631,France,Male,35,9,112392.45,2,1,0,24472.23,0 -1499,15677049,O'Brien,595,Germany,Female,25,7,106570.34,2,0,1,177025.79,0 -1500,15583595,Tao,461,France,Female,28,8,0,1,1,1,103349.74,0 -1501,15590146,Mao,630,France,Male,50,1,81947.76,1,0,1,63606.22,1 -1502,15801548,Buckland,661,France,Female,31,7,144162.3,2,1,1,14490.79,0 -1503,15660833,Flannery,796,Germany,Male,39,5,86350.87,2,0,0,105080.53,0 -1504,15762277,Jamieson,710,France,Male,47,5,158623.14,1,0,0,83499.89,1 -1505,15791302,Swift,741,France,Male,32,8,0,2,1,0,143598.7,0 -1506,15798975,Doherty,606,Germany,Male,48,4,132403.56,1,0,0,36091.91,1 -1507,15599956,Payne,747,France,Male,27,10,0,2,0,0,13007.89,0 -1508,15577274,Genovese,549,Germany,Female,43,3,134985.66,1,1,0,6101.41,0 -1509,15701200,Lucciano,576,France,Male,36,6,0,2,1,1,48314,0 -1510,15638149,Rowley,528,France,Male,37,6,103772.45,1,1,0,197111.99,0 -1511,15786199,Hsing,535,France,Male,33,2,133040.32,1,1,1,110299.78,0 -1512,15701765,Vincent,575,Spain,Female,37,0,0,2,0,0,30114.32,0 -1513,15586974,Pearce,656,France,Male,39,10,0,2,1,1,98894.64,0 -1514,15729040,Lamb,440,France,Male,42,2,0,2,1,0,49826.68,0 -1515,15788676,Riley,539,Spain,Male,38,8,71460.67,2,1,1,10074.05,0 -1516,15602497,Honore,850,Spain,Male,39,6,133214.13,1,0,1,20769.88,0 -1517,15701333,Blackburn,646,France,Female,37,7,96558.66,1,0,0,163427.18,0 -1518,15812071,Endrizzi,744,France,Male,54,6,93806.31,2,0,1,140068.77,0 -1519,15634375,Duncan,710,Spain,Female,36,8,0,2,0,0,83206.19,0 -1520,15738267,Macarthur,544,France,Female,64,3,124043.8,1,1,1,111402.97,1 -1521,15786800,Gould,723,Germany,Male,52,5,131694.97,1,0,1,92873.5,1 -1522,15591130,Medvedev,507,Spain,Female,29,6,0,2,0,1,94780.9,0 -1523,15720662,Sholes,787,France,Female,35,1,106266.8,1,1,1,16607.15,0 -1524,15751531,Shaw,598,Spain,Male,41,8,0,2,1,1,161954.43,0 -1525,15653595,Ts'ai,796,France,Male,51,6,0,2,0,1,194733.28,0 -1526,15568360,Rolon,569,Spain,Female,41,4,139840.36,1,1,1,163524.7,0 -1527,15781210,Reid,711,France,Male,34,8,0,2,0,0,48260.19,0 -1528,15668058,Chinwendu,661,Germany,Male,35,8,124098.54,1,1,0,86678.48,0 -1529,15597131,Fu,415,France,Male,32,5,145807.59,1,1,1,3064.65,0 -1530,15697283,Mackenzie,578,Spain,Male,23,8,0,2,1,0,112124.98,0 -1531,15640953,Bligh,611,France,Female,26,2,107508.93,2,1,1,120801.65,0 -1532,15715031,Davidson,600,France,Female,28,6,0,2,0,1,52193.23,0 -1533,15589660,Lamble,661,Germany,Female,32,1,145980.23,1,0,1,56636.28,0 -1534,15769818,Moore,850,France,Female,37,3,212778.2,1,0,1,69372.88,0 -1535,15782736,Jose,573,Germany,Female,47,4,152522.47,1,0,1,164038.07,1 -1536,15614818,Trevisani,764,Spain,Female,33,9,168964.77,1,0,1,118982.51,0 -1537,15794014,Schofield,838,France,Female,34,8,0,2,1,0,27472.07,0 -1538,15732448,Stewart,821,France,Female,28,8,0,1,1,1,36754.13,0 -1539,15723411,Jamieson,607,Spain,Female,36,4,98266.3,1,1,1,46416.36,0 -1540,15797686,Howard,558,France,Male,38,8,113000.92,1,1,1,152872.39,0 -1541,15605950,Onwuamaeze,530,Germany,Male,23,1,137060.88,2,1,1,165227.23,0 -1542,15812497,D'Albertis,654,Germany,Male,37,5,112146.12,1,1,0,75927.35,0 -1543,15690678,Brooks,530,France,Female,33,4,129307.32,1,1,1,172930.28,0 -1544,15747677,Gordon,656,Spain,Male,69,6,163975.09,1,1,1,36108.5,0 -1545,15618926,Nwachukwu,520,Spain,Male,43,7,0,2,1,1,36202.74,0 -1546,15673908,Chinweike,602,Germany,Female,42,6,158414.85,1,1,1,131886.46,0 -1547,15727944,Simpkinson,701,Germany,Female,48,1,92072.68,1,1,1,133992.36,0 -1548,15807294,Walker,653,Spain,Female,30,2,88243.29,2,1,1,96658.26,0 -1549,15618581,Diribe,668,Spain,Male,25,8,0,2,1,1,135112.09,0 -1550,15584364,Trentini,652,France,Male,48,4,59486.31,1,1,0,163944.18,1 -1551,15599552,Conway,639,Spain,Female,54,2,0,2,1,1,53843.71,0 -1552,15749177,Maslow,730,Spain,Female,52,7,0,2,0,1,122398.84,0 -1553,15718779,Clark,780,France,Male,34,1,0,1,1,1,64804.04,0 -1554,15568106,L?,592,France,Female,38,8,119278.01,2,0,1,19370.73,0 -1555,15779481,Swadling,628,France,Male,34,4,158741.43,2,1,1,126192.54,0 -1556,15709994,Gallo,658,France,Female,40,7,140596.95,1,0,1,135459.02,1 -1557,15772777,Onyemachukwu,850,Spain,Female,29,10,0,2,1,1,94815.04,0 -1558,15706815,Samoylova,515,Germany,Male,37,2,90432.92,1,1,1,188366.04,1 -1559,15618018,Dickson,571,France,Female,35,1,104783.81,2,0,1,178512.52,0 -1560,15671032,He,760,Germany,Male,42,0,77992.97,2,1,1,97906.38,0 -1561,15634281,P'an,720,Germany,Female,43,10,110822.9,1,0,0,72861.94,0 -1562,15766374,Leak,632,Germany,Male,42,4,119624.6,2,1,1,195978.86,0 -1563,15600991,Artemieva,694,Germany,Male,31,6,109052.59,2,1,1,19448.93,1 -1564,15777576,Frost,559,Spain,Female,40,5,139129.44,1,0,1,32635.54,0 -1565,15742613,Warner,773,Germany,Female,42,8,152324.66,2,1,0,171733.22,0 -1566,15649523,Kennedy,581,France,Male,38,1,0,2,1,0,46176.22,0 -1567,15651063,Ifeatu,524,Germany,Female,37,9,127480.58,2,1,0,179634.69,0 -1568,15683124,Evans,713,France,Male,53,6,115029.4,1,0,0,191521.32,1 -1569,15618314,Chu,676,France,Male,40,8,114005.78,1,1,1,67998.45,0 -1570,15670823,Hsueh,651,Germany,Female,42,1,116646.76,1,1,0,44731.8,1 -1571,15607133,Shih,717,Spain,Female,49,1,110864.38,2,1,1,124532.9,1 -1572,15615012,Fan,594,France,Male,23,5,156267.59,1,1,0,160968.44,0 -1573,15725141,Whiddon,716,France,Female,44,3,109528.28,1,1,0,27341.63,1 -1574,15623560,Onyekachukwu,668,France,Female,35,6,102482.76,1,1,1,53994.64,0 -1575,15693018,Ermakova,678,Germany,Male,23,10,115563.71,1,1,1,91633.53,0 -1576,15636756,Marino,545,France,Male,23,2,0,2,1,0,189613.12,0 -1577,15647474,Niu,613,France,Female,40,9,95624.36,2,1,1,60706.33,0 -1578,15576714,Manna,687,Spain,Female,21,8,0,2,1,1,154767.34,0 -1579,15585047,Onyemere,715,France,Male,28,7,160376.61,1,0,0,196853.11,0 -1580,15743976,Archer,618,Germany,Male,41,8,37702.79,1,1,1,195775.48,0 -1581,15793881,Mitchell,721,France,Female,35,6,118273.83,1,0,1,3086.89,0 -1582,15576517,Everingham,445,Germany,Female,34,7,131082.17,2,1,1,70618,0 -1583,15631072,Huie,690,France,Male,38,1,94456,2,0,1,55034.02,0 -1584,15730394,Crowther,709,France,Female,43,8,0,2,0,0,168035.62,1 -1585,15631460,Swift,671,Spain,Female,42,3,0,2,1,1,128449.33,0 -1586,15692002,Skelton,538,France,Male,33,6,93791.38,1,1,1,199249.29,0 -1587,15595282,White,735,France,Female,33,4,0,2,1,0,149474.69,0 -1588,15789548,Giordano,592,France,Female,37,7,0,2,1,1,126726.33,0 -1589,15758035,Bateson,747,France,Male,61,7,155973.13,1,0,1,147554.26,0 -1590,15617518,Hu,675,Germany,Male,36,7,89409.95,1,1,1,149399.7,0 -1591,15651802,Day,632,Spain,Female,39,5,97854.37,2,1,0,93536.38,0 -1592,15631813,Beneventi,621,France,Male,39,6,0,2,1,1,58883.91,0 -1593,15729668,Elizabeth,521,Spain,Male,29,3,60280.62,1,1,0,154271.41,0 -1594,15741728,Atkins,591,Spain,Male,36,7,135216.8,1,1,1,122022.89,0 -1595,15576676,Serrano,706,Germany,Female,28,6,124923.35,2,1,1,50299.14,0 -1596,15711378,Willis,677,France,Male,38,4,0,2,1,0,187800.63,0 -1597,15765520,Stevenson,769,Germany,Male,27,7,188614.07,1,1,0,171344.09,0 -1598,15656726,Ch'ien,771,France,Male,32,5,62321.62,1,1,1,40920.59,0 -1599,15647842,Cunningham,601,Germany,Female,48,8,120782.7,1,1,0,63940.68,1 -1600,15719309,Stephens,670,France,Female,42,1,115961.58,2,0,1,29483.87,0 -1601,15748718,Gordon,517,France,Male,28,2,115062.61,1,1,0,179056.23,0 -1602,15594404,Bevan,834,France,Female,49,8,160602.25,2,1,0,129273.94,0 -1603,15751158,Mashman,571,France,Female,42,4,108825.34,3,1,0,55558.51,1 -1604,15593470,Tu,576,Germany,Female,36,8,166287.85,1,1,1,23305.85,0 -1605,15695129,Milanesi,718,France,Female,31,1,152663.77,1,0,1,17128.64,0 -1606,15640865,Romano,636,Germany,Female,31,9,80844.69,2,1,1,74641.9,0 -1607,15714080,Goliwe,566,Germany,Female,40,2,97001.36,2,1,0,154486.01,0 -1608,15648721,Hsueh,711,France,Male,64,4,0,2,1,1,3185.67,0 -1609,15801466,Gray,574,France,Female,39,2,122524.61,2,1,0,88463.63,0 -1610,15750248,Wright,619,France,Female,35,8,132292.63,1,1,0,65682.93,0 -1611,15758726,Chiemeka,588,France,Female,24,0,0,2,1,1,140586.08,0 -1612,15781553,Chung,760,Germany,Female,49,9,91502.99,1,1,0,117232.9,1 -1613,15649121,Pinto,665,France,Male,52,3,0,1,1,0,116137.01,1 -1614,15674811,Kellway,739,Germany,Male,29,3,59385.98,2,1,1,105533.96,0 -1615,15646037,Sopuluchi,641,France,Male,77,9,0,3,1,1,81514.06,0 -1616,15722578,Spitzer,685,Germany,Female,21,6,97956.5,1,1,1,164966.27,0 -1617,15665695,Potter,594,France,Female,49,4,0,2,1,1,23631.55,0 -1618,15801062,Matthews,557,Spain,Female,40,4,0,2,0,1,105433.53,0 -1619,15662955,Nicholls,697,France,Male,27,8,141223.68,2,1,0,90591.15,0 -1620,15770309,McDonald,656,France,Male,18,10,151762.74,1,0,1,127014.32,0 -1621,15657386,Fiorentini,712,Germany,Male,43,1,141749.74,2,0,1,90905.26,0 -1622,15777797,Kovalyova,689,Spain,Male,38,5,75075.14,1,1,1,8651.92,1 -1623,15783955,Miah,697,France,Female,25,4,165686.11,2,1,0,15467.98,0 -1624,15804516,Builder,589,France,Male,38,2,0,1,1,0,79915.28,0 -1625,15681758,Baddeley,525,Spain,Female,25,10,0,2,1,0,69361.95,0 -1626,15630321,Hu,680,France,Male,44,3,0,2,1,0,86935.08,0 -1627,15588248,Hs?,617,France,Female,28,0,0,2,1,1,7597.83,1 -1628,15591932,Ford,680,France,Male,32,5,92961.61,1,1,0,116957.6,0 -1629,15810347,Todd,662,Spain,Female,30,9,0,2,0,1,157884.83,0 -1630,15595303,Johnston,736,Germany,Male,46,5,130812.91,1,1,1,77981.54,1 -1631,15634950,Obiajulu,657,Germany,Male,57,8,107174.58,1,1,1,126369.55,1 -1632,15685372,Azubuike,350,Spain,Male,54,1,152677.48,1,1,1,191973.49,1 -1633,15745827,Padovesi,617,France,Male,30,3,132005.77,1,1,0,142940.39,0 -1634,15755868,Farmer,562,France,Male,35,7,0,1,0,0,48869.67,0 -1635,15735222,Ignatieff,705,Spain,Female,23,5,0,2,1,1,73131.73,0 -1636,15604804,Lu,516,France,Female,33,7,127305.5,1,1,1,120037.36,0 -1637,15718944,Artemiev,573,France,Female,37,6,0,2,1,0,193995.37,0 -1638,15678626,Okonkwo,538,Spain,Female,31,0,0,2,0,0,179453.66,0 -1639,15571550,Dore,699,France,Male,39,9,0,1,1,0,80963.92,0 -1640,15723053,T'ang,504,Germany,Male,32,8,170291.22,2,0,1,15658.99,0 -1641,15661528,Ashbolt,583,Spain,Male,47,5,102562.23,1,1,0,92708.1,0 -1642,15754177,Bazarova,712,Spain,Male,53,2,111061.01,2,0,0,26542.17,0 -1643,15683544,Buccho,626,Spain,Male,62,3,0,1,1,1,65010.74,0 -1644,15708048,Burn,631,France,Female,34,4,124379.14,1,1,0,106892.91,0 -1645,15701109,Andreyev,663,France,Female,37,7,0,1,1,1,185210.63,0 -1646,15600110,Endrizzi,506,Germany,Female,41,3,57745.76,1,1,0,4035.46,0 -1647,15651533,Brown,570,Germany,Female,50,5,129293.74,1,1,0,177805.44,1 -1648,15777904,Nock,703,France,Female,45,7,0,2,1,1,68831.72,0 -1649,15655574,Okeke,698,Germany,Female,40,8,150777.1,1,1,0,114732.62,0 -1650,15569423,Cunningham,731,Spain,Male,41,4,0,2,1,0,22299.27,0 -1651,15718106,Kelley,625,France,Male,34,6,0,2,0,0,197283.2,0 -1652,15585067,Wilson,634,Spain,Male,31,9,108632.48,1,1,1,179485.96,1 -1653,15675501,Woods,616,France,Male,59,5,153861.1,1,1,1,17699.48,0 -1654,15633233,McFarland,500,France,Male,56,1,100374.58,1,1,0,118490.8,1 -1655,15667134,Cisneros,446,France,Male,32,8,0,2,0,0,133292.94,0 -1656,15659105,Borchgrevink,669,France,Female,47,9,61196.54,1,1,0,58170.24,0 -1657,15575409,Rozhkova,581,Germany,Male,31,6,116891.72,1,1,0,107137.3,0 -1658,15752342,Bradley,704,Germany,Female,54,6,133656.91,3,1,0,145071.33,1 -1659,15654851,Obialo,748,France,Male,44,2,92911.52,1,0,1,85495.24,0 -1660,15741429,Hudson,680,Spain,Female,31,9,119825.75,2,1,1,101139.3,0 -1661,15682356,Veltri,655,France,Female,37,7,111852.84,2,1,0,10511.13,0 -1662,15806447,Mazzanti,690,Germany,Male,32,0,106683.52,2,1,1,137916.49,0 -1663,15800229,Thorpe,695,Germany,Male,40,7,139022.24,1,0,1,193383.13,0 -1664,15663441,Golibe,700,Germany,Female,40,4,148571.07,1,1,0,189826.96,1 -1665,15791991,Udinesi,773,France,Male,52,4,0,1,0,1,144113.42,0 -1666,15775082,Stewart,749,France,Male,42,1,129776.72,2,0,1,143538.51,0 -1667,15579706,Curtis,611,France,Female,46,5,0,1,1,0,77677.14,1 -1668,15718247,Hayden,606,Spain,Female,46,8,0,2,1,1,183717.94,0 -1669,15755722,H?,554,France,Male,24,10,0,1,0,0,92180.62,0 -1670,15582259,Campbell,567,France,Female,37,7,0,2,1,1,28690.9,0 -1671,15716994,Green,559,Spain,Male,24,3,114739.92,1,1,0,85891.02,1 -1672,15586880,P'eng,594,Germany,Male,41,2,122545.65,2,1,1,42050.24,0 -1673,15713854,Cremonesi,513,France,Female,37,6,0,2,1,0,110142.34,0 -1674,15780835,Liang,652,Germany,Female,26,1,131908.35,1,1,1,179269.79,0 -1675,15675896,Gough,680,Germany,Female,42,7,105722.69,1,1,1,90558.24,1 -1676,15658459,Bates,784,Spain,Male,33,10,0,2,1,0,162022.47,0 -1677,15658057,Padovesi,812,Spain,Female,44,8,0,3,1,0,66926.83,1 -1678,15801767,Yin,784,Spain,Female,40,8,0,2,1,0,108891.3,0 -1679,15569178,Kharlamov,570,France,Female,18,4,82767.42,1,1,0,71811.9,0 -1680,15731478,Nicholls,712,France,Female,42,1,87842.98,1,0,0,92223.59,0 -1681,15811236,Burns,705,Spain,Male,39,6,133261.13,1,1,1,78065.9,0 -1682,15746749,Fleming,681,Spain,Female,32,3,0,2,1,1,59679.9,0 -1683,15662758,Watson,620,France,Male,41,0,97925.11,1,1,0,85000.32,0 -1684,15709387,Obiajulu,711,France,Male,52,5,0,1,1,1,159808.95,0 -1685,15572093,Han,613,France,Female,24,7,140453.91,1,1,0,129001.3,0 -1686,15713826,Ferguson,613,Germany,Female,20,0,117356.19,1,0,0,113557.7,1 -1687,15570205,Tao,682,Spain,Male,36,5,0,2,1,1,147758.51,0 -1688,15589348,Le Grand,850,Spain,Male,37,4,137204.77,1,1,1,28865.59,0 -1689,15804610,Valdez,601,France,Female,41,1,0,2,0,1,160607.06,0 -1690,15700854,Cunningham,595,Spain,Male,35,8,0,1,1,0,100015.79,1 -1691,15758836,Godfrey,675,Spain,Male,36,3,54098.18,2,0,1,54478.52,0 -1692,15772933,Mai,591,Spain,Male,31,8,0,1,1,1,141677.33,0 -1693,15809006,Walker,602,France,Male,23,7,113758.48,2,0,0,84077.6,0 -1694,15689612,Pirozzi,554,Spain,Female,34,8,0,1,0,1,106981.03,0 -1695,15744614,Feng,541,France,Male,37,9,118636.92,1,1,1,73551.44,0 -1696,15704250,Akabueze,506,France,Male,34,7,0,2,0,0,115842.1,0 -1697,15700255,Robson,814,Germany,Male,44,8,95488.82,2,0,0,107013.59,0 -1698,15669410,Yevdokimova,683,France,Male,30,8,110829.52,2,0,0,24938.84,0 -1699,15807595,Ijendu,485,Germany,Male,51,7,144244.59,2,1,0,51113.14,0 -1700,15664523,Colombo,696,Germany,Female,31,8,122021.92,2,1,0,33828.64,0 -1701,15642833,Akubundu,608,France,Female,30,8,0,2,1,0,128875.86,0 -1702,15605279,Francis,792,France,Male,50,9,0,4,1,1,194700.81,1 -1703,15713644,Marshall,686,Spain,Male,22,5,0,2,1,0,158974.45,0 -1704,15750466,Rhodes,790,Germany,Male,42,1,85839.62,1,1,0,198182.73,0 -1705,15739054,Y?,654,France,Female,29,4,96974.97,1,0,1,141404.07,0 -1706,15612771,Bell,452,France,Male,35,4,148172.44,1,1,1,4175.68,0 -1707,15788483,Kerr,719,Spain,Male,38,0,0,1,1,0,126876.47,0 -1708,15732832,Jideofor,707,France,Female,40,5,0,2,1,0,41052.82,0 -1709,15772892,Robertson,699,France,Female,49,2,0,1,0,0,105760.01,0 -1710,15713843,Kao,850,Spain,Male,30,2,0,2,0,1,27937.12,0 -1711,15567993,Palmer,828,Spain,Male,28,8,134766.85,1,1,0,79355.87,0 -1712,15617603,Mackay,850,Germany,Male,30,5,123210.56,2,1,1,102180.27,0 -1713,15744983,Burgmann,712,Spain,Male,47,1,139887.01,1,1,1,95719.73,0 -1714,15630419,Davis,634,France,Male,44,9,149961.11,1,1,0,57121.51,0 -1715,15738828,Milano,730,Germany,Male,45,6,152880.97,1,0,0,162478.11,0 -1716,15778025,Dellucci,685,Germany,Male,43,9,108589.47,2,0,1,194808.51,0 -1717,15799479,Coles,809,Spain,Male,33,9,0,1,1,1,124045.65,0 -1718,15684269,Gray,707,Spain,Female,35,3,56674.48,1,1,0,17987.4,1 -1719,15762745,Macvitie,648,Spain,Male,32,8,0,1,1,0,133653.38,0 -1720,15746970,Townsend,760,Spain,Female,57,1,0,2,1,1,25101.17,0 -1721,15725024,Pope,805,Germany,Female,33,3,105663.56,2,0,1,33330.89,0 -1722,15592116,Jensen,585,France,Female,39,7,0,2,1,0,2401.26,0 -1723,15624391,Thomson,595,Spain,Female,30,5,100683.54,1,1,1,178361.04,0 -1724,15567422,Chiazagomekpele,630,France,Male,42,6,0,2,1,0,162697.93,0 -1725,15612627,Ozuluonye,627,Germany,Male,29,5,139541.58,2,1,0,80607.33,0 -1726,15574879,Wright,631,Germany,Female,37,2,121801.72,2,0,1,23146.62,0 -1727,15745107,Lung,776,Germany,Male,38,5,112281.7,1,0,1,89893.6,0 -1728,15734491,Lombardo,676,Spain,Female,36,4,0,2,1,1,3173.31,0 -1729,15675320,Leonard,758,Spain,Female,40,5,93499.82,2,0,0,123218.81,0 -1730,15643824,Johnston,637,France,Male,33,0,132255.99,2,0,1,74588.41,0 -1731,15643438,P'eng,850,France,Male,20,7,0,2,1,0,31288.77,0 -1732,15721730,Amechi,601,Spain,Female,44,4,0,2,1,0,58561.31,0 -1733,15680727,Fang,735,France,Male,49,5,121973.28,1,1,0,148804.36,0 -1734,15752508,Docherty,614,Germany,Male,32,7,99462.8,2,1,1,51117.06,0 -1735,15808846,Horton,672,Germany,Female,21,3,165878.76,2,1,1,164537.17,0 -1736,15727251,Vincent,642,France,Male,30,8,117494.27,1,0,0,61977.82,0 -1737,15663489,Onio,633,Germany,Female,29,0,138577.34,1,1,0,193362.99,0 -1738,15683677,Schiavone,769,Spain,Male,39,9,0,1,1,1,47722.79,0 -1739,15596414,Chandler,796,Spain,Male,41,8,107525.07,1,1,0,18510.41,0 -1740,15730639,Fiorentino,715,France,Male,23,7,139224.92,2,1,0,65057.71,0 -1741,15672132,Butusov,695,France,Female,42,7,121453.63,1,0,0,46374.64,0 -1742,15742638,Wang,747,France,Female,25,4,0,2,0,1,42039.67,0 -1743,15578603,Alexeieva,584,Germany,Female,54,1,77354.37,1,0,0,138192.98,1 -1744,15726088,Vinogradova,476,France,Male,40,6,0,1,1,1,22735.45,0 -1745,15682533,Hughes,850,France,Female,39,7,79259.99,1,0,1,186910.74,0 -1746,15772995,Ts'ao,529,France,Male,30,2,116295.29,1,1,0,75285.47,0 -1747,15765694,Bage,584,Spain,Female,59,1,0,1,0,1,130260.11,1 -1748,15659486,Yudina,586,Germany,Male,34,9,74309.81,1,1,0,15034.93,0 -1749,15568963,Naquin,674,Germany,Male,34,2,152797.9,1,1,0,175709.4,1 -1750,15703820,Endrizzi,552,France,Male,42,9,133701.07,2,1,0,101069.71,1 -1751,15569410,Tang,601,Germany,Female,33,7,114430.18,2,1,1,153012.13,0 -1752,15632256,Schroeder,541,France,Male,29,7,127504.57,1,0,0,86173.92,0 -1753,15724466,Swearingen,744,Germany,Female,41,2,84113.41,1,1,0,197548.63,0 -1754,15777639,McGregor,595,Spain,Female,23,10,101126.66,2,0,0,37042.8,0 -1755,15802501,Onyeorulu,724,Germany,Male,33,5,103564.83,2,1,0,121085.72,0 -1756,15778410,Clarke,533,Spain,Female,52,7,0,1,0,1,194113.99,1 -1757,15670702,Smith,618,France,Male,37,2,168178.21,2,0,1,101273.23,0 -1758,15704763,Kozlova,523,Germany,Female,39,1,143903.11,1,1,1,118711.75,1 -1759,15645544,Nekrasov,642,Germany,Female,30,5,129753.69,1,1,0,582.53,0 -1760,15757646,Olague,584,France,Male,35,9,0,2,1,0,192381.21,0 -1761,15701121,Holt,521,France,Male,38,5,110641.18,1,0,1,136507.69,1 -1762,15796313,Olsen,662,France,Female,36,4,166909.2,2,1,0,138871.12,1 -1763,15815660,Mazzi,758,France,Female,34,1,154139.45,1,1,1,60728.89,0 -1764,15602844,Niu,717,France,Male,38,7,97459.06,1,0,0,189175.71,0 -1765,15636238,Graham,611,France,Male,40,1,0,2,1,1,102547.56,0 -1766,15770101,Millar,766,Germany,Male,43,6,112088.04,2,1,1,36706.56,0 -1767,15645543,Bell,636,France,Female,34,3,0,2,1,1,44756.25,0 -1768,15596397,Kelly,814,France,Female,48,7,0,2,1,1,132870.15,0 -1769,15770525,T'an,760,Spain,Male,28,1,141038.57,2,0,0,16287.38,0 -1770,15684267,Davila,607,Germany,Male,39,2,84468.67,2,1,1,121945.42,0 -1771,15689980,Willis,725,Spain,Female,36,4,118520.26,1,0,0,131173.9,1 -1772,15633260,Dumetochukwu,600,France,Male,37,1,142663.46,1,0,1,88669.89,0 -1773,15756471,Giles,656,Germany,Male,27,4,118627.16,2,1,1,160835.3,0 -1774,15721303,O'Meara,640,Spain,Male,34,1,137523.02,1,0,0,24761.36,0 -1775,15802256,Yao,439,France,Male,28,7,110976.23,2,1,0,138526.96,0 -1776,15725664,Wallace,549,France,Female,38,8,107283.4,1,0,0,157442.75,0 -1777,15674851,T'ien,622,France,Male,38,5,0,2,0,0,105295.77,0 -1778,15701946,Ndubueze,715,France,Male,34,4,124314.45,1,0,0,97782.92,0 -1779,15748947,Chukwuraenye,657,France,Female,41,5,95858.37,1,1,1,68255.88,0 -1780,15673342,K'ung,703,France,Male,36,2,0,2,1,0,108790.95,0 -1781,15601008,Stevenson,802,France,Male,33,8,0,2,1,0,143706.18,0 -1782,15771636,Marshall,793,Spain,Female,36,0,0,1,0,0,148993.47,0 -1783,15642002,Hayward,554,France,Female,35,6,117707.18,2,0,0,95277.15,1 -1784,15693381,Tipton,533,Spain,Male,38,1,135289.33,2,0,1,152956.33,0 -1785,15607691,Gibson,658,France,Male,36,8,174060.46,1,1,1,94925.62,0 -1786,15589380,Fraser,713,Germany,Male,40,3,114446.84,2,1,1,87308.18,0 -1787,15603846,Fang,711,Spain,Male,37,2,0,2,1,0,83978.86,1 -1788,15753549,Dubinina,669,France,Male,25,1,157848.53,1,0,0,37543.93,1 -1789,15725355,Morey,439,France,Female,43,8,0,1,0,1,104889.3,0 -1790,15773017,Todd,763,Spain,Female,37,6,0,2,1,1,149705.25,0 -1791,15625641,Forbes,697,Germany,Female,74,3,108071.36,2,1,1,16445.79,0 -1792,15776467,De Salis,702,Spain,Female,35,8,14262.8,2,1,0,54689.16,0 -1793,15746451,Barry,686,Spain,Male,41,7,102749.72,1,0,1,194913.86,0 -1794,15777922,Afamefuna,629,Spain,Male,36,1,161757.87,2,1,1,146371.72,0 -1795,15606841,Ibbott,823,France,Male,38,1,0,2,1,0,156603.7,0 -1796,15757648,Marshall,683,Germany,Female,35,5,95698.79,1,0,1,182566.76,0 -1797,15677173,Law,555,France,Male,37,9,124969.13,1,1,0,60194.05,0 -1798,15764170,Pinto,647,Germany,Male,44,4,93960.35,1,1,0,36579.53,1 -1799,15610446,Chinedum,714,France,Female,51,4,88308.87,3,0,0,5862.53,1 -1800,15612776,McKay,850,Spain,Female,39,10,0,2,1,1,143030.09,0 -1801,15794122,Otutodilinna,713,France,Female,59,3,0,2,1,1,62700.08,0 -1802,15774931,She,452,France,Male,30,7,112935.87,1,1,1,99017.34,0 -1803,15779247,Pai,683,Spain,Female,24,8,98567.1,1,1,0,187987.01,0 -1804,15707078,Kruglov,577,France,Female,26,1,180530.51,1,0,0,123454.62,0 -1805,15605263,Chin,552,France,Male,33,5,140931.57,1,0,1,10921.5,0 -1806,15607381,King,769,Germany,Female,31,7,148913.72,2,1,0,53817.23,0 -1807,15683471,Hansen,691,France,Male,38,7,0,2,0,0,81617.4,0 -1808,15605037,Ting,818,France,Female,49,2,0,1,0,1,192298.84,1 -1809,15576085,Stone,739,France,Male,41,5,0,2,0,0,143882.25,0 -1810,15770435,McLean,639,France,Female,50,6,115335.32,2,1,1,53130.41,0 -1811,15592994,Zikoranachidimma,651,France,Female,65,0,0,2,1,1,190454.04,0 -1812,15624068,Fu,779,France,Female,26,0,0,2,0,1,111906,0 -1813,15595221,Trevisano,850,Germany,Female,33,7,134678.13,1,1,0,113177.95,0 -1814,15637131,Fallaci,829,France,Male,38,9,0,2,1,0,30529.88,0 -1815,15613471,Wiley,579,Germany,Male,31,2,90547.48,2,1,1,18800.13,0 -1816,15583499,Chiagoziem,510,France,Male,32,9,103324.78,1,1,1,46127.7,0 -1817,15752816,Murray,531,France,Male,29,3,114590.58,1,0,0,75585.48,0 -1818,15804075,Chuang,628,Germany,Female,36,3,91286.51,1,1,0,63085.94,0 -1819,15800517,Huang,633,Spain,Male,32,5,163340.12,2,1,1,74415.2,0 -1820,15712319,Chukwukere,714,Spain,Male,45,8,150900.29,2,0,1,139889.15,0 -1821,15797389,Hsia,604,Spain,Male,23,9,124577.33,1,1,1,7267.25,0 -1822,15621432,Lee,630,Spain,Male,35,1,0,2,0,0,186826.22,0 -1823,15779390,Theus,850,Spain,Female,31,4,91292.7,1,1,1,162149.07,0 -1824,15711219,Jennings,788,Germany,Female,57,8,93716.72,1,1,1,180150.49,1 -1825,15770498,Parker,798,France,Female,37,4,111723.08,1,1,1,83478.12,0 -1826,15678727,Tan,770,Germany,Male,45,4,110765.68,1,1,0,26163.74,1 -1827,15573893,Barry,569,Germany,Male,25,9,173459.45,2,1,1,44381.06,0 -1828,15740104,Tuan,425,Spain,Female,22,7,169649.73,2,0,1,136365,1 -1829,15792649,Patterson,547,Spain,Female,31,9,0,2,0,0,99294.22,0 -1830,15605275,Ofodile,725,Germany,Male,45,8,116917.07,1,0,0,173464.43,1 -1831,15572467,Chandler,506,France,Male,37,5,0,2,1,1,127543.81,0 -1832,15738219,Nash,632,France,Female,36,7,0,2,1,1,52526.65,0 -1833,15600710,Atkinson,620,France,Male,22,0,0,1,1,0,32589.45,0 -1834,15804394,Brenan,663,Germany,Male,32,8,130627.66,1,1,0,47161.25,1 -1835,15694188,Obidimkpa,700,Spain,Female,46,5,56580.95,2,0,1,45424.13,0 -1836,15583718,Terry,696,Germany,Male,38,6,142316.14,1,1,1,8018.49,0 -1837,15802478,Spring,767,Spain,Male,31,6,0,2,1,1,195668,0 -1838,15619343,Mahmood,561,France,Male,56,7,152759,2,1,0,133167.11,1 -1839,15758813,Campbell,350,Germany,Male,39,0,109733.2,2,0,0,123602.11,1 -1840,15761374,Bellucci,706,France,Male,54,9,117444.51,1,1,1,186238.85,0 -1841,15569209,Amaechi,464,Spain,Female,34,5,76001.57,1,1,1,158668.87,0 -1842,15788539,Foxall,501,France,Female,34,3,107747.57,1,1,0,9249.36,0 -1843,15747222,Bentley,745,Spain,Female,35,8,0,2,1,1,116581.1,0 -1844,15769346,Baird,587,France,Female,36,1,134997.49,2,1,0,44688.08,0 -1845,15699634,Howard,667,France,Female,48,2,0,2,1,1,148608.39,0 -1846,15589076,Henry,737,France,Male,36,9,0,1,0,1,188670.9,1 -1847,15812338,Sopuluchukwu,485,Spain,Female,30,7,0,1,1,0,107067.37,0 -1848,15758845,Rocher,590,Spain,Female,37,0,64345.21,1,0,1,61759.33,1 -1849,15685844,White,518,Germany,Female,35,8,141665.63,1,0,1,192776.64,0 -1850,15583090,Komar,581,Spain,Female,29,8,0,2,1,0,46735.19,0 -1851,15587581,Russo,785,Germany,Female,33,5,136624.6,2,1,1,169117.74,0 -1852,15633640,Loewenthal,799,France,Female,52,4,161209.66,1,1,1,89081.41,0 -1853,15573741,Aliyeva,698,Spain,Male,38,10,95010.92,1,1,1,105227.86,0 -1854,15633574,Montes,730,France,Female,41,4,167545.32,1,1,0,128246.81,0 -1855,15711455,Kuo,740,Germany,Female,36,4,109044.6,1,0,0,94554.74,1 -1856,15570601,Cheng,785,France,Female,47,9,122031.55,1,1,1,33823.5,1 -1857,15690925,McIntosh,527,Spain,Female,29,2,27755.97,1,1,0,97468.44,1 -1858,15709338,T'ao,544,France,Female,29,1,118560.55,1,1,1,164137.36,0 -1859,15780746,Tyndall,705,France,Male,61,4,0,2,1,1,191313.7,0 -1860,15681956,Bailey,684,France,Male,34,9,0,2,1,1,65257.57,0 -1861,15778190,Onyekaozulu,639,Spain,Female,28,8,97840.72,1,1,1,178222.77,0 -1862,15786852,Nwachukwu,565,Germany,Female,38,2,158651.29,2,1,1,179445.28,0 -1863,15726494,Romani,481,France,Male,44,9,175303.06,1,1,0,65500.53,1 -1864,15641183,Chin,731,Spain,Male,25,8,96950.21,1,1,0,97877.92,0 -1865,15805312,Bellucci,607,France,Male,45,7,123859.6,1,0,1,113051.57,0 -1866,15636572,Christmas,760,France,Female,32,7,0,2,1,1,105969.05,0 -1867,15632575,Moore,559,France,Female,70,9,0,1,1,1,122996.76,0 -1868,15740164,Genovesi,715,France,Female,33,3,85227.84,1,1,1,68087.15,0 -1869,15574947,Cartwright,656,France,Male,36,8,97786.08,2,0,1,21478.36,0 -1870,15597909,Johnstone,652,Germany,Male,33,7,128135.99,1,1,0,158437.73,0 -1871,15782574,Warner,624,Spain,Male,33,6,0,2,0,0,76551.7,0 -1872,15734999,Stephenson,634,Spain,Male,36,2,85996.19,1,1,0,15887.68,0 -1873,15706593,Ellis,850,Spain,Female,50,10,0,2,1,1,33741.84,0 -1874,15766686,Nebechi,659,Germany,Female,39,1,104502.11,1,1,0,20652.69,0 -1875,15590268,Chu,529,Spain,Male,35,5,95772.97,1,1,1,112781.5,0 -1876,15763055,Onuchukwu,572,Spain,Male,31,5,98108.79,1,0,1,119996.95,0 -1877,15664754,Steele,640,Germany,Male,39,9,131607.28,4,0,1,6981.43,1 -1878,15643630,Quaife,770,Spain,Male,55,9,63127.41,2,1,0,185211.28,1 -1879,15641043,Scott,648,Spain,Male,35,7,0,2,1,1,78436.36,0 -1880,15768095,Yeh,579,France,Male,31,9,0,1,0,1,139048,0 -1881,15811314,Y?,589,Germany,Female,36,9,140355.56,2,1,0,136329.96,0 -1882,15669922,Conti,530,Spain,Female,36,2,0,2,1,1,14721.8,0 -1883,15707114,Holder,831,France,Male,30,2,0,2,0,1,3430.38,0 -1884,15670602,Burgess,790,Germany,Male,24,7,107418.27,1,0,1,160450.21,0 -1885,15713479,Ozuluonye,656,France,Male,35,6,0,2,1,0,1485.27,0 -1886,15663830,De Luca,563,Spain,Male,32,6,0,2,1,1,19720.08,0 -1887,15566958,Li Fonti,667,Spain,Male,39,7,167557.12,1,1,1,41183.02,0 -1888,15680918,Freeman,613,Spain,Male,34,8,117300.02,1,1,0,139410.08,0 -1889,15663921,Pisani,429,France,Male,60,7,0,2,1,1,163691.48,0 -1890,15716324,Ignatieff,665,France,Female,23,9,143672.9,1,1,1,115147.33,0 -1891,15796969,Lahti,731,France,Male,33,4,0,2,1,1,74945.11,0 -1892,15574783,Perkins,584,France,Female,37,1,0,2,1,1,180363.56,0 -1893,15773487,Conway,634,Germany,Female,31,8,76798.92,1,0,0,196021.73,0 -1894,15802486,Hayes,488,France,Male,34,3,0,2,1,1,125979.36,0 -1895,15783398,Rizzo,535,Spain,Female,49,7,115309.75,1,1,0,111421.77,0 -1896,15649418,Krylov,776,France,Female,29,7,178171.04,2,1,1,115818.51,0 -1897,15604588,Li Fonti,850,Spain,Female,38,3,0,2,0,1,179360.76,0 -1898,15735428,Talbot,673,Spain,Female,37,0,0,2,0,0,82351.06,0 -1899,15629078,Matthias,850,Germany,Female,45,5,127258.79,1,1,1,192744.23,1 -1900,15806880,Boyle,627,Spain,Female,30,6,0,1,1,1,113408.47,0 -1901,15754999,Ch'eng,570,France,Female,33,8,0,1,1,1,124641.42,0 -1902,15781034,Mason,796,Spain,Male,67,5,0,2,0,1,54871.02,0 -1903,15622017,Bruno,773,Spain,Female,33,10,0,1,1,1,98820.09,0 -1904,15705885,Smeaton,752,Spain,Male,36,2,0,2,1,1,45570.84,0 -1905,15677382,Miller,625,Spain,Female,69,1,107569.96,1,1,1,182336.45,0 -1906,15566843,Gotch,535,Germany,Male,20,9,134874.4,1,1,1,118825.56,0 -1907,15608387,Fu,786,France,Female,29,4,0,2,1,0,103372.79,0 -1908,15810786,O'Toole,620,France,Female,67,3,0,2,1,1,43486.73,0 -1909,15626983,Ledford,605,Spain,Female,48,6,0,2,1,1,40062.99,0 -1910,15773605,Iadanza,670,Spain,Female,32,3,0,2,1,0,46175.7,0 -1911,15811261,Alaniz,617,Spain,Male,42,0,70105.87,1,1,1,120830.73,0 -1912,15590606,Saunders,595,France,Male,41,9,0,2,1,0,5967.09,0 -1913,15576644,Lin,687,Germany,Female,29,4,78939.15,1,1,0,122134.56,1 -1914,15750264,Pinto,757,Germany,Male,30,6,105128.85,2,1,1,62972.13,0 -1915,15741554,Streeter,746,Spain,Male,31,2,113836.27,1,1,1,174815.54,0 -1916,15769051,Shaw,503,Spain,Male,25,7,0,1,0,1,192841.13,0 -1917,15812198,Chen,543,Germany,Male,48,1,100900.5,1,0,0,33310.72,1 -1918,15699772,Barclay,428,Germany,Female,40,3,129248.11,2,1,0,72876.43,1 -1919,15744105,Kodilinyechukwu,768,France,Female,28,3,109118.05,2,0,1,50911.41,0 -1920,15739858,Otitodilichukwu,618,France,Male,56,7,0,1,1,1,142400.27,1 -1921,15723720,McKenzie,591,France,Female,31,7,0,2,0,1,48778.46,0 -1922,15638355,Woods,658,France,Female,35,5,126397.66,1,0,0,156361.58,1 -1923,15805637,Hsing,625,France,Male,36,9,108546.16,3,1,0,133807.77,1 -1924,15629575,Wheare,717,France,Male,36,2,148061.89,1,1,0,179128.69,1 -1925,15586243,Yobachi,667,France,Male,44,8,122277.87,1,1,1,91810.71,0 -1926,15757931,Fang,804,France,Male,24,3,0,2,1,0,173195.33,0 -1927,15716023,Pearson,693,France,Male,31,1,0,2,0,1,182270.88,0 -1928,15647782,Brown,729,Germany,Male,36,8,152899.24,2,1,0,177130.33,0 -1929,15716609,L?,484,Germany,Male,54,3,134388.11,1,0,0,49954.79,1 -1930,15623791,Padovesi,632,Spain,Female,40,3,109740.62,1,1,0,141896.74,0 -1931,15627262,Soto,536,Germany,Male,23,6,92366.72,2,1,0,120661.71,0 -1932,15652693,Greco,573,France,Female,26,4,129109.02,1,0,0,149814.68,1 -1933,15586993,Giordano,655,Spain,Female,56,5,0,2,1,1,41782.7,0 -1934,15815560,Bogle,666,Germany,Male,74,7,105102.5,1,1,1,46172.47,0 -1935,15584930,Grimmett,726,Germany,Male,30,5,111375.32,2,1,0,2704.09,0 -1936,15799031,Ayers,523,France,Male,39,3,0,2,1,0,6726.53,0 -1937,15810457,Miller,728,Germany,Female,33,9,150412.14,2,1,0,170764.08,0 -1938,15697879,Webb,701,France,Male,30,3,156660.72,2,1,0,45742.42,0 -1939,15594902,Lombardi,518,France,Male,38,3,90957.81,1,0,1,162304.59,0 -1940,15799710,Wei,739,France,Male,37,7,104960.46,1,0,1,80883.82,0 -1941,15659651,Ross,531,Germany,Female,31,7,117052.82,1,1,0,118508.09,1 -1942,15645956,Jideofor,452,Spain,Male,44,3,88915.85,1,1,0,69697.74,0 -1943,15651713,King,684,France,Male,45,6,148071.39,1,1,0,183575.01,0 -1944,15737265,Nwokeocha,728,Germany,Male,39,6,152182.83,1,0,0,161203.6,0 -1945,15687310,Humphries,783,Spain,Male,39,9,0,2,1,0,143752.77,0 -1946,15607347,Olisaemeka,734,France,Male,22,5,130056.23,1,0,0,121894.31,1 -1947,15698321,Yobanna,648,Germany,Male,34,3,95039.73,2,1,1,147055.87,0 -1948,15657812,Ch'iu,688,France,Male,52,1,0,2,1,1,172033.57,0 -1949,15569187,Fleming,680,Spain,Male,35,9,0,2,0,0,143774.06,0 -1950,15681562,Trevisan,516,France,Female,43,2,112773.73,2,1,1,139366.58,0 -1951,15615456,Aleksandrova,680,France,Female,37,10,123806.28,1,1,0,81776.84,1 -1952,15589793,Onwuamaeze,604,France,Male,53,8,144453.75,1,1,0,190998.96,1 -1953,15781884,Knox,624,Germany,Male,27,9,94667.29,2,0,1,4470.52,0 -1954,15675190,Chia,623,France,Male,21,10,0,2,0,1,135851.3,0 -1955,15600734,Townsend,624,Spain,Male,51,5,174397.21,2,1,1,172372.63,0 -1956,15779176,Dike,565,Germany,Female,58,3,108888.24,3,0,1,135875.51,1 -1957,15605286,Moyes,565,France,Male,55,4,118803.35,2,1,1,128124.7,1 -1958,15674922,Beavers,710,France,Male,54,6,171137.62,1,1,1,167023.95,1 -1959,15737506,Tretiakova,645,France,Male,42,6,0,1,0,0,149807.01,0 -1960,15780514,Fuller,707,France,Male,33,8,136678.52,1,1,0,54290.62,0 -1961,15623647,Dellucci,655,Spain,Female,36,1,135515.76,1,1,0,86013.96,0 -1962,15668472,Ritchie,705,Spain,Female,24,5,177799.83,2,0,0,79886.06,0 -1963,15692416,Aikenhead,358,Spain,Female,52,8,143542.36,3,1,0,141959.11,1 -1964,15771139,Douglas,578,Germany,Male,34,8,147487.23,2,1,0,66680.77,0 -1965,15738318,Kung,800,France,Female,40,5,97764.41,1,1,0,98640.15,1 -1966,15772243,MacDonald,612,France,Female,33,9,0,1,0,0,142797.5,1 -1967,15638463,Okwudilichukwu,681,Germany,Female,48,8,139480.18,1,1,1,163581.67,0 -1968,15598088,Ni,559,Spain,Male,25,5,0,2,1,1,163221.22,0 -1969,15693468,Simmons,488,Spain,Female,39,9,140553.46,1,0,0,12440.44,0 -1970,15671930,H?,717,France,Female,36,5,0,2,1,1,145551.6,0 -1971,15762268,Hancock,666,France,Female,41,10,141162.08,1,1,0,50908.48,0 -1972,15780954,Cran,582,Spain,Male,26,4,65848.36,2,1,0,30149.21,0 -1973,15700174,McKay,733,Spain,Female,30,0,83319.28,1,0,0,57769.2,0 -1974,15635728,P'an,693,France,Male,41,4,0,2,0,0,156381.47,0 -1975,15679283,Parkhill,694,France,Female,33,4,129731.64,2,1,0,178123.86,0 -1976,15591386,Golubova,622,France,Female,35,5,0,2,1,0,51112.8,0 -1977,15694192,Nwankwo,598,Spain,Female,38,6,0,2,0,0,173783.38,0 -1978,15585901,Johnson,717,Spain,Male,35,1,0,3,0,0,174770.14,1 -1979,15792329,Mao,494,Germany,Male,37,5,107106.33,2,1,0,172063.09,0 -1980,15635597,Echezonachukwu,644,France,Male,33,8,0,2,1,1,155294.17,0 -1981,15775880,McElyea,554,France,Female,30,9,0,2,1,1,40320.3,0 -1982,15630913,Rosas,476,Spain,Female,69,1,105303.73,1,0,1,134260.34,0 -1983,15756680,Phillips,667,France,Male,28,6,165798.1,1,1,0,147090.9,0 -1984,15587913,Palerma,748,Spain,Female,40,4,0,2,1,0,132368.47,0 -1985,15737605,Morris,531,Spain,Female,45,1,126495.57,2,1,1,164741.5,0 -1986,15627876,Pavlova,719,Spain,Female,47,9,116393.59,1,1,0,63051.32,1 -1987,15772601,Lu,845,Germany,Female,41,2,81733.74,2,0,0,199761.29,0 -1988,15758606,Yamamoto,738,France,Male,54,4,0,1,0,1,55725.04,1 -1989,15657107,Angelo,563,Spain,Female,46,8,106171.68,1,1,0,163145.5,1 -1990,15622454,Zaitsev,695,Spain,Male,28,0,96020.86,1,1,1,57992.49,0 -1991,15775803,Cawker,841,Spain,Male,41,1,0,2,0,1,193093.77,0 -1992,15570859,Froggatt,626,Germany,Male,36,2,181671.16,2,1,1,57531.14,0 -1993,15748381,Gorbunov,613,France,Female,29,6,185709.28,2,1,1,77242.19,0 -1994,15787189,Tai,824,Germany,Male,60,8,134250.17,3,0,0,153046.16,1 -1995,15666055,Rowe,705,France,Female,49,7,0,1,1,0,63405.2,1 -1996,15617648,Mikkelsen,584,France,Female,44,5,95671.75,2,1,1,106564.88,0 -1997,15755678,Kovalyov,534,France,Male,62,2,0,2,0,0,42763.12,1 -1998,15624781,Mbanefo,672,France,Female,34,1,142151.75,2,1,1,168753.34,0 -1999,15779497,Ts'ai,603,France,Male,43,5,127823.93,1,1,1,19483.35,0 -2000,15567399,Enderby,633,Germany,Male,43,3,144164.29,1,1,1,158646.46,0 -2001,15613656,Lombardi,842,France,Male,58,1,63492.94,1,1,1,83172.19,0 -2002,15734311,Hamilton,661,France,Female,27,3,0,2,1,1,76889.79,0 -2003,15657214,Hsia,601,France,Male,74,2,0,2,0,1,51554.58,0 -2004,15799350,Mao,632,France,Male,41,0,106134.46,1,0,1,105570.39,0 -2005,15729970,Ugochukwu,684,Germany,Male,29,8,127269.75,1,0,1,79495.01,0 -2006,15725835,West,785,Germany,Female,32,3,124493.03,2,0,1,52583.79,1 -2007,15745543,Hughes,687,France,Male,39,7,0,2,1,0,26848.25,0 -2008,15727384,Chukwuemeka,705,Germany,Female,43,10,146547.78,1,0,1,10072.55,1 -2009,15666916,Lira,639,France,Male,43,6,99610.92,2,1,0,187296.78,0 -2010,15732917,Li,729,Germany,Male,46,5,117837.43,1,1,0,104016.61,1 -2011,15612050,Castiglione,556,Spain,Female,48,8,168522.37,1,1,1,151310.16,0 -2012,15726267,Paterson,570,France,Male,32,9,117337.54,2,0,1,62810.91,0 -2013,15780124,Blair,841,France,Male,74,9,108131.53,1,0,1,60830.38,0 -2014,15742238,Dellucci,705,Germany,Male,35,4,136496.12,2,1,0,116672.02,0 -2015,15679024,Udinesi,553,France,Male,32,3,116324.53,1,1,0,77304.49,0 -2016,15715297,Yuan,779,Germany,Female,40,2,75470.23,1,1,1,52894.01,0 -2017,15633612,Yuryeva,696,France,Male,28,4,172646.82,1,1,1,116471.43,0 -2018,15602929,Wilson,728,Spain,Female,37,4,0,1,0,0,4539.38,0 -2019,15696703,Dean,691,Germany,Male,27,3,160358.68,2,1,0,142367.72,0 -2020,15756668,Ross,706,France,Male,30,3,98415.37,1,1,1,110520.48,0 -2021,15565779,Kent,627,Germany,Female,30,6,57809.32,1,1,0,188258.49,0 -2022,15795519,Vasiliev,716,Germany,Female,18,3,128743.8,1,0,0,197322.13,0 -2023,15761477,Golibe,501,Germany,Male,24,4,130806.42,2,1,0,80241.14,0 -2024,15731890,Chukwukere,601,France,Male,41,1,123971.16,1,0,1,172814.99,0 -2025,15633043,Fedorova,545,Spain,Female,39,6,0,1,0,0,38410.74,1 -2026,15752953,Chien,634,France,Male,45,9,0,2,0,0,17622.82,0 -2027,15603088,Rossi,451,Spain,Female,23,9,0,2,0,1,48021.71,0 -2028,15606613,Samson,655,France,Female,59,7,0,1,1,0,88958.49,1 -2029,15635939,Fenton,458,France,Female,39,9,0,2,1,0,116343.09,0 -2030,15666043,Mackey,520,France,Male,33,4,156297.58,2,1,1,166102.61,0 -2031,15746190,Payton,624,Spain,Female,28,2,0,2,0,1,104353.26,0 -2032,15591357,Cowger,765,France,Male,51,3,123372.3,1,1,1,115429.32,0 -2033,15658716,Banks,667,Germany,Female,37,5,92171.35,3,1,0,178106.34,1 -2034,15679909,Pugliesi,665,Spain,Male,41,8,0,2,1,0,132152.32,0 -2035,15634262,Fantin,709,Germany,Male,34,4,148375.19,2,1,1,21521.38,0 -2036,15799825,Bentley,583,France,Female,44,8,0,2,1,1,27431.62,0 -2037,15756875,Freeman,782,Spain,Male,34,6,147422.44,1,0,1,42143.61,0 -2038,15678146,Wong,668,Spain,Female,24,7,173962.32,1,0,0,106457.11,1 -2039,15710743,Onwuamaeze,621,France,Male,47,0,0,1,1,1,133831.37,1 -2040,15595831,Shen,579,Germany,Female,64,6,145215.43,1,1,1,164083.72,0 -2041,15626684,Huang,547,France,Female,38,5,167539.97,1,0,1,159207.34,0 -2042,15709846,Yeh,840,France,Female,39,1,94968.97,1,1,0,84487.62,0 -2043,15635459,Shih,667,Germany,Female,27,3,106116.5,2,1,0,3674.71,0 -2044,15642544,Henderson,723,France,Male,34,5,0,2,0,1,12092.03,0 -2045,15566494,Fang,487,France,Male,45,2,0,2,1,0,77475.73,0 -2046,15655238,Dellucci,668,France,Female,31,9,0,2,0,0,41291.73,0 -2047,15733429,Chou,520,Germany,Male,34,8,120018.86,2,1,1,343.38,0 -2048,15814536,Conti,549,France,Male,37,2,112541.54,2,0,0,47432.43,0 -2049,15771702,Roberts,567,France,Female,35,5,166118.45,2,1,0,127827.18,0 -2050,15723008,Lo Duca,720,France,Female,45,1,102882.4,2,1,1,35633.15,1 -2051,15797160,Glover,492,France,Female,49,8,0,1,1,1,182865.09,1 -2052,15792222,Johnstone,712,France,Female,37,1,106881.5,2,0,0,169386.81,0 -2053,15644765,Ashton,689,Germany,Male,26,4,120727.97,1,0,1,149073.88,0 -2054,15610686,Melton,850,France,Male,63,8,169832.57,1,0,0,184107.26,1 -2055,15730868,Marshall,747,France,Male,41,5,0,2,1,1,22750.17,0 -2056,15705991,Kenenna,469,Germany,Male,38,9,113599.42,1,0,0,11950.29,0 -2057,15577078,Zakharov,539,Spain,Male,38,6,0,1,1,1,152880.07,1 -2058,15679550,Chukwualuka,743,France,Male,32,9,0,2,1,0,175252.78,0 -2059,15787655,Chu,707,France,Male,47,3,0,2,1,0,174303.29,0 -2060,15668081,Capon,581,Spain,Female,50,4,0,2,1,1,80701.72,0 -2061,15747980,Cattaneo,737,Spain,Male,38,6,146282.79,2,1,0,198516.2,0 -2062,15710295,Patrick,445,Germany,Female,38,6,119413.62,2,1,0,175756.36,0 -2063,15724443,Taylor,703,Germany,Female,29,3,122084.63,1,0,1,82824.08,0 -2064,15571305,Stephenson,588,Germany,Female,35,1,103060.63,1,1,0,179866.01,1 -2065,15569503,Yeh,765,France,Male,44,6,0,2,1,1,159899.97,0 -2066,15581840,DeRose,626,France,Male,33,8,0,2,1,0,138504.28,0 -2067,15772262,Vavilov,545,Germany,Male,37,9,110483.86,1,1,1,127394.67,0 -2068,15767794,Browne,744,France,Male,31,9,120718.28,1,1,1,58961.49,0 -2069,15629338,Collingridge de Tourcey,658,Spain,Female,31,2,36566.96,1,1,0,103644.98,1 -2070,15790379,Rowe,629,Germany,Male,28,8,108601,1,1,1,119647.7,0 -2071,15750684,Jibunoh,719,France,Female,42,4,0,1,1,0,28465.86,1 -2072,15697214,Korovin,686,Spain,Female,36,5,0,2,1,1,152979.14,0 -2073,15711015,Hammonds,743,France,Male,36,4,0,2,1,1,190911.02,0 -2074,15573309,Ward,626,Spain,Female,48,2,0,2,1,1,95794.98,0 -2075,15805303,Olisanugo,661,Germany,Male,44,1,141136.62,1,1,0,189742.78,1 -2076,15741385,Gallop,710,Germany,Male,45,9,108231.37,1,1,1,188574.08,0 -2077,15780254,Gartrell,654,France,Male,40,6,0,1,0,0,183872.88,1 -2078,15744843,K'ung,569,Spain,Female,34,6,144855.34,1,0,0,196555.32,0 -2079,15815626,Oluchi,640,France,Male,63,2,68432.45,2,1,1,112503.24,1 -2080,15784736,Jamieson,562,France,Male,45,6,136855.24,1,1,0,46864,0 -2081,15813412,Barlow,721,France,Female,55,3,44020.89,1,1,0,65864.4,1 -2082,15809143,White,456,Germany,Male,32,9,133060.63,1,1,1,125167.92,0 -2083,15617617,Stewart,811,Spain,Male,39,7,0,2,1,1,177519.39,0 -2084,15779738,Buccho,534,France,Male,24,1,0,1,1,1,169653.32,0 -2085,15668669,Benson,423,France,Female,36,5,97665.61,1,1,0,118372.55,1 -2086,15687477,Thompson,594,Germany,Male,28,5,185013.02,1,1,0,16481.12,0 -2087,15578908,Todd,725,Spain,Female,32,0,0,2,1,1,138525.19,0 -2088,15687658,Burgin,716,France,Female,52,7,65971.61,2,1,0,14608,1 -2089,15615020,Nnaife,595,Germany,Female,41,9,150463.11,2,0,1,81548.38,0 -2090,15608886,Okwudiliolisa,679,France,Female,33,1,0,2,0,0,69608.48,0 -2091,15602551,Johnson,667,Spain,Male,39,9,0,2,1,0,68873.8,0 -2092,15672945,Parkes,661,France,Female,37,5,136425.18,1,1,0,81102.81,0 -2093,15757408,Lo,655,Spain,Male,38,3,250898.09,3,0,1,81054,1 -2094,15806132,Martin,555,France,Male,55,4,146798.81,1,1,1,74149.77,0 -2095,15813022,Kapustina,531,Spain,Male,70,1,0,2,0,0,99503.19,0 -2096,15673578,Page,611,Germany,Female,40,7,128486.91,2,1,0,10109.47,0 -2097,15757916,Amaechi,600,France,Female,38,9,0,2,1,1,58855.85,0 -2098,15689168,Munro,531,Spain,Male,37,1,143407.29,2,0,1,84402.46,0 -2099,15769216,Panicucci,601,France,Female,43,2,0,1,1,0,49713.87,1 -2100,15593295,Greathouse,548,France,Male,57,6,76165.65,1,1,1,133537.53,0 -2101,15804814,Ts'ui,759,France,Male,40,4,0,2,1,0,124615.59,0 -2102,15778934,Napolitani,678,Spain,Female,49,8,0,2,0,1,98090.69,0 -2103,15802351,Beers,755,Germany,Female,33,6,90560.3,2,1,1,42607.69,0 -2104,15630241,Tretyakova,594,France,Male,61,3,62391.22,1,1,1,192434.11,0 -2105,15719561,Lin,768,France,Male,42,5,0,3,0,0,60686.4,0 -2106,15615096,Costa,492,France,Female,31,7,0,2,1,1,49463.44,0 -2107,15659931,Ibezimako,637,Germany,Female,55,1,123378.2,1,1,0,81431.99,1 -2108,15714586,Marcelo,646,Spain,Female,42,3,99836.47,1,0,1,22909.56,0 -2109,15634949,Hay,593,Germany,Male,74,5,161434.36,2,1,1,65532.17,0 -2110,15589224,Moore,596,Spain,Male,41,5,0,2,0,1,141053.85,0 -2111,15795990,Lumholtz,722,Germany,Female,48,10,138311.76,1,1,1,3472.63,1 -2112,15603216,Simpson,642,France,Male,25,7,0,2,1,0,102083.78,0 -2113,15631201,Hill,472,Spain,Female,28,4,0,2,1,0,1801.77,0 -2114,15686255,Mouzon,738,Germany,Male,35,6,101744.84,1,0,0,85185.44,0 -2115,15746594,Wu,732,Spain,Male,33,8,0,1,1,0,119882.7,0 -2116,15718893,Pirozzi,404,Germany,Female,54,4,125456.07,1,1,0,83715.66,1 -2117,15671609,Ibeabuchi,701,France,Male,44,7,0,2,1,0,23425.78,0 -2118,15652540,Garnsey,683,France,Male,31,2,0,2,0,1,77326.78,0 -2119,15774857,Synnot,460,France,Female,27,7,0,2,1,0,156150.08,1 -2120,15791836,Wildman,690,France,Male,29,5,0,2,1,0,108577.97,0 -2121,15651554,Anenechukwu,618,Germany,Female,54,4,118449.21,1,1,1,133573.29,1 -2122,15583576,Tai,671,France,Male,30,2,0,1,0,1,102057.86,0 -2123,15732740,Plant,765,Spain,Female,32,9,178095.55,1,0,0,47247.56,0 -2124,15723320,Azubuike,651,Germany,Female,25,2,109175.14,2,1,0,114566.47,0 -2125,15603851,Galkin,704,France,Male,32,7,127785.17,4,0,0,184464.7,1 -2126,15777923,Johnston,544,France,Female,45,6,0,2,0,1,151401.33,0 -2127,15735719,Babbage,790,France,Female,40,9,0,2,1,1,70607.1,0 -2128,15703482,Walker,710,Germany,Male,34,9,134260.36,2,1,0,147074.67,0 -2129,15605835,Rice,743,France,Male,37,8,69143.91,2,0,1,105780.18,0 -2130,15664881,Norton,702,France,Male,34,4,100054.77,1,1,0,109496.45,0 -2131,15757568,Bogolyubov,704,France,Female,45,6,0,1,1,1,137739.45,0 -2132,15792660,Gibbons,614,France,Male,38,2,116248.88,1,1,0,105140.92,0 -2133,15599722,Chia,609,Spain,Female,43,6,86053.52,2,1,1,113276.46,1 -2134,15726354,Smith,688,France,Female,32,6,123157.95,1,1,0,172531.23,0 -2135,15610355,Hunter,713,France,Male,44,1,63438.91,1,1,0,64375.4,0 -2136,15704284,Ekechukwu,736,Germany,Male,57,9,95295.39,1,1,0,28434.44,1 -2137,15621893,Bellucci,727,France,Male,18,4,133550.67,1,1,1,46941.41,0 -2138,15588219,Ford,850,France,Female,38,1,106871.81,2,1,0,29333.01,0 -2139,15688619,Scott,718,Spain,Male,45,3,105266.32,2,1,1,193724.51,0 -2140,15765518,Gregson,643,France,Female,51,2,105229.53,1,1,0,34967.75,1 -2141,15616931,Moore,653,France,Male,41,8,102768.42,1,1,0,55663.85,0 -2142,15758372,Wallace,674,France,Male,18,7,0,2,1,1,55753.12,1 -2143,15782591,Cook,690,France,Male,35,6,112689.95,1,1,0,176962.31,0 -2144,15612109,Speth,819,France,Male,38,9,122334.26,2,1,1,181507.44,0 -2145,15613712,Boag,634,Spain,Male,34,1,0,2,1,0,61995.57,0 -2146,15639322,Grave,633,Spain,Male,33,4,137847.41,2,1,0,98349.13,0 -2147,15594349,Streeten,850,France,Male,49,5,122486.47,1,0,1,59748.19,0 -2148,15574167,Fox,665,France,Male,33,2,101286.11,1,1,1,159840.51,0 -2149,15811842,Artemyeva,630,Spain,Male,26,7,0,2,1,1,6656.64,0 -2150,15648794,Giordano,836,Spain,Male,57,4,101247.06,1,1,0,37141.62,1 -2151,15771211,Perkins,668,France,Male,38,10,86977.96,1,0,1,37094.75,0 -2152,15588614,Walton,753,France,Male,57,7,0,1,1,0,159475.08,1 -2153,15630698,Hay,745,France,Female,55,9,110123.59,1,0,1,51548.14,1 -2154,15694200,Gardner,693,France,Male,36,8,178111.82,1,0,0,58719.63,1 -2155,15721426,Milne,606,Germany,Male,65,10,126306.64,3,0,0,7861.68,1 -2156,15725997,She,660,France,Female,35,6,100768.77,1,1,0,19199.61,0 -2157,15762138,Hu,608,France,Male,42,5,0,2,1,0,178504.29,0 -2158,15750649,Uwakwe,744,France,Female,44,3,0,2,1,1,189016.14,0 -2159,15685706,Bird,731,France,Female,40,7,118991.79,1,1,1,156048.64,0 -2160,15641835,Anderson,683,France,Male,72,3,140997.26,1,0,1,52876.41,0 -2161,15586821,Bellew,727,France,Male,28,5,0,2,0,1,19653.08,0 -2162,15569678,Cocci,561,Germany,Male,32,6,166824.59,1,1,0,139451.98,0 -2163,15793842,Krichauff,700,France,Female,34,2,76322.69,1,1,0,128136.29,0 -2164,15667554,Cameron,605,France,Male,35,6,0,2,1,1,45206.57,0 -2165,15794479,Becker,767,Spain,Male,77,8,149083.7,1,1,1,190146.83,0 -2166,15585041,Ainsworth,511,France,Male,33,7,0,2,0,1,158313.87,0 -2167,15780650,Biryukov,667,France,Male,40,9,0,1,1,1,96670.2,0 -2168,15780846,Redding,787,France,Male,33,1,126588.81,2,0,1,62163.53,0 -2169,15805260,Wood,705,Germany,Female,56,2,143249.67,1,1,0,88428.41,1 -2170,15621629,Scott,773,Germany,Male,43,8,81844.91,2,1,1,35908.46,0 -2171,15662151,Gould,554,France,Male,40,4,0,1,0,1,168780.04,0 -2172,15747174,Hao,526,Germany,Male,58,9,190298.89,2,1,1,191263.76,0 -2173,15651585,Power,661,Germany,Male,35,2,117212.18,1,1,1,83052.03,0 -2174,15649738,White,698,France,Female,46,0,0,2,1,1,125962.02,0 -2175,15633108,Thorpe,646,France,Male,26,4,139848.17,1,1,0,164696.27,0 -2176,15769254,Tuan,757,Germany,Female,34,9,101861.36,2,0,0,187011.96,0 -2177,15704746,Inman,699,Spain,Male,35,2,167455.66,2,1,1,55324.49,0 -2178,15637644,Hanson,667,France,Female,24,4,0,2,0,1,34335.55,0 -2179,15609562,MacDonald,774,Spain,Female,43,1,116360.07,1,1,0,17004.14,0 -2180,15787459,Parkes,745,Spain,Male,40,3,88466.82,1,0,0,116331.42,0 -2181,15762902,Stanley,649,France,Female,42,7,0,2,0,1,22974.01,0 -2182,15738605,Fischer,634,Germany,Female,46,5,123642.36,1,1,1,49725.16,1 -2183,15724889,Chinweuba,665,Spain,Male,38,9,0,1,0,1,87412.74,0 -2184,15730735,Henning,713,France,Male,38,9,72286.84,2,1,1,26136.89,0 -2185,15689147,Ogochukwu,652,France,Female,40,1,0,2,1,0,126554.96,0 -2186,15730397,Narelle,739,Spain,Male,40,1,109681.61,1,1,1,193321.3,0 -2187,15762169,Bergman,556,Germany,Male,37,9,145018.64,2,1,0,90928.02,1 -2188,15589320,Sagese,699,Spain,Male,34,8,0,1,1,1,76510.46,0 -2189,15799211,Anenechi,708,Spain,Female,32,8,187487.63,1,1,1,120115.5,0 -2190,15798310,Palerma,480,France,Male,35,2,165692.91,1,1,1,197984.58,0 -2191,15609998,Okwudilichukwu,700,Germany,Female,59,5,137648.41,1,1,0,142977.05,1 -2192,15583548,Harrison,525,Spain,Female,47,6,118560,1,1,0,82522.61,1 -2193,15761763,Jamieson,845,France,Male,33,8,164385.53,1,1,0,150664.97,0 -2194,15764409,Goodman,613,France,Male,37,9,108286.5,1,1,1,114153.44,0 -2195,15710161,Ko,850,France,Female,34,2,0,2,1,1,171706.66,0 -2196,15735246,Norman,798,Spain,Female,58,9,0,2,0,0,119071.56,1 -2197,15791700,Ugochukwutubelum,773,Germany,Male,47,2,118079.47,4,1,1,143007.49,1 -2198,15670753,Uvarova,614,Spain,Male,35,2,127283.78,1,1,1,31302.35,0 -2199,15573876,Chia,473,Spain,Male,48,8,0,2,1,0,71139.8,0 -2200,15770174,Piazza,762,France,Male,29,6,141389.06,1,1,0,54122.89,0 -2201,15641114,Power,701,France,Male,37,8,130091.5,1,1,1,120031.29,0 -2202,15682435,P'eng,600,France,Male,35,4,143744.77,2,1,0,104076.51,0 -2203,15751788,Johnson,850,Spain,Male,28,9,97408.03,1,1,1,175853.64,0 -2204,15672598,Walker,613,Spain,Male,30,9,111927.45,1,1,1,175795.87,0 -2205,15762803,Innes,509,France,Male,31,3,0,2,1,0,15360.91,0 -2206,15812982,Francis,509,Spain,Male,38,2,0,1,0,0,168460.12,0 -2207,15597901,Chidozie,609,France,Male,34,1,0,1,1,1,181177.9,0 -2208,15731507,Mackenzie,456,France,Female,33,1,188285.68,1,0,0,58363.94,0 -2209,15809826,Craigie,728,France,Female,46,2,109705.52,1,1,0,20276.87,1 -2210,15764237,Manfrin,663,Spain,Male,33,9,0,2,0,0,91514.62,0 -2211,15769917,Onyekachi,673,Germany,Female,34,1,127122.79,3,0,1,76703.1,0 -2212,15641850,Pethard,717,France,Male,40,0,98241.04,1,1,0,110887.14,0 -2213,15770974,Nwabugwu,741,Germany,Female,37,8,170840.08,2,0,0,109843.16,0 -2214,15803749,DeRose,498,Germany,Female,41,4,87541.06,2,1,1,12577.21,1 -2215,15684999,Ch'eng,850,France,Female,26,4,62610.96,2,0,1,179365.1,0 -2216,15770225,Padovesi,493,France,Male,36,9,0,2,1,1,65816.53,0 -2217,15627484,Obielumani,686,France,Female,47,5,113328.93,1,1,0,124170.9,0 -2218,15610337,Stephens,666,Spain,Male,35,2,104832.49,1,1,0,175015.12,0 -2219,15752488,Emery,733,Spain,Female,31,9,102289.85,1,1,1,115441.66,0 -2220,15610056,Dufresne,631,Germany,Female,34,6,125227.82,2,0,1,128247.03,0 -2221,15806049,Lee,714,Germany,Female,49,5,140510.89,1,1,0,141914.94,0 -2222,15736069,Hsing,767,Germany,Female,35,6,132253.22,1,1,0,115566.57,1 -2223,15763662,Longo,711,Germany,Male,43,2,39043.29,2,1,1,175423.69,0 -2224,15615575,Vial,722,France,Male,34,8,0,2,1,1,133447.49,0 -2225,15691723,Chukwudi,631,Spain,Male,55,9,99685.06,1,1,0,114474.98,0 -2226,15774098,Grant,701,Germany,Male,38,3,125385.49,2,0,1,52044.66,0 -2227,15750808,Ma,790,Spain,Male,46,2,131365.37,2,1,1,180290.68,0 -2228,15744368,Sun,633,Spain,Male,58,6,98308.51,1,1,1,132034.13,0 -2229,15610594,Moss,644,France,Female,37,8,0,2,1,0,20968.88,0 -2230,15756125,Booth,757,Spain,Male,44,5,140856.16,2,1,0,158735.1,0 -2231,15623277,Ross,696,France,Female,30,8,0,2,1,1,196134.44,0 -2232,15795954,Ndukaku,746,France,Male,35,2,172274.01,1,1,0,22374.97,0 -2233,15671969,Pruneda,649,Spain,Male,36,8,0,2,1,0,161668.15,0 -2234,15791268,Neumann,565,Spain,Male,38,0,122447.76,1,0,0,67339.34,0 -2235,15713655,Calabrese,720,France,Female,38,10,0,2,1,1,56229.72,1 -2236,15633930,Yobachukwu,648,Spain,Female,56,6,157559.59,2,1,0,140991.23,1 -2237,15712849,Tung,632,Germany,Male,41,3,126550.7,1,0,0,177644.52,1 -2238,15639077,Marchesi,622,France,Female,30,2,158584.82,3,1,0,142342.55,1 -2239,15808784,Hess,835,France,Male,28,2,163569.61,2,1,1,154559.28,0 -2240,15648577,Pickering,493,France,Female,31,3,0,1,1,1,176570.28,1 -2241,15670345,Mazzi,785,Germany,Female,33,6,127211.45,1,0,0,191961.83,0 -2242,15633112,Madukaego,681,Germany,Male,42,3,118199.97,2,1,0,9452.88,1 -2243,15714397,Trentino,621,Germany,Female,30,2,101014.08,2,1,1,165257.31,0 -2244,15780038,Paterson,756,Spain,Male,38,6,119208.85,1,1,0,169763.89,1 -2245,15756305,Marchesi,515,France,Female,66,6,0,2,1,1,160663.11,0 -2246,15578799,Anayolisa,625,France,Female,58,10,53772.73,1,1,1,192072.1,1 -2247,15800326,Poole,717,Spain,Female,39,6,0,2,1,0,93275.61,0 -2248,15785485,Zhou,595,Germany,Female,41,2,138878.81,1,0,1,112269.67,0 -2249,15783958,Bates,539,Spain,Female,37,1,130922.81,2,0,0,2186.83,0 -2250,15727546,Olejuru,762,France,Male,35,9,0,2,1,1,43075.7,0 -2251,15739576,Bustard,706,Spain,Male,20,8,0,2,1,1,12368.11,0 -2252,15631333,Wade,677,Spain,Female,25,8,130866.19,1,1,0,42410.21,0 -2253,15604782,Tan,733,Germany,Female,33,7,187257.94,1,0,1,190430.81,0 -2254,15589643,Ngozichukwuka,684,Spain,Female,41,7,0,1,1,1,138394.37,0 -2255,15585533,Calabrese,679,France,Male,36,6,147733.64,1,0,1,172501.38,0 -2256,15681506,Lane,478,Spain,Male,43,1,0,2,1,1,197916.43,0 -2257,15630551,Forbes,696,France,Male,33,2,163139.27,1,1,1,7035.36,0 -2258,15698349,Davy,686,Spain,Female,35,4,0,2,1,1,159676.55,0 -2259,15776631,Ma,466,France,Female,36,5,119540.15,1,0,1,80603.99,0 -2260,15762216,Barrera,686,France,Female,41,4,129553.76,2,1,0,187599.8,0 -2261,15623927,Alexander,576,France,Male,55,9,0,2,1,1,94450.97,0 -2262,15681402,Ngozichukwuka,763,Germany,Female,61,1,66101.89,1,1,1,143981.27,0 -2263,15586264,Murray,572,France,Male,43,2,140431.98,1,1,0,26450.57,1 -2264,15594685,Hall,757,France,Female,49,2,0,2,0,0,164482.92,0 -2265,15812945,Padovesi,582,France,Female,29,0,0,1,1,1,84012.81,0 -2266,15734628,Lysaght,623,France,Female,35,5,0,2,1,0,101192.08,0 -2267,15629323,Kelechi,617,Germany,Female,37,4,116471.43,2,1,0,175324.74,1 -2268,15666823,Nebechi,425,France,Male,39,4,0,2,1,0,197226.32,0 -2269,15777553,Hanson,659,France,Female,56,9,123785.24,1,1,0,99504.03,1 -2270,15613097,Kao,605,France,Female,33,4,0,2,0,1,83700.66,0 -2271,15622217,Tu,538,France,Female,38,8,88758.95,2,0,0,28226.15,1 -2272,15703588,Palerma,665,Germany,Male,25,5,153611.83,2,1,0,35321.65,0 -2273,15570835,Fallaci,491,Germany,Female,57,4,112044.72,1,1,1,41229.73,1 -2274,15679299,Shen,726,Spain,Female,27,7,123826.07,1,0,1,78970.58,0 -2275,15808044,Ts'ui,580,France,Female,65,9,106804.26,3,1,0,107890.69,1 -2276,15579208,Chikezie,550,France,Female,48,6,0,2,1,1,191870.28,0 -2277,15684951,He,542,France,Female,59,2,68892.77,2,1,0,7905.06,1 -2278,15667620,Dreyer,732,France,Female,43,6,0,2,1,0,65731.53,0 -2279,15582960,Short,473,France,Female,33,5,125827.43,1,0,1,145698.73,0 -2280,15590730,Hunt,745,Spain,Male,34,9,0,2,1,0,50046.25,0 -2281,15763747,Ricci,732,France,Male,36,7,0,2,1,1,60830.24,0 -2282,15778320,Teng,848,Germany,Female,40,5,148495.64,1,0,0,158853.98,0 -2283,15642787,Ijendu,572,France,Male,37,1,133043.66,1,0,0,111243.09,0 -2284,15624633,Kibby,702,France,Male,45,9,74989.58,1,1,1,171014.69,0 -2285,15766765,Obiuto,664,Germany,Male,39,7,60263.23,1,1,0,170835.32,0 -2286,15783615,Ramos,630,Germany,Male,50,3,129370.91,4,1,1,47775.34,1 -2287,15640161,Calabrese,618,Germany,Male,44,5,157955.83,2,0,0,139297.71,0 -2288,15619889,Vasin,556,France,Male,26,4,0,1,1,0,195167.38,0 -2289,15579166,Munro,619,France,Female,30,7,70729.17,1,1,1,160948.87,0 -2290,15789097,Keeley,644,France,Male,48,8,0,2,0,1,44965.54,1 -2291,15674880,Archer,658,Spain,Male,50,2,0,2,1,0,52137.73,0 -2292,15778157,Murray,598,Spain,Male,27,8,90721.52,2,1,0,109296.18,0 -2293,15779064,Chidiegwu,677,France,Male,27,2,0,2,1,1,20092.89,0 -2294,15801265,Tang,689,Spain,Female,45,0,57784.22,1,1,0,197804,1 -2295,15589204,Farrar,591,France,Male,33,9,131765.72,1,1,0,118782.06,0 -2296,15664543,Shaw,699,France,Male,40,7,0,1,0,1,152876.13,1 -2297,15582714,Napolitani,749,Germany,Male,47,9,110022.74,1,0,1,135655.29,1 -2298,15797595,Greenhalgh,709,France,Female,40,9,131569.63,1,1,1,103970.58,0 -2299,15614034,Martin,607,Germany,Male,61,2,164523.5,2,1,1,35786.76,0 -2300,15763171,Hu,650,Germany,Female,25,2,114330.95,1,1,1,25325.07,0 -2301,15647266,Y?an,651,Spain,Female,45,10,135923.16,1,1,0,18732.84,0 -2302,15757577,Odili,676,France,Female,61,8,0,2,1,1,118522.73,0 -2303,15736656,H?,723,France,Female,49,4,0,2,0,1,89972.25,0 -2304,15635078,Chiemela,714,Spain,Male,45,0,124693.48,1,0,1,187194.15,0 -2305,15680141,Yuan,759,Spain,Female,35,7,147936.42,1,1,1,106785.7,0 -2306,15576945,Clements,582,France,Male,29,0,0,1,1,0,142516.35,0 -2307,15602034,Kolesnikov,697,France,Female,34,2,126558.92,1,1,0,73334.43,0 -2308,15732020,Rutherford,610,Germany,Male,57,6,106938.11,2,0,1,186612.47,0 -2309,15611029,Hsiung,488,Germany,Female,33,4,140002.35,1,1,0,123613.81,0 -2310,15621210,Angelo,599,Germany,Male,46,9,123444.72,1,1,1,31368.08,1 -2311,15569222,Mendes,781,France,Male,32,6,147107.91,1,1,1,40066.95,0 -2312,15664639,McGregor,645,France,Male,19,9,128514.84,1,0,0,175969.19,0 -2313,15724223,Bronner,545,France,Female,55,5,0,1,0,0,10034.77,1 -2314,15644621,Mironova,597,Germany,Female,40,9,106756.01,2,1,0,151167.94,0 -2315,15756056,Ku,561,Spain,Female,28,3,0,2,1,0,191387.76,0 -2316,15700353,Evans,662,France,Female,37,6,0,2,1,0,51229.17,0 -2317,15624388,Henderson,649,Germany,Female,50,5,155393.32,1,1,1,87351.42,1 -2318,15627212,Smith,630,France,Female,36,2,110414.48,1,1,1,48984.95,0 -2319,15648005,Russell,672,Spain,Male,33,2,0,2,1,1,182738,0 -2320,15681446,Sun,636,Germany,Female,37,9,157098.52,1,1,1,153535.27,0 -2321,15775888,McDonald,593,Germany,Female,38,5,85626.6,1,1,1,125079.65,0 -2322,15749019,Wong,545,Germany,Male,45,6,93796.42,2,1,1,162321.26,0 -2323,15709928,Niu,567,Spain,Female,41,1,0,2,1,0,3414.72,0 -2324,15784676,Fanucci,583,France,Male,51,6,125268.03,2,1,0,165082.25,0 -2325,15748116,Zetticci,681,France,Female,29,2,148143.84,1,1,1,52021.39,0 -2326,15612193,Hsia,762,Spain,Male,29,10,115545.33,2,1,0,148256.43,0 -2327,15762984,McIntosh,648,Spain,Male,35,7,0,2,0,0,122899.01,0 -2328,15613713,Kozlova,644,France,Male,30,5,44928.88,1,1,1,10771.46,0 -2329,15664204,Meany,706,Spain,Male,29,2,0,2,1,1,18255.51,0 -2330,15639415,Thompson,850,France,Male,35,3,162442.35,1,1,0,183566.78,0 -2331,15806332,Le Gallienne,484,Spain,Female,39,5,0,2,1,1,175224.12,0 -2332,15614929,Cheng,508,Germany,Male,28,0,96213.82,2,1,0,147913.56,0 -2333,15695492,P'eng,439,France,Female,29,6,156569.43,1,1,0,180598.66,0 -2334,15635972,Lloyd,484,Spain,Male,36,8,0,2,1,0,186136.48,0 -2335,15616380,Wheeler,803,Spain,Female,37,1,0,2,0,0,7455.2,0 -2336,15581440,Christie,724,Germany,Female,48,6,110463.25,2,1,1,80552.11,1 -2337,15654390,He,640,France,Male,33,7,154575.76,1,1,0,25722.28,1 -2338,15660688,King,701,Spain,Female,35,9,0,2,0,0,170996.86,0 -2339,15806307,Favors,537,France,Male,37,3,0,2,1,1,20603.32,0 -2340,15647975,Vida,651,Germany,Male,26,5,147037.32,1,0,0,141763.26,0 -2341,15595728,Thomas,523,Germany,Male,41,0,119276.31,1,0,0,122284.38,1 -2342,15735388,Wayn,717,France,Female,25,7,108664.85,2,1,0,190011.85,0 -2343,15788535,Tan,593,Spain,Male,44,5,0,1,1,0,128046.98,0 -2344,15765902,Gibson,706,Germany,Male,38,5,163034.82,2,1,1,135662.17,0 -2345,15642345,Y?,714,Germany,Female,49,4,93059.34,1,1,0,7571.51,1 -2346,15641250,Calabresi,794,Spain,Male,38,9,179581.31,1,1,0,23596.24,0 -2347,15706163,Enyinnaya,518,Germany,Male,46,4,113625.93,1,0,0,92727.42,1 -2348,15746708,Ritchie,589,Germany,Male,55,7,119961.48,1,1,0,65156.83,1 -2349,15775203,Chia,824,France,Male,45,3,129209.48,1,0,0,60151.77,0 -2350,15787907,Wang,719,Germany,Female,42,5,137227.04,3,1,0,149097.38,1 -2351,15646764,Lorenzo,617,Germany,Female,58,3,119024.75,2,1,0,35199.24,1 -2352,15678284,Pai,651,France,Male,35,7,74623.5,3,1,0,129451.29,1 -2353,15726791,Nuttall,637,Spain,Female,45,2,157929.45,1,1,1,145134.49,1 -2354,15813144,Osborne,554,France,Female,26,7,92606.86,2,1,0,192709.69,0 -2355,15669342,Ferri,731,Germany,Male,35,2,127862.93,2,1,0,139083.7,0 -2356,15710366,Hamilton,569,Spain,Female,42,1,0,1,1,1,83629.6,1 -2357,15614934,McEwan,625,Germany,Female,37,4,142711.81,1,1,0,35625.41,0 -2358,15588701,Lai,592,France,Female,38,4,0,2,1,0,35338.96,0 -2359,15665438,Hs?,669,France,Male,43,1,163159.85,1,0,1,15602.8,0 -2360,15644896,Thompson,663,Germany,Male,32,3,108586.86,1,1,1,182355.21,0 -2361,15670205,Boyd,518,Germany,Female,41,5,110624.99,1,1,0,89327.67,0 -2362,15635776,Trevisani,686,Germany,Female,43,5,154846.24,2,1,1,151903.6,0 -2363,15791053,Lucciano,709,Germany,Male,45,4,122917.71,1,1,1,11.58,1 -2364,15644005,Holman,571,France,Female,33,9,0,2,0,1,77519.62,0 -2365,15796343,Bazhenov,707,France,Female,31,2,82787.93,2,0,0,91423.69,0 -2366,15751057,Douglas,701,Germany,Male,32,5,102500.34,1,0,0,106287.77,0 -2367,15623430,Hill,672,France,Male,34,9,0,2,1,0,161800.77,0 -2368,15682600,Lo,620,Germany,Male,39,9,159492.79,1,1,0,80582.34,1 -2369,15769312,Forbes,557,Spain,Male,48,10,0,2,1,1,185094.48,0 -2370,15708212,Lin,648,Spain,Female,54,7,118241.02,1,1,0,172586.89,1 -2371,15650258,Sinclair,479,France,Female,35,2,113090.4,1,1,0,195649.79,0 -2372,15604345,Kemp,730,France,Female,22,9,65763.57,1,1,1,145792.01,0 -2373,15578297,Ebelegbulam,737,Germany,Female,43,1,125537.38,1,1,0,138510.01,1 -2374,15671789,Woods,616,France,Male,31,3,94263.91,2,1,0,168895.06,0 -2375,15726186,Genovese,639,Spain,Male,29,4,133434.57,2,1,0,97983.44,0 -2376,15764618,Tseng,815,Spain,Female,39,6,0,1,1,1,85167.88,0 -2377,15730738,Chiang,786,Spain,Male,31,9,0,2,1,1,18210.36,0 -2378,15637650,Williams,549,France,Male,50,9,94748.76,2,0,1,13608.18,0 -2379,15606267,Wilson,622,France,Female,38,4,98640.74,1,1,1,110457.99,0 -2380,15625904,Wang,624,France,Male,26,9,74681.9,2,0,0,31231.35,0 -2381,15654463,Moore,841,France,Male,34,4,0,2,1,0,141582.66,0 -2382,15774151,Iadanza,614,Spain,Female,41,7,179915.85,1,0,0,14666.35,1 -2383,15693259,Wallace,676,France,Male,30,1,128207.23,1,1,1,55400.17,0 -2384,15642468,Clark,697,France,Male,42,9,132739.26,2,0,0,174667.65,0 -2385,15758531,Y?,732,France,Female,40,10,0,2,1,0,154189.08,0 -2386,15728352,Yermakov,623,France,Male,27,4,120509.81,1,0,0,142170.44,0 -2387,15637240,Wei,541,France,Male,46,4,124547.13,2,1,0,94499.06,0 -2388,15595588,Chukwunonso,773,Spain,Female,39,4,0,2,0,1,182081.45,0 -2389,15778395,McIntyre,762,Germany,Male,34,4,88815.56,2,1,0,68562.26,1 -2390,15711825,Ts'ai,655,Spain,Female,35,1,82231.51,2,1,0,88798.02,0 -2391,15599251,Chung,602,Germany,Male,32,7,184715.86,2,1,0,113781.99,0 -2392,15570004,Tsou,850,France,Male,31,3,0,2,1,0,121866.87,0 -2393,15656912,Aitken,649,Spain,Male,51,4,0,1,1,1,150390.57,0 -2394,15657342,Dawson,850,Germany,Male,28,4,147972.19,1,1,0,60708.72,1 -2395,15716284,Ward,543,France,Male,43,9,0,2,1,1,78858.07,0 -2396,15672374,Pai,672,France,Male,52,8,170008.84,1,0,0,56407.42,1 -2397,15732476,Ifeanyichukwu,600,France,Female,27,3,0,2,0,1,125698.97,0 -2398,15747724,Briggs,671,Spain,Female,34,10,0,1,1,0,23235.38,0 -2399,15633877,Morrison,706,Spain,Female,42,8,95386.82,1,1,1,75732.25,0 -2400,15672516,Wall,541,Germany,Male,51,7,90373.28,2,1,0,179861.79,0 -2401,15607827,Nebechukwu,711,Germany,Male,34,4,133467.77,2,1,1,42976.64,0 -2402,15751336,Yao,630,Spain,Male,30,3,0,2,0,1,10486.69,0 -2403,15646539,Liao,531,France,Male,31,3,96288.26,1,1,0,56794.73,0 -2404,15756901,Ch'ang,641,France,Female,26,4,91547.84,2,0,1,28157.34,0 -2405,15809286,Burke,631,Germany,Male,37,8,138292.64,2,0,0,152422.91,1 -2406,15759021,Kay,685,France,Male,35,9,0,1,1,0,167033.83,0 -2407,15725039,McIntyre,702,Spain,Male,32,8,71667.74,1,1,1,126082.18,0 -2408,15579130,Chidiegwu,708,Germany,Female,43,0,118994.84,1,1,0,181499.77,1 -2409,15754112,Musgrove,653,Spain,Male,55,7,0,2,1,1,41967.03,0 -2410,15735522,Boulger,654,Germany,Male,37,2,145610.07,2,0,0,186300.59,0 -2411,15613326,Gow,596,France,Female,33,1,138162.81,1,1,0,85412.54,0 -2412,15739502,Amaechi,549,Germany,Female,31,9,135020.21,2,1,1,23343.18,0 -2413,15670914,Robe,754,France,Male,38,2,0,2,1,0,180698.32,0 -2414,15604073,Bibi,815,Germany,Female,25,8,135161.67,1,1,1,136071.05,0 -2415,15806027,Niu,556,France,Female,52,9,0,1,1,0,175149.2,1 -2416,15574886,Palerma,706,France,Male,32,6,94486.47,1,1,1,146949.74,0 -2417,15707120,Cocci,850,France,Male,46,9,117640.39,1,1,0,88920.68,0 -2418,15800845,Artemieva,732,Spain,Female,33,8,111379.55,1,1,1,45098.62,0 -2419,15603914,Arcuri,614,France,Male,40,6,0,1,1,1,20339.79,1 -2420,15722765,Owen,580,Spain,Female,57,0,136820.99,1,0,1,108528.74,0 -2421,15783305,Franklin,593,France,Female,46,7,98752.51,1,1,0,145560.38,0 -2422,15574842,Lorenzo,653,Germany,Female,25,2,158266.42,3,1,1,199357.24,0 -2423,15607837,Muriel,746,France,Female,29,4,105599.67,1,1,1,43106.17,0 -2424,15714877,MacDevitt,662,France,Female,29,10,0,2,1,0,137508.31,0 -2425,15782941,Chijindum,573,France,Male,31,2,0,2,1,1,91957.39,0 -2426,15630167,Gibson,684,Spain,Female,39,4,139723.9,1,1,1,120612.11,0 -2427,15759038,Whitehead,793,France,Female,41,3,141806.46,1,1,0,102921.17,0 -2428,15661821,Johnstone,798,Germany,Female,49,5,132571.67,1,1,1,31686.33,1 -2429,15728006,Endrizzi,524,France,Male,40,2,180516.9,1,1,0,180002.42,0 -2430,15712176,Burke,816,France,Male,31,8,0,2,1,1,28407.4,0 -2431,15689351,Johnson,742,Germany,Female,41,4,92805.72,1,0,1,73743.95,1 -2432,15782247,Yeh,540,France,Male,22,4,0,3,1,1,186233.26,1 -2433,15769064,Marshall,537,Germany,Male,39,3,135309.36,1,1,0,31728.86,1 -2434,15718153,Kao,759,Spain,Female,74,6,128917.84,1,1,1,48244.64,0 -2435,15613189,Browne,774,France,Female,52,2,56580.93,1,1,0,113266.28,1 -2436,15661734,Taylor,608,Germany,Male,42,8,131390.75,2,1,0,71178.09,0 -2437,15592645,Gibbons,704,Spain,Male,37,4,0,2,0,0,25684.93,0 -2438,15768387,Nott,581,France,Male,41,8,0,2,0,0,29737.14,0 -2439,15792525,Lei,628,Germany,Female,61,1,97361.66,1,1,1,149922.38,1 -2440,15586976,Alexeeva,566,France,Female,42,6,0,1,1,0,180702.12,1 -2441,15790659,Sheets,701,Spain,Male,59,7,0,2,0,1,27597.59,0 -2442,15691446,Tokaryev,735,Spain,Male,29,10,0,2,1,1,95025.27,0 -2443,15772632,Ts'ui,680,France,Female,34,1,0,2,1,0,167035.07,0 -2444,15706587,Johnston,560,France,Male,57,0,0,2,0,1,116781.71,0 -2445,15572461,Kung,663,Germany,Female,29,4,102714.65,2,0,0,21170.81,0 -2446,15654409,Unwin,665,France,Female,34,5,67816.72,1,1,1,29641.58,0 -2447,15568025,Hsueh,758,France,Male,51,8,81710.46,1,1,1,116520.07,0 -2448,15715769,Hao,621,France,Male,26,2,75237.54,1,0,1,44220.4,0 -2449,15667458,L?,764,Germany,Male,28,10,124023.18,1,1,0,166188.28,0 -2450,15567980,Frater,537,Germany,Female,46,5,100727.5,1,0,1,140857.76,1 -2451,15679294,Brennan,589,France,Female,46,10,107238.85,2,1,0,37024.28,0 -2452,15606507,Pisani,555,France,Male,24,5,0,2,1,0,27513.47,0 -2453,15578825,Golubev,734,France,Female,29,0,139994.66,1,1,0,17744.72,0 -2454,15619935,Vanmeter,783,Spain,Female,59,9,126224.87,1,1,1,4423.63,0 -2455,15636089,Hs?,678,Germany,Female,51,1,145751.03,1,0,0,109718.44,1 -2456,15727490,Scott,661,France,Male,47,5,0,1,0,1,107243.31,1 -2457,15591766,Crawford,607,Spain,Female,25,4,121166.89,1,0,1,115288.24,0 -2458,15641629,P'eng,537,Spain,Female,38,1,0,2,0,1,41233.97,0 -2459,15813303,Rearick,513,Spain,Male,88,10,0,2,1,1,52952.24,0 -2460,15756920,Genovesi,576,France,Male,63,9,70655.48,1,0,0,78955.8,1 -2461,15726403,Glenny,660,Germany,Male,41,1,129901.21,1,1,0,26025.6,1 -2462,15592765,Marks,637,France,Male,40,8,125470.81,1,1,1,174536.17,0 -2463,15704442,Fleming,672,France,Female,53,9,169406.33,4,1,1,147311.47,1 -2464,15641136,Davison,629,France,Male,32,2,0,2,0,1,77965.44,0 -2465,15725818,Chibuzo,583,Germany,Male,40,4,107041.3,1,1,1,5635.63,0 -2466,15612071,Wilson,763,Spain,Female,32,10,95153.77,1,0,1,81310.1,0 -2467,15719809,Endrizzi,516,Germany,Male,32,3,145166.09,2,0,0,111421.45,0 -2468,15716518,Yuryeva,617,France,Female,27,4,0,2,0,0,190269.21,0 -2469,15742210,Ugochukwu,700,France,Male,38,9,65962.63,1,1,1,100950.48,0 -2470,15630617,Lo Duca,727,Germany,Male,36,6,140418.81,1,1,1,113033.73,1 -2471,15720838,Gallo,689,Spain,Female,31,3,139799.63,1,0,1,120663.57,0 -2472,15595537,Trout,626,Germany,Male,49,9,171787.84,2,1,0,187192.23,0 -2473,15623196,Morley,686,France,Male,38,6,149238.97,1,1,1,97825.23,0 -2474,15679249,Chou,351,Germany,Female,57,4,163146.46,1,1,0,169621.69,1 -2475,15693199,Shao,739,France,Female,37,8,0,2,1,0,191557.1,1 -2476,15661219,Trentino,627,France,Male,32,10,0,2,1,0,103287.62,0 -2477,15617136,Mazzanti,451,Germany,Female,38,9,61482.47,1,1,1,167538.66,0 -2478,15760294,Endrizzi,512,France,Female,41,8,145150.28,1,1,0,64869.32,1 -2479,15652808,Monaldo,774,France,Female,41,5,126670.37,1,1,0,102426.06,0 -2480,15657139,Otutodilinna,652,France,Female,40,8,84390.8,2,0,1,107876.2,0 -2481,15803790,Allen,638,Germany,Male,37,2,89728.86,2,1,1,37294.88,0 -2482,15764105,Milne,475,France,Female,57,1,0,2,1,0,89248.99,0 -2483,15672610,Somadina,567,Spain,Male,40,4,118628.8,1,0,0,91973.63,0 -2484,15766896,Chieloka,750,France,Male,37,3,0,2,1,0,16870.2,0 -2485,15587735,Chukwuebuka,850,France,Male,39,6,96863.13,1,1,1,121681.19,0 -2486,15659501,Chioke,753,France,Female,38,6,142263.45,1,0,1,33730.43,0 -2487,15745001,Kovalev,683,Spain,Female,36,7,0,2,1,0,104786.59,0 -2488,15651140,Doherty,710,France,Female,32,3,0,1,1,0,94790.34,0 -2489,15571148,Baranov,645,Spain,Female,21,1,0,2,0,0,28726.07,0 -2490,15776824,Rossi,714,France,Male,28,6,122724.37,1,1,1,67057.27,0 -2491,15633141,Robinson,696,Germany,Female,35,4,174902.26,1,1,0,69079.85,0 -2492,15764174,Bidencope,612,Spain,Female,26,4,0,2,1,1,179780.74,0 -2493,15778155,T'ien,520,Germany,Female,31,3,108914.17,1,1,1,183572.39,1 -2494,15715920,De Bernales,782,Spain,Male,23,10,98052.66,1,1,1,142587.32,0 -2495,15671917,Wade,666,France,Male,46,5,123873.19,1,1,1,177844.06,0 -2496,15666548,Chung,466,Germany,Female,56,2,111920.13,3,1,0,197634.11,1 -2497,15625623,Stevenson,567,France,Female,45,4,0,2,0,1,121053.19,0 -2498,15748123,Chienezie,613,France,Male,20,3,0,2,1,1,149613.77,0 -2499,15648735,Cashin,718,France,Male,37,8,0,2,1,1,142.81,0 -2500,15634974,Seppelt,614,France,Female,37,8,75150.34,4,0,1,131766.67,1 -2501,15713378,Brownless,711,France,Male,38,10,0,2,0,0,53311.78,0 -2502,15753370,McDonald,691,Germany,Female,38,5,114753.76,1,1,0,107665.02,0 -2503,15782659,Mamelu,527,France,Male,32,0,0,1,1,0,109523.88,0 -2504,15583364,McGregor,476,France,Female,32,6,111871.93,1,0,0,112132.86,0 -2505,15625942,McDonald,619,Spain,Female,45,0,0,2,0,0,113645.4,0 -2506,15720284,Crawford,607,Germany,Female,37,4,135927.06,1,0,0,180890.4,0 -2507,15679642,Feng,695,Spain,Male,44,8,0,2,1,1,70974.13,0 -2508,15628007,Genovese,653,France,Male,33,1,0,2,0,0,53379.52,0 -2509,15661974,Pirozzi,677,France,Male,46,2,57037.74,1,1,1,158531.01,0 -2510,15689341,Gibbs,655,France,Female,50,10,0,4,1,0,179267.94,1 -2511,15607993,Milne,625,France,Female,52,2,79468.96,1,1,1,84606.03,0 -2512,15693267,Dickson,679,Germany,Female,34,7,121063.85,1,1,0,56984.58,0 -2513,15769522,O'Connor,734,France,Male,51,1,118537.47,1,1,1,116912.45,0 -2514,15755825,McGuirk,666,France,Male,39,10,0,2,1,0,102999.33,0 -2515,15598175,Toscani,592,Germany,Female,26,4,105082.07,2,1,0,132801.57,0 -2516,15744327,Ruth,564,France,Male,40,4,0,1,1,0,85455.62,1 -2517,15798666,Hughes,814,France,Female,36,6,0,2,1,1,98657.01,0 -2518,15577064,Onyekaozulu,592,Germany,Male,36,2,104702.65,2,1,0,107948.72,0 -2519,15759436,Aksenov,758,France,Female,50,2,95813.76,3,1,1,67944.09,1 -2520,15690231,K'ung,612,Spain,Female,62,0,167026.61,2,1,1,192892.05,0 -2521,15751561,Meng,498,Germany,Male,61,7,102453.26,1,1,0,187247.56,1 -2522,15739068,Nwoye,638,Germany,Male,25,4,148045.45,2,1,1,114722.42,0 -2523,15758056,Calabresi,558,France,Male,35,1,0,2,0,0,111687.57,0 -2524,15742269,Milano,756,France,Female,24,1,0,2,1,0,184182.25,0 -2525,15726490,Kirby,782,Spain,Male,52,4,0,1,1,1,52759.82,1 -2526,15738411,Ho,505,France,Male,34,10,104498.79,1,0,1,126451.14,0 -2527,15727919,Chukwuemeka,671,Spain,Female,29,6,0,2,0,0,12048.67,0 -2528,15709396,Hale,801,France,Male,42,6,0,2,1,1,95804.33,0 -2529,15654106,K?,604,France,Male,26,8,149542.52,2,0,1,197911.52,0 -2530,15621653,Rice,716,France,Female,29,10,87946.39,1,1,1,182531.74,0 -2531,15598086,Brown,624,France,Female,45,3,68639.57,1,1,0,168002.31,1 -2532,15752300,Sagese,607,Germany,Male,47,4,148826.32,1,1,1,79450.61,0 -2533,15658693,Aksyonova,827,France,Female,60,2,0,2,0,1,60615.83,0 -2534,15631838,Findlay,606,France,Male,61,5,108166.09,2,0,1,8643.21,0 -2535,15803804,Walker,717,Germany,Female,35,5,103214.71,1,1,0,172172.7,0 -2536,15578809,Hao,651,Germany,Male,40,1,134760.21,2,0,0,174434.06,1 -2537,15752026,Hammer,691,France,Male,58,3,0,1,0,1,194930.3,1 -2538,15723706,Abbott,573,France,Female,33,0,90124.64,1,1,0,137476.71,0 -2539,15752838,Lucas,723,Spain,Male,38,6,0,2,1,1,94415.6,0 -2540,15569571,Davydova,584,Germany,Female,46,6,87361.02,2,1,0,120376.87,1 -2541,15769703,West,550,Germany,Female,45,8,111257.59,1,0,0,97623.42,1 -2542,15679770,Smith,611,France,Female,61,3,131583.59,4,0,1,66238.23,1 -2543,15791102,Mai,549,Germany,Male,41,9,95020.8,3,1,1,131710.59,1 -2544,15655192,Fiorentino,850,Spain,Female,24,1,0,2,0,1,69052.87,0 -2545,15709487,Freeman,668,Germany,Male,34,5,80242.37,2,0,0,56780.97,0 -2546,15687130,Nkemjika,686,France,Female,43,0,0,1,1,1,170072.9,0 -2547,15755178,Ramos,660,France,Male,50,1,0,3,1,1,191849.15,1 -2548,15634772,Mario,682,Spain,Female,59,0,122661.39,1,0,1,84803.76,0 -2549,15617197,Chien,524,France,Male,50,4,0,2,1,1,31840.59,1 -2550,15631240,Dubinina,645,France,Female,36,8,0,2,1,1,12096.61,1 -2551,15784301,Wang,850,France,Male,42,0,0,2,1,0,44165.84,0 -2552,15631310,Hsieh,537,France,Female,53,3,0,1,1,1,91406.62,0 -2553,15756560,Moran,599,Spain,Female,46,7,81742.84,2,1,0,83282.21,0 -2554,15732270,Hung,727,Spain,Male,71,8,0,1,1,1,198446.91,1 -2555,15739357,Moss,756,Spain,Male,30,2,145127.85,1,0,0,7554.68,0 -2556,15771540,Fedorova,755,France,Male,38,9,148912.44,1,1,0,80416.16,0 -2557,15567486,Li,634,Spain,Female,41,4,0,2,1,1,164549.74,0 -2558,15714634,Nebechi,837,France,Male,26,4,89900.24,2,1,0,175477.03,0 -2559,15727021,Obialo,727,Germany,Female,30,8,119027.28,2,1,1,137903.54,0 -2560,15650670,Bateson,567,Germany,Female,40,2,105222.86,2,1,0,93795.86,0 -2561,15711834,Long,650,Spain,Female,30,6,0,1,0,0,67997.13,1 -2562,15729763,Nelson,655,Spain,Male,34,1,116114.93,1,1,1,49492.15,0 -2563,15646566,Bell,763,France,Female,58,9,187911.55,1,0,1,35825.18,0 -2564,15645463,Udinese,843,France,Female,27,5,0,2,1,1,67494.23,0 -2565,15672144,Mao,667,France,Female,38,6,144432.04,1,1,1,73963.17,1 -2566,15596088,Fanucci,705,France,Female,50,4,77065.9,2,0,1,145159.26,0 -2567,15614878,Yeh,660,Germany,Female,29,6,180520.29,1,1,1,123850.58,0 -2568,15635240,Onuoha,553,France,Male,42,1,0,2,0,0,23822.04,0 -2569,15775905,Moore,612,Germany,Female,47,6,130024.87,1,1,1,45750.21,1 -2570,15700657,Thornton,641,Germany,Female,40,2,110086.69,1,1,0,159773.14,0 -2571,15611905,Warlow-Davies,513,Spain,Female,31,5,174853.46,1,1,0,84238.63,0 -2572,15652527,Champion,680,France,Male,44,7,108724.98,1,0,1,72330.46,0 -2573,15785865,Mazzanti,711,France,Male,58,9,91285.13,2,1,1,26767.85,0 -2574,15645942,Macleod,689,Spain,Male,40,2,0,2,1,1,164768.82,0 -2575,15688691,Lei,665,Germany,Female,51,9,110610.41,2,0,1,1112.76,1 -2576,15592736,Lucchese,551,Germany,Male,54,5,102994.04,1,1,0,176680.16,1 -2577,15673529,Lombardo,645,Spain,Male,36,4,59893.85,2,1,0,43999.64,0 -2578,15724145,William,616,Germany,Male,29,8,149318.55,1,1,0,140746.13,0 -2579,15704629,Wright,582,France,Female,32,1,116409.55,1,0,1,152790.92,0 -2580,15597896,Ozoemena,365,Germany,Male,30,0,127760.07,1,1,0,81537.85,1 -2581,15731790,Boyle,697,Germany,Female,38,6,132591.36,1,1,1,7387.8,1 -2582,15634719,Chinwendu,704,France,Male,31,0,0,2,1,0,183038.33,0 -2583,15703205,Uwaezuoke,656,France,Female,46,5,113402.14,2,1,1,138849.06,0 -2584,15567333,Archambault,712,France,Female,31,7,0,2,1,0,170333.38,0 -2585,15754537,Ko,748,France,Male,40,0,0,1,0,0,60416.76,0 -2586,15612030,Udegbulam,724,France,Male,28,9,0,2,1,1,100240.2,0 -2587,15573242,Greene,691,France,Male,50,6,136953.47,1,1,1,2704.98,0 -2588,15601892,Hunter,563,France,Male,33,8,0,2,0,1,68815.05,0 -2589,15663885,Blinova,741,France,Male,32,5,0,1,1,1,64839.23,0 -2590,15701096,De Garis,778,France,Male,44,8,123863.64,1,1,0,144494.94,0 -2591,15710450,Okwudiliolisa,848,Spain,Male,22,7,120811.89,1,1,1,185510.34,0 -2592,15790846,Ts'ai,634,Germany,Male,38,2,148430.55,1,1,1,56055.72,0 -2593,15658956,Tuan,505,Germany,Male,40,6,47869.69,2,1,1,155061.97,0 -2594,15755223,Tseng,692,Germany,Male,53,7,150926.99,2,0,0,119817.19,0 -2595,15787318,Holmwood,537,Germany,Female,47,6,103163.35,1,1,0,16259.64,1 -2596,15737310,Thompson,633,France,Male,29,10,130206.28,1,1,0,184654.87,0 -2597,15763665,Y?,833,France,Female,28,4,136674.51,2,0,0,5278.78,0 -2598,15668818,Chidubem,592,Spain,Female,40,2,200322.45,1,1,1,113244.73,0 -2599,15765812,Trevisani,587,Spain,Male,48,1,0,2,1,1,8908,0 -2600,15704844,Hsiung,550,Spain,Male,62,7,80927.56,1,0,1,64490.67,0 -2601,15744582,Randall,680,France,Female,24,10,0,3,1,0,154971.63,1 -2602,15616700,Leach,622,Spain,Female,41,9,0,2,1,1,155786.39,0 -2603,15683521,Godfrey,594,Germany,Male,28,0,142574.71,2,1,0,129084.82,0 -2604,15583049,Wallace,643,Germany,Female,34,7,160426.07,1,0,1,188533.11,0 -2605,15643752,Wei,540,France,Male,25,5,116160.23,1,1,0,13411.67,0 -2606,15620398,Mitchell,635,Spain,Female,34,5,98683.47,2,1,0,15733.19,0 -2607,15715707,Light,657,France,Male,32,3,118829.03,2,1,1,73127.61,0 -2608,15814209,Capon,814,France,Male,31,1,118870.92,1,1,0,101704.19,0 -2609,15733768,Hou,600,France,Male,32,1,0,1,1,1,101986.16,0 -2610,15755242,Rowe,682,France,Female,46,2,0,1,1,1,114442.66,0 -2611,15729412,Holloway,682,France,Male,38,4,107192.38,1,1,1,15669.17,0 -2612,15746564,O'Sullivan,566,France,Male,42,3,108010.78,1,1,1,157486.1,0 -2613,15588446,Udinesi,550,Spain,Male,34,3,0,2,0,0,131281.28,0 -2614,15665221,Nwebube,630,France,Male,26,7,129837.72,2,0,1,197001.15,0 -2615,15640846,Chibueze,546,Germany,Female,58,3,106458.31,4,1,0,128881.87,1 -2616,15700209,Walker,486,France,Male,63,9,97009.15,1,1,1,85101,0 -2617,15658360,Gregory,762,Spain,Male,35,9,122929.42,2,0,0,149822.04,0 -2618,15602735,Kuo,692,Germany,Male,45,6,152296.83,4,0,1,108040.86,1 -2619,15724834,Wilson,498,France,Female,30,1,0,2,0,0,135795.53,0 -2620,15800062,Lanford,850,Spain,Male,49,8,0,1,0,0,25867.67,1 -2621,15685300,Meng,603,France,Male,35,6,128993.76,2,1,0,130483.56,0 -2622,15760102,Yeh,551,France,Female,36,5,0,1,1,0,183479.12,0 -2623,15787026,Onwuatuegwu,627,Germany,Male,27,0,185267.45,2,1,1,77027.34,0 -2624,15653696,Goliwe,515,France,Female,28,9,0,2,0,0,94141.75,0 -2625,15788946,Anthony,605,Spain,Female,29,3,116805.82,1,0,0,4092.75,0 -2626,15600724,Scott,567,Germany,Male,29,5,129750.68,1,1,0,109257.59,0 -2627,15574324,Genovese,568,Germany,Female,29,2,129177.01,2,0,1,104617.99,0 -2628,15707144,Onyeorulu,571,Germany,Male,25,6,82506.72,2,1,0,167705.07,0 -2629,15775891,Myers,634,Germany,Male,48,2,107247.69,1,1,1,103712.05,1 -2630,15711789,Davey,768,Spain,Female,42,3,0,1,0,0,161242.99,1 -2631,15600879,Parsons,554,Germany,Female,36,3,157780.93,2,1,0,6089.13,0 -2632,15681196,Chikere,629,France,Male,35,1,172170.36,1,1,1,159777.37,0 -2633,15716000,Hs?eh,638,Spain,Male,48,2,0,2,1,1,7919.08,0 -2634,15766776,Sal,576,France,Male,41,1,0,1,1,1,188274.6,0 -2635,15680278,Ts'ai,661,Spain,Female,42,9,75361.44,1,1,0,27608.12,1 -2636,15688637,Witt,592,France,Female,27,4,0,2,1,1,183569.25,0 -2637,15591179,Skelton,702,Spain,Male,30,2,0,2,1,1,145537.32,0 -2638,15677435,Kazantseva,647,France,Female,29,0,98263.46,2,1,0,164717.95,0 -2639,15698619,Bowhay,593,France,Male,43,9,0,2,1,1,76357.43,0 -2640,15581036,Beyer,712,Germany,Female,40,3,109308.79,2,1,0,120158.72,1 -2641,15622117,Fries,625,Spain,Female,31,8,0,2,1,0,151843.54,0 -2642,15599301,Tao,538,Germany,Female,28,6,164365.44,1,0,1,5698.97,0 -2643,15581548,Kaodilinakachukwu,637,Spain,Female,22,5,98800,1,1,0,122865.55,0 -2644,15586870,Ni,632,France,Male,27,4,193125.85,1,1,1,152665.85,0 -2645,15735263,Hsueh,736,France,Male,27,5,51522.75,1,0,1,192131.77,0 -2646,15765322,Connely,755,France,Male,23,5,84284.48,2,1,1,62851.6,0 -2647,15582944,Becker,425,Spain,Female,39,5,0,2,1,0,140941.47,0 -2648,15687162,Clayton,461,France,Male,51,9,119889.84,1,0,0,56767.67,1 -2649,15644962,Connolly,745,France,Male,21,4,137910.45,1,1,1,177235.23,0 -2650,15612615,Graham,616,France,Female,37,6,0,2,1,0,86242.18,0 -2651,15813439,Ch'ien,587,France,Male,33,5,100116.82,1,1,0,34215.58,0 -2652,15604544,Manfrin,850,Germany,Male,40,4,166082.15,2,0,1,44406.17,0 -2653,15761348,Kuo,601,France,Female,38,0,0,2,1,0,165196.65,0 -2654,15785078,Fomin,730,Spain,Male,26,3,0,1,1,0,34542.41,0 -2655,15759874,Chamberlain,532,France,Male,44,3,148595.55,1,1,0,74838.64,1 -2656,15643658,Barber,850,Germany,Male,53,2,94078.97,2,1,0,36980.54,0 -2657,15713267,Zimmer,779,Spain,Female,34,5,0,2,0,1,111676.63,0 -2658,15737782,Brazenor,562,France,Male,29,9,0,1,1,1,25858.68,0 -2659,15815490,Cocci,670,Germany,Male,40,2,164948.98,3,0,0,177028,1 -2660,15679410,Caldwell,729,France,Female,62,4,140549.4,1,1,0,30990.16,1 -2661,15756241,Yirawala,767,France,Female,44,2,152509.25,1,1,1,136915.15,0 -2662,15688409,Donaldson,742,France,Female,28,2,191864.51,1,1,0,108457.99,1 -2663,15742272,Ozerova,669,France,Female,44,8,96418.09,1,0,0,131609.48,1 -2664,15717898,Bruce,542,Spain,Male,32,2,131945.94,1,0,1,159737.56,0 -2665,15769582,Kang,586,France,Male,29,3,0,2,1,1,142238.54,0 -2666,15635660,Rossi,612,Germany,Male,30,9,142910.15,1,1,0,105890.55,1 -2667,15576723,Ts'ai,740,France,Female,37,7,0,2,1,1,194270.91,0 -2668,15591577,Moran,584,France,Male,35,3,146311.58,1,1,1,105443.47,0 -2669,15582325,Jennings,524,France,Male,52,2,87894.26,1,1,0,173899.42,1 -2670,15693947,Tokareva,614,France,Female,19,5,97445.49,2,1,0,122823.34,0 -2671,15760446,Pagnotto,598,France,Female,64,9,0,1,0,1,13181.37,1 -2672,15611105,Castella,799,Spain,Male,35,7,0,2,0,1,140780.8,0 -2673,15630920,Du Cane,724,France,Male,34,2,154485.74,2,0,0,78560.64,0 -2674,15574910,Ferguson,601,France,Male,50,2,115625.07,1,1,0,185855.21,0 -2675,15756472,Odinakachukwu,804,France,Male,25,7,108396.67,1,1,0,128276.95,0 -2676,15682890,Woronoff,745,Germany,Male,38,5,65095.41,2,1,1,140197.42,0 -2677,15641994,Meng,667,Germany,Male,43,1,103018.45,1,1,0,32462.39,1 -2678,15733297,Sinclair,518,France,Female,38,10,84764.79,1,1,1,162253.9,0 -2679,15767793,Hsu,819,France,Female,38,10,0,2,1,0,30498.7,0 -2680,15725698,Panicucci,520,Spain,Female,35,4,115680.81,1,1,1,90280.7,0 -2681,15813532,Burns,625,France,Female,39,5,0,2,1,0,32615.21,0 -2682,15576760,Onodugoadiegbemma,673,Germany,Male,36,5,73088.06,2,0,0,196142.26,0 -2683,15732102,Darling,656,Germany,Female,27,3,150905.03,2,1,0,16998.72,0 -2684,15739046,Maggard,850,Spain,Female,23,9,143054.85,1,0,1,62980.96,0 -2685,15631927,Thomas,574,Spain,Female,28,7,0,2,0,0,185660.3,0 -2686,15672115,Lettiere,679,France,Male,60,6,0,2,1,1,77331.77,0 -2687,15618765,Ponomaryov,530,Germany,Female,42,0,99948.45,1,0,1,97338.62,0 -2688,15679148,Oliver,508,France,Male,44,3,115451.05,2,0,0,67234.33,0 -2689,15728474,Chienezie,558,Germany,Male,32,4,108235.91,1,1,1,143783.28,0 -2690,15636999,Mao,414,France,Male,38,8,0,1,0,1,77661.12,1 -2691,15754261,Ho,648,Spain,Male,42,2,98795.61,2,1,0,89123.99,0 -2692,15629150,Lucchese,721,France,Female,37,1,0,2,1,0,70810.8,0 -2693,15736274,Prokhorova,751,France,Male,31,8,0,2,0,0,17550.49,0 -2694,15627697,Alekseyeva,662,France,Male,34,2,0,2,0,1,21497.27,0 -2695,15721585,Blacklock,628,Germany,Male,29,3,113146.98,2,0,1,124749.08,0 -2696,15639946,Sazonova,597,Germany,Female,39,8,162532.14,3,1,0,36051.46,1 -2697,15792176,Henty,698,Spain,Female,40,0,92053.44,1,1,1,143681.83,0 -2698,15699450,Li,723,France,Male,48,7,0,2,1,1,150694.58,0 -2699,15729954,Azuka,586,France,Female,28,5,0,3,1,0,170487.4,1 -2700,15600103,Alexander,633,Germany,Female,29,8,104944.1,1,1,1,97684.46,0 -2701,15786200,Brock,564,France,Male,31,4,0,2,1,0,53520.03,0 -2702,15797010,Shen,649,France,Female,31,2,0,2,1,0,15200.61,0 -2703,15670172,Padovesi,622,France,Female,30,4,107879.04,1,0,1,196894.62,0 -2704,15627352,Bulgakov,459,Germany,Male,46,7,110356.42,1,1,0,4969.13,1 -2705,15622494,Mazzanti,718,France,Male,27,2,0,2,0,0,26229.24,0 -2706,15585835,Lord,655,Spain,Female,34,4,109783.69,2,1,0,134034.32,0 -2707,15595071,Ramos,696,France,Male,22,9,149777,1,1,1,198032.93,0 -2708,15628203,Pai,637,France,Female,38,3,104339.56,1,0,0,119882.86,0 -2709,15667190,Yuan,630,Spain,Female,21,1,85818.18,1,1,1,133102.3,0 -2710,15780212,Mao,592,France,Male,37,4,212692.97,1,0,0,176395.02,0 -2711,15766869,Uspenskaya,634,Germany,Male,37,1,89696.84,2,1,1,193179.88,0 -2712,15775741,Powell,608,France,Female,28,9,0,2,1,1,125062.02,0 -2713,15628170,Brown,565,Germany,Female,32,9,68067.24,1,1,0,143287.58,0 -2714,15701318,Poole,763,Spain,Male,67,9,148564.66,1,0,1,87236.4,0 -2715,15710928,McChesney,665,France,Female,55,8,136354.16,1,1,1,93769.89,0 -2716,15682547,Lucchese,649,France,Male,38,1,122214,1,0,1,88965.46,0 -2717,15631170,Clements,695,France,Male,45,3,0,2,1,1,30793.61,0 -2718,15648702,Yuriev,775,Germany,Male,70,6,119684.88,2,1,1,74532.02,0 -2719,15783444,Endrizzi,788,France,Female,39,3,135139.33,1,0,1,113086.08,0 -2720,15809178,Pan,569,Germany,Female,42,9,146100.75,1,1,0,32574.01,1 -2721,15806688,Manfrin,726,Spain,Female,56,8,123110.9,3,0,1,130113.78,1 -2722,15576824,Kennedy,564,Germany,Female,44,3,111760.4,3,1,1,104722.47,1 -2723,15675422,Conway,544,France,Female,32,9,110728.39,1,1,1,14559.62,0 -2724,15681550,Lablanc,614,France,Female,41,8,121558.46,1,1,1,598.8,0 -2725,15812628,Dodd,453,Germany,Female,38,8,120623.21,1,1,0,129697.99,0 -2726,15597951,Muir,471,France,Female,58,4,114713.57,1,1,1,36315.03,0 -2727,15807045,Milanesi,829,Germany,Female,37,3,103457.76,1,0,0,1114.12,0 -2728,15581748,Shen,754,Germany,Male,57,2,101134.87,2,1,1,70954.41,0 -2729,15770420,Dillon,749,Germany,Male,46,10,78136.36,2,1,1,73470.98,0 -2730,15608230,Hoelscher,667,France,Male,23,1,0,2,1,0,91573.19,0 -2731,15730339,Bell,670,Spain,Male,30,3,133446.34,1,0,0,3154.95,0 -2732,15712584,Liao,670,France,Female,33,7,0,2,1,1,88187.81,0 -2733,15592816,Udokamma,623,Germany,Female,48,1,108076.33,1,1,0,118855.26,1 -2734,15641480,Sinnett,571,France,Male,32,5,131354.25,1,1,0,125256.53,0 -2735,15708505,Palerma,641,Germany,Female,37,7,62974.64,2,0,1,39016.43,0 -2736,15791131,Chimaijem,551,Germany,Female,30,2,143340.44,1,1,0,145796.49,0 -2737,15618225,Porter,741,Germany,Male,36,8,116993.43,2,1,0,168816.22,0 -2738,15644724,Fan,472,France,Male,31,4,58662.92,2,0,1,73322,0 -2739,15662098,Palmer,650,Spain,Male,41,3,128808.65,3,0,0,113677.53,1 -2740,15723894,Younger,625,France,Male,45,7,137555.44,1,0,0,124607.7,0 -2741,15787699,Burke,650,Germany,Male,34,4,142393.11,1,1,1,11276.48,0 -2742,15687738,Nwagugheuzo,535,France,Female,38,8,0,2,1,0,136620.64,0 -2743,15576126,Young,649,France,Female,41,2,125785.23,1,1,1,70523.92,0 -2744,15658889,Watson,689,France,Male,22,4,136444.25,1,1,0,51980.25,1 -2745,15667046,Tseng,694,Spain,Male,38,7,121527.4,1,1,0,113481.02,0 -2746,15669957,Drake,655,Germany,Male,52,9,144696.75,1,1,1,49025.79,0 -2747,15655794,Hanna,620,France,Male,36,8,0,2,1,1,145937.99,0 -2748,15599829,Padovesi,577,France,Female,35,10,0,2,1,1,25161.61,0 -2749,15753332,Loftus,401,Germany,Male,48,8,128140.17,1,1,0,175753.55,1 -2750,15671124,Buccho,599,France,Male,25,6,120383.41,1,1,1,24903.09,0 -2751,15767474,Lorenzo,481,France,Female,57,9,0,3,1,1,169719.35,1 -2752,15720671,Ibezimako,704,France,Male,42,8,129735.3,2,1,1,179565.57,0 -2753,15626787,Wei,698,Spain,Female,31,8,185078.26,1,0,0,115337.74,1 -2754,15774491,Ross,480,France,Female,28,6,0,2,0,0,48131.92,0 -2755,15579647,Oluchukwu,682,France,Male,42,0,0,1,1,1,160828.98,0 -2756,15625522,Walker,700,Spain,Male,31,7,0,2,0,1,145151.96,0 -2757,15765806,Wu,492,France,Male,29,1,144591.96,1,1,1,196293.76,0 -2758,15566708,Chidalu,444,France,Female,45,4,0,2,1,0,161653.5,1 -2759,15668347,Ingram,624,France,Male,36,6,0,2,0,0,84635.64,0 -2760,15575214,Ch'en,709,France,Male,37,7,0,1,1,0,159486.76,0 -2761,15591123,Iredale,557,Germany,Male,68,2,100194.44,1,1,1,38596.34,0 -2762,15573280,Gallagher,646,Germany,Male,50,6,145295.31,2,1,1,27814.74,0 -2763,15589018,Padilla,719,Germany,Male,28,3,106070.29,2,1,1,183893.31,0 -2764,15654495,Potter,706,Germany,Female,47,6,120621.89,1,1,1,140803.7,0 -2765,15597265,Mao,660,France,Male,38,7,0,2,0,1,146585.53,0 -2766,15733876,Schneider,667,France,Male,36,9,0,2,1,1,40062.29,0 -2767,15677217,Ibragimova,705,France,Male,30,1,0,1,1,1,181300.32,0 -2768,15747265,Huang,598,Germany,Female,27,10,171283.91,1,1,1,84136.12,0 -2769,15713379,Anderson,669,France,Male,26,4,0,2,1,1,197594.34,0 -2770,15730433,Nakayama,580,Germany,Female,38,1,128218.47,1,1,0,125953.83,1 -2771,15693347,Gardener,676,France,Female,32,5,0,2,1,1,75465.41,0 -2772,15715465,Aksenova,714,Germany,Male,28,7,77776.39,1,1,0,177737.07,0 -2773,15680736,Milne,597,Germany,Female,72,6,124978.19,2,1,1,7144.46,0 -2774,15610765,Onwumelu,559,France,Male,29,1,0,2,0,0,155639.76,0 -2775,15650034,Kudryashova,564,France,Female,28,1,0,1,1,1,162428.05,0 -2776,15782468,Hart,850,Spain,Male,51,3,109799.55,2,1,1,12457.76,1 -2777,15685109,Teng,689,France,Male,39,7,0,2,0,0,14917.09,0 -2778,15776233,Kruglova,758,Germany,Female,61,8,125397.21,1,1,0,182184.09,1 -2779,15761141,Palerma,604,Spain,Female,71,10,0,2,1,1,129984.2,0 -2780,15781702,Brookes,733,Germany,Male,38,9,111347.37,2,0,1,194872.97,0 -2781,15790235,Hsing,778,Spain,Male,40,8,104291.41,2,1,1,117507.11,0 -2782,15641416,Shaffer,732,Germany,Female,61,9,94867.18,2,1,1,157527.6,1 -2783,15775234,Laurie,646,France,Male,24,8,0,2,0,0,92612.88,0 -2784,15659475,Chung,597,France,Female,33,6,135703.59,2,0,0,74850.84,0 -2785,15642202,Whitfield,821,Germany,Female,37,5,106453.53,2,0,1,127413,0 -2786,15771417,Thomas,640,France,Male,43,7,132412.38,1,0,0,69584.3,1 -2787,15585100,Rioux,511,Germany,Female,40,9,124401.6,1,1,0,198814.24,1 -2788,15700487,Osonduagwuike,805,France,Male,46,6,118022.06,3,1,0,162643.15,1 -2789,15726589,Matveyev,540,Germany,Male,39,1,82531.11,1,1,0,114092.52,0 -2790,15747503,Hayward,705,Spain,Male,44,0,184552.12,1,1,0,68860.3,1 -2791,15595883,Nkemdirim,540,Germany,Male,39,4,127278.31,1,1,1,16150.34,0 -2792,15663826,Brim,532,Spain,Female,66,3,0,1,1,1,115227.02,0 -2793,15742820,Trevisano,535,France,Female,45,2,0,2,0,1,170621.55,0 -2794,15624793,Soubeiran,627,Germany,Male,23,5,184244.86,1,1,0,103099.22,0 -2795,15597930,Wilson,646,France,Male,52,8,59669.43,1,0,0,172495.81,1 -2796,15665110,Helena,515,France,Female,25,7,79543.59,1,0,1,38772.82,0 -2797,15770719,Duncan,697,France,Female,39,6,151553.19,1,1,1,44946.29,0 -2798,15731327,Hale,652,Germany,Male,27,2,166527.88,2,0,1,146007.7,0 -2799,15576044,Macdonald,579,Germany,Male,28,6,150329.15,1,1,0,145558.42,0 -2800,15775662,McKay,760,France,Male,43,8,121911.59,1,1,0,193312.33,0 -2801,15646817,Chiekwugo,769,France,Male,51,9,156773.78,2,1,0,40257.79,0 -2802,15596060,Skinner,498,Spain,Male,29,8,127864.26,1,1,1,46677.9,0 -2803,15723299,Sorokina,774,France,Male,53,4,113709.28,1,1,1,153887.93,1 -2804,15636982,Weller,705,Germany,Female,43,7,79974.55,1,1,1,103108.33,0 -2805,15751175,Bess,648,France,Female,44,2,0,2,1,1,58652.23,0 -2806,15618936,MacDonald,688,France,Female,51,5,0,1,1,0,91624.11,1 -2807,15787529,Gray,592,Spain,Male,38,0,0,1,1,0,65986.48,1 -2808,15780128,Ogbonnaya,705,France,Male,33,3,144427.96,2,1,0,113845.19,0 -2809,15615991,Udegbulam,654,France,Male,42,7,99263.09,1,1,1,67607.9,0 -2810,15757001,Mai,624,France,Female,32,2,79368.87,2,1,1,145471.94,0 -2811,15595388,Yeh,594,France,Female,30,10,0,2,1,1,124071.71,0 -2812,15699550,Babbage,695,Spain,Female,34,9,0,2,1,1,67502.12,0 -2813,15581620,Franklin,597,France,Male,28,2,0,3,1,1,78707.97,0 -2814,15600934,Randell,758,France,Female,52,7,125095.94,1,1,0,171189.83,1 -2815,15738672,Paterson,737,Germany,Female,40,2,162485.8,2,1,0,149381.32,0 -2816,15721307,Pickering,694,Germany,Male,37,1,95668.82,2,1,0,100335.55,0 -2817,15619280,Uspensky,683,France,Male,25,4,0,2,1,0,152698.24,0 -2818,15768244,Macleod,538,Spain,Female,30,8,0,2,1,1,41192.95,0 -2819,15806837,Nnaife,669,France,Male,37,4,0,1,1,0,132540.33,0 -2820,15643496,Randolph,730,France,Female,34,5,74197.38,2,1,0,96875.52,0 -2821,15813916,Kudryashova,622,France,Female,31,1,89688.94,1,1,1,152305.47,0 -2822,15626385,George,714,Spain,Female,33,10,103121.33,2,1,1,49672.01,0 -2823,15603582,Robertson,569,Spain,Female,34,3,0,1,1,0,133997.53,0 -2824,15764351,Yuryeva,668,Germany,Female,59,5,120170.07,1,0,1,50454.8,0 -2825,15667938,Hurst,628,France,Male,32,9,149136.31,2,1,1,16402.11,0 -2826,15576360,Ch'iu,600,France,Male,40,1,141136.79,1,1,1,67803.83,0 -2827,15628813,King,693,France,Female,43,4,152341.55,1,1,0,9241.78,0 -2828,15584190,Esposito,704,France,Male,36,7,120026.98,2,0,1,100601.73,0 -2829,15716449,Fraser,527,Spain,Male,33,9,132168.28,1,0,0,98734.15,0 -2830,15759913,Trentini,553,Germany,Male,43,6,85200.82,2,1,1,160574.09,0 -2831,15701555,Nicholls,575,Spain,Male,53,1,84903.33,2,0,1,26015.8,0 -2832,15758482,Montalvo,626,France,Female,32,0,0,2,0,0,187172.54,0 -2833,15758171,Tien,582,France,Male,20,4,0,1,1,1,55763.66,0 -2834,15680346,Chuang,683,Spain,Male,40,8,0,1,1,0,75848.22,0 -2835,15649124,Fang,850,France,Male,30,9,121535.18,1,0,0,40313.47,0 -2836,15812917,Kosisochukwu,653,Spain,Male,35,6,116662.96,2,1,1,23864.21,0 -2837,15768455,Young,679,France,Male,60,8,0,2,1,1,51380.9,0 -2838,15703059,Scott,549,Germany,Female,49,6,124829.16,1,0,1,93551.36,0 -2839,15646196,Yeh,850,Spain,Female,36,2,155180.56,2,0,0,169415.54,0 -2840,15585451,Vigano,558,Germany,Female,32,1,108262.87,1,1,1,6935.31,0 -2841,15714057,Windradyne,528,Spain,Male,40,4,0,2,1,0,25399.7,0 -2842,15748473,Curnow,801,France,Male,38,5,0,2,1,0,66256.27,0 -2843,15785782,Ugonna,513,Spain,Male,48,2,0,1,1,1,114709.13,1 -2844,15693233,De Neeve,666,Germany,Male,38,6,99812.88,2,1,1,158357.97,0 -2845,15757521,Ricci,606,France,Male,35,2,132164.26,1,0,1,164815.59,0 -2846,15812513,Nnaife,599,Germany,Male,45,10,103583.05,1,1,0,132127.69,1 -2847,15674950,Ebelechukwu,544,Germany,Male,39,4,142406.43,2,1,0,146637.45,0 -2848,15678572,Keating,529,Spain,Male,38,7,99842.5,2,1,0,90256.06,1 -2849,15713608,Tuan,850,France,Female,41,5,0,2,1,1,34827.43,0 -2850,15579262,Shearston,497,France,Male,41,9,0,1,0,0,22074.48,0 -2851,15610426,Tien,764,France,Female,39,5,81042.42,1,0,1,109805.17,0 -2852,15776454,Hamilton,603,France,Female,48,5,0,1,1,0,100478.6,1 -2853,15771483,Arnold,609,France,Male,40,6,0,2,1,1,97416.34,0 -2854,15648489,Ting,487,France,Male,53,4,199689.49,1,1,1,24207.86,1 -2855,15646609,Chao,748,France,Male,33,1,142645.43,1,0,0,69132.66,0 -2856,15693203,Powell,710,Spain,Female,75,5,0,2,1,1,9376.89,0 -2857,15813067,Williams,432,Germany,Female,45,3,110219.14,1,1,0,43046.7,1 -2858,15769829,Cheng,534,Spain,Male,51,3,0,2,0,1,20856.31,0 -2859,15662434,Zhdanova,607,France,Male,25,3,0,2,0,0,187048.72,0 -2860,15773503,Tsai,551,Spain,Male,32,4,0,2,1,0,53420.53,0 -2861,15705890,Nebechukwu,674,France,Male,45,7,142072.02,1,1,0,37013.29,0 -2862,15711398,Fetherstonhaugh,525,France,Female,25,6,0,2,1,0,89566.64,0 -2863,15752375,Ojiofor,645,Germany,Male,33,8,149564.61,1,0,0,149913.84,0 -2864,15659175,Severson,755,France,Female,43,9,0,2,1,0,18066.69,0 -2865,15597033,Speight,708,Germany,Male,37,8,153366.13,1,1,1,26912.34,0 -2866,15590228,Greenwalt,715,France,Male,21,6,76467.16,1,1,1,173511.72,0 -2867,15631848,Grover,727,France,Female,26,9,121508.28,1,1,1,146785.44,0 -2868,15654211,Milani,559,Spain,Female,27,1,0,1,0,1,1050.33,0 -2869,15707968,Akobundu,545,Spain,Male,36,8,73211.12,2,1,0,89587.34,1 -2870,15594084,Anderson,524,France,Male,22,9,0,2,1,0,74405.34,0 -2871,15651093,Chien,707,France,Female,55,1,0,2,0,1,54409.48,0 -2872,15798824,Kennedy,671,Spain,Male,38,0,92674.94,2,1,0,3647.57,0 -2873,15671591,Castiglione,439,Spain,Male,52,3,96196.24,4,1,0,198874.52,1 -2874,15707189,Marshall,667,Germany,Female,36,1,114391.62,1,1,1,53412.54,0 -2875,15733581,Duncan,831,Germany,Male,32,9,80262.66,1,1,0,194867.78,0 -2876,15641640,Uspenskaya,545,Spain,Female,33,7,173331.52,1,1,0,150452.88,0 -2877,15585284,Thomson,604,Spain,Female,35,7,147285.52,1,1,1,57807.05,0 -2878,15617866,Calabrese,657,Spain,Male,67,5,119785.47,2,1,1,107534.32,0 -2879,15667751,Herrera,487,Spain,Female,36,1,140137.15,1,1,0,194073.33,0 -2880,15669411,Muse,750,Germany,Female,52,6,107467.56,1,1,0,126233.18,1 -2881,15789425,Marsden,694,Germany,Female,37,8,98218.04,2,1,0,182354.46,1 -2882,15570943,Artemyeva,711,Germany,Female,35,2,133607.75,1,1,1,120586.32,0 -2883,15685829,McKay,551,France,Male,37,3,0,2,1,1,50578.4,0 -2884,15721917,Chuang,559,France,Female,38,8,95139.41,1,1,1,86575.46,0 -2885,15776047,Nicholls,620,France,Female,29,3,0,2,0,1,153392.28,0 -2886,15716024,Dennis,660,Spain,Male,42,5,0,2,1,0,115509.59,0 -2887,15675328,Knight,449,France,Female,37,6,0,2,1,0,82176.48,0 -2888,15604314,Webb,703,Germany,Female,26,1,97331.19,1,1,0,63717.49,0 -2889,15658339,Pugliesi,795,Germany,Male,37,2,139265.63,2,1,1,198745.94,0 -2890,15630402,Nebechukwu,594,France,Female,31,9,0,1,0,1,5719.11,0 -2891,15689616,Ward,586,Spain,Male,34,5,168094.01,1,0,0,20058.61,0 -2892,15774224,Nixon,613,Germany,Female,30,5,131563.88,2,1,0,170638.98,0 -2893,15701291,Chidubem,601,France,Male,44,3,0,2,1,0,30607.11,0 -2894,15719606,Rivers,657,France,Male,50,9,0,2,0,0,37171.46,0 -2895,15644119,Sochima,531,France,Male,31,3,0,1,1,1,42589.33,0 -2896,15646859,Heydon,621,Germany,Male,47,7,107363.29,1,1,1,66799.28,0 -2897,15606836,Lombardo,782,France,Female,33,2,94493.03,1,0,1,101866.39,0 -2898,15664150,Holland,528,Germany,Female,29,9,170214.23,2,1,0,49284,0 -2899,15624510,Tien,696,France,Male,52,6,139781.06,1,1,0,27445.4,1 -2900,15810944,Bryant,586,France,Female,35,7,0,2,1,0,70760.69,0 -2901,15668575,Hao,626,Spain,Female,26,8,148610.41,3,0,1,104502.02,1 -2902,15603246,Genovesi,498,France,Male,73,2,170241.7,2,1,1,165407.96,0 -2903,15804002,Kovalev,691,France,Female,33,1,128306.83,1,1,1,113580.79,0 -2904,15728773,Hsieh,568,France,Female,47,7,0,2,1,1,45978.39,0 -2905,15598044,Debellis,715,France,Female,35,3,0,1,1,1,152012.36,0 -2906,15694829,Chibueze,680,Germany,Male,32,7,175454,1,0,1,77349.92,0 -2907,15600575,Padovano,802,Spain,Male,41,6,0,2,1,0,47322.05,0 -2908,15727311,Yen,539,France,Female,22,0,100885.93,2,1,1,38772.65,0 -2909,15570769,Kibble,494,France,Male,69,9,93320.8,1,1,1,24489.44,0 -2910,15606274,Lori,594,Germany,Male,38,6,63176.44,2,1,1,14466.08,0 -2911,15746139,Enemuo,596,France,Male,33,2,139451.67,1,0,0,63142.12,0 -2912,15704987,Lu,649,France,Female,52,8,49113.75,1,1,0,41858.43,0 -2913,15628972,Nebeolisa,699,Germany,Male,32,1,123906.22,3,1,1,127443.82,1 -2914,15697686,Stewart,787,France,Female,40,6,0,2,1,1,84151.98,0 -2915,15733883,Ward,604,France,Male,28,7,0,2,0,0,58595.64,0 -2916,15617482,Milanesi,489,Germany,Female,52,1,131441.51,1,1,0,37240.11,1 -2917,15704583,Chikwado,651,France,Male,56,2,0,1,1,0,114522.68,1 -2918,15621083,Douglas,698,France,Male,57,6,136325.48,2,1,1,72549.27,1 -2919,15649487,Sal,578,Germany,Female,38,4,113150.44,2,1,0,176712.59,1 -2920,15736760,Douglas,538,Spain,Female,42,9,0,1,0,0,152855.96,0 -2921,15714658,Yates,696,France,Female,33,4,0,2,1,1,73371.65,0 -2922,15599081,Watt,507,Germany,Female,46,8,102785.16,1,1,1,70323.68,0 -2923,15705113,P'an,685,Spain,Male,34,6,83264.28,1,0,0,9663.28,0 -2924,15631159,H?,705,Germany,Male,41,4,72252.64,2,1,1,142514.66,0 -2925,15792818,Perry,499,Germany,Female,29,6,148051.52,1,1,0,118623.94,0 -2926,15633531,Lavrov,717,France,Female,76,9,138489.66,1,1,1,68400.14,0 -2927,15744529,Chiekwugo,510,France,Male,63,8,0,2,1,1,115291.86,0 -2928,15669656,Macdonald,632,France,Male,32,6,111589.33,1,1,1,170382.99,0 -2929,15581198,Jenkins,668,Germany,Female,39,0,122104.79,1,1,0,112946.67,1 -2930,15729054,Korovina,744,Germany,Male,32,4,96106.83,1,1,1,79812.77,0 -2931,15573452,Manning,663,Germany,Male,42,7,115930.87,1,1,0,19862.78,0 -2932,15776733,Wilson,638,Germany,Female,37,7,124513.66,2,1,0,158610.89,0 -2933,15724858,Begum,688,France,Female,54,9,0,1,1,0,191212.63,1 -2934,15713144,Ingrassia,588,Spain,Male,46,8,0,1,1,0,61931.21,0 -2935,15690188,Maclean,631,France,Male,33,7,0,1,1,1,58043.02,1 -2936,15689425,Olejuru,687,Spain,Male,35,8,100988.39,2,1,0,22247.27,0 -2937,15671766,Enyinnaya,599,France,Male,44,10,118577.24,1,1,1,31448.52,0 -2938,15782806,Watson,718,Spain,Male,28,6,0,2,1,0,146875.86,0 -2939,15764419,Langdon,730,France,Male,27,5,0,2,1,1,116081.93,0 -2940,15591915,Frolov,533,France,Female,39,2,0,1,0,1,73669.94,1 -2941,15772798,Chikezie,711,Spain,Female,28,5,0,2,1,1,93959.96,0 -2942,15792008,Zetticci,555,Spain,Female,26,9,0,2,0,1,158918.03,0 -2943,15715541,Yang,850,France,Female,42,9,113311.11,1,1,1,198193.75,0 -2944,15639277,Lin,678,France,Female,41,9,0,1,0,0,13160.03,0 -2945,15798850,Goddard,576,France,Male,32,7,0,2,1,0,4660.91,0 -2946,15776348,Rogers,835,Germany,Male,20,4,124365.42,1,0,0,180197.74,1 -2947,15727696,Zubareva,592,France,Male,42,1,147249.29,2,1,1,63023.02,0 -2948,15793813,Onochie,774,France,Male,36,7,103688.19,1,0,1,118971.74,0 -2949,15694395,Ts'ui,620,France,Female,29,1,138740.24,2,0,0,154700.61,0 -2950,15764195,Newsom,519,Spain,Male,39,4,111900.14,1,1,1,97577.17,0 -2951,15744919,Genovese,734,Spain,Female,37,0,152760.24,1,1,1,48990.5,0 -2952,15671655,Thorpe,763,Germany,Male,31,7,143966.3,2,1,1,140262.96,1 -2953,15654901,Horton,733,France,Male,51,10,141556.96,1,1,0,130189.53,0 -2954,15649136,Williamson,650,France,Female,43,6,0,2,1,1,16301.91,0 -2955,15775562,Shoobridge,538,France,Female,33,5,0,2,1,0,126962.41,0 -2956,15807481,Peng,577,France,Female,46,1,0,1,1,1,158750.53,0 -2957,15642885,Gray,792,France,Male,30,8,0,2,1,0,199644.2,0 -2958,15789109,Watson,686,France,Female,41,10,0,1,1,1,144272.71,1 -2959,15814004,Fyodorova,589,France,Male,29,2,0,2,0,1,98320.27,0 -2960,15673619,Bazhenov,530,France,Male,25,9,162560.32,1,1,0,64129.03,0 -2961,15595135,Solomon,778,Germany,Female,29,7,123229.46,1,1,0,181221.09,0 -2962,15583681,Layh,616,Spain,Male,31,7,76665.71,2,1,1,163809.08,0 -2963,15605000,John,550,France,Male,38,9,140278.99,3,1,1,171457.06,1 -2964,15718071,Tuan,655,France,Female,51,3,0,2,0,1,15801.02,0 -2965,15679760,Slattery,721,France,Male,46,1,115764.32,2,0,0,102950.79,0 -2966,15654574,Onyekachi,499,Germany,Male,36,5,131142.53,2,1,0,174918.46,0 -2967,15577178,Genovese,511,France,Male,45,5,68375.27,1,1,0,193160.25,1 -2968,15595324,Daniels,579,Germany,Female,39,5,117833.3,3,0,0,5831,1 -2969,15756932,Caldwell,696,Spain,Female,36,7,0,2,1,1,82298.59,0 -2970,15726358,Chiemenam,681,France,Male,34,7,0,2,0,0,130686.59,0 -2971,15595228,Wanliss,815,France,Male,45,7,0,1,0,1,52885.23,1 -2972,15782530,Bruce,681,Spain,Male,30,2,111093.01,1,1,0,68985.99,0 -2973,15592877,Wright,641,Spain,Male,42,9,132657.55,1,1,0,35367.19,0 -2974,15651983,Fang,591,France,Female,56,9,128882.49,1,1,1,196241.94,1 -2975,15746737,Eames,565,Germany,Male,59,9,69129.59,1,1,1,170705.53,0 -2976,15774179,Sutherland,487,France,Male,37,6,0,2,1,1,126477.41,0 -2977,15667265,Cavenagh,729,France,Male,39,4,121404.64,1,1,1,159618.17,0 -2978,15655123,Dumetolisa,505,Spain,Female,45,9,131355.3,3,1,0,195395.33,1 -2979,15595917,Mackay,580,France,Female,35,1,102097.33,1,0,1,168285.85,0 -2980,15668385,Dellucci,642,France,Male,40,1,154863.15,1,1,1,138052.51,0 -2981,15709476,Kenyon,850,Spain,Female,41,3,99945.93,2,1,0,71179.31,0 -2982,15711218,Parry,616,Germany,Male,39,2,121704.32,2,1,0,55556.3,0 -2983,15798659,Kennedy,526,Spain,Female,43,3,0,2,1,0,31705.19,0 -2984,15663939,Arnott,523,Germany,Male,35,8,138782.76,1,1,1,186118.93,0 -2985,15694946,Hanson,663,France,Male,35,9,0,2,1,1,195580.28,0 -2986,15631912,T'ao,840,France,Male,30,8,136291.71,1,1,0,54113.38,0 -2987,15768816,Shen,570,Germany,Male,42,0,107856.57,2,1,0,127528.84,0 -2988,15682268,Steere,676,Germany,Female,26,1,108348.66,1,0,0,60231.74,1 -2989,15684801,Abbott,689,France,Male,47,1,93871.95,3,1,0,156878.42,1 -2990,15636428,Sutherland,703,Spain,Female,45,1,0,1,1,0,182784.11,1 -2991,15809823,Thurgood,491,Germany,Male,19,2,125860.2,1,0,0,129690.5,0 -2992,15699284,Johnson,584,France,Male,49,8,172713.44,1,1,0,113860.81,0 -2993,15786993,Lung,810,France,Female,51,5,0,2,0,1,184524.74,0 -2994,15709441,Cocci,745,Spain,Female,59,8,0,1,1,1,36124.98,0 -2995,15710257,Matveyeva,625,France,Female,39,3,130786.92,1,0,1,121316.07,0 -2996,15582492,Moore,535,France,Female,29,2,112367.34,1,1,0,185630.76,0 -2997,15575694,Yobachukwu,729,Spain,Female,45,7,91091.06,2,1,0,71133.12,0 -2998,15756820,Fleming,655,France,Female,26,7,106198.5,1,0,1,32020.42,0 -2999,15766289,Dickinson,751,France,Male,47,5,142669.93,2,1,0,162760.96,0 -3000,15593014,Evseyev,525,France,Male,33,1,112833.35,1,0,1,175178.56,0 -3001,15584545,Aksenov,532,France,Female,40,5,0,2,0,1,177099.71,0 -3002,15675949,Fleming,696,Spain,Female,43,4,0,2,1,1,66406.37,0 -3003,15672091,Ulyanov,786,Germany,Female,32,2,104336.43,2,0,0,59559.81,0 -3004,15801658,Summers,580,France,Male,55,6,104305.74,1,0,1,175750.21,0 -3005,15706185,Clements,596,Germany,Male,47,5,140187.1,2,1,1,174311.3,0 -3006,15789863,Kazakova,683,France,Male,39,4,0,2,1,0,171716.81,0 -3007,15720943,Pirozzi,747,France,Female,45,1,114959.12,1,1,0,189362.39,1 -3008,15697997,Jamieson,602,France,Male,33,5,164704.38,1,0,1,180716.1,1 -3009,15665416,Ferri,779,France,Male,62,10,119096.55,1,0,1,116977.89,0 -3010,15660200,Mai,551,France,Male,31,1,0,2,1,1,185105.44,0 -3011,15619653,Hannaford,666,France,Male,47,2,0,1,1,0,35046.97,1 -3012,15773447,Fomin,526,Spain,Male,30,8,0,1,1,0,36251,0 -3013,15739160,Mahon,849,France,Female,41,9,115465.28,1,1,0,103174.5,0 -3014,15689237,Shaw,471,France,Female,27,4,0,2,1,0,122642.09,0 -3015,15679297,Volkova,628,Spain,Male,43,3,184926.61,1,1,0,122937.57,0 -3016,15591433,Miles,674,Germany,Male,43,8,85957.88,2,1,0,8757.39,0 -3017,15642725,Madison,797,France,Male,32,10,114084.6,1,0,1,125782.29,0 -3018,15701962,Scott,590,Spain,Female,29,2,166930.76,2,1,0,122487.73,0 -3019,15811613,Voss,588,France,Female,27,8,0,1,1,0,20066.38,0 -3020,15741049,Colebatch,577,France,Male,29,7,0,2,1,1,55473.15,0 -3021,15724423,Wilson,571,France,Female,38,6,107193.82,2,0,0,38962.94,0 -3022,15574305,T'ang,680,France,Male,36,3,116275.12,1,1,1,63795.8,0 -3023,15678168,Gibson,648,Spain,Female,27,7,0,2,1,1,163060.43,0 -3024,15697020,Hs?eh,618,France,Male,39,2,91068.56,1,1,0,26578.69,0 -3025,15610801,Pan,648,Germany,Male,41,5,123049.21,1,0,1,5066.76,0 -3026,15745232,Chikelu,759,France,Female,39,6,0,2,1,1,140497.67,0 -3027,15722758,Allan,585,France,Male,40,7,0,2,0,0,146156.98,0 -3028,15792102,Yefremova,774,France,Female,42,3,137781.65,1,0,0,199316.19,0 -3029,15675185,Chuang,697,Germany,Female,48,2,108128.96,2,1,1,103944.37,0 -3030,15801247,Fan,605,Spain,Male,39,10,105317.73,2,1,0,138021.36,0 -3031,15725660,Dellucci,676,France,Male,20,1,80569.73,1,0,0,68621.98,0 -3032,15638963,Garran,678,France,Female,22,4,174852.89,1,1,1,28149.06,0 -3033,15800061,Moretti,495,Spain,Female,45,3,89158.94,3,1,0,135169.76,1 -3034,15578006,Yao,787,France,Female,85,10,0,2,1,1,116537.96,0 -3035,15668504,Lucchesi,770,France,Male,36,2,89800.14,1,1,1,105922.69,0 -3036,15687491,Nkemdilim,817,Germany,Male,45,9,101207.75,1,0,0,88211.12,1 -3037,15610403,Anderson,659,France,Male,43,1,106086.42,2,1,0,26900.63,0 -3038,15741094,Sagese,693,France,Male,21,1,0,2,1,1,3494.02,0 -3039,15807909,Rubensohn,744,France,Male,47,9,0,2,1,0,113163.17,0 -3040,15666141,Baldwin,829,Spain,Female,26,8,101440.36,2,1,1,19324.5,0 -3041,15617134,Iqbal,716,France,Male,38,4,0,2,1,0,189678.7,0 -3042,15783029,Monaldo,671,France,Male,34,7,106603.74,2,1,1,26387.71,0 -3043,15622833,Mahon,835,Germany,Female,29,10,130420.2,2,0,0,106276.55,0 -3044,15746422,Muir,636,France,Female,38,1,0,1,1,0,45015.38,0 -3045,15750839,Burns,649,Spain,Male,29,2,45022.23,1,1,1,173495.77,0 -3046,15749130,Dyer,621,Germany,Male,27,1,74298.43,1,1,1,52581.96,0 -3047,15779862,Lyons,658,Germany,Female,31,3,133003.03,1,0,1,146339.27,1 -3048,15767871,H?,784,Spain,Male,48,7,0,2,1,1,182609.97,0 -3049,15679651,Gardiner,783,Spain,Female,37,1,136689.66,1,1,0,197890.65,0 -3050,15576219,Cameron,615,France,Male,32,4,0,2,1,1,6225.63,0 -3051,15699247,Chapman,791,France,Female,44,5,0,2,1,1,123977.86,1 -3052,15619087,Taylor,762,France,Male,53,1,102520.37,1,1,1,170195.4,0 -3053,15605327,Namatjira,607,France,Male,35,2,0,2,1,1,114190.3,0 -3054,15610140,He,601,France,Female,34,5,0,2,1,0,27022.57,0 -3055,15791174,Leibius,540,Spain,Male,67,1,88382.01,1,0,1,59457,0 -3056,15602373,White,812,France,Male,44,4,115049.15,2,1,0,165038.41,0 -3057,15762605,Wall,685,France,Male,58,1,104796.54,1,1,1,154181.41,0 -3058,15598840,Moretti,680,France,Male,33,1,123082.08,1,1,0,134960.98,0 -3059,15744279,Patterson,680,Spain,Female,58,8,0,2,1,1,65708.5,0 -3060,15670619,Coppin,631,France,Female,33,8,0,2,0,0,117374.22,0 -3061,15599533,Tsao,569,France,Female,43,7,0,2,1,1,77703.19,0 -3062,15757837,Kao,584,Germany,Male,33,3,88311.48,2,1,1,177651.38,0 -3063,15697574,Stewart,582,France,Female,40,9,0,3,1,1,60954.45,0 -3064,15578738,Tuan,609,France,Male,32,7,71872.19,1,1,1,151924.9,0 -3065,15762228,Barnes,506,Spain,Male,35,6,110046.93,2,1,0,26318.73,0 -3066,15614827,Sun,503,France,Male,42,8,104430.08,1,1,1,147557.71,0 -3067,15789815,Fallaci,503,France,Female,28,5,0,2,1,0,125918.17,0 -3068,15579781,Buccho,806,Germany,Male,31,10,138653.51,1,1,0,190803.37,0 -3069,15587013,Tien,653,France,Female,31,7,102575.04,1,1,1,11043.54,0 -3070,15570932,Pirozzi,666,France,Male,43,7,137780.74,2,1,1,119100.05,1 -3071,15794661,Liu,674,Spain,Male,32,2,0,2,1,0,140579.17,0 -3072,15581654,Long,798,France,Male,32,7,0,2,0,1,37731.95,0 -3073,15644296,Scott,740,France,Female,30,8,105209.54,1,1,0,1852.58,0 -3074,15614420,Gerasimova,531,Germany,Female,32,0,109570.21,2,1,1,172049.84,0 -3075,15609653,Ifeatu,614,Germany,Female,44,6,118715.86,1,1,0,133591.11,1 -3076,15594577,De Luca,556,France,Male,35,10,0,2,1,1,192751.18,0 -3077,15584114,Ogbonnaya,678,Germany,Female,43,2,153393.18,2,1,1,193828.27,0 -3078,15673367,Humffray,587,Germany,Male,33,6,132603.36,1,1,0,55775.72,0 -3079,15685576,Degtyaryov,527,Spain,Female,36,6,0,2,1,1,102280.29,0 -3080,15774727,Monaldo,757,Germany,Female,34,1,129398.01,2,0,0,44965.44,0 -3081,15694288,Cawthorne,468,Spain,Male,28,3,0,2,1,0,170661.02,0 -3082,15603319,Graham,693,France,Male,29,2,151352.74,1,0,0,197145.89,0 -3083,15759066,Carpenter,483,France,Female,44,5,136836.49,1,1,0,192359.9,1 -3084,15814816,Kambinachi,466,France,Male,40,4,91592.06,1,1,0,141210.18,1 -3085,15724402,Tyler,770,France,Female,30,8,0,2,1,0,100557.03,0 -3086,15571059,Martin,734,France,Female,54,3,0,1,1,0,130805.54,1 -3087,15674206,Walker,716,France,Female,22,8,0,2,1,1,92606.98,0 -3088,15715160,Khan,439,France,Male,36,2,165536.28,2,1,1,123956.83,0 -3089,15730448,Iroawuchi,538,Germany,Male,25,5,62482.95,1,1,1,102758.43,0 -3090,15662067,Summers,743,France,Male,40,8,68155.59,1,1,0,94876.65,0 -3091,15779581,Bottrill,734,Spain,Female,43,3,55853.33,2,0,1,94811.85,1 -3092,15662901,Hu,656,France,Male,37,2,0,2,0,1,67840.81,0 -3093,15689751,Jones,666,France,Female,31,2,79589.43,1,0,0,4050.57,0 -3094,15667742,Vincent,627,Spain,Male,41,5,100880.76,1,0,1,134665.25,0 -3095,15738448,Sanford,480,Germany,Female,25,3,174330.35,2,0,0,181647.13,0 -3096,15680243,Brown,792,France,Male,19,7,143390.51,1,1,0,33282.84,0 -3097,15745083,Lei,613,Germany,Male,59,8,91415.76,1,0,0,27965,1 -3098,15708228,Toscani,476,Germany,Male,30,3,134366.42,1,1,0,68343.53,0 -3099,15628523,Chien,539,France,Female,24,3,0,2,1,1,198161.07,0 -3100,15708196,Uchenna,696,Spain,Male,60,8,88786.81,1,1,1,196858.4,0 -3101,15735549,Lori,810,Germany,Male,35,3,96814.46,2,1,1,120511.03,0 -3102,15809347,Fanucci,763,Germany,Male,32,9,160680.41,1,1,0,30886.35,0 -3103,15660866,Chimaobim,640,France,Female,29,3,0,2,1,0,2743.69,0 -3104,15766609,Jowers,655,France,Female,47,10,0,2,1,0,167778.62,0 -3105,15654230,Miller,526,Germany,Male,31,5,145537.21,1,1,0,132404.64,0 -3106,15794566,Kirsova,678,France,Female,28,4,0,2,1,1,144423.17,1 -3107,15800890,T'ien,554,France,Female,45,6,0,2,1,1,181204.5,0 -3108,15697424,Ku,597,Spain,Female,30,2,119370.11,1,1,1,182726.22,1 -3109,15724536,Chin,560,Spain,Female,28,1,0,2,1,1,120880.72,0 -3110,15735878,Law,850,Germany,Female,47,10,134381.52,1,0,0,26812.89,1 -3111,15707596,Chung,546,Germany,Female,74,8,114888.74,2,1,1,66732.63,1 -3112,15657163,Cockrum,623,Germany,Male,42,1,149332.48,2,1,0,100834.22,0 -3113,15622478,Greaves,698,France,Female,40,7,105061.74,3,1,0,107815.31,1 -3114,15779529,Grant,620,France,Male,32,7,0,2,1,1,34665.79,0 -3115,15636023,O'Donnell,619,France,Female,40,10,0,1,1,1,147093.84,1 -3116,15582066,Maclean,561,France,Male,21,4,0,1,1,1,36942.35,0 -3117,15666675,Hsieh,753,France,Female,39,7,155062.8,1,1,1,16460.77,0 -3118,15732987,Hs?,721,Spain,Male,43,3,88798.34,1,0,0,45610.63,0 -3119,15789432,Mazzanti,451,France,Male,33,6,0,2,1,0,184954.11,0 -3120,15663161,Chiu,680,Germany,Female,51,5,143139.87,1,0,0,47795.43,1 -3121,15694879,Reeves,590,Spain,Female,23,7,0,2,1,0,196789.9,0 -3122,15593715,Castiglione,634,Germany,Male,27,3,107027.52,1,1,0,173425.68,0 -3123,15575002,Ferguson,676,France,Male,29,4,140720.93,1,1,0,36221.18,0 -3124,15622171,Nnamdi,642,France,Male,30,8,80964.57,2,1,0,174738.2,0 -3125,15795224,Wu,760,France,Male,39,6,178585.46,1,1,0,67131.3,1 -3126,15685346,Chu,736,Spain,Female,26,4,135889.13,1,1,1,165692.03,0 -3127,15691808,King,656,France,Male,43,7,134919.85,1,1,0,194691.95,0 -3128,15721007,Charlton,776,Germany,Male,33,8,115130.34,1,0,0,129525.5,1 -3129,15794253,Marsh,832,Spain,Female,34,6,138190.13,2,0,1,146511.2,0 -3130,15694453,Walker,631,Germany,Male,37,9,131519.49,2,1,1,51752.18,0 -3131,15813113,Chang,795,Spain,Female,56,5,0,1,1,0,35418.69,1 -3132,15614187,Pottinger,648,Germany,Female,39,3,126935.98,2,0,1,57995.74,0 -3133,15619407,Buckley,615,France,Male,39,4,133707.09,1,1,1,108152.75,0 -3134,15646227,Folliero,682,France,Female,27,1,97893.2,1,1,0,166144.98,0 -3135,15660541,Olisanugo,694,France,Male,34,5,127900.03,1,1,0,101737.8,0 -3136,15753874,Kent,694,France,Male,37,10,143835.47,1,0,1,33326.71,0 -3137,15617877,Jessop,607,France,Male,44,0,0,2,1,1,81140.09,0 -3138,15772073,Hodge,664,France,Male,48,10,0,1,1,0,140173.17,1 -3139,15701537,Ignatiev,756,France,Male,60,2,0,1,1,1,166513.49,1 -3140,15736228,Chambers,645,France,Female,40,3,129596.77,1,1,1,103232.6,0 -3141,15780572,Mansom,653,Spain,Male,30,4,0,2,1,0,120736.04,0 -3142,15769596,Yen,710,Germany,Female,24,2,110407.44,2,0,0,15832.43,1 -3143,15586996,Azikiwe,697,France,Female,76,7,0,2,0,1,188772.45,0 -3144,15722061,Allen,619,Germany,Female,41,8,142015.76,2,1,0,114323.66,0 -3145,15638003,Komarova,648,Spain,Male,55,1,81370.07,1,0,1,181534.04,0 -3146,15775590,Mackay,482,Germany,Female,48,2,69329.47,1,0,0,102640.52,1 -3147,15730688,Yu,548,France,Female,28,8,116755.5,2,1,1,158585.17,1 -3148,15753102,Curtis,752,Spain,Male,44,6,83870.33,1,1,0,178722.24,0 -3149,15810075,Fang,648,France,Female,39,6,130694.89,2,1,1,153955.38,1 -3150,15723373,Page,643,Spain,Female,34,8,117451.47,1,1,0,65374.86,0 -3151,15795298,Olisaemeka,573,Germany,Female,35,9,206868.78,2,0,1,102986.15,0 -3152,15584320,Brennan,686,France,Female,39,3,111695.62,1,0,0,136643.84,0 -3153,15724161,Sutton,644,France,Female,40,9,137285.26,4,1,0,77063.63,1 -3154,15750056,Hyde,702,France,Female,29,6,149218.39,1,1,1,9633.01,0 -3155,15609637,Nkemakolam,652,France,Male,51,7,0,2,0,1,43496.36,0 -3156,15794493,Chimaijem,641,Spain,Male,32,7,0,2,1,1,24267.28,0 -3157,15569641,Sung,692,Germany,Female,41,8,130701.29,1,1,0,59354.24,1 -3158,15815236,Chiganu,574,Spain,Male,34,5,0,2,0,0,28269.86,0 -3159,15811177,Beneventi,643,France,Female,31,3,167949.48,1,1,0,143162.34,0 -3160,15680587,Esposito,834,France,Male,23,4,131254.81,1,1,0,20199.3,0 -3161,15672821,Owen,591,France,Male,28,5,0,2,1,1,48606.92,0 -3162,15767681,Smalley,470,Spain,Male,34,9,0,2,0,1,89013.67,0 -3163,15600379,Hsiung,608,Spain,Male,34,7,86656.13,1,0,1,59890.29,0 -3164,15801336,Ch'ang,649,Germany,Female,37,8,114737.26,1,1,1,106655.88,1 -3165,15721592,Barton,665,France,Female,38,5,0,2,1,0,156439.56,0 -3166,15581282,Lucchese,651,France,Female,39,6,0,1,1,0,24176.44,0 -3167,15746203,Hsia,555,Germany,Male,62,4,119817.33,1,0,1,43507.1,1 -3168,15583137,Pope,637,France,Female,48,7,130806.99,2,1,1,132005.85,1 -3169,15680752,Horrocks,675,France,Female,49,0,0,1,1,1,80496.71,1 -3170,15688172,Tai,677,Spain,Male,40,5,0,2,1,0,88947.56,0 -3171,15791373,Chikezie,850,Germany,Female,35,2,80931.75,1,0,0,12639.67,1 -3172,15589449,Frye,815,France,Female,56,3,0,3,1,1,94248.16,1 -3173,15692819,Toscani,665,Germany,Male,32,1,132178.67,1,0,0,11865.76,0 -3174,15727467,Mellor,485,France,Female,27,3,0,2,1,0,141449.86,0 -3175,15734312,Kang,577,Spain,Male,43,6,0,2,1,1,149457.81,0 -3176,15764604,Sutherland,586,France,Female,35,7,164769.02,3,1,0,119814.25,1 -3177,15613014,Hs?,722,Germany,Male,29,1,107233.85,2,1,0,24924.92,0 -3178,15759684,Ting,528,France,Female,27,7,176227.07,2,0,1,139481.53,0 -3179,15609669,Chuang,542,France,Female,39,4,109949.39,2,1,1,41268.65,0 -3180,15685536,Chu,552,France,Female,34,5,0,2,1,1,1351.41,0 -3181,15750447,Ozoemena,678,France,Female,60,10,117738.81,1,1,0,147489.76,1 -3182,15663249,Howells,575,Spain,Female,37,9,133292.45,1,1,0,111175.09,0 -3183,15638646,Lucchese,669,France,Female,43,1,160474.59,1,1,1,95963.14,0 -3184,15734161,Nnonso,636,France,Male,43,6,0,2,1,0,43128.95,0 -3185,15631070,Gerasimova,667,Germany,Male,55,9,154393.43,1,1,1,137674.96,1 -3186,15761950,Woronoff,652,Germany,Female,45,9,110827.49,1,1,1,153383.54,1 -3187,15649668,Wilhelm,637,Germany,Female,36,10,145750.45,2,1,1,96660.76,0 -3188,15713912,Nebechukwu,516,Spain,Female,45,8,109044.3,1,0,1,115818.16,0 -3189,15586757,Anenechukwu,801,France,Female,32,4,75170.54,1,1,1,37898.5,0 -3190,15596522,Meredith,692,France,Female,42,2,0,2,1,0,145222.93,0 -3191,15625395,Chinomso,585,France,Female,28,6,105795.9,1,1,1,41219.09,0 -3192,15760570,Stephenson,590,France,Male,32,5,0,2,1,0,59249.83,0 -3193,15566689,Chimaoke,554,Spain,Male,66,8,0,2,1,1,116747.62,0 -3194,15725794,Winters,659,France,Female,49,1,0,1,1,0,116249.72,1 -3195,15673539,Napolitani,690,France,Female,26,3,118097.87,1,1,0,61257.83,0 -3196,15705298,L?,697,Germany,Male,29,0,172693.54,1,0,0,141798.98,0 -3197,15675791,Williams,610,France,Male,36,4,129440.3,2,1,0,102638.35,0 -3198,15747043,Giles,599,Spain,Male,36,4,0,2,0,0,13210.56,0 -3199,15736397,Wang,544,France,Male,23,1,96471.2,1,1,0,35550.97,0 -3200,15678201,Robertson,548,France,Female,46,1,0,1,1,1,104469.06,1 -3201,15720745,Murray,635,Spain,Male,24,4,140197.18,1,1,1,142935.83,0 -3202,15637593,Greco,722,France,Male,20,6,0,2,1,0,195486.28,0 -3203,15598070,Marchesi,564,France,Female,33,4,135946.26,1,1,0,63170,0 -3204,15787550,Chao,719,France,Male,69,3,0,2,1,1,58320.06,0 -3205,15603942,Hawthorn,547,Germany,Male,50,3,81290.02,3,0,1,177747.03,1 -3206,15733973,Bibi,850,France,Female,42,8,0,1,1,0,19632.64,1 -3207,15596761,Hawdon,515,Germany,Male,60,9,113715.36,1,1,0,18424.24,1 -3208,15652400,Moss,667,Spain,Male,56,2,168883.08,1,0,1,18897.78,0 -3209,15717893,Briggs,607,Germany,Male,36,8,143421.74,1,1,0,97879.02,0 -3210,15622585,McIntyre,525,France,Male,26,7,153644.39,1,1,1,63197.88,0 -3211,15733964,Russo,606,Spain,Female,53,1,109330.06,1,1,1,75860.01,0 -3212,15753861,Ballard,686,Germany,Female,27,1,115095.88,2,0,0,78622.46,0 -3213,15747097,Hs?,611,France,Male,35,10,0,1,1,1,23598.23,1 -3214,15594762,Pisani,827,Spain,Male,46,1,183276.32,1,1,1,13460.27,0 -3215,15667417,Tao,572,France,Male,33,9,68193.72,1,1,0,19998.31,0 -3216,15684861,Thomson,726,France,Female,32,8,0,2,0,0,185075.63,0 -3217,15742204,Hsu,579,Germany,Male,31,6,139729.54,1,0,1,135815.38,0 -3218,15623502,Morrison,598,Spain,Female,56,4,98365.33,1,1,1,44251.33,0 -3219,15774872,Joslin,663,France,Male,36,10,0,2,1,0,136349.55,0 -3220,15611191,Scott,505,Germany,Female,37,10,122453.97,2,1,1,52693.99,0 -3221,15674331,Bidwill,576,Germany,Male,30,7,132174.41,2,0,0,93767.03,0 -3222,15619465,Cameron,555,Spain,Female,24,2,0,2,0,1,197866.55,0 -3223,15575247,Cartwright,524,France,Male,30,1,0,2,1,0,126812.85,0 -3224,15695679,Yao,776,Spain,Male,39,2,104349.45,1,0,0,79503.05,0 -3225,15713463,Tate,645,Germany,Female,41,2,138881.04,1,1,0,129936.53,1 -3226,15785170,Neal,850,Germany,Female,32,0,116968.91,1,0,0,175094.62,0 -3227,15796351,Yao,603,Germany,Male,35,1,105346.03,2,1,1,130379.5,0 -3228,15639576,Burns,691,France,Male,26,9,136623.19,1,1,0,153228,0 -3229,15693264,Onyinyechukwuka,583,France,Female,29,10,0,2,1,1,111285.85,0 -3230,15589715,Fulks,584,France,Female,66,5,0,1,1,0,49553.38,1 -3231,15769902,Christie,679,France,Female,33,6,0,2,1,1,98015.85,0 -3232,15587177,Lloyd,646,France,Male,36,6,124445.52,1,1,0,88481.32,0 -3233,15814553,Ball,559,France,Female,34,5,68999.66,2,1,1,66879.27,0 -3234,15601550,Genovesi,595,Spain,Male,36,6,85768.42,1,1,1,24802.77,0 -3235,15664907,Alexander,527,France,Male,47,1,0,1,1,0,21312.16,1 -3236,15612465,Siciliano,684,Spain,Male,34,9,100628,2,1,1,190263.78,0 -3237,15810800,Ositadimma,673,Spain,Female,32,0,0,1,1,1,72873.33,0 -3238,15665760,Kazantsev,802,Spain,Male,38,7,0,2,0,1,57764.65,0 -3239,15588080,Giles,675,France,Male,54,6,0,1,1,0,110273.84,1 -3240,15776844,Hao,762,Spain,Female,19,6,0,2,1,0,55500.17,0 -3241,15717560,Martin,580,France,Male,50,0,125647.36,1,1,0,57541.08,1 -3242,15629739,Hartley,621,Germany,Female,31,8,100375.39,1,1,1,90384.26,0 -3243,15729908,Allan,411,France,Female,36,10,0,1,0,0,120694.35,0 -3244,15716781,Dolgorukova,815,France,Male,24,7,171922.72,1,0,1,178028.96,0 -3245,15646936,Nnamdi,631,Germany,Female,32,2,146810.99,2,1,1,180990.29,0 -3246,15768151,Romano,514,Germany,Female,45,3,109032.23,1,0,1,155407.21,1 -3247,15579212,Chuang,638,France,Male,57,6,0,1,1,0,33676.48,1 -3248,15721835,Owen,791,Spain,Male,25,7,0,1,1,0,89666.28,0 -3249,15800515,Singh,516,France,Male,35,5,128653.59,1,1,0,127558.26,0 -3250,15591279,Nwagugheuzo,734,France,Male,37,3,80387.81,1,0,1,77272.62,0 -3251,15587419,Shipton,611,France,Male,58,8,0,2,0,1,107665.68,1 -3252,15750335,Paterson,850,Germany,Male,43,0,108508.82,3,1,0,184044.8,1 -3253,15699619,Rivas,641,France,Male,31,10,155978.17,1,1,0,91510.71,0 -3254,15606472,Lung,585,France,Female,38,5,0,1,1,1,87363.56,0 -3255,15778368,Allan,552,Germany,Male,50,4,121175.56,1,1,0,117505.07,1 -3256,15671387,Fetherstonhaugh,507,France,Female,29,4,89349.47,2,0,0,180626.68,0 -3257,15573926,Lung,735,Spain,Male,38,7,86131.71,2,0,0,93478.96,0 -3258,15709183,Davidson,707,France,Female,58,3,102346.86,1,1,1,114672.64,0 -3259,15577514,Mai,698,Germany,Female,36,7,121263.62,1,1,1,13387.88,0 -3260,15778830,Dellucci,841,France,Male,31,2,0,2,1,0,173240.52,0 -3261,15768072,Mitchell,688,Spain,Female,33,2,0,1,0,0,27557.18,1 -3262,15768293,Sun,614,France,Male,51,3,0,2,1,1,5552.37,0 -3263,15654456,Napolitano,511,Germany,Male,48,6,149726.08,1,0,0,88307.87,1 -3264,15807525,Bailey,447,France,Male,43,2,0,2,1,0,33879.26,1 -3265,15574372,Hoolan,738,France,Male,35,5,161274.05,2,1,0,181429.87,0 -3266,15671249,Kent,422,France,Female,33,2,0,2,1,0,102655.31,0 -3267,15779744,Chou,537,Spain,Male,30,1,103138.17,1,1,1,96555.42,0 -3268,15624755,Pepper,707,Germany,Female,40,3,109628.44,1,1,0,189366.03,0 -3269,15611430,Abramowitz,690,France,Male,54,5,0,1,1,0,12847.61,1 -3270,15774744,Lord,664,Germany,Male,33,7,97286.16,2,1,0,143433.33,0 -3271,15629885,Wilson,850,France,Female,33,7,118004.26,1,1,0,183983.82,0 -3272,15708791,Abazu,584,Spain,Male,32,9,85534.83,1,0,0,169137.24,0 -3273,15793890,Harriman,728,France,Female,59,4,0,1,1,1,163365.85,1 -3274,15646091,Frankland,560,Spain,Female,43,4,95140.44,2,1,0,123181.44,1 -3275,15596984,Pinto,629,France,Female,31,6,0,1,1,1,16447.6,1 -3276,15800215,Kwemtochukwu,658,France,Male,25,3,0,2,0,1,173948.4,0 -3277,15577806,Chiu,794,Germany,Female,54,1,75900.84,1,1,1,192154.66,0 -3278,15749381,Yu,790,France,Female,41,2,126619.27,1,1,0,198224.38,0 -3279,15683758,Onyekachukwu,640,France,Male,44,7,111833.47,1,1,0,67202.74,0 -3280,15670615,Castiglione,652,Spain,Male,37,7,0,2,1,0,68789.93,0 -3281,15715622,To Rot,583,France,Female,57,3,238387.56,1,0,1,147964.99,1 -3282,15707634,Anenechukwu,775,France,Female,32,2,108698.96,2,1,1,161069.73,0 -3283,15806901,Henderson,584,France,Female,39,2,112687.69,1,1,1,127749.61,0 -3284,15775335,Ellis,635,Germany,Female,48,4,81556.89,2,1,0,191914.37,0 -3285,15724150,Nkemdirim,814,France,Male,48,9,136596.85,1,1,1,185791.9,0 -3286,15627220,Kang,735,Germany,Female,43,9,98807.45,1,0,0,184570.04,1 -3287,15672330,Lear,678,France,Female,31,1,0,2,0,1,130446.65,0 -3288,15668521,Jamieson,693,France,Male,37,1,0,2,1,1,82867.55,0 -3289,15807837,Mazzanti,640,France,Female,30,6,107499.7,1,1,1,187632.22,0 -3290,15592570,Marino,773,Spain,Female,23,8,0,2,1,0,56759.79,0 -3291,15748589,Winter,736,France,Female,30,9,0,2,1,0,34180.33,0 -3292,15635893,T'ien,693,France,Female,28,8,0,2,1,1,158545.25,0 -3293,15757632,Hughes-Jones,496,France,Female,41,1,176024.05,2,1,0,182337.98,0 -3294,15691863,Cody,751,France,Female,39,3,0,2,1,1,84175.34,0 -3295,15706071,Hunt,528,Germany,Male,39,0,127631.62,1,0,1,22197.8,1 -3296,15654296,Estrada,754,Spain,Female,19,9,0,1,1,0,189641.11,0 -3297,15755018,Dickinson,568,Germany,Female,26,10,109819.16,2,1,0,154491.39,0 -3298,15594041,Fanucci,592,Spain,Female,41,2,138734.94,1,1,0,90020.74,0 -3299,15670587,Yang,558,Germany,Male,25,10,111363.1,2,1,0,197264.35,0 -3300,15724527,Forbes,825,France,Male,34,9,0,2,1,1,31933.06,0 -3301,15801904,Heard,677,Germany,Male,28,0,143988,2,1,0,8755.69,1 -3302,15658195,Efremova,653,France,Male,34,5,118838.75,1,1,1,52820.13,0 -3303,15630113,Morphett,593,Spain,Male,35,4,161637.75,1,1,1,20008.46,0 -3304,15784320,Lenhardt,632,France,Female,44,3,133793.89,1,1,1,34607.14,1 -3305,15676513,Burns,601,Germany,Male,35,8,71553.83,1,1,0,177384.45,0 -3306,15574072,Ch'ien,786,France,Female,62,8,0,1,1,1,165702.64,0 -3307,15633854,Sun,654,France,Female,40,3,0,2,1,0,167889.1,0 -3308,15618566,Jamieson,572,France,Female,38,7,0,2,1,1,133122.62,0 -3309,15733014,Nolan,813,France,Female,62,10,64667.95,2,0,1,140454.14,0 -3310,15753343,Barry,523,France,Female,28,2,121164.11,1,1,1,59938.81,0 -3311,15746076,Saunders,506,Spain,Male,50,3,0,2,1,0,12016.79,0 -3312,15608226,McMorran,513,Spain,Male,72,3,98903.06,1,1,1,81251.24,0 -3313,15605684,Phelan,664,France,Female,31,7,104158.84,1,1,0,134169.85,0 -3314,15638988,Fu,684,France,Male,54,6,0,2,1,1,94888.6,0 -3315,15628767,Hotchin,608,Spain,Female,63,3,139529.93,2,1,1,175696.16,1 -3316,15737977,Aksyonov,527,France,Female,25,6,0,2,0,1,96758.58,0 -3317,15758116,Rossi,666,France,Male,53,5,64646.7,1,1,0,128019.48,1 -3318,15575119,Hughes,779,France,Male,71,3,0,2,1,1,146895.36,1 -3319,15625126,Duncan,629,France,Female,40,6,0,2,1,1,139356.3,0 -3320,15567114,McGarry,430,France,Male,35,1,118894.22,1,0,0,2923.61,0 -3321,15672242,Aksenov,712,France,Male,24,2,0,1,0,1,121232.51,0 -3322,15681327,Akhtar,682,France,Male,30,9,0,2,1,1,2053.42,0 -3323,15802585,Pisani,634,France,Female,41,8,68213.99,1,1,1,6382.46,0 -3324,15740630,Pisano,487,Spain,Female,31,1,0,2,1,0,158750.13,0 -3325,15815420,McDaniels,808,Spain,Male,47,8,139196,1,0,1,74028.36,0 -3326,15711468,Tennant,527,France,Female,32,7,0,2,1,1,44099.75,0 -3327,15799626,Donaghy,637,Germany,Male,50,4,126345.55,1,0,1,17323,1 -3328,15659325,Todd,802,Spain,Male,40,5,0,2,1,1,175043.69,0 -3329,15651352,Tobenna,529,France,Female,38,2,0,1,1,0,146388.85,1 -3330,15684925,Vicars,850,France,Female,43,3,0,2,0,0,2465.8,0 -3331,15657439,Chao,738,France,Male,18,4,0,2,1,1,47799.15,0 -3332,15574122,Tien,817,France,Male,34,5,129278.43,1,0,0,165562.84,0 -3333,15720508,Hsing,735,France,Male,31,3,119558.35,1,0,0,72927.68,0 -3334,15599078,Yang,619,Germany,Female,41,5,92467.58,1,1,0,38270.47,0 -3335,15702300,Walker,671,France,Male,27,5,0,2,0,0,120893.07,0 -3336,15660735,T'ang,581,Spain,Female,31,6,0,2,1,0,188377.21,0 -3337,15671390,Chukwukere,690,Spain,Male,36,10,0,2,1,0,55902.93,0 -3338,15647385,Ch'iu,579,Spain,Male,56,4,99340.83,1,0,0,4523.74,1 -3339,15739223,Pai,688,Spain,Female,24,3,0,2,1,1,102195.16,0 -3340,15631305,Franklin,599,Spain,Female,28,4,126833.79,2,1,0,60843.09,1 -3341,15809263,Y?,729,Germany,Male,29,5,109676.52,1,1,1,25548.47,0 -3342,15640866,Peng,718,France,Female,29,3,0,1,0,1,134462.29,0 -3343,15775663,Otitodilichukwu,712,Germany,Male,53,6,134729.99,2,1,1,132702.64,0 -3344,15631800,Pagnotto,474,France,Male,37,3,98431.37,1,0,0,75698.44,0 -3345,15654292,Vessels,565,Germany,Male,33,8,130368.31,2,1,0,105642.43,0 -3346,15648320,Heller,658,France,Female,31,7,123974.96,1,1,0,102153.75,0 -3347,15726747,Donaldson,714,France,Male,63,4,138082.16,1,0,1,166677.54,0 -3348,15694510,Ifeanyichukwu,725,France,Male,45,1,129855.32,1,0,0,24218.65,0 -3349,15572291,Kao,825,France,Male,40,6,132308.22,1,0,0,117122.5,0 -3350,15603465,Dunn,665,Germany,Female,45,5,155447.65,2,1,0,51871.95,1 -3351,15685628,Calabresi,670,Spain,Male,35,2,124268.64,2,0,1,84321.03,0 -3352,15792729,Holland,474,Germany,Female,34,9,176311.36,1,1,0,160213.27,0 -3353,15767414,Calabresi,591,France,Male,40,2,99886.42,2,1,1,88695.19,0 -3354,15568044,Butusov,508,France,Female,31,7,0,2,1,1,6123.15,0 -3355,15751333,Atkinson,695,France,Female,36,2,0,2,0,1,167749.54,0 -3356,15623062,Vasilyeva,660,Germany,Male,24,5,85089.3,1,1,1,71638,0 -3357,15713621,Mollison,687,Germany,Male,41,10,134318.21,2,1,1,198064.52,0 -3358,15670668,Webb,658,Germany,Male,29,5,75395.53,2,0,1,54914.92,0 -3359,15750638,Obiajulu,705,Germany,Female,33,5,116765.7,1,0,0,190659.17,1 -3360,15747878,Aiken,739,Spain,Male,60,4,0,1,1,1,51637.67,0 -3361,15726796,Brabyn,844,France,Male,38,7,111501.66,1,1,1,119333.38,0 -3362,15754952,Su,602,Germany,Female,48,7,76595.08,2,0,0,127095.14,0 -3363,15652192,Traeger,759,France,Female,33,9,160541.36,2,0,0,93541.14,0 -3364,15681924,Ekwueme,747,Germany,Male,38,2,129728.6,1,1,0,89289.54,0 -3365,15763544,Thompson,673,France,Male,47,1,0,2,0,0,108762.16,0 -3366,15764431,Chinwenma,671,Spain,Female,34,5,130929.02,4,1,1,28238.25,1 -3367,15684010,Tuan,640,Germany,Female,74,2,116800.25,1,1,1,34130.43,0 -3368,15648881,Tsai,581,Germany,Male,40,0,101016.53,1,0,1,7926.35,1 -3369,15733303,Liu,630,France,Male,67,5,0,2,1,1,27330.27,0 -3370,15643294,Robinson,703,France,Female,33,8,190566.65,1,1,1,79997.14,0 -3371,15749905,Carr,698,Spain,Female,47,6,0,1,1,0,50213.81,1 -3372,15625175,Palerma,742,Germany,Female,43,6,97067.69,1,0,1,60920.03,1 -3373,15643967,Chineze,652,France,Female,37,4,92208.54,1,0,1,197699.8,1 -3374,15578251,Fang,644,France,Male,37,2,186347.97,2,1,0,92809.73,0 -3375,15772573,Simpson,735,Spain,Male,55,2,103176.62,1,0,1,163516.16,0 -3376,15733234,Moretti,777,France,Female,58,4,0,1,1,1,62449.07,1 -3377,15721582,Hale,644,Germany,Female,40,4,77270.08,2,1,1,115800.1,1 -3378,15628219,Benson,665,Germany,Female,37,3,111911.63,1,1,1,110359.68,1 -3379,15571302,Estep,529,Germany,Male,72,5,94216.05,1,1,1,78695.68,0 -3380,15637178,Mishina,803,Spain,Female,45,7,0,2,1,1,128378.04,0 -3381,15601184,Abramovich,604,Spain,Female,26,3,0,2,1,0,155248.62,0 -3382,15629511,Lavrentiev,738,France,Male,49,6,106770.82,1,1,0,123499.27,0 -3383,15570629,Alexeyeva,655,Germany,Female,72,5,138089.97,2,1,1,99920.41,0 -3384,15665766,T'ang,698,Germany,Male,39,9,133191.19,2,0,1,53289.49,0 -3385,15693732,Kilgour,775,France,Female,66,9,0,2,1,1,67622.34,0 -3386,15765982,Chin,735,France,Male,41,7,74135.85,1,1,1,11783.1,1 -3387,15582016,Fiorentini,766,Spain,Male,41,6,99208.46,2,1,0,62402.38,0 -3388,15798024,Lori,537,Germany,Male,84,8,92242.34,1,1,1,186235.98,0 -3389,15588622,Marchesi,599,Germany,Male,25,7,108380.72,1,1,1,79005.95,0 -3390,15724863,Sheppard,420,Spain,Female,55,4,91893.32,1,1,0,144870.28,1 -3391,15618213,Nnanna,674,France,Female,32,7,85757.93,1,1,1,95481,0 -3392,15780411,Norris,570,France,Female,46,3,0,2,0,0,820.46,0 -3393,15725429,Vincent,623,Germany,Male,33,8,96759.42,1,1,1,174777.98,0 -3394,15600626,Bradley,710,France,Male,30,6,0,2,1,1,8991.17,0 -3395,15668460,Bellucci,466,France,Male,29,6,0,2,1,1,2797.27,0 -3396,15576263,Clements,759,France,Female,22,5,0,1,1,0,22303.17,0 -3397,15720354,Knowles,581,France,Male,71,4,0,2,1,1,197562.08,0 -3398,15691624,Chidiebere,820,France,Male,33,2,132150.26,2,1,0,23067.97,0 -3399,15793196,Kelly,759,France,Male,41,9,0,2,0,1,190294.12,0 -3400,15633352,Okwukwe,628,France,Female,31,6,175443.75,1,1,0,113167.17,1 -3401,15750874,Onyemere,676,France,Male,31,3,78990.15,1,1,1,124777.14,0 -3402,15588923,Murphy,591,France,Female,33,4,113743.37,1,1,0,124625.08,0 -3403,15715745,Elliott,690,France,Female,26,5,157624.84,1,1,1,49599.27,0 -3404,15611800,Loggia,624,France,Female,62,7,125163.62,2,1,1,151411.5,0 -3405,15576928,Walsh,573,France,Female,23,2,0,1,1,0,122964.18,0 -3406,15793693,Mahomed,694,France,Male,60,9,0,1,1,1,57088.97,0 -3407,15581252,Dolgorukova,632,Spain,Female,29,7,80922.75,1,1,0,7820.78,0 -3408,15797760,Bogdanov,632,France,Male,40,3,193354.86,2,1,0,149188.41,0 -3409,15790564,She,832,Germany,Female,40,9,107648.94,2,1,1,134638.97,0 -3410,15593736,Cook,598,Germany,Female,46,7,131769.04,1,0,0,184980.23,1 -3411,15595937,Bruno,430,Germany,Male,36,1,138992.48,2,0,0,122373.42,0 -3412,15815628,Moysey,711,France,Female,37,8,113899.92,1,0,0,80215.2,0 -3413,15782802,Beneventi,582,Germany,Male,26,6,114450.32,1,1,1,14081.64,0 -3414,15627412,Ferri,605,France,Male,39,3,0,2,1,0,199390.45,0 -3415,15734609,Skinner,657,France,Female,37,2,0,2,1,1,7667.48,0 -3416,15710689,Angel,578,Spain,Male,40,6,63609.92,1,0,0,74965.61,1 -3417,15565806,Toosey,532,France,Male,38,9,0,2,0,0,30583.95,0 -3418,15815530,Chin,612,France,Female,42,10,75497.51,1,0,0,149682.78,0 -3419,15632272,Lung,792,France,Female,42,2,0,2,1,0,92664.09,0 -3420,15684103,Mellor,674,France,Female,26,10,0,2,1,1,138423.1,0 -3421,15654519,Hassall,680,France,Male,31,1,0,2,1,1,3148.2,0 -3422,15767722,Richardson,593,France,Female,39,0,117704.73,1,1,0,197933.5,0 -3423,15654346,Poninski,679,Germany,Male,35,1,130463.55,2,1,1,37341.17,0 -3424,15660147,Dore,493,Spain,Male,32,8,46161.18,1,1,1,79577.4,0 -3425,15814998,Bonham,688,Spain,Male,42,5,0,2,0,0,197602.29,0 -3426,15802207,Ibezimako,769,Germany,Male,43,4,110182.54,2,1,1,87537.32,0 -3427,15658668,Hunter,581,Spain,Male,49,10,0,2,0,0,41623.59,0 -3428,15715079,Bold,465,France,Male,41,9,117221.15,1,1,0,168280.95,0 -3429,15570360,Wan,641,France,Female,35,4,0,2,0,0,125986.18,0 -3430,15674678,Bradley,731,Germany,Female,43,9,79120.27,1,0,0,548.52,1 -3431,15780925,Tretyakova,625,France,Male,37,1,177069.24,2,1,1,96088.54,0 -3432,15688193,Graham,468,France,Male,36,3,61636.97,1,0,0,107787.42,0 -3433,15778219,Izmailov,790,France,Male,26,5,0,1,1,0,20510.79,0 -3434,15696514,Calabrese,587,Germany,Female,37,6,104414.03,1,1,0,192026.02,0 -3435,15712303,Valentin,692,France,Male,66,4,159732.02,1,1,1,118188.15,0 -3436,15719090,Osonduagwuike,676,Germany,Female,34,4,89437.03,1,1,1,189540.95,0 -3437,15735632,Williamson,571,France,Male,41,8,0,1,1,1,63736.17,0 -3438,15619436,Pan,700,France,Female,32,3,0,1,0,0,95740.37,0 -3439,15722404,Carpenter,445,France,Female,30,3,0,2,1,1,127939.19,0 -3440,15662063,McIver,746,France,Male,36,7,142400.77,1,1,1,193438.69,0 -3441,15745605,Trevisan,722,France,Female,47,2,88011.4,1,1,1,90655.94,1 -3442,15636658,Rozhkova,596,France,Male,36,2,0,2,1,1,12067.39,0 -3443,15784130,He,850,Germany,Female,30,8,154870.28,1,1,1,54191.38,0 -3444,15606755,Moretti,597,Spain,Female,46,4,0,2,1,0,58667.16,1 -3445,15801699,Fishbourne,436,Spain,Male,43,5,0,2,1,1,35687.43,0 -3446,15784097,Gibson,660,Germany,Male,28,1,118402.25,2,1,0,14288.93,0 -3447,15764654,Zikoranachidimma,649,France,Male,37,9,87374.88,2,1,1,247.36,0 -3448,15612092,Palmer,646,Germany,Male,32,8,105397.8,1,1,0,78111.84,1 -3449,15610903,Chukwueloka,560,Spain,Female,31,5,125341.69,1,1,0,79547.39,0 -3450,15705777,Real,710,Germany,Male,49,10,129164.88,1,1,1,193266.72,0 -3451,15661936,Chikelu,513,France,Male,40,3,141004.46,1,1,0,105028.46,0 -3452,15700864,Fiorentini,607,France,Female,21,0,0,2,1,0,116106.52,0 -3453,15722965,Yefimova,757,France,Male,57,3,89079.41,1,1,1,53179.21,1 -3454,15737521,Ball,619,Germany,Male,40,9,103604.31,2,0,0,140947.05,0 -3455,15814465,Ch'in,612,France,Male,24,1,182705.05,1,1,1,171837.06,0 -3456,15580988,Odell,842,France,Male,29,8,0,2,1,1,123437.05,0 -3457,15789974,Enemuo,713,France,Male,33,6,94598.48,1,0,0,197519.66,1 -3458,15713370,Hunter,657,Spain,Male,36,8,188241.05,2,0,0,183058.51,1 -3459,15748673,Nepean,770,France,Female,37,9,0,2,0,0,22710.72,0 -3460,15754919,Nwebube,773,France,Female,40,10,0,2,0,1,69303.15,0 -3461,15641662,Enticknap,470,Germany,Male,39,5,117469.91,2,0,0,63705.9,0 -3462,15813422,Lu,781,Spain,Male,35,4,80790.74,1,1,0,116429.51,0 -3463,15713596,Ugochukwu,428,France,Female,62,1,107735.93,1,0,1,58381.77,0 -3464,15791216,Mann,600,Germany,Male,43,8,133379.41,1,1,0,177378.66,1 -3465,15689031,Murphy,697,Spain,Female,37,7,168066.87,1,1,0,35450.53,0 -3466,15763704,Docherty,692,Germany,Female,43,2,69014.49,2,0,0,164621.43,0 -3467,15631339,Adams,791,France,Male,28,4,0,1,1,0,174435.48,0 -3468,15771509,Hirst,538,Germany,Female,42,1,98548.62,2,0,1,94047.75,0 -3469,15769586,Horan,820,France,Female,49,1,0,2,1,1,119087.25,0 -3470,15656096,Cumbrae-Stewart,679,Spain,Female,26,3,76554.06,1,1,1,184800.27,0 -3471,15585280,Kinney,649,France,Female,36,2,0,2,0,1,75035.48,0 -3472,15743582,T'ang,632,France,Female,27,3,107375.82,1,1,1,62703.38,0 -3473,15761692,Muir,594,France,Male,40,9,122417.17,2,0,1,190882.69,0 -3474,15627840,Toscano,682,France,Female,42,0,0,1,0,1,91981.85,1 -3475,15778861,Wallace,720,Spain,Male,33,6,97188.62,1,0,0,91881.29,0 -3476,15770554,Fraser,769,France,Male,31,4,61297.05,2,1,1,7118.02,0 -3477,15806956,Iqbal,746,Spain,Male,30,1,112666.67,1,0,0,11710.4,1 -3478,15701908,Nina,623,Spain,Female,40,7,0,1,1,1,25904.12,0 -3479,15736990,Chuang,537,France,Male,28,3,157842.07,1,1,0,86911.49,0 -3480,15743714,Ch'ien,468,France,Male,46,7,91443.75,1,1,0,10958.18,0 -3481,15807993,Bruno,588,Germany,Female,30,0,110148.49,1,1,0,5790.9,1 -3482,15644686,Kennedy,729,Spain,Female,34,9,53299.96,2,1,1,42855.97,0 -3483,15677377,Lawrence,543,Spain,Male,37,3,0,2,1,1,78915.68,0 -3484,15626412,Mort,499,Spain,Male,39,6,0,2,1,1,81409,0 -3485,15643679,Goliwe,784,Germany,Male,28,2,70233.74,2,1,1,179252.73,0 -3486,15728456,Martinez,604,France,Male,33,3,0,1,1,0,42171.13,1 -3487,15630661,Vasilyev,614,Spain,Female,25,10,75212.28,1,1,0,58965.04,0 -3488,15734044,Black,671,France,Female,31,7,41299.03,1,0,1,102681.32,0 -3489,15705001,Napolitani,587,Spain,Female,35,3,83286.56,1,1,0,125553.52,0 -3490,15809817,Ch'en,593,Spain,Male,43,10,0,2,0,0,53478.02,0 -3491,15809137,Sagese,453,France,Male,29,6,0,1,0,0,198376.02,1 -3492,15751593,Fraser,570,Germany,Male,35,6,85668.59,1,1,0,105525.36,0 -3493,15626491,Hughes,655,France,Female,45,7,57327.04,1,0,1,47349,0 -3494,15765461,Giles,632,Spain,Male,47,3,0,2,1,0,178822.32,0 -3495,15568120,Lacross,681,France,Female,37,7,69609.85,1,1,1,72127.83,0 -3496,15787161,Pisani,591,Germany,Male,46,4,129269.27,1,1,0,163504.33,0 -3497,15812324,King,779,France,Male,27,1,0,2,1,1,190623.02,0 -3498,15588944,Maughan,456,France,Female,63,1,165350.61,2,0,0,140758.07,1 -3499,15694253,Palerma,686,France,Female,41,7,152105.57,2,0,1,132374.41,0 -3500,15759566,Tochukwu,617,France,Male,74,10,0,2,1,1,53949.98,0 -3501,15675675,Slate,850,France,Female,32,5,106290.64,1,1,0,121982.73,0 -3502,15802060,Ch'ang,646,Germany,Female,30,10,100548.67,2,0,0,136983.77,0 -3503,15660505,Romani,735,Germany,Male,46,2,106344.95,1,1,0,114371.33,1 -3504,15782630,Genovese,543,France,Male,35,5,137482.19,1,0,0,62389.35,0 -3505,15700710,Chiebuka,490,France,Female,37,3,116465.53,1,0,1,24435.77,0 -3506,15742834,Liao,640,France,Male,45,1,0,1,1,1,10908.33,0 -3507,15806511,Berry,445,Spain,Male,45,10,0,2,0,1,90977.48,0 -3508,15608166,Fallaci,761,France,Male,36,9,127637.92,1,1,1,81062.93,0 -3509,15614230,T'an,426,France,Female,34,3,0,2,1,1,61230.83,0 -3510,15729958,Wilkinson,777,France,Male,37,1,0,1,1,1,126837.72,0 -3511,15800814,Palerma,534,France,Male,35,2,81951.74,2,1,0,115668.53,0 -3512,15674727,Lazarev,777,France,Female,42,5,147531.82,1,1,1,38819.45,0 -3513,15657779,Boylan,806,Spain,Male,18,3,0,2,1,1,86994.54,0 -3514,15801395,Warren,790,France,Female,33,10,135120.72,1,0,0,195204.99,0 -3515,15757911,Trevisani,643,Spain,Female,32,2,0,1,0,0,131301.74,0 -3516,15665340,Trevisano,584,Spain,Female,37,8,0,2,0,1,100835.19,0 -3517,15787151,Liao,638,France,Female,34,7,0,2,1,1,198969.78,0 -3518,15757821,Burgess,771,Spain,Male,18,1,0,2,0,0,41542.95,0 -3519,15600688,Liston,600,France,Female,39,5,0,2,0,0,118272.07,0 -3520,15594878,Thompson,661,Spain,Female,41,5,28082.95,1,1,0,69586.27,1 -3521,15569248,Milanesi,554,France,Female,43,10,0,2,1,0,149629.13,1 -3522,15812706,Mazure,627,Spain,Male,49,4,111087.5,1,0,1,146680.25,0 -3523,15645045,Rudduck,659,France,Female,38,9,0,2,1,1,132809.18,0 -3524,15766746,Darwin,835,France,Male,35,6,127120.07,1,1,0,28707.69,0 -3525,15700383,Uvarova,763,France,Female,35,7,115651.6,2,1,1,104706.29,0 -3526,15632551,Buccho,625,Germany,Male,31,4,77743.01,2,1,0,75335.68,0 -3527,15795129,Gallo,799,France,Female,30,9,0,2,1,0,136827.96,0 -3528,15650545,Tomlinson,849,France,Male,69,7,71996.09,1,1,1,139065.94,0 -3529,15612769,Carr,692,France,Male,28,5,61581.97,1,1,1,70179.91,0 -3530,15710853,Ts'ui,623,France,Female,24,5,0,2,1,0,116160.04,0 -3531,15623712,Coates,453,Spain,Female,42,5,0,3,1,0,83008.49,1 -3532,15653251,Hickey,408,France,Female,84,8,87873.39,1,0,0,188484.52,1 -3533,15755077,Norton,778,Germany,Female,37,0,105617.73,2,1,1,133699.82,1 -3534,15808557,Mancini,695,France,Female,42,5,0,1,0,1,72172.13,1 -3535,15614687,Tien,677,Germany,Female,44,4,148770.61,2,1,1,191057.76,0 -3536,15626882,Stobie,662,Spain,Male,37,5,94901.09,1,1,1,48233.75,0 -3537,15748034,Drakeford,534,France,Male,29,7,174851.9,1,1,1,79178.31,0 -3538,15632324,Pisani,602,France,Male,59,7,0,2,1,1,162347.05,0 -3539,15761023,Murphy,554,Germany,Female,43,2,120847.11,1,1,0,7611.61,1 -3540,15761453,Kovalev,667,France,Male,42,6,0,1,1,0,88890.05,0 -3541,15646726,Crawford,672,France,Male,43,5,0,1,0,0,63833.09,0 -3542,15637169,Maclean,838,Spain,Female,67,4,103267.8,1,1,1,78310.04,0 -3543,15636024,Blackburn,692,Spain,Female,34,4,109699.08,1,1,1,37898.91,0 -3544,15801218,Bermudez,675,France,Male,49,8,135133.39,1,0,1,179521.24,1 -3545,15642655,Savage,731,Spain,Male,33,1,0,1,1,0,130726.96,0 -3546,15690130,Wyatt,468,France,Female,32,8,137649.47,1,0,0,198714.29,0 -3547,15653753,Chiemenam,542,Spain,Male,43,6,113567.94,1,1,0,89543.25,0 -3548,15641359,Shao,662,Spain,Female,35,6,0,2,0,0,2423.9,1 -3549,15776827,Langdon,770,Germany,Male,37,5,141547.26,2,0,1,180326.83,0 -3550,15647725,Napolitano,675,France,Female,61,5,62055.17,3,1,0,166305.16,1 -3551,15648455,Kung,647,Germany,Male,51,4,131156.76,1,1,0,29883.63,0 -3552,15580629,Blackwood,604,France,Male,31,6,134837.58,1,1,0,192029.19,0 -3553,15730161,Marcelo,833,France,Female,39,3,0,2,1,0,1710.89,0 -3554,15626612,Yin,741,Spain,Male,40,4,104784.23,1,1,0,135163.76,1 -3555,15662865,Storey,658,Spain,Male,36,1,0,2,0,1,84927.42,0 -3556,15629094,Fomin,528,France,Female,36,1,156948.41,1,1,1,149912.28,1 -3557,15651823,Nkemjika,590,France,Female,60,6,147751.75,1,1,0,88206.04,1 -3558,15594827,Glasgow,675,France,Male,34,1,124619.33,2,0,1,163667.56,0 -3559,15786392,Chen,765,France,Male,41,4,124182.21,1,0,0,100153.43,0 -3560,15727353,Ch'ang,650,France,Female,64,7,142028.36,1,1,0,32275.09,1 -3561,15733777,Evans,817,France,Male,44,8,0,1,0,0,65501.91,1 -3562,15614302,Crotty,699,Germany,Female,31,10,125837.86,2,1,0,189392.66,0 -3563,15723263,Cocci,495,Germany,Female,34,9,117160.32,1,1,1,116069.24,1 -3564,15687270,Iroawuchi,491,Spain,Female,61,8,0,2,0,1,139861.53,0 -3565,15803121,Chia,847,France,Male,51,5,97565.74,1,0,0,144184.06,1 -3566,15598700,Hysell,676,Spain,Female,30,5,0,2,0,1,157888.5,0 -3567,15741875,Williamson,746,Spain,Female,25,3,104833.79,1,0,0,71911.3,0 -3568,15631709,Ginikanwa,470,Spain,Female,31,2,101675.22,2,1,0,45033.75,0 -3569,15672970,Chigolum,714,Spain,Male,20,3,0,2,0,1,150465.93,0 -3570,15761670,Morley,695,France,Female,50,8,0,1,1,0,126381.6,1 -3571,15706005,Roberts,674,France,Male,46,2,174701.05,1,1,0,90189.72,1 -3572,15790336,Tokareva,664,Germany,Male,36,6,71142.77,2,1,0,122433.09,0 -3573,15754267,Fleming,697,Germany,Male,31,3,108805.42,2,0,1,123825.83,0 -3574,15791988,Chinomso,670,France,Male,68,4,0,2,1,1,11426.7,0 -3575,15683375,Compton,541,France,Female,32,4,0,1,1,1,114951.42,0 -3576,15625151,Wan,640,France,Female,66,9,116037.76,1,0,1,184636.05,0 -3577,15635285,Taylor,647,France,Male,28,8,0,2,1,1,91055.27,0 -3578,15574296,Kambinachi,757,France,Male,23,2,80673.96,2,1,0,93991.65,0 -3579,15711618,Chang,704,Germany,Female,39,1,124640.51,1,1,0,116511.12,1 -3580,15670943,See,778,Germany,Male,31,9,182275.23,2,1,0,190631.23,0 -3581,15634359,Dyer,639,Germany,Female,41,5,98635.77,1,1,0,199970.74,0 -3582,15586629,Campbell,637,France,Male,33,5,0,2,1,0,139947.17,0 -3583,15588461,Cremonesi,686,France,Male,35,4,0,1,1,0,8816.37,0 -3584,15773221,Harris,577,Spain,Male,43,8,79757.21,1,1,0,135650.72,1 -3585,15664227,Threatt,506,Germany,Male,28,8,53053.76,1,0,1,24577.34,0 -3586,15741745,Lane,757,France,Male,28,7,120911.75,2,1,1,131249.46,0 -3587,15652626,Grave,826,France,Male,55,4,115285.85,1,1,0,140126.17,0 -3588,15599410,Stanley,721,France,Male,41,2,0,2,1,0,168219.75,0 -3589,15571958,McIntosh,489,Spain,Male,40,3,221532.8,1,1,0,171867.08,0 -3590,15785406,Watts,446,France,Female,51,4,105056.13,1,0,0,70613.52,0 -3591,15687884,Alekseyeva,677,France,Male,37,3,88363.03,1,0,1,117946.3,0 -3592,15621685,Davies,769,France,Male,29,2,123757.52,2,1,0,84872.66,0 -3593,15628886,Matlock,677,Spain,Male,56,5,123959.97,1,1,1,60590.72,1 -3594,15699325,Fedorova,555,Germany,Female,62,10,114822.64,1,0,1,8444.5,0 -3595,15578369,Chiedozie,652,Germany,Female,37,9,145219.3,1,1,0,159132.83,0 -3596,15654156,Marcelo,722,Germany,Female,32,5,106807.64,1,1,1,76998.69,0 -3597,15707199,Cooper,643,France,Male,36,0,148159.71,1,0,0,55835.66,0 -3598,15671630,McMillan,796,Germany,Female,40,1,99745.95,1,1,0,177524.19,0 -3599,15632079,Hardy,720,Germany,Female,37,8,156282.79,1,1,0,45985.52,0 -3600,15767921,Madukwe,613,France,Male,41,7,0,2,1,0,60297.72,0 -3601,15573599,Adamson,506,France,Female,57,6,0,2,0,1,194421.12,1 -3602,15747208,Watt,608,France,Male,50,6,0,1,1,0,93568.77,1 -3603,15582762,Mazzanti,667,Spain,Male,77,2,0,1,1,1,34702.92,0 -3604,15772528,Mishin,750,France,Female,47,7,121376.15,2,1,0,54473.6,1 -3605,15755798,Feng,610,France,Male,33,4,111582.11,1,0,0,113943.17,0 -3606,15788683,Kang,588,Germany,Female,34,10,129417.82,1,1,0,153727.32,0 -3607,15616922,Kelly,479,France,Female,26,1,0,2,1,1,19116.97,0 -3608,15771855,Yu,682,France,Male,37,5,0,2,0,1,112554.68,0 -3609,15601873,Bull,677,France,Female,36,7,0,1,1,0,47318.75,0 -3610,15657868,Serra,850,Germany,Male,40,6,94607.08,1,1,0,36690.49,0 -3611,15711716,Ferguson,580,France,Female,56,1,131368.3,1,1,0,106918.67,1 -3612,15734246,She,746,France,Female,21,8,166883.07,2,0,1,194563.65,0 -3613,15792151,Hamilton,635,Spain,Female,37,3,0,2,1,0,91086.73,0 -3614,15770159,Nnanna,664,Germany,Male,25,6,172812.72,2,1,1,108008.65,0 -3615,15747649,Summerville,558,Germany,Female,36,0,126606.63,2,1,1,172363.52,0 -3616,15639357,Allan,415,France,Male,46,9,134950.19,3,0,0,178587.36,1 -3617,15738907,Tobenna,798,France,Female,60,6,96956.1,1,1,0,31907.44,1 -3618,15663446,Volkova,792,Germany,Female,29,4,107601.79,1,1,0,18922.18,1 -3619,15750867,Nucci,489,Germany,Female,46,8,92060.06,1,1,0,147222.95,1 -3620,15715939,Wright,730,France,Male,33,0,0,2,1,0,1474.79,0 -3621,15763806,Astorga,773,France,Male,41,4,0,2,1,1,24924.92,0 -3622,15637993,Pokrovsky,711,France,Male,36,9,137688.71,1,1,1,46884.1,0 -3623,15720338,Mazzanti,592,Spain,Male,55,8,85845.43,2,1,1,128918.42,0 -3624,15627162,Blesing,695,Germany,Male,27,6,125552.96,1,1,0,105291.26,0 -3625,15596710,Ku,640,France,Female,33,1,167298.42,1,0,1,145381.65,0 -3626,15781678,Pisani,470,Spain,Male,31,4,55732.92,2,1,1,103792.53,0 -3627,15634968,Hsueh,789,Germany,Female,37,6,110689.07,1,1,1,71121.04,1 -3628,15609475,Ricci,604,Spain,Female,39,7,98544.11,1,1,1,52327.57,0 -3629,15573319,Azubuike,493,Germany,Female,35,8,178317.6,1,0,0,197428.64,0 -3630,15738291,Nevzorova,671,France,Female,48,8,115713.84,2,0,0,83210.84,0 -3631,15782456,Odili,656,France,Male,46,9,143267.14,2,0,0,193099.43,0 -3632,15794841,Kung,739,Spain,Male,19,5,89750.21,1,1,0,193008.52,0 -3633,15684696,Lei,560,Spain,Female,26,3,116576.45,1,1,0,157567.37,0 -3634,15629846,Sheehan,827,Germany,Female,47,8,143001.5,2,1,0,108977.5,0 -3635,15674442,Kung,681,France,Male,23,7,157761.56,1,0,0,147759.84,0 -3636,15571689,Kelechi,740,France,Female,37,5,0,2,1,1,27528.4,0 -3637,15730469,Anenechi,663,Spain,Male,31,4,103430.11,2,0,1,36479.27,0 -3638,15809320,McElhone,845,Spain,Female,52,0,0,1,1,0,31726.76,1 -3639,15684367,Chigbogu,555,Spain,Male,27,5,0,2,0,0,96398.51,0 -3640,15793049,Atkins,680,Germany,Female,48,8,115115.38,1,1,0,139558.6,1 -3641,15603665,Colombo,638,Germany,Female,39,0,122501.28,2,1,1,95007.8,0 -3642,15613623,Tilley,640,Spain,Male,62,3,0,1,1,1,101663.47,0 -3643,15569572,Sopuluchi,778,France,Male,42,6,0,2,1,1,106197.44,0 -3644,15698791,Udinesi,679,France,Male,45,3,146758.24,1,1,0,48466.89,0 -3645,15626233,Onyekachi,593,France,Female,32,3,0,2,1,1,151978.36,0 -3646,15607263,McCartney,788,France,Male,55,3,0,1,0,1,13288.46,1 -3647,15610900,Thompson,770,France,Female,70,9,110738.89,1,1,0,22666.77,1 -3648,15624775,Onyeoruru,729,France,Male,67,2,94203.8,1,0,1,102391.06,0 -3649,15691703,Shih,545,France,Male,47,8,105792.49,1,0,1,67830.2,1 -3650,15745355,Golibe,597,France,Male,41,4,153198.23,1,1,1,92090.36,0 -3651,15724955,Lucchesi,537,France,Male,38,3,0,2,0,0,141023.01,0 -3652,15628999,Townsend,732,France,Male,79,10,61811.23,1,1,1,104222.8,0 -3653,15654341,Chao,542,France,Male,34,8,101116.06,1,1,0,196395.05,0 -3654,15744240,Shen,688,Germany,Female,46,0,74458.25,1,0,1,6866.31,0 -3655,15632365,Booth,542,Germany,Male,33,8,142871.27,2,0,0,77737.86,0 -3656,15729689,Chan,754,Germany,Male,35,6,98585.94,2,0,1,106116.84,0 -3657,15759284,Yeh,750,France,Female,37,6,0,1,1,1,117948,1 -3658,15602124,Badgery,731,France,Male,30,7,0,2,1,1,184581.68,0 -3659,15661903,Hsia,699,France,Female,43,3,80764.03,1,1,0,199378.58,1 -3660,15664668,Zarate,534,France,Female,42,9,144801.97,1,0,1,12483.39,1 -3661,15736431,Congreve,494,Spain,Male,27,2,0,2,1,0,22404.64,0 -3662,15748639,Hayslett,497,Germany,Male,35,7,110053.62,2,1,1,92887.06,0 -3663,15628123,Robinson,632,France,Female,28,5,118890.81,1,0,1,145157.97,0 -3664,15602731,Wong,724,France,Male,31,5,0,1,1,0,134889.95,1 -3665,15794137,Nevzorova,751,Germany,Female,37,0,151218.98,1,1,1,109309.29,0 -3666,15748696,Page,733,France,Male,42,9,150507.21,1,0,1,169964.12,0 -3667,15725068,Quinn,701,Spain,Female,21,9,0,2,1,1,26327.42,0 -3668,15807340,O'Donnell,525,Germany,Male,33,4,131023.76,2,0,0,55072.93,0 -3669,15586133,Pisano,666,Germany,Female,44,2,122314.5,1,0,0,68574.88,1 -3670,15576185,Sinclair,653,France,Male,29,2,0,2,1,1,41671.81,0 -3671,15660809,Loving,850,France,Male,28,4,0,2,1,1,12409.01,0 -3672,15616666,Artemova,646,Germany,Female,52,6,111739.4,2,0,1,68367.18,0 -3673,15706904,Robertson,750,France,Male,43,6,113882.31,1,1,1,74564.41,0 -3674,15606915,Genovese,764,France,Male,24,7,98148.61,1,1,0,26843.76,0 -3675,15749693,Ugonnatubelum,658,France,Female,32,9,0,2,1,0,156774.75,0 -3676,15791743,Corbett,727,France,Male,32,1,59271.82,1,1,1,46019.43,0 -3677,15796480,Reilly,687,France,Female,31,2,0,2,0,1,145411.39,0 -3678,15790442,Wright,631,Spain,Male,33,2,0,2,1,1,158268.84,0 -3679,15609458,Vincent,797,France,Male,30,10,69413.44,1,1,1,74637.57,0 -3680,15593897,Carr,650,Spain,Male,25,7,160599.06,2,1,1,28391.52,0 -3681,15604576,Eiland,850,Spain,Male,22,3,0,1,1,1,144385.54,0 -3682,15666270,Omeokachie,676,France,Female,40,2,147803.48,1,1,0,95181.06,1 -3683,15572626,Mackenzie,620,Spain,Male,44,8,0,2,1,1,15627.51,0 -3684,15727197,Pinto,576,France,Female,52,9,170228.59,2,0,0,148477.57,1 -3685,15714006,Gardener,482,France,Female,35,2,133111.73,1,0,1,79957.95,0 -3686,15642137,Fang,695,Spain,Female,39,5,0,2,0,0,102763.69,0 -3687,15665327,Cattaneo,706,France,Male,18,2,176139.5,2,1,0,129654.22,0 -3688,15626806,Labrador,668,France,Female,32,2,0,2,1,1,40652.33,0 -3689,15662578,Dettmann,679,Germany,Male,35,1,110245.13,1,1,1,178291.09,0 -3690,15790829,Gibson,703,France,Female,45,5,0,2,1,0,131906.44,0 -3691,15654959,Hope,670,Spain,Male,67,6,158719.57,1,1,1,118607.4,0 -3692,15760244,Ives,590,France,Female,76,5,160979.68,1,0,1,13848.58,0 -3693,15715394,Greece,613,Spain,Male,35,4,123557.65,2,0,1,170903.4,0 -3694,15722246,Omeokachie,742,France,Female,60,4,0,1,1,1,13161.66,1 -3695,15609704,Mao,608,France,Female,33,4,0,1,1,0,79304.38,1 -3696,15757628,Savage,571,France,Male,40,10,112896.86,1,1,1,121402.53,0 -3697,15633586,Brierly,595,France,Female,39,7,120962.13,1,0,0,23305.01,0 -3698,15565796,Docherty,745,Germany,Male,48,10,96048.55,1,1,0,74510.65,0 -3699,15717935,McDonald,589,France,Female,21,3,0,2,0,1,55601.44,0 -3700,15577700,Rapuokwu,749,France,Male,37,10,185063.7,2,1,1,134526.87,0 -3701,15747345,Bergamaschi,678,France,Female,22,6,118064.93,2,1,1,195424.01,0 -3702,15678317,Manfrin,603,France,Male,46,2,0,2,1,1,59563.49,0 -3703,15698335,Bergamaschi,504,France,Female,73,8,0,1,1,1,34595.58,0 -3704,15768451,MacDonald,739,Germany,Male,40,5,149131.03,3,1,1,60036.99,1 -3705,15753213,Lees,604,France,Female,34,7,0,2,1,0,193021.49,0 -3706,15769645,Senior,612,France,Female,35,3,0,1,1,1,48108.72,0 -3707,15657565,Nwokezuike,629,Spain,Female,44,6,125512.98,2,0,0,79082.76,0 -3708,15620323,Ekwueme,652,Spain,Female,42,3,83492.07,2,1,0,37914.12,0 -3709,15679983,Garmon,565,France,Male,34,7,0,1,0,0,74593.84,0 -3710,15812616,Enyinnaya,707,France,Female,49,10,0,1,1,0,82967.97,1 -3711,15601796,Chizuoke,645,France,Male,30,1,125739.26,1,1,1,193441.23,0 -3712,15729489,Hyde,762,Germany,Female,34,8,98592.88,1,0,1,191790.29,1 -3713,15613216,Cameron,639,Spain,Female,39,1,141789.15,1,1,0,92455.96,0 -3714,15657937,Lord,709,Germany,Male,22,0,112949.71,1,0,0,155231.55,0 -3715,15815428,Biryukova,823,France,Male,34,3,105057.33,1,1,0,9217.92,0 -3716,15640409,Carpenter,817,Germany,Female,46,0,89087.89,1,0,1,87941.85,1 -3717,15699492,Lorenzo,665,Germany,Female,27,2,147435.96,1,0,0,187508.06,0 -3718,15623536,Madukwe,646,Germany,Male,39,0,154439.86,1,1,0,171519.06,0 -3719,15707551,Hutcheon,568,France,Male,30,8,73054.37,2,1,1,27012,0 -3720,15577999,Sleeman,850,France,Female,62,1,124678.35,1,1,0,70916,1 -3721,15788775,Milne,473,Germany,Male,40,8,152576.25,2,1,0,73073.68,0 -3722,15758362,Williamson,731,France,Female,41,9,152243.57,1,1,1,88783.59,0 -3723,15807961,Bruno,619,France,Male,25,4,0,1,1,0,145524.36,0 -3724,15710978,Palerma,715,Germany,Male,42,2,88120.97,2,1,1,21333.22,0 -3725,15703541,Wang,772,Germany,Female,51,9,143930.92,1,0,1,46675.51,1 -3726,15626474,Onyemere,686,France,Female,31,1,0,2,1,0,4802.25,0 -3727,15608344,Dawson,749,Germany,Female,29,7,137059.05,3,1,0,102975.72,1 -3728,15768367,Nebechukwu,781,France,Female,27,7,186558.55,1,1,1,175071.29,1 -3729,15806210,Bateman,675,Spain,Male,66,5,115654.47,2,1,1,131970.86,0 -3730,15697702,Lord,730,Spain,Male,29,2,0,2,1,0,14174.09,0 -3731,15689152,Loggia,683,Spain,Male,38,3,126152.84,1,0,0,15378.75,0 -3732,15568573,Graham,554,Germany,Female,51,7,105701.91,1,0,1,179797.79,1 -3733,15689598,Dean,722,France,Male,46,6,0,1,1,1,93917.68,1 -3734,15713374,Jarvis,689,Germany,Male,67,9,157094.78,1,1,1,99490.01,0 -3735,15679733,Haugh,796,Germany,Male,40,2,113228.38,2,1,1,46415.09,0 -3736,15759274,Micklem,447,France,Female,32,10,0,1,1,1,151815.76,0 -3737,15607748,Bennett,498,Germany,Male,37,8,108432.88,2,1,1,14865.05,0 -3738,15607577,Roberts,663,Spain,Male,27,8,0,1,1,1,188007.99,0 -3739,15813697,Onyekaozulu,498,Germany,Female,44,2,120702.67,2,1,1,98175.74,0 -3740,15801125,Kegley,627,France,Female,32,1,0,1,1,0,106851.7,0 -3741,15777855,Manna,649,France,Male,45,7,0,2,0,1,75204.21,0 -3742,15635396,Thompson,738,Germany,Female,29,9,139106.19,1,1,0,141872.05,1 -3743,15698031,Romano,587,Germany,Female,39,6,101851.8,2,1,0,7103.71,0 -3744,15678944,Brown,655,Germany,Female,32,6,130935.56,1,1,0,9241.83,1 -3745,15718507,Su,647,Germany,Male,37,3,116509.99,1,1,1,149517.71,1 -3746,15808334,Mackay,776,Germany,Female,37,1,93124.04,2,1,1,196079.32,0 -3747,15804709,Watt,688,Germany,Male,35,5,111578.18,1,0,0,166165.93,1 -3748,15645835,Milani,605,France,Male,32,9,0,2,1,1,55724.24,0 -3749,15738166,Hsu,596,France,Female,39,10,86546.29,1,0,1,131768.98,0 -3750,15675360,Valenzuela,427,France,Male,33,8,0,1,1,1,13858.95,0 -3751,15793042,Sung,629,France,Male,39,2,129669.32,2,1,0,82774.07,0 -3752,15630106,Lo,496,Spain,Male,29,2,0,2,1,0,55389.59,0 -3753,15810385,Giordano,717,Spain,Female,36,2,164557.95,1,0,1,82336.73,0 -3754,15578211,Connolly,777,France,Male,23,6,0,2,1,1,163225.48,0 -3755,15572792,Bellucci,535,Spain,Male,35,8,118989.92,1,1,1,135536.72,0 -3756,15620030,Jamieson,744,France,Male,29,1,0,1,0,0,82422.97,0 -3757,15783541,Fomina,755,France,Male,31,5,0,2,0,1,194660.78,0 -3758,15679284,Aksenov,593,Spain,Female,45,6,79259.75,1,1,0,55347.28,0 -3759,15582910,Turnbull,514,France,Male,38,4,112230.38,1,1,0,16717.11,1 -3760,15688337,Dixon,721,France,Male,40,9,118129.87,1,1,1,160277.65,0 -3761,15734970,White,835,Spain,Male,38,7,86824.09,1,0,0,175905.97,0 -3762,15759140,Long,682,France,Female,64,10,128306.7,1,0,1,66040.83,0 -3763,15643042,Han,590,Germany,Female,40,2,117641.43,2,0,0,92198.05,0 -3764,15773868,Belov,653,Germany,Female,37,3,125734.2,2,1,0,134625.09,1 -3765,15615820,MacDonald,837,France,Male,49,8,103302.37,1,1,1,50974.57,0 -3766,15730273,Parsons,841,France,Male,27,8,0,1,1,0,171922.72,0 -3767,15724890,Cross,584,Spain,Male,36,4,82696.09,2,0,0,83058.14,0 -3768,15765952,Milanesi,769,France,Male,29,4,145471.37,1,1,0,188382.77,0 -3769,15685920,Lombardo,599,Spain,Male,34,2,101506.66,1,0,0,198030.24,0 -3770,15663263,Collins,698,France,Male,47,5,156265.31,2,0,0,1055.66,0 -3771,15568953,Alexeieva,477,France,Male,27,1,128554.98,1,1,1,133173.19,0 -3772,15643361,Cullen,477,Germany,Male,34,8,139959.55,2,1,1,189875.83,0 -3773,15699486,Johnson,745,Spain,Male,34,7,132944.53,1,1,1,31802.92,0 -3774,15747854,Rudd,749,France,Female,35,3,0,3,1,1,132649.85,0 -3775,15691785,Findlay,850,France,Male,61,1,0,1,1,0,53067.83,1 -3776,15709004,Mai,528,Germany,Male,22,5,93547.23,2,0,1,961.57,0 -3777,15652218,Morrison,750,France,Male,33,2,152302.72,1,1,0,71333.44,0 -3778,15697127,Monaldo,543,France,Female,31,2,147674.26,1,1,1,16658.76,0 -3779,15658486,Gidney,579,Spain,Female,59,3,148021.12,1,1,1,74878.22,0 -3780,15694160,Sagese,624,France,Male,37,0,0,2,0,0,112104.55,0 -3781,15685290,Wall,595,Germany,Male,46,5,142360.62,2,1,0,48421.4,1 -3782,15701042,Dalton,596,Germany,Female,27,2,151027.56,1,1,0,170320.58,0 -3783,15680449,Hsing,431,Germany,Female,44,2,138843.7,1,1,0,37688.31,1 -3784,15599860,Warner,647,Spain,Female,26,8,109958.15,1,1,1,136592.24,1 -3785,15723169,Williams,640,France,Female,31,9,138857.59,1,1,0,48640.77,0 -3786,15803842,Dunn,752,Germany,Female,45,3,105426.5,2,0,1,89773.45,0 -3787,15728224,Kerr,710,Germany,Female,41,9,149155.53,2,1,0,42131.26,1 -3788,15644174,Marchesi,638,Germany,Male,27,4,135096.05,1,1,1,186523.72,1 -3789,15707110,Endrizzi,660,Germany,Male,28,2,170890.05,2,1,0,41758.9,0 -3790,15765415,King,609,Spain,Female,45,4,89122.3,1,1,1,199256.98,0 -3791,15756751,Griffiths,596,Spain,Female,54,0,78126.28,1,1,1,153482.91,1 -3792,15795151,Hartzler,705,France,Female,38,3,123894.43,1,1,0,21177.1,0 -3793,15632859,Chukwudi,444,France,Male,36,7,0,2,0,1,138743.86,0 -3794,15584037,Denisov,727,Germany,Male,58,5,106913.43,1,1,0,25881,1 -3795,15621409,Endrizzi,496,France,Male,32,4,127845.83,1,1,0,66469.2,0 -3796,15581102,Baresi,554,France,Female,22,8,0,2,0,1,142670.61,0 -3797,15578096,Nnachetam,537,France,Male,26,7,106397.75,1,0,0,103563.23,0 -3798,15669887,Lambert,839,France,Female,51,3,0,1,1,1,69101.23,1 -3799,15621834,Game,700,Spain,Female,43,0,0,2,1,0,59475.35,0 -3800,15655341,Chinagorom,458,Spain,Female,35,5,166492.48,1,1,0,135287.74,0 -3801,15685314,Noble,850,France,Female,28,2,0,2,1,1,38773.74,0 -3802,15653997,Haynes,699,Spain,Male,31,6,114493.68,1,0,0,138396.32,0 -3803,15629551,Cattaneo,615,Germany,Female,44,9,126104.98,2,0,1,110718.02,0 -3804,15651264,Yobanna,850,Germany,Male,51,4,124425.99,1,0,0,118545.49,1 -3805,15760825,Fraser,604,France,Female,40,1,0,2,1,0,123207.17,0 -3806,15597394,Rhodes,668,Spain,Male,34,0,0,1,0,0,99984.86,0 -3807,15740383,Jimenez,594,Spain,Female,38,10,0,2,1,0,58332.91,0 -3808,15670562,Pharr,470,France,Male,30,3,101140.76,1,1,1,50906.65,0 -3809,15698117,Jerger,701,Germany,Male,41,0,150844.94,1,0,1,127623.36,0 -3810,15694805,McIntyre,664,Spain,Male,35,1,115024.5,1,0,1,169665.79,0 -3811,15746802,Onio,477,France,Female,30,6,131286.46,1,1,0,194144.45,0 -3812,15589428,Tomlinson,756,France,Female,42,9,0,2,1,0,35673.42,0 -3813,15790267,Onuoha,625,France,Female,40,7,141267.67,1,0,1,177397.49,0 -3814,15665402,Panicucci,703,Spain,Male,73,5,137761.55,1,1,1,159677.46,0 -3815,15642093,Piccio,646,France,Male,30,7,0,2,1,0,153566.97,0 -3816,15666181,Ramsden,650,France,Male,33,0,98064.97,1,1,0,52411.99,0 -3817,15602554,Vorobyova,664,France,Female,31,9,114519.57,2,0,1,79222.02,0 -3818,15724251,Todd,682,Germany,Female,29,6,101012.77,1,0,0,32589.89,1 -3819,15740147,Cremonesi,725,France,Female,44,10,0,1,0,1,93777.61,0 -3820,15718289,Bradley,553,Germany,Male,46,3,82291.1,1,1,0,112549.99,1 -3821,15763148,Stanley,576,France,Male,39,9,84719.98,1,0,0,191063.36,0 -3822,15685245,Jowett,608,Spain,Female,56,5,0,2,0,1,153810.41,0 -3823,15626985,Yefremova,850,France,Female,39,0,104386.53,1,1,0,105886.77,0 -3824,15585823,Wilson,627,France,Male,31,8,128131.73,1,1,0,96131.47,0 -3825,15728167,Abramovich,667,France,Male,44,2,122806.95,1,0,0,15120.86,0 -3826,15762928,Venables,548,Spain,Male,44,8,0,1,1,0,16989.77,0 -3827,15751774,Monnier,774,France,Male,76,4,112510.89,1,1,1,143133.18,0 -3828,15654733,Hsieh,794,Germany,Male,57,3,117056.46,1,1,0,93336.93,1 -3829,15809777,Gadsden,497,Germany,Female,55,7,131778.66,1,1,1,9972.64,0 -3830,15744200,Ni,587,France,Female,36,1,70784.27,1,1,0,30579.82,0 -3831,15720713,Chibueze,850,France,Female,29,10,0,2,1,1,199775.67,0 -3832,15695356,Chinwemma,722,France,Male,46,5,0,2,1,0,179908.71,0 -3833,15653315,Kang,555,Spain,Female,35,1,0,2,1,0,101667,0 -3834,15604792,Kuo,609,Germany,Male,38,6,140752.06,2,0,1,171430.16,0 -3835,15704819,Ositadimma,734,Spain,Female,39,6,92126.26,2,0,0,112973.34,0 -3836,15670859,Smith,718,Germany,Female,39,7,93148.74,2,1,1,190746.38,0 -3837,15602797,Okwudilichukwu,645,Spain,Female,49,5,110132.55,3,0,1,187689.91,1 -3838,15662533,Porter,598,Spain,Female,23,6,0,2,1,0,153229.19,0 -3839,15778154,Kung,628,Germany,Male,50,4,122227.71,1,0,1,14217.77,1 -3840,15806230,Trevisano,629,Germany,Male,40,2,121647.54,2,1,1,64849.74,1 -3841,15662884,Naylor,739,Germany,Male,58,1,110597.76,1,0,1,160122.66,1 -3842,15750778,Ponomarev,653,France,Female,60,2,120731.39,4,1,1,138160.11,1 -3843,15717185,Udinese,711,France,Male,28,8,0,2,1,1,64286.39,0 -3844,15677804,Aliyeva,783,Spain,Male,38,1,0,3,1,1,80178.54,1 -3845,15568915,Bailey,681,France,Male,38,6,153722.47,1,1,0,101319.76,0 -3846,15736495,Jackson,712,France,Male,34,8,114088.32,1,1,0,92794.61,0 -3847,15737354,Yin,554,France,Female,48,7,0,2,1,1,63708.07,0 -3848,15667889,Akobundu,611,France,Female,37,6,0,2,1,0,110782.88,0 -3849,15577831,Byrne,560,Germany,Male,41,4,152532.3,1,0,0,10779.69,0 -3850,15729836,Robinson,646,Spain,Male,32,1,0,2,1,0,183289.22,0 -3851,15775293,Stephenson,680,France,Male,34,3,143292.95,1,1,0,66526.01,0 -3852,15697597,Chiemenam,631,France,Male,26,1,149144.61,1,0,1,123697.95,0 -3853,15639669,Forbes,746,France,Male,36,9,127157.04,1,1,1,155700.15,0 -3854,15631392,Douglas,654,Germany,Male,43,9,84673.17,2,0,1,82081.35,0 -3855,15580935,Okechukwu,687,Germany,Male,33,9,135962.4,2,1,0,121747.96,0 -3856,15590344,Russell,708,Germany,Male,32,3,151691.44,2,1,1,172810.51,0 -3857,15653306,Ermakova,679,Germany,Female,32,0,88335.05,1,0,0,159584.81,0 -3858,15805025,Oster,636,France,Female,45,7,139859.23,1,1,1,108402.54,0 -3859,15658449,Chizoba,695,France,Male,45,9,43134.65,1,0,1,77330.35,0 -3860,15694450,Bianchi,677,France,Male,42,5,99580.13,1,1,0,21007.96,0 -3861,15605666,Peyser,720,France,Female,34,6,110717.38,1,1,1,9398.45,0 -3862,15615126,Cocci,780,France,Female,37,3,0,2,0,0,182156.81,1 -3863,15726588,Seleznev,653,Spain,Female,36,3,0,2,0,0,110525.6,0 -3864,15645095,Huang,674,France,Female,28,3,0,1,1,0,51536.99,0 -3865,15808960,Alleyne,620,Germany,Male,40,5,108197.11,2,1,0,49722.34,0 -3866,15729435,McKenzie,623,France,Male,40,6,0,2,1,1,66119.07,0 -3867,15656840,Zikoranachukwudimma,547,France,Female,29,6,104450.86,1,1,1,37160.28,0 -3868,15659149,King,530,France,Male,39,2,0,2,1,0,197923.05,0 -3869,15585490,Nkemdilim,746,France,Female,34,4,0,1,0,1,65166.6,0 -3870,15674929,Anderson,512,France,Female,31,7,0,2,0,0,49326.07,0 -3871,15746341,Ejikemeifeuwa,630,France,Male,40,8,0,2,1,1,42495.81,0 -3872,15662091,Adams,570,Spain,Male,21,7,116099.82,1,1,1,148087.62,0 -3873,15620123,Christie,605,France,Male,39,6,111169.91,1,0,0,9641.4,0 -3874,15616240,Yeh,530,Spain,Male,37,4,0,2,1,1,164844.37,0 -3875,15624186,McGregor,813,Germany,Female,25,5,123616.43,1,0,1,132959.33,0 -3876,15605036,Pisano,704,Spain,Female,37,9,155619.58,1,1,1,135088.58,0 -3877,15805151,Ginikanwa,565,Germany,Male,31,2,89558.39,2,1,1,4441.54,0 -3878,15753847,Hawkins,645,Spain,Male,45,4,0,1,0,1,174916.85,1 -3879,15653222,Otutodilichukwu,526,Germany,Female,32,6,131938.92,2,1,1,1795.93,0 -3880,15757541,Rickard,778,France,Female,33,9,151772.63,2,0,0,180249.94,1 -3881,15726945,Andreev,677,France,Female,72,8,0,2,1,1,153604.44,0 -3882,15794276,Steele,588,France,Female,64,3,0,1,1,1,189703.65,0 -3883,15568328,Black,488,France,Female,22,6,0,2,1,1,66393.89,0 -3884,15604355,Shand,519,France,Male,39,1,97700.02,1,1,1,30709.03,0 -3885,15735788,Chiagoziem,709,France,Male,31,6,0,2,1,1,71009.84,0 -3886,15618255,Fedorov,642,Germany,Female,56,6,103244.86,2,1,0,143049.72,1 -3887,15720941,Tien,710,Germany,Male,34,8,147833.3,2,0,1,1561.58,0 -3888,15769110,Stehle,653,France,Female,46,5,0,2,1,0,49707.85,0 -3889,15576094,Sung,743,France,Male,71,0,0,2,0,1,29837.65,0 -3890,15756150,Alexander,418,France,Female,39,2,0,2,0,0,9041.71,0 -3891,15719579,McIntosh,670,Germany,Female,33,9,84521.48,2,0,1,198017.05,0 -3892,15748854,Sung,723,Germany,Female,28,5,91938.31,1,1,0,143481.85,0 -3893,15612455,Yao,549,Germany,Male,45,6,124240.93,1,1,1,146372.51,0 -3894,15664802,Chinweuba,543,France,Female,42,5,0,2,0,0,101905.34,0 -3895,15735687,Chinweuba,595,Spain,Male,37,2,157084.99,1,1,0,134767.13,0 -3896,15664734,T'ao,673,Germany,Female,25,3,108244.82,2,1,1,103573.96,0 -3897,15767894,Ch'ien,741,France,Female,21,9,0,2,0,1,139259.54,0 -3898,15666884,Su,508,Germany,Female,41,5,82161.7,2,1,0,187776.49,0 -3899,15750156,Yu,662,Germany,Male,59,2,104568.41,1,1,0,8059.44,1 -3900,15751120,Loyau,752,France,Female,36,2,119912.46,1,1,0,124354.92,0 -3901,15575748,Conti,809,France,Male,36,9,68881.59,2,0,1,109135.11,0 -3902,15714610,Alexeeva,575,Spain,Male,30,2,0,2,1,1,82222.86,0 -3903,15720305,Power,591,Spain,Female,40,1,86376.29,1,0,1,136767.16,1 -3904,15678129,Hill,643,Spain,Female,45,9,150840.03,2,1,0,155516.35,0 -3905,15566633,Freeman,698,Germany,Male,55,8,155059.1,2,1,1,144584.29,0 -3906,15680436,Hsing,496,France,Female,29,4,0,2,1,0,164806.89,0 -3907,15674343,Esposito,597,France,Male,44,8,78128.13,2,0,1,109153.04,0 -3908,15658890,Belonwu,603,Germany,Male,46,4,98899.76,2,1,1,86190.34,0 -3909,15599004,Tsao,655,Spain,Male,37,1,0,1,1,1,106040.97,0 -3910,15726487,P'eng,431,France,Male,63,6,160982.89,1,1,1,168008.17,0 -3911,15698716,Baker,620,France,Female,70,3,87926.24,2,1,0,33350.26,1 -3912,15710527,Matthews,782,France,Female,35,4,0,1,1,1,119565.34,0 -3913,15655590,Garcia,581,Spain,Male,46,2,79385.21,2,0,0,188492.82,0 -3914,15732266,Field,553,Germany,Male,53,5,127997.83,1,1,0,165378.66,1 -3915,15669326,Gordon,658,France,Male,44,2,168396.34,1,1,1,14178.73,0 -3916,15672246,Jefferies,686,Germany,Male,43,2,134896.03,1,1,1,97847.05,0 -3917,15620276,Palermo,539,Spain,Male,36,6,0,3,1,1,118959.64,0 -3918,15640258,Chou,685,France,Female,50,6,94238.75,2,1,1,50664.07,1 -3919,15740283,Ewing,850,France,Male,29,1,0,2,0,0,152996.89,0 -3920,15759717,Mazzi,763,Spain,Female,39,7,0,2,1,0,19458.75,0 -3921,15620268,Thomson,634,Germany,Male,43,3,212696.32,1,1,0,115268.86,0 -3922,15743871,Nkemdirim,567,France,Male,59,3,0,2,1,0,25843.7,1 -3923,15614491,Lockyer,539,France,Male,39,3,139153.68,2,1,0,147662.33,0 -3924,15595047,Murray,764,France,Male,41,7,0,2,0,0,134878.34,0 -3925,15732334,Black,653,France,Female,40,0,0,2,1,0,35795.85,0 -3926,15701206,Torreggiani,566,Spain,Male,44,5,0,2,1,0,66462.79,0 -3927,15581280,Atkinson,714,Germany,Male,29,6,92887.13,1,1,1,69578.49,0 -3928,15651943,Richards,580,Spain,Female,65,1,0,2,0,1,103182.46,0 -3929,15609545,Azubuike,548,France,Male,29,5,83442.98,1,0,1,177017.39,0 -3930,15658548,Ignatiev,646,Germany,Female,36,6,144773.29,2,1,0,53217.3,0 -3931,15626008,Miller,622,Germany,Female,52,9,111973.97,1,1,1,162756.29,1 -3932,15774133,Cox,706,France,Female,35,8,178032.53,1,0,1,42181.68,0 -3933,15763798,McMillan,680,France,Male,23,5,140007.19,1,0,1,31714.08,0 -3934,15758013,Napolitano,698,France,Male,37,5,98400.61,2,0,0,25017.28,0 -3935,15705765,Lane,581,Spain,Female,46,1,0,2,1,0,104272.04,0 -3936,15648362,Kennedy,728,Germany,Male,45,3,108924.33,2,1,0,84300.4,1 -3937,15761102,T'ao,707,Spain,Female,32,4,132835.56,1,0,0,136877.24,0 -3938,15610165,Hsiung,761,France,Female,26,1,0,2,1,1,199409.19,0 -3939,15723717,Heath,483,Germany,Male,41,1,118334.44,1,0,0,163147.99,1 -3940,15654611,Parry,736,Germany,Female,25,9,81732.88,2,1,0,136497.28,0 -3941,15659736,Herbert,716,Germany,Male,66,5,121411.9,1,0,0,10070.4,1 -3942,15603170,Kang,654,France,Male,32,9,121455.65,1,1,0,190068.53,1 -3943,15786167,Andreyeva,649,Spain,Male,20,5,0,2,1,1,58309.54,0 -3944,15671915,Bowen,649,France,Male,46,5,0,2,1,1,76946.6,0 -3945,15794792,Golubev,612,France,Female,31,8,117989.76,1,1,1,54129.86,0 -3946,15652789,Hancock,657,Spain,Male,40,10,0,2,1,1,52990.7,0 -3947,15739168,Fowler,511,France,Female,31,5,137411.29,1,0,1,161854.98,0 -3948,15719950,Sutherland,682,France,Male,61,10,73688.2,1,1,1,172141.33,0 -3949,15743818,Rowley,748,Spain,Male,58,9,122330.7,2,0,1,124429.19,0 -3950,15717937,Gibbons,554,Germany,Male,43,5,99906.89,1,0,0,24983.39,0 -3951,15602841,Lockett,794,Spain,Female,28,5,0,2,0,1,86699.98,0 -3952,15619972,Akabueze,807,France,Female,47,9,167664.83,1,0,0,125440.11,1 -3953,15796114,Phelps,594,France,Female,34,7,141525.55,1,0,0,9443.15,0 -3954,15633546,Frederick,652,Spain,Female,33,3,124832.51,1,1,0,195877.06,0 -3955,15758755,Beneventi,729,France,Female,34,9,132121.71,1,0,1,105409.31,0 -3956,15695168,Bruce,625,France,Male,39,2,0,2,1,0,100403.05,0 -3957,15754342,Green,597,Germany,Female,60,0,78539.84,1,0,1,48502.88,0 -3958,15756610,Carlson,657,Germany,Female,38,5,123770.46,1,0,0,47019.66,1 -3959,15640917,Tang,633,France,Male,43,5,0,2,1,1,48249.88,0 -3960,15663164,Yudin,663,Germany,Male,49,7,116150.65,3,1,1,84358.71,1 -3961,15616811,MacDonald,535,France,Male,47,0,160729.1,1,0,1,145986.35,0 -3962,15610781,Watt,702,France,Female,29,10,88378.6,1,1,0,88550.28,0 -3963,15600911,Mbadiwe,712,France,Male,33,2,182888.08,1,1,0,3061,0 -3964,15629603,Chuang,607,France,Male,31,8,0,2,1,1,43196.5,0 -3965,15714981,Sabbatini,476,France,Male,37,4,0,1,1,1,55775.84,1 -3966,15775892,Caldwell,748,Spain,Female,23,8,85600.08,1,0,0,134077.71,0 -3967,15782778,Ewers,815,France,Male,35,4,0,2,0,1,198490.33,0 -3968,15786643,Tsao,602,France,Male,32,10,0,2,1,1,116052.92,0 -3969,15595657,Hannam,649,Germany,Male,40,4,95001.33,1,0,1,123202.99,0 -3970,15743673,Wood,551,Spain,Male,27,2,113873.22,1,1,1,85129.77,1 -3971,15634310,Ko,509,France,Male,30,6,0,2,1,0,180598.86,0 -3972,15790809,Lo Duca,685,Spain,Male,40,7,74896.92,1,1,0,198694.2,0 -3973,15668695,Endrizzi,536,France,Female,22,5,89492.62,1,0,0,42934.43,0 -3974,15669281,Ch'iu,711,Spain,Male,38,3,128718.78,1,0,0,114793.45,0 -3975,15621031,Mofflin,761,Spain,Male,27,8,0,2,1,0,63297.7,0 -3976,15720071,Fiorentini,535,France,Female,49,3,0,1,0,0,61820.41,1 -3977,15792180,Chiekwugo,566,Germany,Male,22,7,144954.75,2,1,0,102246,0 -3978,15813894,Bogle,620,Spain,Male,21,9,0,2,0,0,154882.79,0 -3979,15669490,Ifeanacho,837,Germany,Male,37,6,94001.61,2,1,0,140723.05,0 -3980,15783030,Owens,685,France,Female,40,7,0,1,1,0,72852.74,1 -3981,15695792,Ch'ien,673,France,Male,65,0,0,1,1,1,85733.33,0 -3982,15575676,Chung,638,France,Male,24,1,0,2,0,1,162597.15,0 -3983,15627665,Sung,614,France,Male,46,4,0,1,1,0,74379.57,1 -3984,15814092,Wang,626,France,Female,44,2,0,1,0,1,173117.22,1 -3985,15695225,Sun,834,Spain,Male,38,8,0,2,1,1,66485.26,0 -3986,15615091,Maitland,691,France,Male,24,6,0,2,1,1,92811.2,0 -3987,15794345,Ma,706,Spain,Male,38,8,0,2,0,1,46635.11,0 -3988,15726484,Pollard,633,France,Male,37,7,141546.35,1,1,1,124830.11,0 -3989,15650442,Hsieh,644,Germany,Female,32,8,141528.88,1,1,1,167087.34,1 -3990,15714256,Gerasimov,666,France,Male,30,7,109805.3,1,0,1,163625.56,0 -3991,15778752,Johnson,708,France,Male,32,10,86614.06,2,1,1,172129.26,0 -3992,15601659,Fiorentino,496,Germany,Female,59,7,91680.1,2,1,0,163141.18,1 -3993,15602811,Chioke,730,Germany,Male,38,0,38848.19,2,0,0,94003.11,0 -3994,15779414,Rossi,696,Spain,Male,40,3,153639.11,1,1,1,138351.68,0 -3995,15763097,Siciliano,809,Spain,Male,80,8,0,2,0,1,34164.05,0 -3996,15633666,Efremov,701,Spain,Female,33,7,123870.07,1,1,0,97794.71,0 -3997,15718789,Brigstocke,604,France,Male,30,5,0,2,1,0,75786.55,0 -3998,15690620,Olisaemeka,665,France,Male,39,10,46323.57,1,1,0,136812.02,0 -3999,15737071,Tang,639,France,Female,60,5,162039.78,1,1,1,84361.72,1 -4000,15665062,Lucchese,696,France,Male,19,1,110928.51,1,1,1,2766.63,0 -4001,15600692,West,520,France,Male,38,5,0,2,1,0,163185.76,0 -4002,15792064,Pai,545,Germany,Male,53,5,114421.55,1,1,0,180598.28,1 -4003,15811486,Tang,634,Germany,Female,29,8,130036.21,2,0,1,69849.55,0 -4004,15626141,Fedorov,750,France,Female,26,1,151510.17,2,1,1,19921.72,0 -4005,15738546,Gboliwe,530,Spain,Female,41,4,0,2,0,1,147606.71,0 -4006,15677052,Ko,589,France,Female,59,2,0,2,1,1,126160.24,1 -4007,15656454,Le Gallienne,654,France,Male,37,6,83568.55,1,1,0,47046.72,0 -4008,15645496,Seleznyova,648,France,Female,43,7,139972.18,1,1,0,143668.58,0 -4009,15612505,Joseph,835,Spain,Male,45,3,100212.13,1,1,0,152577.62,0 -4010,15708513,Bevan,446,France,Female,39,1,90217.07,1,1,0,191350.48,0 -4011,15685654,Allan,514,Spain,Male,66,9,0,2,1,1,14234.31,0 -4012,15732307,Lavrentiev,694,Germany,Male,33,4,124067.32,1,1,1,77906.87,0 -4013,15726814,Walton,554,Spain,Male,46,4,0,2,0,1,57320.92,0 -4014,15653776,Salier,720,Germany,Female,57,1,162082.31,4,0,0,27145.73,1 -4015,15597914,Evdokimov,641,Germany,Female,51,2,117306.69,4,1,1,26912.72,1 -4016,15631603,Ponomaryova,813,France,Male,32,1,122889.88,1,1,1,26476.18,0 -4017,15789753,Millar,480,France,Male,40,6,148790.61,1,0,1,79329.7,0 -4018,15678034,Grosse,811,France,Male,46,9,180226.24,1,1,0,13464.64,1 -4019,15690209,Hsiao,715,Germany,Female,32,3,104857.19,2,1,0,114149.8,0 -4020,15592091,Belbin,620,Spain,Male,31,2,166833.86,2,1,1,135171.6,0 -4021,15647453,Ifeajuna,721,France,Male,42,4,102936.72,1,0,0,1187.88,0 -4022,15697100,Wright,772,Germany,Female,48,6,108736.52,1,1,0,184564.67,1 -4023,15811290,Komarova,680,Germany,Male,44,0,129974.79,2,1,1,33391.38,0 -4024,15629187,Titheradge,535,France,Male,38,8,85982.07,1,1,0,9238.35,0 -4025,15758073,Dellucci,655,France,Female,20,7,134397.61,1,0,0,28029.54,0 -4026,15640769,Hobbs,660,France,Male,63,8,137841.53,1,1,1,42790.29,0 -4027,15606641,Beggs,762,Germany,Male,56,10,100260.88,3,1,1,77142.42,1 -4028,15718280,Luffman,662,Germany,Male,39,5,139822.11,2,1,1,146219.9,0 -4029,15764335,Caldwell,463,Germany,Female,41,8,123151.51,2,1,0,70127.93,0 -4030,15634218,Mancini,501,Germany,Male,27,4,95331.83,2,1,0,132104.76,0 -4031,15808760,Evseev,603,Spain,Female,42,6,0,1,1,1,90437.87,0 -4032,15648461,Hs?eh,688,Spain,Male,37,7,138162.41,2,1,1,113926.31,0 -4033,15593555,Chinedum,430,France,Male,38,9,0,2,1,1,12050.77,0 -4034,15569079,Hagins,632,Germany,Male,48,6,126066.26,1,1,0,64345.61,1 -4035,15800736,Kirwan,601,Spain,Female,42,4,96763.89,1,1,1,199242.65,0 -4036,15792607,Little,769,France,Female,38,2,0,2,0,0,75578.67,0 -4037,15640034,Milligan,551,France,Male,42,2,139561.46,1,1,0,43435.43,1 -4038,15807563,Ch'iu,841,France,Female,52,5,0,1,0,0,183239.71,1 -4039,15684461,McKay,469,Spain,Female,31,6,0,1,1,0,146213.75,1 -4040,15580134,Crawford,479,Spain,Male,27,2,172463.45,1,1,1,40315.27,0 -4041,15679075,Onyemere,701,France,Male,37,8,107798.85,1,1,0,16966.73,0 -4042,15742504,Azuka,593,France,Male,36,2,70181.48,2,1,0,80608.12,0 -4043,15567328,Ch'en,738,Spain,Male,38,5,177997.07,1,0,1,19233.41,0 -4044,15698294,Royster,635,Spain,Male,31,1,0,2,1,0,135382.23,0 -4045,15607142,Parkin,658,France,Male,32,8,0,1,1,1,80410.68,0 -4046,15738516,Kozlova,687,Spain,Female,36,5,0,1,1,0,17696.22,0 -4047,15806403,Hu,650,France,Male,37,9,0,2,1,0,17974.08,0 -4048,15656707,Ma,720,Spain,Male,21,2,123200.78,1,1,1,180712.28,0 -4049,15653715,Coates,602,France,Female,63,7,0,2,1,1,56323.21,0 -4050,15806184,Burns,618,Spain,Male,33,4,0,2,1,1,77550.18,0 -4051,15585734,Gouger,803,Germany,Male,41,9,137742.9,2,1,1,166957.82,0 -4052,15725639,Ignatyev,793,France,Female,63,9,116270.72,1,1,1,184243.25,0 -4053,15618401,Douglas,616,Germany,Male,41,10,113220.2,2,1,1,114072.91,0 -4054,15785385,Fiorentino,550,Spain,Male,51,5,0,2,1,0,153917.41,0 -4055,15734762,Ignatiev,602,France,Female,56,3,115895.22,3,1,0,4176.17,1 -4056,15767129,Munz,452,France,Female,60,6,121730.49,1,1,1,142963.29,0 -4057,15797204,Paling,655,Spain,Female,28,3,113811.85,2,0,1,76844.23,0 -4058,15769272,Clark,510,France,Female,26,6,136214.08,1,0,0,159742.33,0 -4059,15771966,Akobundu,557,France,Male,39,8,146200.01,1,1,0,177944.64,0 -4060,15691952,Fanucci,676,France,Male,37,10,106242.67,1,1,1,166678.28,0 -4061,15593250,Hsiao,640,France,Female,29,4,0,2,1,0,44904.26,0 -4062,15605333,Clancy,529,Spain,Male,31,6,0,1,1,0,10625.91,0 -4063,15800083,Macdonald,559,France,Male,45,8,24043.45,1,0,1,169781.45,1 -4064,15575691,Palerma,689,France,Female,58,5,0,2,0,1,49848.86,0 -4065,15689886,Holden,626,Germany,Male,39,10,132287.92,3,1,1,51467.92,1 -4066,15809838,Moore,697,Spain,Male,30,1,0,2,0,0,735.79,0 -4067,15736154,Gallo,823,France,Female,44,1,0,2,0,1,182495.7,0 -4068,15767391,Otutodilinna,565,Germany,Female,32,4,90322.99,2,0,1,118740.37,0 -4069,15704910,Rios,631,Spain,Male,23,3,0,2,1,0,13813.24,0 -4070,15656613,McGregor,646,France,Female,34,3,131283.11,1,0,0,130500.65,0 -4071,15611551,Hill,676,Spain,Male,48,1,131659.59,2,0,1,14152.15,0 -4072,15732430,H?,850,Spain,Female,54,4,120952.74,1,1,0,66963.15,0 -4073,15741865,Ferrari,810,France,Female,38,9,153166.17,1,1,1,93261.69,0 -4074,15634143,Onyemauchechi,581,Spain,Male,30,0,53291.86,1,0,0,196582.28,0 -4075,15609676,Nkemakonam,718,France,Female,35,2,167924.95,1,1,0,43024.64,0 -4076,15761600,White,713,France,Male,43,5,86394.14,1,1,1,130001.13,0 -4077,15676404,Kirillov,672,France,Female,50,1,0,1,1,0,12106.82,1 -4078,15659236,Iadanza,781,Spain,Male,33,3,0,2,1,1,42556.33,0 -4079,15690440,Stiles,656,Spain,Male,47,1,0,2,1,1,197961.93,0 -4080,15694601,Ankudinov,583,France,Female,31,4,158978.79,1,1,0,12538.92,0 -4081,15812262,Gaffney,808,Germany,Female,37,2,100431.84,1,1,0,35140.49,1 -4082,15762821,Udinese,721,Spain,Male,33,5,0,2,0,1,117626.9,0 -4083,15669301,Romani,778,Germany,Female,29,6,150358.97,1,1,0,62454.01,1 -4084,15672640,Kambinachi,850,Spain,Female,45,4,114347.85,2,1,1,109089.04,0 -4085,15750458,Hawkins,693,France,Female,39,4,0,2,0,1,142331.39,0 -4086,15627251,Tsui,520,France,Male,34,4,134007.9,1,1,1,193209.11,0 -4087,15764294,Ifeatu,759,Germany,Male,31,4,98899.91,1,1,1,47832.82,0 -4088,15659962,McIntosh,637,France,Male,60,3,0,2,1,1,70174.03,0 -4089,15788536,Armit,755,Germany,Male,40,2,137430.82,2,0,0,176768.59,0 -4090,15596979,Fang,662,France,Female,47,6,0,2,1,1,129392.75,0 -4091,15681220,Chou,503,France,Female,37,8,0,2,1,1,97893.32,0 -4092,15635097,Okeke,599,Germany,Male,39,2,188976.89,2,0,1,176142.09,0 -4093,15780779,Ramsbotham,583,Spain,Female,40,4,0,2,1,0,114093.73,0 -4094,15798470,Scannell,764,Spain,Female,48,1,75990.97,1,1,0,158323.81,1 -4095,15760880,Edman,513,France,Male,29,10,0,2,0,1,25514.77,0 -4096,15616929,De Luca,730,Spain,Male,62,5,112181.08,1,0,1,61513.87,0 -4097,15758775,Vasilyeva,820,Spain,Male,34,10,97208.46,1,1,1,59553.34,0 -4098,15663386,Tuan,597,Spain,Female,26,7,0,2,1,0,110253.2,0 -4099,15621267,Ejimofor,637,France,Male,32,5,0,1,0,0,148769.08,0 -4100,15720509,Hs?,696,France,Male,34,9,150856.79,1,0,1,8236.78,0 -4101,15693322,Shaver,635,Germany,Female,37,9,146748.07,1,0,1,11407.58,0 -4102,15589544,Wallis,673,Spain,Female,57,4,0,2,1,1,49684.09,0 -4103,15772030,Coupp,662,Spain,Male,33,3,0,2,0,1,68064.83,0 -4104,15693337,Perry,683,Spain,Male,41,0,148863.17,1,1,1,163911.32,0 -4105,15676571,Bezrukova,850,France,Male,55,6,0,1,1,0,944.41,1 -4106,15701392,Lucciano,815,Spain,Male,28,6,0,2,0,1,185547.71,0 -4107,15741092,Ingram,671,Spain,Male,34,10,153360.02,1,1,0,140509.86,0 -4108,15643865,Lo Duca,601,France,Female,40,3,92055.36,1,0,1,164652.02,1 -4109,15769389,Wan,709,Germany,Female,39,9,124723.92,1,1,0,73641.86,0 -4110,15807768,Cohn,702,Germany,Male,28,1,103033.83,1,1,1,40321.87,0 -4111,15801630,Yen,558,France,Male,40,6,0,2,1,0,173844.89,0 -4112,15705034,Peng,691,Spain,Male,40,1,0,2,1,1,145613.17,0 -4113,15763107,Little,700,France,Female,30,9,0,1,1,1,174971.64,0 -4114,15667085,Meng,667,France,Male,33,4,0,2,1,1,131834.75,0 -4115,15647008,Adams,624,Germany,Male,54,3,116726.22,1,1,0,110498.1,1 -4116,15584505,Hill,580,France,Female,23,5,113923.81,2,0,0,196241.43,0 -4117,15748068,Boyle,571,Spain,Female,31,3,0,2,1,1,194667.92,0 -4118,15663964,Pagnotto,561,France,Male,37,5,0,2,1,0,83093.25,0 -4119,15782311,Feng,529,France,Male,28,9,0,2,1,1,52545.24,0 -4120,15588197,Endrizzi,670,France,Male,36,7,0,2,0,0,59571.5,0 -4121,15610105,Shen,666,Germany,Female,21,1,121827.43,2,1,1,99818.31,0 -4122,15606133,Lay,628,Spain,Male,42,7,0,2,0,1,172967.87,0 -4123,15599403,Wu,577,France,Male,60,10,125389.7,2,1,1,178616.73,0 -4124,15648225,Shephard,652,Spain,Female,38,1,103895.31,1,0,1,159649.44,0 -4125,15608406,Schmidt,678,France,Male,26,5,111128.04,1,1,0,60941.27,1 -4126,15633378,Davidson,692,Spain,Female,49,9,0,2,1,0,178342.63,0 -4127,15664759,Lamb,675,Spain,Male,32,10,0,2,1,0,191545.65,0 -4128,15625545,Hussey,712,Spain,Male,52,9,0,1,1,1,117977.45,1 -4129,15772148,Ferrari,639,Germany,Female,37,5,151242.48,1,0,1,49637.65,0 -4130,15810829,Macfarlan,618,France,Male,48,7,0,1,1,0,13921.82,1 -4131,15731669,Szabados,554,France,Male,39,2,129709.62,1,1,0,173197.12,0 -4132,15738634,Yuan,533,France,Male,47,9,83347.25,1,1,1,137696.25,0 -4133,15737571,Matveyev,540,Spain,Female,28,6,84121.04,1,0,1,80698.54,0 -4134,15667602,Cheng,704,Spain,Male,33,3,0,2,1,0,73018.74,0 -4135,15684147,Palerma,678,France,Male,43,5,102338.19,1,1,1,79649.62,0 -4136,15789874,Wang,712,France,Female,29,3,87375.78,2,0,0,166194.53,0 -4137,15757952,Teng,651,France,Male,44,2,0,3,1,0,102530.35,1 -4138,15698732,K'ung,789,Germany,Male,51,3,104677.09,1,1,0,74265.38,0 -4139,15714355,Sinclair,775,Germany,Male,32,8,121669.23,1,0,1,125898.39,0 -4140,15599090,McKelvey,564,Germany,Male,40,7,108407.34,1,1,1,83681.2,0 -4141,15762048,Yuan,841,Germany,Female,33,7,154969.79,2,1,1,99505.75,0 -4142,15790596,Moran,850,Spain,Male,39,0,141829.67,1,1,1,92748.16,0 -4143,15609623,McConnell,637,France,Female,63,5,0,1,1,0,28092.77,1 -4144,15711901,Iheatu,500,France,Male,45,2,109162.82,1,1,1,126145.08,0 -4145,15779809,Giordano,655,France,Male,44,8,87471.63,1,0,1,188593.98,0 -4146,15729018,Alexander,666,France,Female,33,2,147229.65,1,1,1,56410.17,0 -4147,15698246,Gordon,658,France,Female,24,2,0,2,1,1,84694.49,0 -4148,15712409,Tang,749,Germany,Male,66,6,182532.23,2,1,1,195429.92,0 -4149,15758306,T'an,654,France,Male,32,6,0,2,1,1,137898.57,0 -4150,15621435,Davies,623,France,Female,39,1,160903.2,1,0,0,78774.36,0 -4151,15566295,Sanders,761,France,Female,33,6,138053.79,2,1,0,148779.41,0 -4152,15569098,Winifred,627,France,Male,44,6,153548.12,1,0,0,35300.08,1 -4153,15662532,Holmes,757,Germany,Male,31,8,149085.9,2,1,1,197077.36,0 -4154,15664001,Riddle,695,Germany,Female,53,8,95231.91,1,0,0,70140.8,1 -4155,15703437,Chinedum,726,France,Male,34,3,0,2,1,0,196288.46,0 -4156,15708003,Aleksandrova,587,Spain,Male,41,8,85109.21,1,1,0,1557.82,0 -4157,15599452,Conti,605,Germany,Female,43,8,125338.8,2,1,0,23970.13,0 -4158,15719793,Watson,850,Spain,Male,62,5,0,2,1,1,180243.56,0 -4159,15771580,Davison,850,France,Female,38,0,106831.69,1,0,1,148977.72,0 -4160,15732268,Cook,751,France,Male,29,3,159597.45,1,1,0,39934.41,0 -4161,15722350,Udinesi,627,Germany,Female,37,7,147361.57,1,1,1,133031.96,0 -4162,15611371,Siciliani,736,France,Male,43,4,176134.54,1,1,1,52856.88,0 -4163,15673584,Bell,652,France,Female,74,5,0,2,1,1,937.15,0 -4164,15636396,Jackson,627,France,Female,35,7,0,2,0,1,193022.44,0 -4165,15706170,Onyemere,636,France,Male,34,1,84055.43,1,0,0,37490.84,0 -4166,15725478,McClemans,775,France,Male,60,7,0,2,1,1,111558.7,0 -4167,15654562,Ma,850,Spain,Female,45,5,174088.3,4,1,0,5669.31,1 -4168,15737509,Morrison,850,Spain,Male,34,8,199229.14,1,0,0,68106.29,0 -4169,15690796,Chambers,516,France,Male,37,8,0,1,1,0,101834.58,0 -4170,15716728,Basedow,513,Spain,Female,42,10,0,2,0,1,73151.25,0 -4171,15605665,Nwora,673,Germany,Female,69,3,78833.15,2,1,1,37196.15,0 -4172,15748481,Howey,564,France,Female,27,6,0,1,0,0,7819.76,0 -4173,15757777,Pai,636,France,Female,35,2,0,2,1,1,23129.46,0 -4174,15747808,Ni,712,France,Male,29,3,102540.61,1,1,1,189680.79,0 -4175,15810593,Forbes,568,France,Male,51,4,0,3,1,1,66586.56,0 -4176,15693376,Baryshnikov,741,Spain,Male,43,0,0,2,1,1,2920.63,1 -4177,15579808,Kramer,754,Germany,Female,39,8,129401.87,1,1,1,87684.93,0 -4178,15598275,Sochima,709,France,Female,32,7,0,2,1,1,199418.02,0 -4179,15737080,Marchesi,510,France,Female,32,1,0,2,0,1,28515.17,0 -4180,15668580,Todd,716,Spain,Male,33,2,0,2,1,1,92916.53,0 -4181,15569438,Mai,607,Germany,Male,36,10,106702.94,2,0,0,198313.69,0 -4182,15675842,Pinto,656,Spain,Male,26,4,139584.57,1,1,0,36308.93,0 -4183,15577587,Reynolds,550,Germany,Male,52,5,121016.23,1,1,1,41730.37,1 -4184,15625592,Sal,486,France,Male,26,2,0,2,1,1,31399.4,0 -4185,15635141,Miller,598,Germany,Male,59,8,118210.42,2,0,0,60192.14,1 -4186,15642570,Scott,675,Spain,Male,35,8,0,2,1,0,29062.25,0 -4187,15702175,Herrin,755,France,Female,29,4,148654.84,2,1,1,28805.09,0 -4188,15677785,Stevenson,656,Spain,Male,32,5,136963.12,1,1,0,133814.28,0 -4189,15786153,McKenzie,644,Germany,Male,47,9,137774.11,2,1,0,151902.78,0 -4190,15759499,Gardiner,598,France,Female,32,4,111156.52,1,1,1,167376.26,0 -4191,15659568,Atkinson,850,Spain,Female,31,3,121237.65,1,1,1,31022.56,0 -4192,15715597,Onyemauchechi,679,France,Male,36,1,97234.58,1,1,0,188997.08,0 -4193,15610147,Ross,632,France,Male,60,2,0,2,0,1,2085.32,0 -4194,15802362,Newland,550,Spain,Male,45,0,0,2,0,1,70399.71,0 -4195,15660524,Hu,572,Germany,Female,54,9,97382.53,1,1,1,195771.95,0 -4196,15747168,Sanders,626,Germany,Female,47,2,103108.8,1,0,1,166475.44,1 -4197,15796910,Tsui,625,Spain,Female,57,7,0,1,0,0,84106.17,1 -4198,15707674,Marino,515,France,Female,58,2,131852.81,1,1,0,81436.68,1 -4199,15565706,Akobundu,612,Spain,Male,35,1,0,1,1,1,83256.26,1 -4200,15587596,Morrison,628,Spain,Female,39,8,107553.33,1,1,0,117523.41,0 -4201,15751943,Mai,529,Spain,Female,43,5,0,2,0,0,79476.63,0 -4202,15621227,Hs?eh,668,Germany,Female,46,7,161806.09,1,1,1,173052.19,0 -4203,15757588,Wright,526,France,Male,30,9,0,2,0,0,100995.68,0 -4204,15640922,Demaine,791,France,Female,52,7,0,1,1,1,122782.5,0 -4205,15567557,Chien,573,France,Male,27,2,128243.03,1,1,1,11631.34,0 -4206,15670103,Dickinson,565,France,Female,38,5,126645.13,1,1,1,168303.55,0 -4207,15720929,Kazantseva,604,France,Female,47,8,62094.71,3,0,0,9308.1,1 -4208,15732774,Marchesi,656,France,Male,37,7,112291.34,1,1,0,153157.97,0 -4209,15628558,Pan,447,France,Female,44,5,89188.83,1,1,1,75408.24,0 -4210,15729201,Harewood,682,France,Male,55,9,0,1,1,0,153356.8,1 -4211,15731117,Kao,437,Spain,Male,28,2,109161.25,1,1,0,152987.42,0 -4212,15615207,Yeh,792,Spain,Male,47,0,0,1,1,1,5557.88,1 -4213,15773512,Bischof,627,Spain,Female,25,4,0,1,1,1,194313.93,0 -4214,15572145,Ashton,767,France,Female,34,8,0,2,1,0,94767.77,0 -4215,15642710,Napolitani,686,France,Male,26,7,0,2,1,0,1540.89,0 -4216,15574213,Wilson,789,France,Female,53,1,158271.74,1,1,1,5036.39,1 -4217,15718852,Uren,794,France,Male,56,9,96951.21,1,1,1,71776.76,0 -4218,15583840,Okechukwu,587,Germany,Male,35,5,121863.61,1,1,1,23481.69,1 -4219,15782418,Ku,589,Germany,Female,19,9,83495.11,1,1,1,143022.31,1 -4220,15813504,Onyemachukwu,543,Germany,Female,25,1,146566.01,1,0,1,161407.48,0 -4221,15711314,Kao,589,Spain,Female,45,1,0,1,0,0,125939.22,1 -4222,15621064,Russell,701,Germany,Male,23,5,186101.18,2,1,1,76611.33,0 -4223,15627847,Woronoff,850,France,Male,40,6,0,1,1,0,136985.08,1 -4224,15588090,Ferri,726,Germany,Female,51,8,107494.86,2,1,0,140937.91,1 -4225,15735270,Ruggiero,767,Spain,Male,47,2,0,1,1,0,48161.18,1 -4226,15671804,Wilding,648,Spain,Male,36,8,146943.38,2,1,1,130041.45,0 -4227,15753215,Yashina,651,Spain,Female,36,8,0,2,1,0,91652.43,0 -4228,15789941,Yevseyev,633,France,Female,36,6,125130.28,1,0,0,125961.48,0 -4229,15691061,Rapuokwu,740,France,Female,37,9,0,2,1,1,73225.31,0 -4230,15808326,Maslov,592,France,Female,34,9,0,2,1,1,20460.2,0 -4231,15566660,Cole,670,France,Female,41,10,0,3,1,0,81602.02,0 -4232,15778947,Sullivan,628,France,Male,36,3,0,2,1,1,8742.91,0 -4233,15632977,Hsiao,745,France,Male,47,5,0,2,0,0,145789.71,0 -4234,15591747,Rossi,705,France,Male,32,3,0,2,0,0,129576.99,0 -4235,15567335,Allsop,559,France,Female,42,7,0,2,1,1,190040.29,0 -4236,15609299,Chamberlain,595,France,Male,29,6,150685.79,1,1,0,87771.06,0 -4237,15669945,Jackson,492,France,Male,35,4,141359.37,2,1,0,39519.53,0 -4238,15736271,Dumetochukwu,498,France,Female,29,9,0,1,1,0,190035.83,0 -4239,15710390,Uspensky,655,France,Female,39,6,94631.26,2,1,1,148948.52,0 -4240,15756481,Garcia,636,France,Female,39,3,118336.14,1,1,0,184691.77,0 -4241,15736730,Soto,634,France,Female,45,2,0,1,1,1,143458.31,0 -4242,15626040,McDonald,793,Spain,Male,63,0,0,2,0,1,27166.75,0 -4243,15746553,Castles,526,Germany,Male,50,5,124233.24,1,0,1,159456.87,1 -4244,15622518,Stephenson,768,France,Female,26,5,51116.26,1,1,1,70454.79,1 -4245,15684908,Davidson,540,Germany,Male,64,1,91869.69,1,0,1,95421,0 -4246,15569446,Tu,732,France,Female,34,8,122338.43,2,1,0,187985.85,0 -4247,15777504,Colbert,617,France,Female,30,8,0,1,1,1,92621.9,0 -4248,15677906,Owens,637,Spain,Female,54,5,0,1,0,1,150836.98,0 -4249,15703292,Chimezie,573,France,Male,26,8,86270.93,2,1,1,90177.3,0 -4250,15712938,Genovese,531,France,Male,44,3,0,2,1,1,34416.79,0 -4251,15631359,Daluchi,489,France,Female,38,5,117289.92,1,0,0,85231.88,0 -4252,15720847,Sheffield,601,France,Male,35,2,0,2,1,1,118983.18,0 -4253,15787830,Bailey,452,Germany,Male,33,7,153663.27,1,1,0,111868.23,0 -4254,15599869,Dyson,728,Spain,Female,29,1,0,1,1,1,83056.22,0 -4255,15592078,Davide,590,Germany,Female,27,8,123599.49,2,1,0,1676.92,0 -4256,15596228,Uwaezuoke,490,France,Male,29,4,0,2,1,0,32089.57,0 -4257,15578462,Hs?,596,Spain,Female,76,9,134208.25,1,1,1,13455.43,0 -4258,15756894,Onwuka,635,France,Male,29,1,0,1,0,1,24865.54,0 -4259,15796167,Flores,782,Germany,Male,35,7,98556.89,2,1,0,117644.36,0 -4260,15664808,Nicoll,790,Spain,Female,37,3,0,3,0,0,98897.32,0 -4261,15664555,Hughes,587,France,Male,40,2,0,4,0,1,106174.7,1 -4262,15607278,Romano,794,Spain,Female,46,8,134593.79,1,1,1,46386.37,0 -4263,15585222,Norman,515,France,Male,41,8,0,2,1,1,185054.14,0 -4264,15750299,Davison,746,Spain,Male,24,10,68781.82,1,0,1,47997.39,0 -4265,15761294,Manna,667,Germany,Female,56,8,137464.04,1,1,0,130846.79,1 -4266,15810454,Reed,709,France,Male,32,4,147307.91,1,0,1,40861.55,0 -4267,15673984,Daniels,536,France,Female,35,8,0,1,1,0,171840.24,1 -4268,15609319,Hunt,711,France,Female,41,3,145754.91,1,1,1,101455.07,0 -4269,15709941,Feng,753,France,Male,46,8,0,3,1,0,90747.94,1 -4270,15580252,Waters,748,France,Male,44,4,112610.77,1,0,1,2048.55,0 -4271,15741275,Yuan,623,France,Female,57,7,71481.79,2,1,1,84421.34,0 -4272,15707132,Yudin,465,France,Male,33,5,0,2,0,1,78698.09,0 -4273,15600708,Calabresi,640,Spain,Female,34,3,77826.8,1,1,1,168544.85,0 -4274,15804787,Onyemauchechukwu,562,France,Male,75,5,87140.85,1,1,1,39351.64,0 -4275,15690021,Martin,502,Germany,Female,42,0,132002.7,1,0,1,28204.98,1 -4276,15763895,Hung,536,France,Male,32,7,178011.5,2,1,0,22375.14,0 -4277,15623478,Maslova,670,Germany,Female,32,4,102954.68,2,0,1,134942.45,0 -4278,15797910,Zetticci,775,Germany,Male,51,2,123783.25,1,1,1,134901.57,0 -4279,15577751,Pisano,759,Germany,Male,30,4,101802.67,1,0,0,8693.8,0 -4280,15781777,Sutherland,604,France,Male,33,3,148659.48,1,0,0,42437.75,0 -4281,15740527,Lai,766,Germany,Female,62,7,142724.48,1,0,1,5893.23,1 -4282,15721251,Watson,554,Spain,Female,41,4,112152.89,1,0,1,36242.19,0 -4283,15602994,Gorbunov,487,France,Female,53,10,89550.85,1,0,1,90076.85,0 -4284,15750769,Padovano,725,France,Male,35,7,75915.75,1,1,0,150507.43,0 -4285,15740175,Raynor,732,Germany,Female,42,2,118889.66,2,0,0,87422.15,0 -4286,15679968,Ting,623,France,Male,40,5,118788.57,1,1,0,192867.4,0 -4287,15694404,Eberegbulam,781,France,Female,42,3,156555.54,1,1,1,175674.01,0 -4288,15657529,Chin,714,Germany,Male,53,1,99141.86,1,1,1,72496.05,1 -4289,15762882,Manna,577,Germany,Female,31,4,61211.18,1,1,1,145250.43,0 -4290,15642579,Chang,731,Spain,Female,37,1,128932.4,1,1,1,180712.52,0 -4291,15598884,Kent,650,Spain,Female,23,5,0,1,1,1,180622.43,0 -4292,15770185,Buckley,779,France,Male,32,10,80728.15,1,1,0,86306.75,0 -4293,15800287,Micco,706,Spain,Female,46,2,127660.46,2,1,0,150156.82,1 -4294,15665861,Avdeev,733,Spain,Male,44,3,106070.89,1,0,1,101617.43,0 -4295,15662203,Bremer,579,Germany,Female,42,3,137560.38,2,1,1,85424.34,0 -4296,15616454,Davidson,476,Germany,Female,34,8,111905.43,1,0,1,197221.81,1 -4297,15702788,Gadsdon,775,France,Male,40,9,126212.64,1,1,0,70196.57,0 -4298,15778149,Connolly,538,Spain,Male,68,9,0,2,1,0,110440.5,1 -4299,15680001,McDonald,602,France,Male,38,7,111835.94,2,1,0,124389.61,0 -4300,15711991,Chiawuotu,615,France,Male,30,8,0,2,0,0,3183.15,0 -4301,15633834,Milne,700,Germany,Female,28,3,99705.69,2,0,0,146723.72,0 -4302,15765266,Fleming,615,France,Male,32,1,0,2,0,0,2139.25,0 -4303,15791867,Hicks,544,Germany,Male,44,2,108895.93,1,0,0,69228.2,1 -4304,15675380,Logan,573,Spain,Male,56,3,154669.77,1,0,1,115462.27,1 -4305,15770576,Hammond,555,Spain,Male,50,7,128061,2,1,1,62375.1,0 -4306,15775294,Weber,692,France,Female,31,2,0,2,1,0,91829.17,1 -4307,15727059,Lettiere,476,France,Female,40,4,0,2,0,0,182547.04,0 -4308,15702499,Schnaars,770,Spain,Male,46,9,190678.02,1,1,1,14725.36,0 -4309,15611699,Tao,641,France,Female,40,7,0,1,1,0,126996.67,0 -4310,15654000,Algarin,705,France,Female,35,5,0,1,1,0,133991.11,1 -4311,15657881,Onyemere,784,France,Male,38,5,136712.91,1,0,1,169920.92,0 -4312,15719991,Korovina,727,Spain,Female,52,1,154733.97,1,1,0,80259.67,1 -4313,15720687,Chidubem,576,France,Female,41,4,112609.91,1,0,0,191035.18,1 -4314,15687079,King,646,Spain,Male,69,10,115462.44,1,1,0,40421.87,0 -4315,15582276,Greco,638,France,Male,34,5,133501.36,1,0,1,155643.04,0 -4316,15763980,Beneventi,632,Germany,Male,30,1,58668.02,1,1,1,78670.52,0 -4317,15720774,P'eng,850,Spain,Male,44,7,89118.26,1,1,0,104240.77,1 -4318,15592194,Metcalf,492,France,Female,28,9,0,2,1,0,95957.09,0 -4319,15803685,Greco,673,Germany,Female,77,10,76510.52,2,0,1,59595.66,0 -4320,15759456,Lupton,609,Spain,Male,34,7,140694.78,2,1,0,46266.63,0 -4321,15611544,Ibeamaka,701,Germany,Male,36,7,95448.32,2,1,0,189085.07,0 -4322,15794257,Hsiung,651,France,Male,34,4,91562.99,1,1,1,123954.15,0 -4323,15681697,Rueda,508,France,Male,31,8,72541.48,1,1,0,129803.08,0 -4324,15579566,Li Fonti,616,Spain,Female,43,3,120867.18,1,1,0,18761.92,1 -4325,15577970,Alexeeva,489,France,Male,34,5,0,1,0,0,43540.59,0 -4326,15727489,Madueke,567,Spain,Female,45,1,157320.51,1,1,0,62193.92,0 -4327,15764284,Torres,714,Spain,Male,27,3,0,3,1,1,129130.09,0 -4328,15581811,Chukwubuikem,678,Germany,Female,30,1,139676.95,2,0,1,16146,0 -4329,15622527,Holloway,581,France,Female,55,6,0,1,1,1,22442.13,0 -4330,15753362,Evdokimov,748,Spain,Male,60,3,0,2,1,1,78194.37,0 -4331,15666652,Anayolisa,781,France,Female,19,3,0,2,1,1,124297.32,0 -4332,15789714,Semmens,691,Spain,Male,21,3,103000.94,1,1,1,104648.58,0 -4333,15771543,Tu,507,Germany,Male,31,2,134237.07,1,1,1,166423.66,1 -4334,15748327,Anderson,724,Germany,Male,34,6,118235.7,2,0,0,157137.23,0 -4335,15754649,Fang,705,Spain,Female,57,3,0,2,1,1,34134.14,0 -4336,15810460,Fanucci,708,Spain,Female,64,5,0,3,0,1,112520.07,1 -4337,15771742,Boyle,580,Germany,Male,38,9,115442.19,2,1,0,128481.5,1 -4338,15642160,Milanesi,850,France,Male,38,5,0,2,1,0,16491.64,0 -4339,15798439,Davidson,714,Spain,Male,25,2,0,1,1,1,132979.43,0 -4340,15605293,McKay,559,France,Female,43,1,0,2,1,1,196645.87,0 -4341,15692631,Bogdanova,577,Spain,Female,44,8,115557,1,0,1,127506.76,0 -4342,15665376,Lavrentiev,647,Germany,Female,35,3,166518.63,2,1,0,147930.46,0 -4343,15772412,Corser,554,Spain,Male,30,6,135370.12,1,1,1,179689.05,1 -4344,15654577,Alexeeva,549,Germany,Male,54,5,92877.33,1,1,0,2619.64,1 -4345,15585427,Madueke,528,France,Female,26,10,102073.67,2,0,0,166799.93,0 -4346,15584536,Barber,720,Germany,Male,46,3,97042.6,1,1,1,133516.51,1 -4347,15585853,McCardle,743,Spain,Male,41,7,0,1,1,0,163736.09,1 -4348,15645271,Radcliffe-Brown,615,Germany,Male,24,8,108528.07,2,0,0,179488.41,1 -4349,15579387,Ni,635,Germany,Female,44,2,79064.85,2,0,1,113291.75,0 -4350,15623107,Chukwumaobim,686,Spain,Male,45,3,74274.87,3,1,0,64907.48,1 -4351,15754072,Dennis,840,Spain,Female,36,6,0,2,1,0,141364.27,0 -4352,15666163,Hayward,695,France,Male,43,1,100421.1,1,1,1,101141.28,0 -4353,15765192,Jones,564,France,Male,26,7,84006.88,2,0,0,183490.99,0 -4354,15804822,L?,805,France,Female,31,4,0,2,1,0,4798.12,0 -4355,15612893,Nelson,558,Spain,Male,45,4,0,1,1,0,131807.14,0 -4356,15593636,Cardus,657,France,Female,39,4,80293.81,1,1,0,97192.76,0 -4357,15693326,Whitehouse,641,France,Female,42,7,125437.14,2,0,0,164128.58,0 -4358,15809901,Johnstone,755,France,Male,36,8,0,2,1,0,176809.87,0 -4359,15759751,Tsui,483,France,Male,48,1,0,2,1,1,110059.38,0 -4360,15605425,Chia,545,Germany,Female,44,2,127536.44,1,1,0,108398.63,0 -4361,15801934,Su,678,France,Male,66,8,0,2,1,1,47117.03,0 -4362,15592000,Calabresi,781,Germany,Female,48,9,82794.18,1,1,0,124720.68,1 -4363,15618695,Ts'ui,571,Spain,Female,22,3,108117.1,1,0,1,53328.7,0 -4364,15637110,McCulloch,634,Spain,Female,35,10,0,1,1,0,82634.41,0 -4365,15727408,Koo,523,Germany,Male,27,8,61688.61,2,1,0,147059.16,0 -4366,15716328,Miller,501,France,Female,40,2,0,2,0,0,141946.92,0 -4367,15669060,Woolnough,662,France,Male,74,6,0,2,1,0,123583.85,0 -4368,15675854,Douglas,573,Spain,Male,50,0,159304.07,1,0,1,155915.24,1 -4369,15621116,Fang,648,Germany,Male,33,5,138664.24,1,1,0,29076.27,0 -4370,15781495,Munro,662,France,Female,22,2,126362.57,2,1,1,97382.8,0 -4371,15740470,Vinogradov,725,France,Male,39,4,160652.45,2,1,0,57643.55,0 -4372,15714391,Lai,563,France,Female,35,2,183572.84,1,1,1,66006.75,1 -4373,15730137,Udegbulam,628,France,Male,31,0,88421.81,1,0,0,72350.47,0 -4374,15596455,Mao,546,Spain,Female,45,2,0,1,0,0,197789.83,1 -4375,15717290,Onyekaozulu,688,Germany,Male,41,2,112871.19,2,0,1,65520.74,0 -4376,15616555,Fu,850,Germany,Male,41,8,60880.68,1,1,0,31825.84,0 -4377,15659820,Cross,614,France,Female,34,5,0,2,1,0,185561.89,0 -4378,15696301,Snider,719,France,Female,37,9,101455.7,1,1,0,25803.59,1 -4379,15771087,Harrison,757,France,Female,71,0,88084.13,2,1,1,154337.47,0 -4380,15808831,Dale,669,France,Male,29,7,0,2,1,1,138145.62,0 -4381,15812241,Udinese,438,Germany,Male,59,7,127197.14,1,1,0,51565.98,1 -4382,15680370,DeRose,492,France,Male,39,7,0,2,0,1,71323.23,0 -4383,15780561,Hay,622,France,Female,39,9,83456.79,2,0,0,38882.34,0 -4384,15800784,Bruce,645,France,Male,42,4,98298.18,1,1,1,676.06,0 -4385,15715796,Romani,728,France,Male,37,0,0,2,1,1,72203.8,0 -4386,15605375,Tseng,651,France,Male,35,2,86911.8,1,1,0,174094.24,0 -4387,15621520,Tang,783,Germany,Female,42,2,139707.28,1,1,0,2150.22,0 -4388,15665460,Isayeva,732,Spain,Female,67,1,0,2,1,1,177783.04,0 -4389,15801152,Hill,553,Spain,Female,39,1,142876.98,2,1,0,44363.42,0 -4390,15756425,Barnes,660,France,Male,30,7,146301.31,1,0,0,96847.91,0 -4391,15674328,Moreno,670,France,Female,40,3,47364.45,1,1,1,148579.43,1 -4392,15742404,McGregor,718,France,Male,38,7,0,2,1,0,38308.34,0 -4393,15757140,Genovese,787,France,Male,51,0,58137.08,1,0,1,142538.31,0 -4394,15570051,Gill,775,Germany,Female,38,6,179886.41,2,0,0,153122.58,0 -4395,15669175,Ts'ai,479,Germany,Male,24,6,107637.97,2,0,1,169505.83,0 -4396,15790324,Green,660,France,Female,20,6,167685.56,1,1,0,57929.9,0 -4397,15691119,Martin,721,Germany,Male,68,4,136525.99,1,0,0,175399.14,0 -4398,15743478,Johnson,659,Germany,Male,39,8,52106.33,2,1,1,107964.36,0 -4399,15707007,Onio,743,France,Female,39,8,0,1,1,0,94263.44,0 -4400,15572547,Vaguine,670,France,Female,45,9,104930.38,1,1,0,155921.81,1 -4401,15567063,Manna,766,Germany,Female,34,6,106434.94,1,0,1,137995.66,1 -4402,15689633,Toomey,845,Spain,Female,38,2,112803.92,1,1,0,179631.85,0 -4403,15720637,Bell,710,Germany,Female,46,10,120530.34,1,1,0,166586.99,1 -4404,15616859,Bonwick,602,Germany,Female,43,2,113641.49,4,1,0,115116.35,1 -4405,15766166,Folliero,604,Spain,Male,43,2,145081.72,1,1,1,23881.62,0 -4406,15617655,Holt,564,Spain,Female,35,9,0,2,1,1,105837.38,0 -4407,15623450,Brown,637,Germany,Female,27,7,135842.89,1,1,1,101418.05,0 -4408,15796612,Ch'ang,527,France,Female,31,1,112203.25,1,1,0,182266.01,0 -4409,15795963,Fiorentini,687,France,Male,34,7,129895.19,1,0,1,28698.17,0 -4410,15781598,Middleton,756,Germany,Male,41,6,149049.92,1,0,1,50422.36,1 -4411,15691871,Millar,503,Germany,Male,42,9,153279.39,1,1,1,151336.96,0 -4412,15740345,Osborne,657,Spain,Male,42,5,41473.33,1,1,0,112979.6,1 -4413,15662626,Feng,666,France,Female,40,2,0,2,0,0,36371.27,0 -4414,15596575,Vale,615,Germany,Male,39,5,113193.51,2,1,1,52166.25,0 -4415,15657321,Arkwookerum,712,Germany,Male,27,8,113174.21,2,1,0,147261.58,0 -4416,15575955,Lujan,764,France,Female,24,0,0,2,1,0,88724.49,0 -4417,15743893,Alexeyeva,471,France,Male,42,3,164951.56,1,1,0,190531.77,0 -4418,15697270,Gannon,608,Spain,Male,27,4,153325.1,1,1,1,199953.33,0 -4419,15644356,Prokhorova,682,Spain,Female,47,10,134032.01,1,1,0,144290.97,0 -4420,15677586,Romero,587,Germany,Female,32,3,125445.04,2,1,1,130514.78,0 -4421,15571261,Toscani,714,Germany,Female,35,6,126077.43,2,1,1,53954.24,0 -4422,15698758,Onwuamaegbu,630,Spain,Female,31,1,0,2,1,1,169802.73,0 -4423,15787014,King,648,Germany,Female,28,8,90371.09,1,1,1,146851.73,0 -4424,15739857,Trentino,785,France,Female,40,3,0,2,1,1,96832.82,0 -4425,15774630,Peacock,601,Germany,Female,47,1,142802.02,1,1,1,57553.02,0 -4426,15805523,Nnaife,717,France,Female,28,1,90537.16,1,0,1,74800.99,0 -4427,15749557,Chao,707,France,Female,44,6,0,2,1,1,192542.17,0 -4428,15681180,Barese,771,France,Female,23,7,156123.73,1,1,0,72990.62,0 -4429,15742028,Udegbulam,602,France,Female,35,5,0,2,1,0,31050.02,0 -4430,15686463,Fu,626,France,Male,38,7,141074.59,1,1,0,52795.56,1 -4431,15654379,Onwuatuegwu,588,Spain,Male,59,4,0,2,1,1,27435.41,0 -4432,15783629,Degtyaryov,616,Germany,Female,42,6,117899.95,2,0,0,150266.81,0 -4433,15751193,Nnaemeka,621,Spain,Male,33,4,0,2,1,1,40299.23,0 -4434,15724099,Udinese,674,France,Male,26,6,166257.96,1,1,1,149369.41,0 -4435,15568429,Mitchell,633,Spain,Female,46,3,0,2,1,0,120250.58,0 -4436,15648967,Ch'en,698,Germany,Female,64,1,169362.43,1,1,0,84760.32,1 -4437,15664498,Golovanov,508,France,Male,26,7,205962,1,1,0,156424.4,0 -4438,15779522,Efimov,736,France,Female,24,0,0,2,1,0,109355.73,1 -4439,15583850,Davidson,672,Germany,Male,68,0,126061.51,2,1,1,184936.77,0 -4440,15696539,Wade,613,France,Female,21,7,105627.95,1,1,1,36560.51,0 -4441,15760121,Maynard,712,France,Male,32,9,100606.02,1,1,0,165693.06,0 -4442,15628279,Murphy,624,France,Female,38,3,0,2,1,1,163666.85,0 -4443,15766163,Zotova,676,France,Male,38,1,0,2,0,1,35644.79,0 -4444,15566467,Hannah,683,Germany,Female,32,0,138171.1,2,1,1,188203.58,0 -4445,15639049,Cartagena,489,France,Female,31,7,139395.08,1,0,1,6120.84,0 -4446,15736413,Hall,739,France,Male,29,1,0,2,1,1,164484.78,0 -4447,15634815,Hunt,701,France,Female,37,3,0,2,1,1,164268.28,0 -4448,15716381,Greece,666,Germany,Female,50,7,109062.28,1,1,1,140136.1,1 -4449,15708162,Thomson,565,Germany,Female,40,1,89994.71,2,0,1,121084.27,0 -4450,15569364,Victor,666,France,Male,36,3,0,2,1,0,35156.54,0 -4451,15791191,Mitchell,633,France,Male,59,2,103996.74,1,1,1,103159.11,0 -4452,15621205,Olisaemeka,578,France,Male,34,4,175111.11,1,1,1,74858.3,0 -4453,15704788,Krawczyk,812,Spain,Female,49,8,66079.45,2,0,0,91556.57,1 -4454,15775756,Alexandrova,809,Germany,Male,33,8,148055.74,1,0,0,199203.21,0 -4455,15641312,Paterson,615,France,Male,36,6,0,1,1,1,27011.8,1 -4456,15782531,Chou,684,Spain,Female,31,8,0,2,1,0,188637.05,0 -4457,15724428,Abel,544,France,Male,40,8,0,2,1,0,61581.2,0 -4458,15743617,Chesnokova,713,Germany,Male,47,1,95994.98,1,1,0,197529.23,0 -4459,15585839,Niu,633,France,Male,37,2,0,2,1,0,182258.17,0 -4460,15658158,Sullivan,672,Germany,Female,23,10,110741.56,1,1,0,80778.5,0 -4461,15637678,Ma,661,France,Male,35,5,0,1,1,0,155394.52,0 -4462,15701809,Cavill,749,Spain,Female,28,3,0,1,1,0,3408.7,0 -4463,15676937,Nicholls,635,Spain,Female,32,8,0,2,1,1,19367.98,1 -4464,15778975,Nnonso,850,Germany,Female,70,1,96947.58,3,1,0,62282.99,1 -4465,15710375,Gibson,641,France,Male,41,6,0,2,1,0,65396.79,0 -4466,15579914,Garcia,633,Germany,Male,30,2,109786.82,2,1,1,139712.81,0 -4467,15595160,Renwick,413,Spain,Male,35,2,0,2,1,1,60972.84,0 -4468,15595391,Norris,538,France,Male,31,1,0,2,1,0,1375.46,0 -4469,15630363,Nkemakonam,437,France,Female,39,0,102721.49,1,0,0,22191.82,0 -4470,15692443,Piccio,612,Spain,Male,33,5,69478.57,1,1,0,8973.67,1 -4471,15593795,Linton,516,Germany,Female,53,1,156674.2,1,1,0,118502.34,1 -4472,15642824,Onyekaozulu,826,Spain,Female,56,8,174506.1,2,0,1,161802.82,1 -4473,15683524,Tobenna,660,Germany,Female,23,6,166070.48,2,0,0,90494.72,0 -4474,15713532,Wang,646,Germany,Female,29,4,105957.44,1,1,0,15470.91,0 -4475,15719827,O'Donnell,767,France,Male,36,3,0,1,0,0,65147.27,0 -4476,15578435,Langlands,640,France,Male,40,8,110340.68,1,1,1,157886.6,0 -4477,15723028,Smith,778,France,Male,33,1,0,2,1,0,85439.73,0 -4478,15595609,Sykes,679,Germany,Male,52,9,135870.01,2,0,0,54038.62,0 -4479,15622443,Marshall,549,France,Male,31,4,0,2,0,1,25684.85,0 -4480,15579112,Gibson,598,France,Male,47,2,0,2,1,1,186116.54,0 -4481,15648479,Stephenson,655,France,Female,45,0,0,2,1,0,166830.71,0 -4482,15659234,Y?,494,France,Male,30,3,85704.95,1,0,1,27886.06,0 -4483,15811970,Kang,653,France,Female,42,1,0,2,1,1,5768.32,0 -4484,15774192,Miller,539,Germany,Female,38,8,105435.74,1,0,0,80575.44,1 -4485,15595136,Kryukov,645,France,Female,37,1,0,2,1,1,68987.55,0 -4486,15630580,Y?,751,Germany,Male,34,9,108513.25,2,1,1,27097.82,0 -4487,15660646,Fanucci,528,France,Male,35,3,156687.1,1,1,0,199320.77,0 -4488,15614365,Lombardi,696,Germany,Male,31,3,150604.52,1,0,0,5566.6,0 -4489,15776128,Hs?,716,France,Female,44,6,155114.9,1,0,0,133871.83,0 -4490,15787035,Anderson,602,France,Female,35,8,0,2,1,1,152843.53,0 -4491,15792646,Trentino,647,Spain,Female,64,1,91216,1,1,1,41800.18,0 -4492,15726832,Donnelly,850,Germany,Male,61,3,141784.02,1,1,1,92053.75,0 -4493,15773260,Tsou,590,France,Female,32,0,127763.24,1,1,0,100717.54,0 -4494,15624437,Johnson,825,Spain,Female,32,1,0,2,1,1,42935.15,0 -4495,15717138,Watson,850,Spain,Male,31,6,82613.56,2,1,0,149170.92,0 -4496,15657317,Allan,789,France,Female,32,7,69423.52,1,1,0,107499.39,0 -4497,15626948,Butcher,701,France,Female,42,6,86167.82,1,1,0,153342.38,0 -4498,15758901,Henderson,713,Spain,Female,47,1,0,1,1,0,107825.08,1 -4499,15777759,Boucaut,570,France,Male,30,2,131406.56,1,1,1,47952.45,0 -4500,15773322,Obiajulu,536,Germany,Female,44,4,121898.82,1,0,0,131007.18,0 -4501,15697318,Ifeatu,771,Germany,Male,32,9,77487.2,1,0,0,33143.04,0 -4502,15678916,Kelly,512,France,Female,75,2,0,1,1,0,123304.62,0 -4503,15632118,Pirozzi,698,Spain,Male,45,5,164450.94,1,1,0,141970.02,1 -4504,15788118,Siciliano,656,France,Male,33,7,138705.02,2,1,0,37136.15,0 -4505,15788930,Silva,761,Spain,Male,37,7,132730.17,1,1,0,199293.01,0 -4506,15628583,Iweobiegbunam,709,France,Female,30,5,0,2,0,1,161388.22,0 -4507,15635177,Williamson,597,Spain,Female,66,3,0,1,1,1,70532.53,0 -4508,15587690,Madueke,592,France,Male,28,2,116498.22,1,1,0,144290.25,0 -4509,15627630,Chiagoziem,599,France,Female,41,1,0,2,1,0,96069.82,0 -4510,15610930,Kwemto,572,Germany,Female,35,1,139979.07,1,1,0,185662.84,0 -4511,15657747,Zito,611,Germany,Female,43,9,127216.31,2,0,1,17913.25,0 -4512,15568006,Ukaegbunam,634,France,Female,45,2,0,4,1,0,101039.53,1 -4513,15751748,Trevisani,666,France,Male,51,2,148222.65,1,0,0,156953.54,1 -4514,15722212,Edmondstone,696,France,Female,41,8,0,2,0,0,28276.83,0 -4515,15658670,Chien,669,France,Female,38,8,0,2,1,0,84049.16,0 -4516,15761654,Boni,726,Spain,Male,30,8,134152.29,1,1,1,147822.44,0 -4517,15812210,Yashina,497,Germany,Female,32,8,111537.23,4,1,1,9497.99,1 -4518,15787051,Georg,750,Spain,Female,39,7,119565.92,1,1,0,87067.73,0 -4519,15642991,Tung,850,Spain,Female,29,7,0,2,1,0,23237.25,0 -4520,15713769,Michelides,617,Spain,Male,38,7,0,1,1,1,27239.28,0 -4521,15605826,Korovina,652,Germany,Male,46,10,121063.8,3,1,0,151481.86,1 -4522,15648898,Chuang,560,Spain,Female,27,7,124995.98,1,1,1,114669.79,0 -4523,15705309,Yuriev,629,Spain,Male,39,5,0,2,0,0,116748.14,0 -4524,15734202,Chidimma,660,Germany,Female,52,4,86891.84,1,1,0,90877.76,0 -4525,15658852,Stevens,676,France,Male,38,8,0,2,1,1,133692.88,0 -4526,15612633,Kao,581,Spain,Male,43,9,78022.61,1,0,1,30662.91,0 -4527,15604818,Edmund la Touche,798,France,Male,34,9,154495.79,1,1,0,191395.88,0 -4528,15593900,Belousov,705,France,Male,38,1,189443.72,1,0,1,106648.58,0 -4529,15624995,McCane,714,Spain,Female,31,6,152926.6,1,1,1,50899.91,0 -4530,15570087,Parry-Okeden,664,France,Female,44,8,142989.69,1,1,1,115452.51,1 -4531,15802617,Hudson,697,Germany,Male,43,7,115371.94,2,1,0,64139.1,0 -4532,15656029,Marsden,609,France,Male,37,6,0,2,0,1,22030.72,0 -4533,15739194,Manfrin,548,Spain,Male,38,0,178056.54,2,1,0,38434.73,0 -4534,15607275,Ch'ang,850,Spain,Male,39,6,206014.94,2,0,1,42774.84,1 -4535,15629475,Clark,656,France,Male,41,2,0,2,1,0,158973.77,0 -4536,15635034,Aldrich,727,Germany,Male,37,9,101191.83,1,1,1,34551.35,1 -4537,15756333,Khan,642,France,Female,55,7,0,2,1,1,101515.76,0 -4538,15777436,Murray,710,Spain,Female,31,5,0,2,1,0,9561.73,0 -4539,15676835,Anayolisa,710,Spain,Male,33,1,0,2,1,0,168313.17,0 -4540,15574206,Shillito,718,France,Female,37,7,0,2,1,1,55100.09,0 -4541,15613017,McMillan,586,Germany,Male,32,1,149814.54,1,1,0,31830.06,0 -4542,15815131,Howells,617,Spain,Female,36,7,115617.24,1,1,1,71519.4,0 -4543,15585455,Stewart,630,France,Male,28,9,0,2,0,0,32599.35,0 -4544,15692929,Ikechukwu,791,Germany,Female,42,10,113657.41,2,0,1,139946.68,1 -4545,15758081,Repina,673,Spain,Male,39,8,138160,1,1,1,110468.51,0 -4546,15667476,Cox,477,Germany,Female,36,3,117700.86,1,0,0,74042,0 -4547,15738248,Lo,662,France,Female,37,5,0,2,1,0,151871.84,0 -4548,15672152,Grant,850,Germany,Male,37,9,122506.38,1,0,1,199693.84,1 -4549,15673372,Stevenson,635,France,Female,58,1,0,1,1,1,58907.08,1 -4550,15587611,Kauffmann,537,France,Male,59,9,0,2,0,0,103799.77,1 -4551,15803415,Samsonova,579,France,Female,39,3,166501.17,2,1,0,93835.64,0 -4552,15715673,Niu,651,Spain,Female,46,4,89743.05,1,1,0,156425.57,1 -4553,15655648,Bock,610,France,Female,25,2,0,2,1,0,123723.83,0 -4554,15763613,Barlow,581,France,Male,30,1,0,2,1,0,199464.08,0 -4555,15660385,Stevenson,592,France,Male,39,7,0,2,1,0,83084.33,0 -4556,15733261,Kung,688,Spain,Female,35,6,0,1,1,0,25488.43,1 -4557,15796231,Nwankwo,681,France,Female,18,1,98894.39,1,1,1,9596.4,0 -4558,15624866,Brewer,658,Germany,Male,37,3,168735.74,2,0,0,70370.24,0 -4559,15623730,Ch'iu,792,France,Male,34,1,0,1,0,1,86330.32,0 -4560,15668248,Quinn,528,Germany,Female,62,7,133201.17,1,0,0,168507.68,1 -4561,15694518,Kodilinyechukwu,624,Spain,Female,36,0,0,2,1,0,111605.9,0 -4562,15638028,Ifeanyichukwu,562,Germany,Male,31,4,127237.25,2,0,1,143317.42,0 -4563,15795895,Yermakova,678,Germany,Male,36,1,117864.85,2,1,0,27619.06,0 -4564,15694376,Sullivan,705,Germany,Female,64,3,153469.26,3,0,0,146573.66,1 -4565,15669204,Grant,650,Germany,Male,23,4,93911.3,2,1,0,69055.45,0 -4566,15773779,Jacka,593,Spain,Female,46,2,76597.79,1,1,1,54453.72,0 -4567,15580682,Tsai,652,France,Female,40,4,79927.36,2,1,1,33524.6,0 -4568,15768530,Emery,554,Spain,Female,27,4,0,2,1,1,135083.73,0 -4569,15672875,Piccio,584,Germany,Male,32,8,40172.91,1,1,1,137439.34,0 -4570,15617082,Sanders,516,France,Male,33,7,115195.58,1,1,1,11205.5,0 -4571,15760514,Sharp,789,Germany,Female,43,9,116644.29,2,1,1,60176.1,0 -4572,15761775,Myers,598,Germany,Male,20,8,180293.84,2,1,1,29552.7,0 -4573,15799964,Campbell,669,Germany,Female,30,7,139872.81,1,1,0,188795.85,0 -4574,15693906,Abbott,645,France,Female,24,3,34547.82,1,1,1,11638.17,0 -4575,15739514,Preston,659,France,Female,32,9,0,2,1,1,93155.75,0 -4576,15756926,Atherton,833,Germany,Male,29,1,96462.25,2,0,1,48986.18,0 -4577,15770984,Fanucci,697,Spain,Female,40,7,130334.35,2,0,1,116951.1,0 -4578,15703979,Evans,580,Germany,Male,39,3,119688.81,1,1,0,137041.26,0 -4579,15801821,Cookson,691,France,Male,38,1,0,2,0,0,44653.5,0 -4580,15711028,Nnachetam,534,France,Male,52,1,0,3,1,1,104035.41,1 -4581,15791842,Johnstone,478,France,Female,32,6,71187.24,1,1,1,110593.62,0 -4582,15746127,Hort,572,France,Female,47,2,0,2,1,0,36099.7,0 -4583,15663625,Johnson,501,France,Male,37,4,0,2,0,0,12470.3,0 -4584,15604891,Zaytseva,624,Spain,Female,38,8,0,2,1,0,95403.41,0 -4585,15589666,Sorokina,595,France,Female,39,9,136422.41,1,1,1,151757.81,0 -4586,15627881,Diehl,603,France,Male,30,8,0,2,1,1,47536.46,0 -4587,15664895,Onuchukwu,602,France,Female,25,0,0,2,1,1,101274.17,0 -4588,15676094,Osonduagwuike,500,France,Female,34,6,0,1,1,1,140268.45,0 -4589,15761720,Mead,422,France,Male,41,6,153238.88,1,1,0,11663.09,0 -4590,15611961,Stewart,615,France,Male,35,7,0,2,1,0,150784.29,0 -4591,15680167,Thomson,635,France,Female,78,6,47536.4,1,1,1,119400.08,0 -4592,15762543,Goliwe,711,France,Female,32,1,0,2,1,0,126188.42,0 -4593,15658475,Lori,834,France,Male,36,8,142882.49,1,1,0,89983.02,1 -4594,15779743,Onwuamaeze,633,France,Female,44,7,0,2,1,0,29761.29,0 -4595,15661532,Butusov,650,France,Female,31,1,160566.11,2,0,0,27073.81,0 -4596,15782360,Rogers,743,Germany,Male,65,2,131935.51,1,1,1,96399.67,1 -4597,15767908,Nicholson,567,France,Male,38,6,127678.8,2,0,0,45422.89,0 -4598,15677105,Rossi,706,Germany,Female,46,4,105214.58,1,1,0,108699.59,1 -4599,15641474,Hall,638,France,Male,46,9,139859.54,1,1,0,38967.29,0 -4600,15624451,Huddart,641,France,Female,38,3,0,2,1,0,116466.19,0 -4601,15577985,Chinomso,574,France,Female,34,5,112324.45,2,1,1,17993.43,0 -4602,15571666,Shaw,642,Germany,Male,30,8,134497.27,1,0,0,43250.54,0 -4603,15783691,Hargreaves,722,Spain,Female,35,1,120171.58,1,1,0,125240.8,0 -4604,15671172,Swain,623,France,Male,23,1,106012.2,2,0,1,191415.94,0 -4605,15731760,Butcher,681,France,Male,25,5,0,1,0,1,90860.97,0 -4606,15585599,Stone,530,France,Female,34,8,0,2,0,1,141872.52,0 -4607,15784958,Allan,797,France,Female,55,10,0,4,1,1,49418.87,1 -4608,15734524,Wang,653,France,Male,51,3,0,1,1,0,170426.65,1 -4609,15614103,Colombo,850,Germany,Male,42,8,119839.69,1,0,1,51016.02,1 -4610,15794895,McKay,581,Spain,Male,34,1,0,2,0,1,81175.25,0 -4611,15772381,Brient,589,Germany,Male,38,8,92219.21,1,1,0,99106.97,0 -4612,15710553,Yin,555,Germany,Male,48,3,142055.41,2,0,1,79134.78,0 -4613,15649292,Bellucci,748,France,Female,49,7,29602.08,1,0,0,163550.58,1 -4614,15792565,Duncan,745,France,Female,46,7,0,2,1,1,67769.94,0 -4615,15718245,Pirozzi,730,France,Male,34,1,0,2,1,1,126592.01,0 -4616,15703117,Findlay,565,France,Female,44,1,0,2,0,1,89602.81,0 -4617,15758136,King,778,France,Male,37,3,141803.77,1,0,1,179421.84,0 -4618,15799932,Iweobiegbunam,812,France,Male,24,10,0,2,1,1,156906.15,0 -4619,15633516,Tucker,526,France,Male,42,1,0,1,0,1,168486.02,0 -4620,15622532,Izmailova,708,France,Female,47,0,126589.12,2,0,1,132730.07,1 -4621,15798960,Meng,680,France,Male,33,2,108393.35,1,0,1,39057.67,0 -4622,15698664,Liang,567,Spain,Male,43,2,115643.58,2,0,0,174606.35,0 -4623,15703614,Hutchinson,564,Spain,Male,48,5,132876.23,1,1,0,79259.77,0 -4624,15699195,Shen,709,France,Female,24,3,110949.41,1,1,1,168515.61,0 -4625,15710543,Okwuoma,629,France,Male,46,1,130666.2,1,1,1,161125.67,1 -4626,15695499,Chinwemma,510,France,Female,45,10,103821.47,2,0,1,77878.62,0 -4627,15622321,Golubova,506,France,Female,32,3,0,1,1,1,80823.02,0 -4628,15715744,Schiavone,605,France,Male,39,7,0,1,0,1,119348.28,0 -4629,15788151,Moore,650,Spain,Male,32,1,132187.73,2,1,1,178331.36,0 -4630,15687153,Graham,850,Germany,Male,49,8,98649.55,1,1,0,119174.88,1 -4631,15684958,Amadi,489,Germany,Male,38,2,126444.08,2,1,1,82662.73,0 -4632,15706116,McKay,659,Germany,Female,30,8,154159.51,1,1,0,40441.1,0 -4633,15740557,Fedorova,753,France,Female,43,5,0,2,1,0,109881.71,0 -4634,15707291,Percy,477,Germany,Male,48,8,129250,2,1,1,157937.35,0 -4635,15583353,Floyd,610,Spain,Female,45,3,0,1,1,0,38276.84,1 -4636,15761024,Long,619,France,Female,33,2,167733.51,2,1,1,65222.48,0 -4637,15630709,Castiglione,619,Germany,Female,31,2,56116.3,2,0,0,2181.94,0 -4638,15639590,Melendez,758,France,Female,30,3,141581.08,1,1,0,156249.06,0 -4639,15659399,Mazzi,516,Germany,Male,50,7,139675.07,2,1,0,45591.23,0 -4640,15567078,Kovaleva,789,France,Female,27,8,66201.96,1,1,1,79458.12,0 -4641,15696373,Gill,687,France,Female,44,9,0,2,0,0,103042.2,1 -4642,15786617,Arcuri,485,Germany,Male,34,3,133658.24,1,1,0,70209.83,0 -4643,15657449,Chukwuma,446,Germany,Male,25,3,136202.78,1,1,0,176743.51,0 -4644,15672594,Stevenson,597,France,Female,60,0,131778.08,1,0,0,10703.53,1 -4645,15714240,Ponomarev,712,Spain,Male,74,5,0,2,0,0,151425.82,0 -4646,15782144,Gilroy,522,France,Female,34,3,0,2,1,1,3894.34,0 -4647,15665008,Sidorov,805,Germany,Female,26,8,42712.87,2,1,1,28861.69,0 -4648,15581733,Bates,781,France,Female,28,4,0,2,1,0,177703.15,0 -4649,15751392,Fanucci,689,Spain,Female,57,4,0,2,1,0,136649.8,1 -4650,15785815,Toscano,670,Germany,Male,31,1,142631.54,2,1,1,175894.24,0 -4651,15664214,Hearn,670,France,Male,33,2,141204.65,2,1,0,76257.46,0 -4652,15579996,Iroawuchi,524,Germany,Female,25,7,131402.21,1,0,0,193668.49,0 -4653,15675252,Martin,734,Spain,Female,39,3,92636.96,2,1,1,125671.29,0 -4654,15579617,Sinclair,489,France,Female,51,3,0,2,0,1,174098.28,1 -4655,15593976,Swanson,578,Germany,Female,31,5,102088.68,4,0,0,187866.21,1 -4656,15716041,Chinomso,622,Spain,Male,39,9,0,2,0,1,100862.36,0 -4657,15654489,Fomin,843,France,Female,38,8,134887.53,1,1,1,10804.04,0 -4658,15736302,McKay,687,France,Male,48,4,0,2,1,1,170893.85,0 -4659,15805909,Bergamaschi,700,Spain,Male,28,8,159900.38,1,0,0,22698.56,0 -4660,15572762,Matveyeva,410,Germany,Female,50,2,102278.79,2,1,0,89822.48,0 -4661,15724632,Madukaego,537,France,Female,41,0,0,2,0,1,175262.49,0 -4662,15670416,Ferri,780,France,Female,43,0,0,1,0,1,15705.27,0 -4663,15749528,Achebe,652,Spain,Male,58,6,0,2,0,1,170025.43,0 -4664,15578783,Mai,620,Germany,Male,35,0,76989.97,1,1,1,17242.79,0 -4665,15580719,Davis,697,France,Female,23,10,0,2,1,1,79734.23,0 -4666,15656293,Davey,786,France,Male,35,3,0,2,1,0,92712.97,0 -4667,15691875,Tsou,850,Germany,Female,39,5,114491.82,1,1,0,99689.48,0 -4668,15596870,Marino,749,Germany,Male,54,3,144768.94,1,1,0,93336.3,1 -4669,15780770,Kerr,445,France,Male,31,7,145056.59,1,1,1,175893.53,0 -4670,15751491,Hsiao,443,Germany,Male,50,3,117206.3,1,1,0,42840.18,1 -4671,15706200,Graham,637,Germany,Male,41,2,138014.4,2,1,0,140298.24,0 -4672,15808674,Ejikemeifeuwa,616,Germany,Female,45,6,128352.59,3,1,1,144000.59,1 -4673,15641411,Volkova,756,France,Female,23,1,112568.31,1,1,1,113408.11,0 -4674,15764661,Wang,644,France,Male,33,2,0,1,1,0,96420.58,0 -4675,15689492,Benjamin,850,Germany,Male,41,1,176958.46,2,0,1,125806.3,0 -4676,15602405,Ryrie,703,Germany,Female,38,9,99167.54,1,1,0,65720.92,0 -4677,15610271,Andreev,684,Spain,Female,42,3,103210.27,1,1,0,31002.03,0 -4678,15791780,Ts'ao,706,Germany,Female,48,10,104478.12,3,0,1,158248.71,1 -4679,15589147,Frolov,580,Spain,Male,61,8,125921.37,1,1,1,94677.83,0 -4680,15756975,Montemayor,777,Spain,Female,35,3,0,2,1,1,17257.72,0 -4681,15729582,Fu,676,Germany,Male,48,3,80697.44,1,0,0,101397.86,0 -4682,15742971,Whitehead,708,France,Female,44,2,161887.81,2,1,0,84870.23,0 -4683,15568046,Izuchukwu,809,France,Male,24,7,109558.36,1,1,0,183515.13,0 -4684,15694890,Lai,588,France,Male,38,1,124271.26,1,1,0,75969.19,0 -4685,15736963,Herring,623,France,Male,43,1,0,2,1,1,146379.3,0 -4686,15646490,Duffy,537,Spain,Male,42,1,190569.23,1,0,1,127154.8,0 -4687,15607314,Chiefo,536,Spain,Male,53,2,143923.96,1,1,0,2019.78,1 -4688,15576745,Fyodorov,769,France,Male,48,2,96542.16,2,0,1,197885.72,0 -4689,15669606,Chu,690,France,Male,33,5,0,2,1,0,138017.68,0 -4690,15737832,Robertson,771,Spain,Male,45,0,139825.56,1,0,0,170984.97,1 -4691,15681990,Palmerston,497,Germany,Male,24,6,111769.14,2,1,0,55859.27,0 -4692,15758050,Madukwe,622,Spain,Male,37,4,0,2,1,0,4459.5,0 -4693,15787848,Chinedum,602,Spain,Male,30,9,113672.18,2,0,0,102135.92,0 -4694,15713594,French,543,France,Female,32,7,147256.86,1,1,0,112771.95,0 -4695,15588186,Polyakov,520,Spain,Male,45,7,107023.03,1,1,0,32903.93,0 -4696,15786739,Clements,669,France,Male,37,1,125529.55,1,1,1,162260.93,0 -4697,15699467,Connor,631,Spain,Female,41,0,0,1,0,0,87959.83,0 -4698,15680706,Balashov,537,Germany,Male,48,4,131834.8,1,1,0,166476.95,1 -4699,15645717,Avdeeva,732,France,Male,62,2,0,2,1,1,25438.87,0 -4700,15748597,Chester,844,Spain,Male,56,5,99529.7,1,0,1,157230.06,1 -4701,15773709,Hung,838,Spain,Male,35,0,0,2,0,1,197305.91,0 -4702,15629787,Tu,652,France,Male,27,10,107303.72,2,0,0,44435.76,0 -4703,15661007,Thompson,660,France,Male,33,0,72783.42,1,0,0,181051.99,0 -4704,15686812,Jones,692,Spain,Female,44,8,0,1,0,1,159069.37,0 -4705,15754113,Li,588,France,Female,35,0,0,2,1,1,155485.24,0 -4706,15749489,Denisova,533,Germany,Female,22,10,115743.6,1,0,0,43852.05,0 -4707,15574352,Clogstoun,850,France,Male,43,4,161256.53,1,1,1,140071.57,0 -4708,15701281,Tan,511,France,Male,27,8,0,2,1,1,49089.36,0 -4709,15811985,Power,530,Spain,Male,44,6,0,2,0,0,55893.37,0 -4710,15713505,Harriman,554,France,Male,31,1,0,2,0,1,192660.55,0 -4711,15685653,Benson,585,Germany,Female,40,3,162261.01,2,1,0,137028.51,0 -4712,15758831,Thornton,754,France,Male,39,3,74896.33,1,0,0,34430.16,0 -4713,15618774,White,474,France,Male,54,3,0,1,1,0,108409.17,1 -4714,15764448,Mackenzie,837,Germany,Male,35,0,144037.6,1,1,0,145325.32,0 -4715,15611024,Kalinina,567,France,Female,23,9,93522.2,1,0,1,81425.61,0 -4716,15738220,Bennet,800,Spain,Male,38,1,0,2,1,0,51553.43,0 -4717,15805764,Hallahan,646,France,Male,18,10,0,2,0,1,52795.15,0 -4718,15580487,Martin,627,Germany,Male,38,8,106922.92,2,0,1,84270.09,0 -4719,15675787,Rivera,505,France,Male,26,8,112972.57,1,1,0,145011.62,0 -4720,15583580,Chiawuotu,566,Germany,Female,35,1,123042,1,1,0,66245.44,1 -4721,15780654,Sergeyev,619,Germany,Female,33,3,100488.92,2,0,1,36446.74,0 -4722,15695034,Christie,757,France,Female,44,4,123322.15,1,1,0,137136.29,0 -4723,15805671,Louis,648,France,Male,32,0,0,1,0,1,117323.31,0 -4724,15790658,Iqbal,621,Spain,Male,42,8,68683.68,1,1,1,74157.71,0 -4725,15578648,Marino,543,Germany,Male,49,6,59532.18,1,1,0,104253.56,0 -4726,15734987,Robertson,658,France,Female,43,7,140260.36,2,1,0,2748.72,0 -4727,15721740,Pai,633,Germany,Male,50,7,88302.65,1,1,1,195937.16,0 -4728,15641822,Barese,648,France,Female,19,1,0,2,0,1,22101.86,0 -4729,15765650,Chigolum,501,Germany,Male,40,5,114655.58,1,0,0,126535.92,0 -4730,15788556,Trouette,683,France,Female,42,4,148283.94,1,1,1,44692.63,1 -4731,15576550,Ugochukwu,619,Spain,Female,38,1,0,1,1,0,112442.63,1 -4732,15622230,Cribb,705,France,Female,35,3,0,2,0,1,66331.01,0 -4733,15653937,McIntyre,638,Germany,Female,53,1,123916.67,1,1,0,16657.68,1 -4734,15743538,Pickering,710,France,Female,31,1,0,2,1,0,20081.3,0 -4735,15591740,Fletcher,590,France,Female,54,4,0,2,1,1,93820.49,1 -4736,15650086,Uchenna,725,France,Male,43,2,165896,2,1,0,130795.52,0 -4737,15718773,Pisano,638,France,Female,32,0,0,2,1,0,160129.99,0 -4738,15615140,Corson,791,France,Male,36,6,111168.97,1,1,1,189969.91,0 -4739,15644361,Hooper,702,France,Female,40,1,103549.24,1,0,0,9712.52,1 -4740,15774536,He,607,France,Female,32,6,0,2,0,0,196062.01,0 -4741,15618661,Chidubem,535,France,Male,30,6,103804.97,1,1,1,125710.53,0 -4742,15605020,Schofield,651,France,Male,45,2,165901.59,2,1,0,23054.51,1 -4743,15762134,Liang,506,Germany,Male,59,8,119152.1,2,1,1,170679.74,0 -4744,15685279,Somadina,511,Spain,Female,57,8,122950.31,1,1,1,181258.76,0 -4745,15582849,McIntosh,757,France,Female,51,1,0,1,1,1,22835.13,1 -4746,15655410,Hinton,768,Germany,Male,49,1,133384.66,1,1,0,102397.22,1 -4747,15649129,Sal,757,France,Male,32,9,0,2,1,0,115950.96,0 -4748,15702380,De Luca,663,Spain,Male,64,6,0,2,0,1,15876.52,0 -4749,15759067,Bromby,537,Germany,Female,37,7,158411.95,4,1,1,117690.58,1 -4750,15683027,Chang,570,Germany,Male,29,4,122028.65,2,1,1,173792.77,0 -4751,15597487,Hunter,850,France,Female,35,5,0,1,1,1,80992.8,0 -4752,15763256,Sheppard,661,Germany,Female,64,8,128751.65,2,1,0,189398.18,1 -4753,15620111,Fan,659,France,Male,54,8,133436.52,1,1,0,56787.8,0 -4754,15623053,Muir,454,Spain,Male,40,2,123177.01,1,1,0,148309.98,0 -4755,15595592,Lai,708,France,Female,59,2,0,1,1,0,179673.11,1 -4756,15740072,Padovesi,720,France,Female,37,2,120328.88,2,1,1,138470.21,0 -4757,15778005,Kemp,785,France,Female,39,1,130147.98,1,1,0,163798.41,1 -4758,15583278,Greece,743,Spain,Female,36,8,92716.96,1,1,1,33693.78,0 -4759,15601263,Young,493,Spain,Female,48,7,0,2,1,0,48545.1,0 -4760,15709222,Chukwueloka,557,Spain,Male,34,3,0,1,0,1,123427.98,0 -4761,15713949,Woods,850,France,Male,40,1,76914.21,1,1,0,174183.44,0 -4762,15717706,Forbes,799,France,Female,32,3,106045.92,2,1,1,17938,0 -4763,15756071,Kang,756,France,Male,34,1,103133.26,1,1,1,90059.04,0 -4764,15696564,Nweke,752,France,Male,38,0,145974.79,2,1,1,137694.23,0 -4765,15657637,Ts'ui,696,Spain,Female,36,3,0,3,1,0,65039.9,0 -4766,15755863,Milano,630,Spain,Female,49,1,0,2,0,1,162858.29,0 -4767,15719858,Chao,659,Spain,Female,38,9,0,2,1,1,35701.06,0 -4768,15688876,Wan,685,Spain,Male,39,9,0,2,1,1,18826.06,0 -4769,15698528,Napolitani,599,Spain,Female,31,3,0,1,1,1,130086.47,1 -4770,15770345,Kovaleva,559,Spain,Female,31,1,139183.06,1,0,1,143360.56,0 -4771,15761506,Russell,615,Spain,Male,19,5,0,2,1,0,159920.92,0 -4772,15716619,Chiebuka,580,Germany,Female,36,3,74974.89,1,1,1,12099.67,0 -4773,15788367,Ellis,487,Spain,Male,44,6,61691.45,1,1,1,53087.98,0 -4774,15709451,Gordon,646,Germany,Female,35,1,121952.75,2,1,1,142839.82,0 -4775,15640421,Conway,811,France,Female,35,7,0,1,1,1,178.19,0 -4776,15580068,Buccho,526,Spain,Male,35,5,0,2,1,1,105618.14,0 -4777,15677123,Aksyonova,767,Spain,Male,37,7,0,2,1,1,24734.25,0 -4778,15619801,Batty,548,France,Female,33,1,80107.83,2,0,1,82245.67,0 -4779,15582246,Rowe,737,Spain,Female,45,2,0,2,0,1,177695.67,0 -4780,15711843,Pisani,613,Germany,Male,40,1,147856.82,3,0,0,107961.11,1 -4781,15680046,Onochie,711,Spain,Male,36,8,0,2,1,0,55207.41,0 -4782,15804131,Farmer,850,Spain,Female,53,7,65407.16,2,0,0,182633.63,1 -4783,15722611,Cameron,752,France,Female,53,8,114233.18,1,1,1,51587.04,0 -4784,15729224,Jennings,710,France,Female,37,5,0,2,1,0,115403.31,0 -4785,15811588,Eluemuno,664,Spain,Female,53,7,187602.18,1,1,0,186392.99,1 -4786,15702138,Swift,510,France,Female,22,3,156834.34,1,0,0,44374.44,0 -4787,15749799,Pisani,577,France,Female,34,2,0,2,1,1,84033.35,0 -4788,15752885,Nnonso,529,France,Male,42,1,157498.9,1,1,1,82276.62,0 -4789,15674932,Cameron,757,Spain,Female,44,9,0,2,1,0,177528.92,0 -4790,15743828,Stevens,691,France,Male,41,2,0,1,1,1,56850.92,1 -4791,15642022,Zito,621,Spain,Male,34,8,0,1,0,0,47972.65,0 -4792,15746461,Taylor,709,Spain,Male,35,2,0,2,1,0,104982.39,0 -4793,15809991,Ferrari,756,Spain,Male,19,4,130274.22,1,1,1,133535.29,0 -4794,15787322,Yeh,788,France,Female,41,6,0,1,1,1,25571.37,0 -4795,15575498,Gould,705,France,Female,39,5,149379.66,2,1,0,96075.55,0 -4796,15691387,Agafonova,483,France,Male,29,9,0,1,1,1,81634.45,0 -4797,15765457,Fowler,719,Spain,Male,35,1,100829.94,1,1,1,165008.97,0 -4798,15666173,Chidumaga,793,Germany,Female,32,1,96408.98,1,1,1,138191.81,0 -4799,15627377,Sabbatini,593,France,Male,41,6,0,2,1,1,99136.49,0 -4800,15656683,Johnson,551,France,Male,52,1,0,1,0,0,63584.55,1 -4801,15679810,Chapman,690,France,Male,39,6,0,2,1,0,160532.88,0 -4802,15606310,Birk,823,France,Male,71,5,149105.08,1,0,1,162683.06,0 -4803,15756871,Capon,512,Spain,Male,39,3,0,1,1,0,134878.19,0 -4804,15610002,Chidubem,802,Spain,Male,41,5,0,2,1,1,134626.3,0 -4805,15567802,Childs,450,Spain,Female,34,2,0,2,1,0,175480.93,0 -4806,15745452,Sun,651,Germany,Male,41,1,90218.11,1,1,0,174337.68,0 -4807,15617252,Lung,697,France,Female,33,1,87347.7,1,1,0,172524.51,0 -4808,15753248,Tao,611,France,Male,28,2,0,2,0,0,25395.83,0 -4809,15610755,Napolitano,643,France,Female,33,0,137811.75,1,1,1,184856.89,0 -4810,15662238,Davis,822,France,Male,37,3,105563,1,1,0,182624.93,0 -4811,15799186,Sagese,632,France,Male,38,4,0,2,0,0,192505.62,0 -4812,15686941,Hutchinson,575,Spain,Female,26,7,0,2,1,0,112507.63,0 -4813,15601172,Nelson,672,France,Male,31,6,91125.75,1,1,0,177295.92,0 -4814,15723858,Schiavone,517,Spain,Male,39,3,0,2,0,1,12465.51,0 -4815,15615896,Chienezie,621,Spain,Male,39,8,0,2,1,0,36122.96,0 -4816,15737647,Obioma,775,Germany,Female,77,6,135120.56,1,1,0,37836.64,0 -4817,15582841,Butusov,600,France,Male,29,8,0,2,0,1,34747.43,0 -4818,15760090,Pisano,640,France,Male,28,7,0,2,1,1,131097.9,0 -4819,15588587,Stetson,752,France,Female,36,1,86837.95,1,1,1,105280.55,0 -4820,15683157,Waring,613,France,Male,26,4,100446.57,1,0,1,149653.81,0 -4821,15694209,Fanucci,484,France,Female,32,3,0,2,1,1,139390.99,0 -4822,15655875,Thao,511,France,Female,33,3,0,2,1,0,132436.71,0 -4823,15805704,Murphy,745,France,Female,32,2,0,4,0,1,179705.13,1 -4824,15744789,McConnell,786,Spain,Female,32,6,114512.59,1,1,0,15796.66,0 -4825,15799357,Armfield,727,France,Male,35,5,136364.46,1,0,0,142754.71,0 -4826,15726153,Fanucci,622,France,Male,31,5,106260.67,1,1,1,2578.43,0 -4827,15713346,Panina,794,France,Male,24,10,146126.75,1,1,1,88992.05,0 -4828,15665053,Nixon,636,Spain,Male,52,4,111284.53,1,0,1,32936.44,1 -4829,15592379,Walker,741,Spain,Female,42,9,121056.63,2,1,0,39122.58,0 -4830,15692599,Chiemela,687,France,Male,34,5,128270.56,1,1,0,191092.62,0 -4831,15620758,Martel,660,Spain,Male,30,4,0,2,1,0,129149.06,0 -4832,15637428,Briggs,660,France,Male,35,7,0,2,1,0,13218.6,0 -4833,15808389,Iheatu,617,France,Female,79,7,0,1,1,1,160589.18,0 -4834,15807003,Jennings,762,France,Male,32,10,191775.65,1,1,0,179657.83,0 -4835,15702912,Ch'en,752,Spain,Female,35,2,0,1,1,0,44335.54,1 -4836,15590623,Kovalyov,561,Spain,Male,34,4,85141.79,2,1,1,29217.37,0 -4837,15728078,Yeh,609,France,Male,26,10,126392.18,1,0,1,43651.49,0 -4838,15708256,Chien,803,France,Male,28,3,0,2,1,0,159654,0 -4839,15582335,Brown,556,France,Female,40,9,129860.37,1,0,0,17992.94,0 -4840,15649150,Buddicom,531,France,Female,53,5,127642.44,1,1,0,141501.45,1 -4841,15691647,McGregor,411,France,Female,35,2,0,2,1,1,93825.78,0 -4842,15668270,Thompson,587,Germany,Female,44,5,125584.17,2,1,1,41852.24,1 -4843,15624820,Ross,683,Spain,Male,56,7,50911.21,3,0,0,97629.31,1 -4844,15736254,Ch'ang,654,France,Male,29,2,91955.61,1,1,0,37065.66,0 -4845,15720814,Warren,670,Germany,Female,36,2,84266.44,2,0,0,38614.69,0 -4846,15642997,Uspenskaya,655,France,Female,36,2,147149.59,1,1,1,87816.86,0 -4847,15693200,King,752,France,Female,36,7,0,2,1,0,184866.86,0 -4848,15624596,Trentini,534,France,Female,23,5,104822.45,1,0,1,160176.47,0 -4849,15807167,Konovalova,635,France,Male,42,1,146766.72,2,0,1,164357.1,0 -4850,15660301,Dellucci,491,Germany,Male,70,6,148745.92,2,1,1,17818.33,0 -4851,15593094,Goddard,516,France,Male,27,9,0,1,1,0,142680.64,1 -4852,15618239,Neumann,530,France,Female,48,0,0,1,1,0,85081.09,0 -4853,15574137,Ch'in,687,Spain,Male,35,3,0,2,1,1,176450.19,0 -4854,15614740,Walters,684,France,Female,41,6,135203.81,2,1,1,121967.88,0 -4855,15574071,Muravyova,706,Germany,Male,23,2,93301.97,2,0,1,127187.04,0 -4856,15671148,Barry,490,Germany,Male,33,5,96341,2,0,0,108313.34,0 -4857,15721921,Woolnough,796,France,Male,44,8,165326.2,1,1,1,57205.55,0 -4858,15717995,Keen,849,France,Male,27,0,0,2,0,1,157891.86,0 -4859,15632050,Liebe,779,France,Female,41,10,99786.2,1,1,0,86927.53,0 -4860,15647111,White,794,Spain,Female,22,4,114440.24,1,1,1,107753.07,0 -4861,15759991,Hunter,748,Spain,Male,36,4,141573.55,1,1,0,82158.14,0 -4862,15790204,Myers,663,Spain,Female,22,9,0,1,1,0,29135.89,1 -4863,15686780,Rogova,645,Spain,Female,55,1,133676.65,1,0,1,17095.49,0 -4864,15640491,Raff,464,France,Female,33,10,147493.7,2,1,0,100447.53,0 -4865,15783225,Cocci,737,France,Male,54,9,0,1,1,0,83470.4,1 -4866,15734438,Kanayochukwu,590,France,Female,29,4,0,2,1,0,121846.81,0 -4867,15688760,Obialo,522,Germany,Female,37,3,95022.57,1,1,1,129107.59,0 -4868,15768124,Liu,648,France,Female,34,3,0,1,1,0,54726.43,0 -4869,15661330,Gilbert,754,France,Male,37,6,0,1,1,1,116141.72,0 -4870,15781272,Coles,669,France,Male,50,4,149713.61,3,1,1,124872.42,1 -4871,15573888,Ponomaryov,648,Germany,Female,43,1,107963.38,1,0,0,186438.86,1 -4872,15575858,Bergamaschi,763,France,Male,40,3,0,2,1,0,134281.11,0 -4873,15645937,Guerin,790,Spain,Male,32,3,0,1,1,0,91044.47,0 -4874,15702337,Sinclair,581,France,Male,37,7,0,2,1,1,74320.75,0 -4875,15764537,Dominguez,703,France,Male,43,8,0,2,1,0,9704.66,0 -4876,15619616,Costa,571,France,Female,33,9,102017.25,2,0,0,128600.49,0 -4877,15585133,Wei,657,Spain,Female,27,8,0,2,0,0,6468.24,0 -4878,15573971,Mills,737,France,Male,44,7,0,2,0,0,57898.58,0 -4879,15579433,Pugh,793,Spain,Male,29,8,96674.55,2,0,0,192120.66,0 -4880,15777045,Price,783,Spain,Female,44,3,81811.71,1,1,0,164213.53,1 -4881,15611580,Wood,751,Spain,Male,33,4,79281.61,1,1,0,117547.76,0 -4882,15614778,Robertson,579,France,Male,31,6,0,2,1,0,26149.25,0 -4883,15771750,Sawtell,655,Germany,Female,36,10,122314.39,1,1,0,9181.66,0 -4884,15593280,Yuryeva,614,Germany,Male,43,8,140733.74,1,1,1,166588.76,0 -4885,15569274,Pisano,678,Germany,Male,49,2,116933.11,1,1,0,195053.58,1 -4886,15654408,Kharitonova,562,Spain,Male,41,5,165445.04,2,1,0,85787.31,0 -4887,15657468,Simmons,711,Germany,Female,53,5,123805.03,1,1,0,102428.51,0 -4888,15614213,Muramats,620,France,Male,37,0,107548.94,1,1,0,71175.94,0 -4889,15589869,Tang,437,France,Male,49,9,111634.29,2,0,1,166440.32,0 -4890,15693205,Peng,691,Germany,Female,41,8,109153.96,3,1,1,148848.76,1 -4891,15797113,Bevan,552,Spain,Female,34,4,0,2,1,0,140286.69,0 -4892,15676958,Zito,765,Germany,Male,34,5,86055.17,2,1,1,104220.5,0 -4893,15739592,Sokolov,707,Germany,Female,51,10,98438.23,1,0,0,70778.63,1 -4894,15656263,Teng,764,Spain,Male,29,5,0,2,1,0,65868.28,0 -4895,15636872,Amadi,585,France,Female,32,8,144705.87,2,0,0,171482.56,0 -4896,15589435,Davide,784,France,Male,31,7,0,2,1,1,143204.41,0 -4897,15640464,Parkes,605,France,Male,41,5,91612.91,1,1,1,28427.84,0 -4898,15723851,Mazzanti,699,Spain,Male,40,2,0,1,1,0,78387.32,0 -4899,15722122,Findlay,544,France,Female,40,7,0,1,0,1,161076.92,0 -4900,15696852,Hsu,803,France,Female,32,9,192122.84,1,1,1,54277.45,1 -4901,15634936,Chukwukadibia,735,France,Male,41,7,179904,1,1,1,137180.95,0 -4902,15575935,Baxter,673,France,Male,59,0,178058.06,2,0,1,21063.71,1 -4903,15634491,Kung,652,France,Male,30,2,176166.56,2,1,1,152210.81,0 -4904,15628530,Booth,694,France,Male,42,3,156864.2,2,0,0,88890.75,0 -4905,15678720,Evans,741,France,Female,44,7,0,2,1,1,190534.76,0 -4906,15627999,Kung,590,Spain,Male,30,3,0,2,1,0,83090.35,0 -4907,15571244,Tung,809,Spain,Female,33,3,0,2,0,1,141426.78,0 -4908,15739931,Yuan,523,France,Male,34,2,161588.89,1,1,1,51358.66,0 -4909,15806256,Jackson,540,France,Male,48,2,109349.29,1,1,0,88703.04,1 -4910,15787258,Ross,596,Spain,Female,29,6,0,2,1,0,116696.77,0 -4911,15706463,Yang,597,France,Female,36,9,0,2,1,1,7156.09,0 -4912,15691004,Yu,407,Spain,Male,37,1,0,1,1,1,49161.12,1 -4913,15792228,Onwumelu,748,France,Male,60,0,152335.7,1,1,0,126743.33,1 -4914,15733447,Gay,562,France,Female,51,1,124662.54,1,1,1,65390.46,1 -4915,15679062,Morrison,734,Germany,Female,47,10,91522.04,2,1,1,138835.91,0 -4916,15594409,Belov,710,France,Male,45,1,0,2,1,1,36154.66,0 -4917,15613816,Mao,539,Spain,Female,39,6,62052.28,1,0,1,59755.14,0 -4918,15681991,Walsh,542,France,Male,32,7,107871.72,1,1,0,125302.64,0 -4919,15796074,Bruno,717,France,Female,36,2,99472.76,2,1,0,94274.72,1 -4920,15625941,Gray,682,Spain,Female,50,10,128039.01,1,1,1,102260.16,0 -4921,15615016,Maurer,515,France,Male,33,2,0,2,1,1,136028.97,0 -4922,15748414,Chiang,526,Spain,Female,33,8,114634.63,2,1,0,110114.38,1 -4923,15751203,Cattaneo,702,France,Male,26,5,56738.47,2,1,1,100442.22,1 -4924,15662658,Grieve,651,Germany,Male,34,2,90355.12,2,0,0,193597.94,0 -4925,15574868,Lowell,792,Germany,Male,36,5,115725.24,2,0,0,1871.25,0 -4926,15790282,Trentino,817,Germany,Male,58,3,114327.59,2,1,1,42831.11,0 -4927,15762927,Sung,674,Germany,Female,36,6,100762.64,1,1,0,182156.86,0 -4928,15803456,Yen,641,France,Female,40,9,0,1,0,0,151648.66,1 -4929,15771857,Philipp,513,Spain,Male,39,7,89039.9,2,1,1,146738.83,0 -4930,15700601,Dynon,561,France,Male,34,1,78829.53,1,1,1,12148.2,0 -4931,15569670,Alexeyeva,627,Germany,Male,30,6,112372.96,1,1,1,118029.09,0 -4932,15772341,Hs?eh,682,Germany,Male,81,6,122029.15,1,1,1,50783.88,0 -4933,15661548,Ferri,683,France,Female,29,0,157829.12,1,0,0,129891.66,0 -4934,15787597,Hsu,420,Germany,Female,31,1,108377.75,2,1,1,9904.63,0 -4935,15806913,Bishop,670,France,Female,54,2,95507.12,1,1,1,63213.31,0 -4936,15804862,Toscani,505,Germany,Male,43,6,127146.68,1,0,0,137565.87,0 -4937,15792986,T'ao,580,Germany,Male,24,1,133811.78,1,1,0,17185.95,1 -4938,15625632,Philip,577,France,Male,36,3,121092.47,2,0,1,143783.46,0 -4939,15727703,Li Fonti,773,Germany,Male,34,10,126979.75,1,0,0,36823.28,0 -4940,15606273,Rene,616,France,Male,37,5,144235.73,2,0,0,154957.66,1 -4941,15799652,Daigle,763,France,Female,38,0,152582.2,2,0,0,31892.82,0 -4942,15715047,Joshua,640,Spain,Male,43,9,172478.15,1,1,0,191084.4,1 -4943,15784687,Simmons,592,France,Male,36,1,126477.42,1,0,0,179718.17,0 -4944,15615322,Jamieson,528,Spain,Male,43,7,97473.87,2,1,1,159823.16,0 -4945,15722072,Hou,630,France,Male,53,5,138053.67,1,0,1,114110.97,0 -4946,15646784,Cochran,529,France,Female,31,2,164003.05,2,1,1,60993.23,0 -4947,15644692,Bibb,546,France,Female,47,8,0,1,1,1,66408.01,1 -4948,15670354,Jen,753,France,Female,62,6,0,2,1,1,136398.9,0 -4949,15716357,Corran,772,Spain,Female,39,4,122486.11,2,1,1,140709.25,0 -4950,15786717,He,567,France,Male,36,1,0,2,0,0,8555.73,0 -4951,15771383,Loggia,628,Germany,Female,45,6,53667.44,1,1,0,115022.94,0 -4952,15649793,Lovely,658,France,Male,20,7,0,2,0,0,187638.34,0 -4953,15731543,Becker,679,Spain,Male,58,9,109327.65,1,1,1,3829.13,0 -4954,15684516,Plascencia,629,Spain,Male,34,1,121151.05,1,0,0,119357.93,0 -4955,15677249,Somadina,731,Spain,Male,42,9,101043.63,1,1,1,192175.52,0 -4956,15581525,Walker,775,Germany,Male,33,3,83501.66,2,1,0,128841.31,0 -4957,15628420,Alekseeva,660,Spain,Male,33,2,80462.24,1,0,0,150422.35,0 -4958,15600478,Watson,752,France,Male,39,3,0,1,1,0,188187.05,0 -4959,15594502,Zotov,655,France,Male,37,6,109093.41,2,1,0,1775.52,0 -4960,15784361,Williamson,543,Spain,Female,46,5,140355.6,1,1,1,85086.78,0 -4961,15767626,Carpenter,811,France,Male,42,10,0,2,1,1,3797.79,0 -4962,15632521,Cattaneo,689,Germany,Male,45,0,130170.82,2,1,0,150856.38,0 -4963,15665088,Gordon,531,France,Female,42,2,0,2,0,1,90537.47,0 -4964,15652084,Boni,515,France,Male,40,0,109542.29,1,1,1,166370.81,0 -4965,15574761,Lynch,466,France,Female,41,3,33563.95,2,1,0,178994.13,1 -4966,15729515,McCarthy,782,France,Male,36,1,148795.17,2,1,1,195681.43,0 -4967,15682070,Davies,611,France,Male,64,9,0,2,1,1,53277.15,0 -4968,15743817,Hargreaves,621,Germany,Male,40,8,174126.75,3,1,0,172490.78,1 -4969,15572158,Blackburn,604,Spain,Male,41,3,0,1,0,0,11819.84,0 -4970,15584477,K?,655,Spain,Female,35,1,106405.03,1,1,1,82900.25,0 -4971,15614893,Meng,689,Spain,Male,38,2,0,1,1,1,82709.8,0 -4972,15665963,Cattaneo,681,Spain,Male,30,2,128393.29,1,1,1,180593.45,0 -4973,15612524,Hunt,643,Germany,Male,41,2,127841.52,1,1,0,172363.41,0 -4974,15596962,Owens,617,France,Female,24,4,137295.19,2,1,1,91195.12,0 -4975,15744942,Steele,638,Spain,Female,55,2,155828.22,1,0,1,108987.25,1 -4976,15573278,Kennedy,743,France,Male,39,6,0,2,1,0,44265.28,0 -4977,15717056,Pan,828,Germany,Female,25,7,144351.86,1,1,0,116613.26,0 -4978,15795881,Alexander,776,Spain,Male,35,8,106365.29,1,1,1,148527.56,0 -4979,15758939,Bray,540,Germany,Male,35,7,127801.88,1,0,1,84239.46,0 -4980,15792250,Nnabuife,616,Germany,Female,45,4,122793.96,1,1,1,62002.04,0 -4981,15740406,Padovesi,628,Germany,Male,38,10,113525.84,1,1,0,46044.48,1 -4982,15768137,Bray,667,Spain,Female,23,6,136100.69,2,0,0,169669.33,1 -4983,15569120,Lucas,615,France,Male,30,7,0,2,1,1,156346.84,0 -4984,15723721,Tinline,543,France,Male,30,4,140916.81,1,1,0,157711.18,0 -4985,15777122,Esomchi,553,France,Female,31,4,0,2,1,1,89087.4,0 -4986,15742681,Liao,554,Germany,Male,26,4,121365.39,1,1,1,8742.36,0 -4987,15582090,Iroawuchi,684,Spain,Female,36,4,0,1,1,0,117038.96,0 -4988,15711254,Retana,452,France,Female,35,7,0,2,1,0,164241.67,0 -4989,15775067,Fang,606,France,Male,47,3,93578.68,2,0,1,137720.56,1 -4990,15602851,Ozioma,629,France,Male,40,9,0,1,1,0,106.67,0 -4991,15802857,Robson,659,Spain,Female,33,8,115409.6,1,0,1,1539.21,0 -4992,15701175,Bruno,493,France,Female,33,8,90791.69,1,1,1,59659.53,0 -4993,15783019,Price,794,France,Female,62,9,123681.32,3,1,0,173586.63,1 -4994,15728912,Swanson,554,France,Female,44,6,92436.86,1,1,0,126033.9,0 -4995,15585580,Chang,796,Germany,Female,52,9,167194.36,1,1,1,62808.93,1 -4996,15583480,Morgan,807,France,Female,36,4,0,2,0,1,147007.33,0 -4997,15620341,Nwebube,500,Germany,Male,44,9,160838.13,2,1,0,196261.64,0 -4998,15613886,Trevisan,722,Spain,Male,43,1,0,1,1,0,44560.17,1 -4999,15792916,Ositadimma,559,Spain,Female,40,7,144470.77,1,1,1,18917.95,0 -5000,15710408,Cunningham,584,Spain,Female,38,3,0,2,1,1,4525.4,0 -5001,15598695,Fields,834,Germany,Female,68,9,130169.27,2,0,1,93112.2,0 -5002,15649354,Johnston,754,Spain,Male,35,4,0,2,1,1,9658.41,0 -5003,15737556,Vasilyev,590,France,Male,43,7,81076.8,2,1,1,182627.25,1 -5004,15671610,Hooper,740,France,Male,36,7,0,1,1,1,13177.4,0 -5005,15625092,Colombo,502,Germany,Female,57,3,101465.31,1,1,0,43568.31,1 -5006,15741032,Tsao,733,France,Male,48,5,0,1,0,1,117830.57,0 -5007,15750014,Chikere,755,Germany,Female,37,0,113865.23,2,1,1,117396.25,0 -5008,15784761,Ballard,554,Spain,Female,46,7,87603.35,3,0,1,96929.24,1 -5009,15768359,Akhtar,534,France,Male,36,4,120037.96,1,1,0,36275.94,0 -5010,15805769,O'Loughlin,656,Spain,Male,33,4,0,2,1,0,116706,0 -5011,15719508,Davis,575,Germany,Male,49,7,121205.15,4,1,1,168080.53,1 -5012,15609011,Barry,480,Spain,Male,47,8,75408.33,1,1,0,25887.89,1 -5013,15703106,K'ung,575,France,Male,40,5,0,2,1,1,122488.59,0 -5014,15626795,Gorman,672,France,Female,40,3,0,1,1,0,113171.61,1 -5015,15773731,John,758,Spain,Female,35,5,0,2,0,0,100365.51,0 -5016,15756196,Tsou,682,France,Male,50,6,121818.84,2,0,1,124151.37,0 -5017,15687903,Okonkwo,501,France,Female,29,8,0,2,1,0,112664.24,0 -5018,15777599,Esposito,746,Germany,Male,34,6,141806,2,1,1,183494.87,0 -5019,15754577,Boni,556,France,Female,51,8,61354.14,1,1,0,198810.65,1 -5020,15584113,Pratt,823,Germany,Female,53,4,124954.94,1,0,1,131259.6,1 -5021,15669589,Page,491,Germany,Female,68,1,95039.12,1,0,1,116471.14,1 -5022,15632793,Wilkinson,638,France,Female,29,9,103417.74,1,1,1,15336.4,0 -5023,15711130,Tseng,734,France,Male,45,2,0,2,1,0,99593.28,0 -5024,15615254,Clark,555,France,Male,40,10,43028.77,1,1,0,170514.21,0 -5025,15720583,Finch,745,Germany,Female,44,0,119638.21,1,1,1,34265.08,1 -5026,15780432,Shen,728,France,Male,37,3,122689.51,2,0,0,106977.53,1 -5027,15673223,Hou,626,France,Male,44,10,0,2,0,0,164287.86,0 -5028,15807989,Wall,681,Germany,Male,37,8,73179.34,2,1,1,25292.53,0 -5029,15761168,Manna,478,France,Female,38,4,171913.87,1,1,0,51820.87,1 -5030,15651272,Reyes,709,France,Male,38,5,0,2,1,1,81452.29,0 -5031,15812832,Jideofor,562,Germany,Male,33,8,92659.2,2,1,0,1354.25,0 -5032,15680517,Sal,769,Germany,Female,34,7,137239.17,1,1,1,71379.92,1 -5033,15750569,Iweobiegbunam,684,Germany,Female,46,3,102955.14,2,1,0,154137.33,0 -5034,15690743,Shao,536,France,Female,61,8,65190.29,1,1,1,64308.49,1 -5035,15627741,Heath,631,Germany,Female,29,2,96863.52,2,1,1,31613.35,0 -5036,15712121,Chidimma,657,Spain,Male,34,5,154983.98,1,1,0,27738.01,0 -5037,15805429,Murray,699,Germany,Male,59,3,106819.65,1,0,1,163570.25,0 -5038,15814923,Sullivan,606,Spain,Male,38,7,128578.52,1,1,1,193878.51,0 -5039,15589230,Wu,612,France,Female,63,2,126473.33,1,0,1,147545.65,0 -5040,15775490,Downie,660,France,Female,38,5,110570.78,2,1,0,195906.59,0 -5041,15749727,Chukwufumnanya,829,Spain,Male,50,7,0,2,0,1,178458.86,0 -5042,15619238,Allan,567,Spain,Male,29,8,0,2,1,0,156125.72,0 -5043,15593468,Findlay,850,France,Female,33,3,0,2,1,1,11159.19,0 -5044,15718454,Ch'eng,712,Spain,Female,44,2,0,2,0,0,45738.94,0 -5045,15789498,Miller,562,France,Male,30,3,111099.79,2,0,0,140650.19,0 -5046,15744691,Tsai,755,France,Female,29,3,0,3,1,0,4733.94,0 -5047,15708289,Graham,793,Spain,Male,25,3,100913.57,1,0,0,10579.72,0 -5048,15790412,Norton,471,Spain,Male,26,8,0,2,1,1,179655.87,0 -5049,15741416,Yegorov,707,France,Male,42,2,16893.59,1,1,1,77502.56,0 -5050,15598894,Holt,784,Spain,Male,38,10,122267.85,1,0,0,145759.93,0 -5051,15663294,Kao,703,France,Male,32,1,125685.79,1,1,1,56246.72,0 -5052,15572728,Ross,704,Spain,Male,36,8,127397.34,1,1,0,151335.24,0 -5053,15706729,Hsiao,662,France,Male,38,0,105271.56,1,0,1,179833.45,0 -5054,15674433,Allan,636,Germany,Female,28,2,115265.14,1,0,0,191627.85,0 -5055,15641170,Liang,640,Spain,Male,36,4,0,1,0,0,173016.46,0 -5056,15806284,Briggs,739,Spain,Male,31,1,0,2,1,1,58469.75,0 -5057,15690958,Cantrell,767,Germany,Male,23,2,139542.82,1,0,1,28038.28,0 -5058,15606386,Wang,753,Germany,Female,46,3,111512.75,3,1,0,159576.75,1 -5059,15682322,Aksenov,714,France,Male,37,9,148466.93,2,0,1,151280.96,0 -5060,15579915,Glennon,707,France,Male,29,4,0,2,1,0,139953.94,0 -5061,15681928,Yancy,577,France,Female,35,4,108155.49,1,1,0,105407.79,0 -5062,15734005,Mazzi,633,France,Female,42,1,0,2,1,0,56865.62,0 -5063,15650432,Liu,849,Germany,Male,41,10,84622.13,1,1,1,198072.16,0 -5064,15592578,Nucci,614,Spain,Female,41,7,146997.64,2,0,0,137791.18,0 -5065,15671243,Y?,558,France,Female,47,9,0,2,1,0,103787.28,0 -5066,15775709,Nucci,832,France,Female,27,10,98590.25,1,1,0,30912.89,0 -5067,15702631,Tang,567,France,Female,26,2,0,2,1,1,78651.55,0 -5068,15602282,Kao,587,Germany,Female,45,8,134980.74,1,1,1,123309.57,1 -5069,15717879,Chen,712,Spain,Female,79,5,108078.56,1,1,1,174118.93,0 -5070,15740878,Yao,655,Spain,Female,29,9,0,2,0,1,85736.26,0 -5071,15794468,Tsou,641,France,Female,42,6,0,2,0,0,121138.77,0 -5072,15773277,Barnes,676,France,Male,35,5,106836.67,2,1,0,84199.78,0 -5073,15572657,H?,472,France,Male,29,8,102490.27,1,0,1,181224.56,0 -5074,15800295,Cruz,644,Germany,Male,34,9,112746.54,2,0,0,141230.07,0 -5075,15672397,Smith,598,France,Male,38,0,125487.89,1,0,0,158111.71,0 -5076,15684921,Onuchukwu,792,Spain,Male,25,8,142862.21,1,1,1,130639.01,0 -5077,15720676,Bukowski,700,France,Female,37,7,0,2,1,0,17040.82,0 -5078,15731829,Simmons,616,France,Male,34,10,0,2,1,0,25662.27,0 -5079,15732672,Stewart,743,Spain,Male,35,6,79388.33,1,1,1,193360.69,0 -5080,15692406,Gow,427,France,Male,37,5,0,2,1,1,121485.1,0 -5081,15764405,Williams,731,France,Male,29,10,0,2,1,1,162452.65,0 -5082,15757537,Francis,610,France,Female,31,6,107784.65,1,1,1,141137.53,0 -5083,15793307,Calabresi,724,Spain,Female,41,4,142880.28,3,0,0,185541.2,1 -5084,15660679,Chimaobim,653,Spain,Female,38,9,149571.94,1,1,0,118383.18,0 -5085,15666856,Chikwendu,774,France,Male,49,1,142767.39,1,1,1,8214.41,0 -5086,15687372,Padovesi,547,Germany,Male,49,8,121537.71,2,1,0,46521.45,1 -5087,15667289,Henderson,719,Spain,Male,50,2,0,2,0,0,10772.13,0 -5088,15624641,Kharlamova,740,Spain,Male,43,9,0,1,1,0,199290.68,1 -5089,15734610,Onio,543,France,Male,42,4,89838.71,3,1,0,85983.54,1 -5090,15631882,Yeh,688,Germany,Male,45,9,103399.87,1,0,0,129870.93,0 -5091,15642709,Feng,474,France,Female,30,9,0,2,0,0,63158.22,0 -5092,15811026,Norman,505,Germany,Male,43,5,136855.94,2,1,0,171070.52,0 -5093,15596303,White,688,France,Female,39,0,0,2,1,0,53222.15,1 -5094,15787255,Manfrin,650,Germany,Female,55,2,140891.46,3,1,1,179834.45,1 -5095,15617166,Ritchie,610,France,Male,37,0,0,1,1,0,114514.64,0 -5096,15742442,Udegbulam,705,Spain,Female,46,5,89364.91,1,0,1,139162.15,0 -5097,15758692,Kao,669,France,Female,29,7,146011.4,1,0,0,50249.16,0 -5098,15568238,Diaz,650,Spain,Male,20,8,0,2,1,1,113469.65,0 -5099,15730353,Olisaemeka,550,Germany,Male,29,9,145294.08,2,1,0,147484.13,0 -5100,15731555,Ross-Watt,595,Germany,Female,45,9,106000.12,1,0,0,191448.96,1 -5101,15582404,Miller,572,Spain,Female,26,5,0,2,1,0,119381.41,0 -5102,15721462,Shubin,622,Spain,Female,58,2,0,2,1,1,33277.31,0 -5103,15632899,Nwankwo,662,Spain,Male,20,9,104508.77,2,0,0,73107.53,0 -5104,15808526,Cartwright,783,Germany,Female,58,3,127539.3,1,1,1,96590.39,1 -5105,15694349,Ngozichukwuka,714,Spain,Male,44,7,0,1,0,1,6923.11,0 -5106,15718465,Sadler,671,Germany,Male,51,3,96891.46,1,1,0,176403.33,1 -5107,15682995,Azuka,600,France,Female,32,1,78535.25,1,1,0,64349.6,0 -5108,15584776,Shen,847,Spain,Female,37,9,112712.17,1,1,0,116097.26,0 -5109,15777772,Whittaker,650,Spain,Male,55,9,119618.42,1,1,1,29861.13,0 -5110,15576156,Abazu,710,Spain,Female,28,6,0,1,1,0,48426.98,0 -5111,15646756,Murphy,682,France,Female,33,8,74963.5,1,1,1,32770.56,0 -5112,15742886,Ford,642,France,Male,26,1,138023.79,2,0,1,117060.2,0 -5113,15586135,Gratwick,536,Spain,Female,28,4,0,1,1,1,136197.65,0 -5114,15616152,Pai,754,France,Female,47,1,185513.67,1,1,0,27438.83,0 -5115,15721460,Lorenzo,678,France,Male,60,8,185648.56,1,0,0,192156.54,1 -5116,15727317,Brady,533,Germany,Female,49,1,102286.6,3,1,0,69409.37,1 -5117,15649536,Wong,741,Germany,Male,38,4,128015.83,1,1,0,58440.43,0 -5118,15754929,Douglas,757,France,Male,31,10,39539.39,2,0,0,192519.39,0 -5119,15572051,Kennedy,721,France,Male,40,3,0,1,1,1,144874.67,0 -5120,15668142,Chang,700,France,Male,37,3,77608.46,2,1,1,175373.46,0 -5121,15701176,Brown,663,France,Male,26,5,141462.13,1,1,0,440.2,0 -5122,15708422,Hsiung,677,Spain,Female,35,0,0,2,0,0,76637.38,0 -5123,15655632,MacDonald,655,France,Male,27,2,131691.33,1,1,0,49480.66,0 -5124,15744606,Davidson,832,Spain,Male,29,8,93833.86,1,0,1,10417.87,0 -5125,15612140,Milano,721,Spain,Female,46,7,137933.39,1,1,1,67976.57,0 -5126,15656086,Bovee,542,Spain,Male,54,8,105770.14,1,0,1,140929.98,1 -5127,15655298,Lewis,654,Spain,Female,54,5,0,2,0,1,47139.06,0 -5128,15644796,Dyer,821,Spain,Female,38,8,0,2,0,1,126241.4,1 -5129,15726250,Hsia,508,France,Female,38,3,166328.65,2,0,1,22614.19,0 -5130,15764432,Hicks,588,Germany,Female,42,2,164307.77,1,1,0,48498.19,0 -5131,15631721,Millar,691,Germany,Male,38,9,163965.69,2,0,1,103511.26,0 -5132,15707479,Fan,664,France,Male,40,7,125608.72,1,1,0,122073.48,0 -5133,15579826,Young,439,France,Female,66,9,0,1,1,0,65535.56,0 -5134,15668104,Kerr,479,Spain,Male,37,6,118433.94,1,0,1,160060.9,0 -5135,15641604,Frolova,850,France,Female,55,10,98488.08,1,1,0,155879.57,1 -5136,15587240,Vasilyev,518,France,Male,40,4,0,2,0,1,194416.58,0 -5137,15680767,Sabbatini,717,Germany,Female,64,10,98362.35,2,1,1,21630.21,0 -5138,15601594,Ifeanacho,698,France,Female,51,6,144237.91,4,1,0,157143.61,1 -5139,15589969,Capon,850,France,Male,34,6,0,1,0,1,52796.31,0 -5140,15703728,Chieloka,700,Spain,Male,47,4,0,1,1,0,121798.52,1 -5141,15617790,Hanson,626,France,Female,29,4,105767.28,2,0,0,41104.82,0 -5142,15662500,Ts'ao,774,Spain,Male,32,9,0,2,1,0,10604.48,0 -5143,15778526,Bradshaw,719,Spain,Female,48,5,0,2,0,0,78563.66,0 -5144,15670584,Nkemakolam,646,Spain,Male,31,2,0,1,1,1,170821.43,1 -5145,15748069,Clunie,485,France,Female,25,3,134467.26,1,1,1,113266.09,0 -5146,15680597,Cover,784,Germany,Male,38,1,138515.02,1,1,1,171768.76,0 -5147,15628992,Esposito,850,Germany,Male,32,2,128647.98,2,0,0,54416.18,0 -5148,15719624,Hodgson,669,France,Female,38,9,121858.98,1,1,0,130755.34,0 -5149,15812767,Harvey,731,Spain,Male,70,3,0,2,1,1,141180.66,0 -5150,15689201,Dobie,721,France,Female,49,1,120108.56,1,0,1,183421.76,0 -5151,15614716,Okwudilichukwu,515,France,Female,37,0,196853.62,1,1,1,132770.11,0 -5152,15683618,Dyer,774,France,Female,35,3,121418.62,1,1,1,24400.37,0 -5153,15799631,Chase,585,Spain,Male,36,10,0,2,1,1,180318.6,0 -5154,15692259,Baresi,695,France,Female,29,9,0,2,1,0,111565.45,0 -5155,15590966,Lo,729,Germany,Female,42,4,97495.8,2,0,0,2002.5,0 -5156,15656426,Tyler,713,France,Female,42,3,0,2,0,0,82565.01,0 -5157,15675256,Ts'ui,555,Spain,Male,33,5,127343.4,1,0,1,121789.3,0 -5158,15751185,Aparicio,699,Spain,Female,50,0,158633.61,1,1,0,193785.87,0 -5159,15789582,Macleod,587,France,Male,55,9,0,1,1,0,64593.07,0 -5160,15651103,Sal,762,Spain,Female,69,9,183744.98,1,1,1,196993.69,0 -5161,15672299,Yeh,510,France,Male,44,6,0,2,1,1,175518.31,0 -5162,15772250,Udegbunam,842,Spain,Male,46,9,0,1,0,0,17268.02,0 -5163,15763922,Alexandrov,608,France,Male,31,7,79962.92,2,1,0,60901.72,0 -5164,15633870,Ozioma,850,France,Female,36,10,0,2,1,1,100750.03,0 -5165,15624323,Atkins,642,France,Male,36,4,0,2,1,1,195224.91,0 -5166,15688612,Campos,850,France,Male,33,7,140956.99,1,0,0,3510.18,0 -5167,15694644,Wood,455,Spain,Female,43,6,0,1,1,1,81250.79,0 -5168,15587174,Kerr,726,France,Male,29,7,0,2,1,1,91844.14,1 -5169,15579559,Chienezie,544,Spain,Male,30,8,145241.63,1,1,1,80676.83,0 -5170,15775430,Tsou,651,Germany,Male,31,7,138008.06,2,1,0,129912.74,0 -5171,15623695,McKinnon,814,France,Female,31,4,0,2,1,1,142029.17,0 -5172,15760849,Nwachukwu,537,France,Male,39,2,0,2,1,1,137651.6,0 -5173,15813095,Nwebube,553,France,Male,37,2,0,2,1,0,33877.29,0 -5174,15705281,Burt,800,Spain,Male,38,9,0,1,1,0,78744.39,0 -5175,15812594,Ross,791,France,Male,34,7,0,2,1,0,96734.46,0 -5176,15626322,Lees,699,Spain,Female,29,9,127570.93,2,1,0,164756.81,0 -5177,15723105,Feetham,756,France,Female,28,6,0,1,1,1,164394.65,0 -5178,15588449,Chuang,591,Spain,Female,27,5,107812.67,1,0,1,162501.83,1 -5179,15794849,Aitken,850,Germany,Male,22,7,91560.58,2,0,0,10541.38,0 -5180,15620000,Chambers,760,Germany,Male,34,6,121303.77,2,1,1,59325.21,0 -5181,15799720,Coburn,569,Spain,Male,43,8,161546.68,2,0,1,178187.28,0 -5182,15711287,Ahmed,661,Spain,Female,35,5,128415.45,1,1,0,142626.49,0 -5183,15613102,Ogochukwu,670,France,Female,31,2,57530.06,1,1,1,181893.31,1 -5184,15621440,Soto,694,France,Male,38,1,0,2,0,1,156858.2,0 -5185,15677146,Obiajulu,728,France,Female,28,4,142243.54,2,1,0,33074.51,0 -5186,15801169,Yegorova,764,Germany,Female,39,9,138341.51,1,1,0,50072.94,1 -5187,15722425,Lucchese,639,France,Male,32,9,0,2,1,0,111340.36,0 -5188,15682421,Talbot,683,France,Female,30,2,0,2,0,1,100496.84,1 -5189,15691910,Lu,663,Spain,Male,30,4,0,3,1,0,101371.05,0 -5190,15721779,Arnold,826,Spain,Male,41,5,146466.46,2,0,0,180934.67,0 -5191,15579548,Nicholson,735,Spain,Male,36,5,0,2,1,0,105152.17,0 -5192,15681075,Chukwualuka,682,France,Female,58,1,0,1,1,1,706.5,0 -5193,15607884,Wallace,663,France,Female,39,8,0,2,1,1,101168.9,0 -5194,15767757,Pisano,562,Spain,Female,29,9,120307.58,1,1,1,6795.61,0 -5195,15791550,Kelly,696,France,Male,27,4,87637.26,2,0,0,196111.35,0 -5196,15658589,Brady,850,Spain,Male,38,2,94652.04,1,1,1,171960.76,0 -5197,15670822,Palmer,719,France,Female,22,7,114415.84,1,1,1,177497.4,0 -5198,15629744,Tan,804,France,Female,71,8,0,2,0,1,147995.96,0 -5199,15660768,L?,604,France,Male,40,1,84315.02,1,0,0,36209.1,0 -5200,15726310,Mordvinova,782,Spain,Female,27,3,0,2,1,0,143614.01,0 -5201,15641298,Corones,512,Germany,Male,42,9,93955.83,2,1,0,14828.54,0 -5202,15625675,Clements,569,France,Male,36,1,67087.69,1,1,0,154775.7,0 -5203,15713354,Morrice,597,Germany,Female,22,6,101528.61,1,1,0,70529,1 -5204,15633866,Hsiung,753,Germany,Male,30,1,110824.52,1,1,1,57896.27,0 -5205,15704231,Barrett,430,France,Female,33,8,0,1,1,1,69759.91,0 -5206,15735400,Kanayochukwu,756,France,Male,28,8,179960.2,1,1,0,89938.08,0 -5207,15632826,Tardent,493,France,Male,38,3,134006.77,1,1,0,89578.32,0 -5208,15751022,Bowhay,777,Germany,Female,37,10,121532.17,2,1,1,73464.88,0 -5209,15664737,Lei,779,Spain,Female,38,7,0,2,1,1,138542.87,0 -5210,15681126,Baker,702,Spain,Female,38,2,0,1,1,1,161888.63,0 -5211,15738954,Pisano,551,France,Male,35,7,129717.3,2,0,0,86937.2,0 -5212,15662263,Castillo,749,Germany,Male,22,4,94762.16,2,1,1,42241.54,0 -5213,15621611,Gibson,742,Germany,Male,55,5,155196.17,1,0,1,121207.66,1 -5214,15783752,Lindsay,752,Germany,Male,29,4,129514.99,1,1,1,102930.46,0 -5215,15709474,Macnamara,740,Germany,Female,57,3,113386.36,2,1,1,65121.63,1 -5216,15701280,Romano,576,France,Male,24,3,0,1,0,1,78498.04,1 -5217,15671104,Aksakova,637,Spain,Male,43,3,172196.23,1,1,1,104769.96,0 -5218,15796434,Farnsworth,724,France,Male,28,5,97612.12,1,1,1,96498.14,0 -5219,15781505,Giordano,685,France,Male,20,4,104719.94,2,1,0,38691.34,0 -5220,15625819,Arnold,625,France,Female,38,7,0,1,1,0,164804.02,0 -5221,15753174,Thompson,571,Germany,Male,37,9,139592.98,3,1,0,104152.65,1 -5222,15654067,Koch,584,Spain,Female,29,4,0,2,1,0,88866.92,0 -5223,15724719,Jones,550,France,Female,22,7,139096.85,1,1,0,129890.94,0 -5224,15624695,Otitodilinna,662,Spain,Female,72,7,140301.72,1,0,1,179258.67,0 -5225,15718216,Fleetwood-Smith,803,Spain,Male,43,3,0,1,1,0,72051.44,0 -5226,15586300,Chinonyelum,615,France,Male,66,7,0,2,1,1,74580.8,0 -5227,15783349,Montague,481,Spain,Male,39,1,111233.09,1,1,1,123995.15,0 -5228,15725767,Milani,701,France,Male,23,3,0,2,1,0,38960.59,0 -5229,15791925,Palermo,751,France,Male,29,10,147737.63,1,0,1,94951.27,0 -5230,15793585,Anderson,675,France,Male,35,8,0,2,1,1,56642.97,0 -5231,15576641,Crawford,733,Germany,Male,40,5,125725.02,2,1,1,50783.1,0 -5232,15749519,Lin,822,France,Male,38,6,128289.7,3,1,0,9149.96,1 -5233,15684960,Yewen,559,France,Female,46,5,0,1,1,0,21006.1,1 -5234,15591286,Simmons,731,Germany,Female,49,4,88826.07,1,1,1,33759.41,1 -5235,15668323,Mbadiwe,678,France,Female,41,1,143443.61,1,1,0,196622.28,1 -5236,15608528,Munro,645,France,Female,68,9,0,4,1,1,176353.87,1 -5237,15645184,Graham,701,France,Male,29,2,0,2,1,0,176943.59,0 -5238,15702566,Lombardo,554,Spain,Male,26,8,149134.46,1,1,1,177966.24,0 -5239,15660840,Kalinin,723,France,Male,30,3,124119.54,1,1,0,162198.32,0 -5240,15750811,Woodward,766,Germany,Male,44,3,116822.7,1,0,0,197643.24,0 -5241,15733842,Pirozzi,597,France,Female,24,1,103219.47,1,1,0,60420.07,0 -5242,15581526,Iweobiegbulam,574,France,Male,41,1,0,2,0,0,70550,0 -5243,15662751,Piazza,655,Germany,Female,40,0,81954.6,1,1,1,198798.44,1 -5244,15684319,Baranova,780,Germany,Female,37,10,95196.26,1,1,0,126310.39,1 -5245,15702190,Fan,672,Spain,Male,43,5,0,2,1,1,64515.5,0 -5246,15588517,Sun,717,France,Male,38,7,0,2,1,1,158580.05,0 -5247,15801863,Marino,521,France,Female,32,2,136555.01,2,1,1,129353.21,0 -5248,15584271,Donaldson,633,France,Male,59,5,0,1,1,1,137273.97,0 -5249,15700366,Burton,669,France,Male,39,3,119452.03,1,1,1,171575.54,0 -5250,15804038,Quinn,740,France,Male,44,9,0,1,0,1,96528,1 -5251,15720820,Sabbatini,462,Germany,Female,24,9,69881.09,2,0,1,64421.02,0 -5252,15743759,Brooks,619,France,Male,39,5,0,2,1,1,158444.61,0 -5253,15749947,Black,665,France,Female,44,7,0,2,1,1,66548.58,0 -5254,15670496,Schwartz,655,Spain,Female,27,9,0,2,0,0,108008.05,0 -5255,15746664,Ts'ui,463,Spain,Male,20,8,204223.03,1,1,0,128268.39,0 -5256,15745533,Sargent,799,France,Female,63,1,110314.21,2,1,0,37464,1 -5257,15761497,Udinesi,713,Spain,Female,48,1,163760.82,1,0,0,157381.14,1 -5258,15628600,Lee,807,Germany,Female,31,1,141069.18,3,1,1,194257.11,0 -5259,15627002,Taylor,728,France,Male,38,1,115934.74,1,1,1,139059.05,0 -5260,15614635,Kepley,582,France,Male,52,2,151457.88,1,0,1,40893.61,0 -5261,15731281,Ozuluonye,704,Germany,Female,35,3,154206.07,2,1,1,40261.49,0 -5262,15814022,Lassetter,714,France,Female,26,9,89928.99,1,1,0,46203.31,0 -5263,15659194,Mishina,628,France,Male,30,8,89182.09,1,1,1,13126.9,0 -5264,15745030,Trevisano,809,Germany,Male,41,1,79706.25,2,1,0,165675.01,0 -5265,15691817,Iloerika,547,Spain,Female,44,5,0,3,0,0,5459.07,1 -5266,15707488,Tan,560,France,Female,27,5,0,2,1,0,131919.48,0 -5267,15784700,Chikelu,811,France,Male,31,7,117799.28,1,1,1,182372.35,0 -5268,15710397,Lin,584,France,Male,26,4,0,2,1,0,147600.54,0 -5269,15687648,Nicholson,691,France,Male,28,1,0,2,0,0,92865.41,0 -5270,15732281,Ugoji,680,Germany,Male,34,6,146422.22,1,1,0,67142.97,1 -5271,15607230,Michel,588,Germany,Male,33,9,150186.22,2,1,1,65611.01,0 -5272,15567630,Bruce,721,Germany,Male,40,6,100275.88,1,1,0,138564.48,1 -5273,15587507,Feng,850,France,Male,47,6,0,1,1,0,187391.02,1 -5274,15733904,McDonald,529,France,Male,32,9,147493.89,1,1,0,33656.35,0 -5275,15709511,Watt,622,France,Male,43,8,0,2,1,0,100618.17,0 -5276,15579616,Goodwin,683,France,Female,42,8,0,2,0,1,198134.9,0 -5277,15694852,Arcuri,575,France,Male,29,4,121823.4,2,1,1,50368.87,0 -5278,15589924,Rapuluolisa,577,Spain,Female,40,1,0,2,1,1,108787,0 -5279,15799300,Kao,510,Germany,Male,31,0,113688.63,1,1,0,33099.41,1 -5280,15731330,Tsui,652,Spain,Female,40,7,100471.34,1,1,1,124550.88,0 -5281,15694129,Summers,569,Germany,Female,28,3,100032.52,1,1,0,5159.21,1 -5282,15620372,Cross,687,Spain,Male,31,3,0,2,0,0,48228.1,0 -5283,15744622,Osorio,822,France,Male,32,8,116358,1,1,0,108798.36,0 -5284,15799815,Bobrov,656,Germany,Female,23,4,163549.63,1,0,1,21085.12,0 -5285,15759250,Barnett,745,Germany,Male,51,3,99183.9,1,1,1,28922.25,0 -5286,15732643,Pike,386,Spain,Female,53,1,131955.07,1,1,1,62514.65,1 -5287,15690540,Gearheart,684,Spain,Female,41,1,134177.06,1,0,0,177506.66,0 -5288,15803078,Bruno,635,Spain,Female,38,1,0,2,1,0,90605.05,0 -5289,15652180,Egobudike,582,France,Male,30,2,0,2,1,1,132029.95,0 -5290,15741195,Okechukwu,613,Spain,Male,19,5,0,1,1,1,176903.35,0 -5291,15743490,Zikoranachidimma,795,Germany,Female,56,9,94348.94,1,1,0,29239.29,1 -5292,15575510,Milanesi,659,France,Female,32,2,155584.21,1,0,1,153662.88,0 -5293,15732610,Ahern,745,France,Female,28,6,0,2,1,0,154389.18,0 -5294,15602909,Dickson,604,Spain,Female,41,10,0,2,1,1,166224.39,0 -5295,15734058,Anayochukwu,509,Germany,Male,32,9,170661.47,1,1,1,21646.2,0 -5296,15801788,McDonald,706,Germany,Female,29,6,185544.36,1,1,0,171037.63,0 -5297,15702462,Fiorentini,619,Spain,Female,44,6,52831.13,1,1,1,112649.22,1 -5298,15683416,Russo,572,Germany,Male,51,8,97750.07,3,1,1,193014.26,1 -5299,15794187,Young,695,France,Male,36,6,114007.5,2,1,0,118120.88,0 -5300,15792989,Bianchi,543,France,Female,71,1,104308.77,1,1,1,25650.04,0 -5301,15613734,Fallaci,640,France,Female,33,6,84719.13,2,1,1,113048.79,0 -5302,15606177,Crawford,672,France,Male,39,2,0,2,1,0,87372.49,0 -5303,15636700,Marsh,701,France,Male,39,9,140236.98,1,0,1,146651.99,0 -5304,15645766,Kosisochukwu,634,Spain,Male,25,9,0,2,1,1,8227.91,0 -5305,15671345,Piccio,531,Spain,Female,42,6,75302.85,2,0,0,57034.35,0 -5306,15652469,Nevels,699,France,Male,27,1,0,2,1,0,93003.21,0 -5307,15749638,Kaodilinakachukwu,605,France,Female,51,9,104760.82,1,1,1,165574.54,1 -5308,15728706,Amaechi,534,France,Female,49,7,0,1,1,0,13566.48,1 -5309,15735439,P'an,449,Spain,Female,31,1,113693,1,0,0,82796.29,0 -5310,15778696,Ikemefuna,684,Spain,Female,36,5,174180.39,1,1,0,119830.08,0 -5311,15624744,Tai,622,Germany,Male,42,9,115766.26,1,0,0,72155.85,1 -5312,15584338,Winn,714,France,Female,40,0,0,2,1,0,62762.12,0 -5313,15726178,Hardy,712,Spain,Female,48,8,0,2,1,0,183235.33,0 -5314,15794939,Chiu,783,France,Female,72,5,121215.9,2,1,1,105206.48,0 -5315,15788068,Lopez,743,Germany,Male,45,10,144677.19,3,1,0,22512.44,1 -5316,15572956,Steen,683,France,Male,36,5,115350.63,1,1,1,122305.91,0 -5317,15780386,Ferri,654,Spain,Male,40,5,105683.63,1,1,0,173617.09,0 -5318,15791114,Yegorova,700,France,Male,37,1,135179.49,1,1,0,160670.37,0 -5319,15708046,Knowles,744,Spain,Male,31,0,117551.23,1,1,0,158958.9,0 -5320,15719779,May,645,Germany,Male,25,1,157404.02,2,1,0,93073.04,0 -5321,15591550,Bianchi,525,Spain,Male,36,3,77910.23,1,1,0,67238.01,0 -5322,15639368,Pipes,732,France,Male,25,0,110942.9,1,0,0,172576.56,0 -5323,15699830,Doherty,721,France,Female,40,7,0,2,1,1,122580.48,0 -5324,15569264,Yobanna,622,France,Male,32,5,179305.09,1,1,1,149043.78,0 -5325,15595158,Hsu,654,Germany,Male,31,5,150593.59,2,1,1,105218.45,0 -5326,15599126,Russell,529,France,Female,43,0,123815.86,1,1,1,78463.99,1 -5327,15650575,Payne,720,Spain,Female,59,6,0,2,1,1,160849.43,1 -5328,15641490,Windsor,850,Germany,Female,25,8,69385.17,2,1,0,87834.24,0 -5329,15680234,Bray,667,Germany,Male,27,2,138032.15,1,1,0,166317.71,0 -5330,15592230,Seleznyov,620,France,Male,41,3,0,2,1,1,137309.06,0 -5331,15626212,Wark,616,France,Male,29,9,0,1,1,1,166984.44,0 -5332,15700627,Y?,637,Germany,Female,46,2,143500.82,1,1,0,166996.46,1 -5333,15782641,Brown,710,Spain,Female,29,3,119670.18,1,1,0,188022.44,0 -5334,15784445,Huang,717,Spain,Male,33,1,99106.73,1,0,0,194467.23,0 -5335,15813681,Zito,786,Germany,Male,24,2,120135.55,2,1,1,125449.47,0 -5336,15596649,Bailey,651,France,Female,39,8,0,1,1,0,137452.57,0 -5337,15700460,Allnutt,530,France,Female,55,4,120905.03,1,0,1,123475.88,1 -5338,15724076,Christie,815,Spain,Female,57,5,0,3,0,0,38941.44,1 -5339,15784000,Pope,715,Germany,Female,34,9,102277.52,1,0,0,177852.57,1 -5340,15733966,Johnstone,496,Germany,Female,55,4,125292.53,1,1,1,31532.96,1 -5341,15612667,Bird,680,Spain,Male,42,0,0,1,1,0,136377.21,0 -5342,15654025,Jones,646,France,Female,51,4,101629.3,1,0,0,130541.1,0 -5343,15589431,Pedder,807,Germany,Male,47,1,171937.27,1,1,1,65636.92,0 -5344,15578238,Calabrese,727,France,Male,47,7,0,2,1,0,193305.35,0 -5345,15566269,Chialuka,787,France,Male,25,5,0,2,1,0,47307.9,0 -5346,15639217,McKenzie,806,France,Male,34,6,0,2,0,0,100809.99,0 -5347,15688644,Holloway,603,France,Male,31,1,129743.75,1,1,0,109145.2,0 -5348,15662426,Tang,649,Spain,Male,32,1,0,1,0,1,91167.19,1 -5349,15720511,Byrne,547,Germany,Male,41,3,151191.31,1,1,0,175295.89,1 -5350,15567246,Selwyn,684,Germany,Male,32,3,102630.13,2,1,1,127433.47,0 -5351,15647965,Genovese,477,France,Female,57,9,114023.64,2,1,1,71167.17,1 -5352,15679048,Koger,558,Germany,Male,41,2,124227.14,1,1,1,111184.67,0 -5353,15675749,Baranov,695,France,Female,23,1,0,2,1,1,141756.32,0 -5354,15782181,Greco,592,Spain,Male,35,6,80285.16,1,1,0,72678.75,1 -5355,15795738,Owens,789,France,Male,31,4,175477.15,1,1,1,172832.9,0 -5356,15773751,Y?,597,France,Female,29,1,132144.35,1,1,0,158086.33,0 -5357,15655436,Kendall,839,Germany,Male,47,2,136911.07,1,1,1,168184.62,1 -5358,15691396,Ko,405,Germany,Male,31,5,133299.67,2,1,1,72950.14,0 -5359,15796958,Tang,658,France,Male,39,7,0,2,1,0,48378.4,0 -5360,15801832,Lombardo,684,Germany,Male,42,1,117691,1,1,1,23135.65,1 -5361,15661349,Perkins,633,France,Male,35,10,0,2,1,0,65675.47,0 -5362,15719265,Feng,589,France,Male,46,9,0,2,1,0,170676.67,0 -5363,15779985,Lo,750,Germany,Female,37,1,133199.71,2,1,1,27366.77,0 -5364,15663410,Piccio,771,Spain,Male,51,5,135506.58,3,1,1,152479.64,1 -5365,15704144,Mazzanti,812,Germany,Male,33,2,127154.14,2,0,1,105383.49,0 -5366,15774104,Chukwualuka,539,Spain,Male,39,2,0,2,1,1,48189.94,0 -5367,15812230,Elliot,670,Germany,Female,42,5,49508.79,3,1,1,100324.01,0 -5368,15742848,Gratton,673,France,Male,41,5,0,1,1,1,65657.29,0 -5369,15745326,Carandini,538,France,Female,62,3,75051.49,1,0,0,17682.02,1 -5370,15674541,Robinson,575,Spain,Male,52,8,123925.23,1,0,0,111342.66,1 -5371,15728564,Lo,682,France,Male,41,6,0,2,0,1,134158.09,1 -5372,15580701,Ma,712,France,Male,33,3,153819.58,1,1,0,79176.09,1 -5373,15688973,Vinogradova,598,Spain,Female,39,5,0,2,1,1,83103.46,0 -5374,15709412,H?,776,Spain,Male,30,6,0,2,0,1,63908.86,0 -5375,15607753,Alexandrova,606,Spain,Female,23,10,70417.79,1,0,1,90896.04,0 -5376,15705352,Yang,686,Spain,Male,38,7,111484.88,1,1,1,76076.2,0 -5377,15602500,Maslova,850,Spain,Male,38,1,146343.98,1,0,1,103902.11,0 -5378,15672437,Buccho,642,France,Male,72,1,160541,2,1,1,142223.94,0 -5379,15720968,Young,606,Germany,Male,27,2,130274.26,2,1,0,147533.09,0 -5380,15730796,Barker,627,France,Female,21,7,98993.02,1,1,1,169156.64,0 -5381,15768219,Sung,850,Spain,Male,36,0,0,2,1,0,141242.57,0 -5382,15663883,Hansen,850,Germany,Male,32,9,141827.33,2,1,1,149458.73,0 -5383,15589296,Brown,724,France,Female,40,6,110054.45,1,1,1,86950.72,0 -5384,15586425,Lo Duca,579,France,Male,28,4,0,2,1,1,176925.69,0 -5385,15679813,Ellis,727,Spain,Male,28,1,0,1,1,0,40357.39,0 -5386,15681410,Korff,813,Germany,Female,36,6,98088.09,1,0,1,26687.22,1 -5387,15668283,Gardiner,642,France,Male,48,9,118317.27,4,0,0,78702.98,1 -5388,15624072,Kiernan,669,Spain,Male,22,10,0,2,1,0,176163.74,0 -5389,15669664,Thompson,574,Germany,Male,54,1,99774.5,1,0,0,4896.11,1 -5390,15682728,Mathews,774,France,Female,32,4,0,2,0,0,114899.13,0 -5391,15573851,Macrossan,735,France,Female,38,1,0,3,0,0,92220.12,1 -5392,15733661,Illingworth,639,Spain,Female,27,8,133806.54,2,1,0,6251.3,0 -5393,15710012,Bowen,738,Spain,Male,44,2,0,2,1,0,43018.82,1 -5394,15763327,Craig,835,France,Male,32,8,124993.29,2,1,1,27548.06,0 -5395,15668853,Menhennitt,637,Spain,Female,44,0,157622.58,1,1,1,120454.2,0 -5396,15639303,Moore,589,Germany,Male,48,5,126111.61,1,0,1,133961.19,0 -5397,15691011,Shoebridge,591,France,Male,42,9,161651.37,2,1,1,131753.97,0 -5398,15638513,Palermo,723,France,Female,40,7,142856.95,2,0,0,38019.74,0 -5399,15648933,Reilly,831,Germany,Male,44,3,111100.98,1,1,1,28144.07,1 -5400,15628904,Bowen,733,Spain,Male,35,8,102918.38,1,1,1,45959.86,0 -5401,15644788,Fyodorov,731,France,Female,30,5,0,2,1,0,189528.72,0 -5402,15598161,Clements,654,France,Male,47,10,0,2,1,0,170481.98,0 -5403,15745624,McKenzie,828,France,Male,37,4,0,2,1,0,94845.45,0 -5404,15733169,Craig,590,Spain,Male,22,7,125265.61,1,1,1,161253.08,0 -5405,15801417,Iloerika,657,France,Male,37,4,82500.28,1,1,1,115260.72,0 -5406,15592707,Dolgorukova,531,Germany,Female,64,2,175754.87,2,1,1,60721.4,0 -5407,15593954,Eva,516,France,Female,47,6,109387.33,1,0,0,121365.45,0 -5408,15714431,Yeh,561,France,Male,37,1,100443.36,2,0,1,101693.73,0 -5409,15638257,P'an,682,Spain,Female,54,0,83102.72,2,1,1,54132.93,0 -5410,15690939,Howe,575,Spain,Male,28,7,0,1,1,1,10666.05,0 -5411,15723613,Jenkins,623,France,Female,28,4,0,2,1,0,41227.67,0 -5412,15813640,Shih,642,France,Female,40,7,0,2,1,0,10712.82,0 -5413,15707322,Nnamdi,779,France,Female,48,2,115290.27,1,0,0,98912.69,1 -5414,15588918,Mitchell,671,France,Female,42,6,0,2,1,0,197202.48,0 -5415,15600357,Findlay,495,France,Female,40,1,140197.71,2,1,0,150720.39,0 -5416,15747014,Pisani,850,France,Female,28,1,105245.34,1,0,1,74780.13,0 -5417,15809830,Belisario,630,France,Male,50,8,0,2,0,1,79377.45,0 -5418,15662245,Pomeroy,588,France,Male,32,1,0,2,1,1,8763.87,0 -5419,15651075,Ibrahimova,562,Germany,Male,35,3,142296.13,1,0,1,177112.7,0 -5420,15594456,K?,740,Spain,Female,56,4,99097.33,1,1,1,85016.64,1 -5421,15583462,Graham,695,France,Male,28,5,171069.39,2,1,1,88689.4,0 -5422,15757661,Trevisano,589,France,Female,39,7,0,2,0,0,95985.64,0 -5423,15729117,Trevisano,607,France,Female,31,1,102523.88,1,1,1,166792.71,0 -5424,15749671,K?,794,France,Male,35,6,0,2,1,1,68730.91,0 -5425,15566253,Manning,580,Germany,Male,44,9,143391.07,1,0,0,146891.07,1 -5426,15595153,Tucker,644,Germany,Female,44,8,106022.73,2,0,0,148727.42,0 -5427,15698572,Schaffer,636,Spain,Female,36,1,0,1,1,0,43134.58,0 -5428,15674149,Esomchi,599,Germany,Male,36,3,128960.21,2,1,1,40318.33,0 -5429,15623082,Ch'ang,507,France,Female,35,2,0,2,1,0,97633.93,0 -5430,15797905,Walker,682,France,Female,48,7,0,2,1,0,65069.03,0 -5431,15746028,Chu,714,France,Female,24,7,0,2,1,0,166335,0 -5432,15582951,Crawford,696,France,Female,25,8,126442.59,1,1,0,121904.44,0 -5433,15616471,Milne,599,Spain,Male,51,0,0,1,1,1,175235.99,0 -5434,15641575,Anenechukwu,577,France,Male,37,2,127261.35,1,1,0,56185.05,0 -5435,15638803,Donaldson,733,Spain,Female,32,5,0,2,1,0,131625.14,0 -5436,15808283,Kelly,647,France,Female,33,4,0,1,1,0,152323.04,0 -5437,15811200,Ts'ao,831,France,Female,34,2,0,2,0,0,165840.94,0 -5438,15733476,Gonzalez,543,Germany,Male,30,6,73481.05,1,1,1,176692.65,0 -5439,15633274,Tai,679,France,Male,34,7,160515.37,1,1,0,121904.14,0 -5440,15582168,Muravyova,713,Germany,Female,61,4,149525.34,2,1,0,123663.63,0 -5441,15807269,Milanesi,690,Germany,Male,43,2,166522.78,1,0,0,119644.59,1 -5442,15602979,Lin,751,France,Male,29,1,135536.5,1,1,0,66825.33,0 -5443,15660417,Lambert,613,Germany,Female,43,10,120481.69,1,0,0,94875.03,1 -5444,15590199,Temple,701,Spain,Male,28,1,103421.32,1,0,1,76304.73,0 -5445,15641794,Ridley,698,France,Male,33,5,135658.73,2,0,1,39755,0 -5446,15779174,Young,451,France,Female,36,2,0,2,1,1,180142.42,0 -5447,15785547,Slye,665,France,Male,28,8,191402.82,2,1,0,83238.4,0 -5448,15795124,Pan,726,Germany,Male,50,9,94504.35,1,0,1,5078.9,0 -5449,15718912,Hsueh,608,Germany,Female,44,5,126147.84,1,0,1,132424.69,1 -5450,15592028,Roberts,549,France,Female,46,7,0,1,1,1,109057.56,0 -5451,15580227,Moss,803,France,Male,33,6,0,2,1,0,115676.61,0 -5452,15657830,Andrews,663,France,Male,43,4,87624.03,2,1,0,149401.33,0 -5453,15798256,Takasuka,558,France,Female,45,1,153697.53,2,0,0,89891.4,1 -5454,15643819,Dawson,714,France,Female,25,4,0,2,0,0,82500.84,0 -5455,15754301,Bruche,704,France,Male,39,5,0,1,1,0,6416.92,0 -5456,15726855,Oliver,805,Germany,Female,45,9,116585.97,1,1,0,189428.75,1 -5457,15755225,Ryan,659,Germany,Male,34,9,134464.58,2,1,0,178833.34,0 -5458,15725221,Sabbatini,738,Germany,Male,62,10,83008.31,1,1,1,42766.03,0 -5459,15789055,Watt,635,Spain,Male,35,2,113635.16,1,1,0,90883.12,0 -5460,15617507,Wilson,530,Spain,Female,36,7,0,2,1,0,80619.09,0 -5461,15668894,Abramova,661,Germany,Male,41,5,122552.48,2,0,1,120646.4,0 -5462,15589563,Purdy,531,Spain,Male,31,2,118899.45,2,0,0,41409.36,0 -5463,15693162,Higgins,694,France,Female,29,5,99713.87,1,0,0,112317.89,0 -5464,15750099,Marshall,731,France,Female,36,6,0,1,0,0,152128.36,0 -5465,15795540,Reye,556,France,Female,36,2,134208.22,1,0,1,177670.57,0 -5466,15794941,Chibueze,647,Germany,Female,41,1,85906.65,3,1,0,189159.97,0 -5467,15611848,Kwemtochukwu,850,Germany,Male,32,3,137714.25,1,0,1,159403.68,0 -5468,15581237,Biryukova,573,Spain,Male,33,1,160777.9,1,1,1,149536.15,0 -5469,15738150,Chidozie,591,France,Male,45,5,0,2,1,1,155492.87,0 -5470,15678571,Barber,723,France,Male,21,4,0,2,0,0,24847.02,0 -5471,15736124,Thompson,617,France,Male,25,1,102585.88,2,1,1,115387.4,0 -5472,15623202,Maslov,704,Germany,Female,39,10,102556.18,2,1,0,171971.25,1 -5473,15804201,Jones,457,Germany,Male,42,4,126772.57,1,0,1,126106.4,0 -5474,15596863,Chidumaga,787,Germany,Female,38,3,158373.23,1,1,1,28228.35,0 -5475,15696277,Hs?,651,France,Female,34,9,0,2,1,0,138113.71,0 -5476,15748608,Trentini,612,Germany,Male,42,5,141927.1,1,1,1,43018.98,0 -5477,15723864,Lucas,828,Spain,Male,47,1,109876.82,2,1,0,83611.45,1 -5478,15802390,Willoughby,724,France,Female,34,2,0,2,1,1,118863.38,0 -5479,15774336,Jamieson,648,Germany,Male,44,9,111369.79,2,1,1,91947.74,0 -5480,15648766,Robertson,569,Spain,Male,35,3,116969.35,1,0,0,94488.82,0 -5481,15659094,Ojiofor,765,Germany,Female,34,8,136729.51,2,0,0,47058.21,0 -5482,15606397,Cameron,577,Germany,Female,44,1,152086.15,1,0,1,44719.5,1 -5483,15642619,Mayne,603,Spain,Male,46,2,0,2,1,0,174478.54,0 -5484,15666032,Mancini,568,Spain,Male,28,1,127289.28,1,0,0,45611.51,0 -5485,15595842,Paramor,748,Germany,Male,45,2,119852.01,1,0,0,73853.94,1 -5486,15753837,Young,573,Spain,Male,38,4,0,2,1,1,196517.43,0 -5487,15783882,Daly,771,Spain,Female,41,5,0,2,0,1,92914.67,0 -5488,15799790,Carter,763,France,Male,35,9,0,1,1,1,31372.91,0 -5489,15628155,Dike,410,France,Female,35,7,117183.74,1,1,1,109733.73,0 -5490,15703778,Hughes,728,France,Male,33,8,129907.63,1,0,1,36083.96,0 -5491,15722322,Green,655,Spain,Female,78,2,0,2,0,1,188435.38,0 -5492,15639278,Chinomso,580,Germany,Female,36,6,145387.32,2,1,1,169963.2,1 -5493,15568487,Gorshkov,712,France,Male,35,7,124616.23,1,1,1,69320.97,0 -5494,15682084,Chinomso,680,France,Male,31,9,0,2,1,0,36145.53,0 -5495,15642821,Ijendu,383,Spain,Female,48,8,95808.19,1,0,0,137702.01,1 -5496,15601387,Yen,721,France,Male,35,10,0,2,1,0,71594.26,0 -5497,15642515,Arcuri,620,France,Female,42,1,0,2,0,1,65565.92,0 -5498,15710421,Baresi,774,Spain,Female,36,8,117152.3,1,0,0,101828.39,0 -5499,15726774,Field,563,France,Male,35,3,106250.72,1,0,0,39546.32,0 -5500,15649078,Christian,850,Germany,Female,27,8,111837.78,2,1,1,110805.79,0 -5501,15641877,Ross,681,France,Male,47,9,97023.21,1,1,1,2168.13,0 -5502,15796496,Trevisani,631,France,Female,31,8,137687.72,1,1,0,190067.12,0 -5503,15815690,Akabueze,614,Spain,Female,40,3,113348.5,1,1,1,77789.01,0 -5504,15631739,Dunn,704,Spain,Male,24,10,122109.78,1,1,1,127654.37,0 -5505,15625584,Martin,786,France,Male,32,2,120452.4,2,0,0,79602.86,0 -5506,15802466,Donaldson,534,France,Female,53,7,0,2,1,1,80619.17,0 -5507,15697028,McClinton,590,Spain,Male,34,0,65812.35,2,0,1,160346.3,0 -5508,15575759,Bentley,583,Spain,Female,40,3,54428.37,1,1,0,109638.78,1 -5509,15567442,Ibezimako,656,France,Female,75,3,0,2,1,1,1276.87,0 -5510,15746805,Thomson,597,France,Male,33,9,0,2,1,0,49374.82,0 -5511,15636330,Ch'in,588,Germany,Female,48,1,143279.58,2,1,0,31580.8,1 -5512,15714970,Holbrook,667,Germany,Male,32,0,103846.65,1,1,0,20560.69,0 -5513,15653784,Solomina,627,France,Male,37,2,125190.86,1,0,1,84584.69,0 -5514,15693543,McDonald,708,France,Female,33,8,0,2,0,1,15246.83,0 -5515,15773283,Dennis,641,France,Male,65,6,38340.02,1,1,0,32607.77,1 -5516,15742534,Faulk,527,Germany,Female,28,2,123802.98,2,1,1,155846.69,0 -5517,15569878,Dale,592,France,Male,37,3,96651.03,1,1,1,3232.82,0 -5518,15729454,Gorbunov,465,France,Male,33,8,0,2,1,0,177668.55,0 -5519,15578375,Farrell,628,France,Male,39,6,0,2,0,0,134441.6,0 -5520,15785559,De Luca,678,France,Male,43,1,133237.21,1,1,0,111032.79,1 -5521,15649414,Walker,570,France,Female,61,6,142105.35,1,1,1,45214.04,0 -5522,15701605,Forster,815,France,Male,37,1,166115.42,1,1,0,67208.3,0 -5523,15686696,Brown,817,France,Female,37,6,81070.34,2,1,0,80985.88,0 -5524,15625586,Monaldo,717,France,Male,35,4,0,1,1,1,167573.06,0 -5525,15654975,Wu,641,France,Female,53,0,123835.52,2,0,1,160110.65,0 -5526,15782993,Pan,624,France,Male,51,10,123401.43,2,1,1,127825.25,0 -5527,15774382,Longo,579,Germany,Male,49,4,169377.31,1,1,1,123535.05,0 -5528,15689602,Findlay,698,France,Male,38,2,130015.24,1,1,1,41595.3,0 -5529,15756155,Fu,645,France,Male,32,4,0,2,0,1,97628.08,0 -5530,15812647,Yin,691,France,Male,34,8,133936.04,2,1,0,91359.79,0 -5531,15736043,Hamilton,638,France,Male,34,6,114543.27,1,1,1,97755.29,0 -5532,15696744,Miller,705,France,Female,31,3,119794.67,1,0,0,182528.44,0 -5533,15602572,Hsing,720,France,Male,33,9,0,2,1,1,142956.48,0 -5534,15674765,Mitchell,553,Spain,Male,44,4,0,1,1,0,10789.3,0 -5535,15678725,Chamberlin,658,France,Female,29,8,0,2,0,1,130461.09,0 -5536,15694444,Buttenshaw,648,Germany,Female,32,8,157138.99,3,1,0,190994.48,1 -5537,15795878,Anayochukwu,636,Spain,Male,45,3,0,2,1,1,159463.8,0 -5538,15735346,Wallace,527,Germany,Female,41,10,136733.24,1,1,1,57589.29,0 -5539,15687094,Calabresi,717,Germany,Female,28,9,82498.14,2,0,0,40437.67,0 -5540,15790067,Sun,614,Spain,Male,39,3,151914.93,1,0,0,56459.45,0 -5541,15605742,Tuan,737,France,Male,43,0,80090.93,1,1,0,39920,1 -5542,15566740,Nazarova,587,Spain,Male,51,3,83739.32,1,0,1,148798.45,0 -5543,15664897,Bryant,682,France,Female,35,2,181166.44,1,1,1,63737.19,1 -5544,15585777,Pai,710,France,Male,38,3,130588.82,1,1,1,154997.64,0 -5545,15650864,Power,507,France,Male,42,6,0,2,1,0,34777.23,0 -5546,15806709,Hao,609,Germany,Male,33,6,94126.67,1,0,0,93718.16,0 -5547,15633818,McMillan,786,France,Male,32,9,0,2,1,0,133112.41,0 -5548,15713845,Merrett,688,France,Male,38,7,148045.68,1,1,0,175479.92,1 -5549,15639662,Phillips,710,France,Male,38,2,0,2,1,0,96.27,0 -5550,15567013,De Luca,779,Spain,Male,33,3,0,2,1,0,30804.68,0 -5551,15777784,Tu,733,France,Female,44,6,168165.84,1,0,1,197193.49,0 -5552,15800251,Elder,583,Germany,Female,26,10,72835.56,2,1,0,96792.15,0 -5553,15651315,Dilke,627,France,Male,41,3,0,2,1,0,132719.8,0 -5554,15651450,Panicucci,666,Germany,Male,31,3,123212.08,2,1,1,112157.31,0 -5555,15784218,Mason,620,Spain,Male,38,0,0,2,1,1,38015.34,0 -5556,15572398,Townsend,614,Spain,Female,39,6,0,2,1,1,164018.98,0 -5557,15707962,Gunson,606,France,Male,40,6,119501.88,2,1,0,46774.94,0 -5558,15705663,Milano,700,Germany,Female,39,5,144550.83,2,1,1,189664.43,0 -5559,15645355,Macleod,677,Germany,Male,34,3,126729.41,1,1,1,26106.39,1 -5560,15729557,Olisaemeka,850,Germany,Male,36,5,119984.07,1,1,0,191535.11,1 -5561,15631436,Gleeson,564,France,Male,35,4,0,1,1,0,158937.55,0 -5562,15583073,Martin,771,Spain,Female,56,2,0,1,1,1,25222.6,1 -5563,15614361,Liao,620,Spain,Male,42,9,121490.05,1,1,1,29296.74,0 -5564,15724684,Sung,610,Spain,Male,46,5,91897.8,1,1,0,54394.28,0 -5565,15700083,Lai,609,Spain,Male,39,2,139443.75,2,1,0,9234.06,0 -5566,15636541,Cartwright,683,Germany,Male,35,5,144961.97,1,0,1,26796.73,0 -5567,15796015,Wu,633,Germany,Male,42,3,126041.02,1,0,1,11796.89,0 -5568,15787222,Ch'in,676,Germany,Male,28,1,69459.05,2,1,1,128461.29,0 -5569,15594270,Biryukov,693,France,Male,38,7,198338.77,2,1,1,14278.18,0 -5570,15701524,Ting,709,France,Male,36,0,0,2,1,0,46811.77,0 -5571,15645847,P'eng,569,Germany,Male,35,2,109196.66,3,1,0,109393.19,1 -5572,15708867,Niu,684,Spain,Female,38,3,134168.5,3,1,0,3966.5,1 -5573,15613140,Mellor,565,France,Male,34,6,0,1,1,1,63173.64,0 -5574,15628893,Power,681,France,Male,29,8,0,1,1,0,66367.33,0 -5575,15764073,Arcuri,503,Spain,Female,36,9,0,2,1,1,16274.67,0 -5576,15782879,Lang,656,France,Male,40,2,0,2,1,1,180553.48,0 -5577,15635964,Eve,566,Germany,Male,65,4,120100.41,1,1,0,107563.16,1 -5578,15726087,Ch'in,592,France,Female,62,5,0,1,1,1,100941.57,0 -5579,15726313,Napolitani,687,Spain,Female,50,5,0,2,1,0,110230.4,0 -5580,15578073,Barker,686,Spain,Male,22,8,0,2,0,0,142331.85,0 -5581,15786249,Whitfield,616,Spain,Male,30,2,0,2,1,0,199099.51,0 -5582,15812850,Stradford,494,Spain,Male,67,5,0,2,1,1,85890.16,0 -5583,15596972,Brownlow,534,France,Male,38,3,0,1,0,0,143938.27,0 -5584,15620579,Dunn,695,Spain,Female,31,8,0,2,0,1,131644.41,0 -5585,15768270,DeRose,579,Spain,Female,31,9,0,2,1,0,112395.98,0 -5586,15656597,Wang,432,Germany,Male,38,2,135559.8,2,1,1,71856.3,0 -5587,15699446,Hobbs,816,Germany,Female,25,2,150355.35,2,1,1,35770.84,0 -5588,15615004,Anderson,730,France,Female,37,1,0,2,1,1,124364.63,0 -5589,15704771,Ugochukwu,593,France,Female,35,6,133489.12,2,1,1,78101.29,0 -5590,15588372,Kirsova,715,Germany,Female,37,9,105489.31,1,0,0,143096.49,1 -5591,15681439,Tsou,775,Germany,Male,25,10,60205.2,2,1,0,14073.11,0 -5592,15607509,Ozerova,539,France,Male,38,5,0,2,1,0,47388.41,0 -5593,15670343,Li,576,Spain,Male,19,6,0,2,0,0,72306.07,0 -5594,15597968,Fyans,617,Spain,Male,50,7,0,1,1,0,184839.7,1 -5595,15658432,Freeman,688,France,Male,40,6,0,1,1,1,47886.44,0 -5596,15616431,Chiu,608,France,Male,33,4,0,1,0,1,130474.03,0 -5597,15796957,Iadanza,597,Spain,Male,35,9,0,3,0,1,73181.39,1 -5598,15815552,Ferguson,670,France,Female,42,6,112333.63,1,1,1,65706.86,0 -5599,15631871,Kelly,616,Germany,Female,57,7,116936.81,1,1,1,104379.36,0 -5600,15635870,She,579,Germany,Female,50,5,117721.02,1,0,1,192146.63,1 -5601,15596713,Christie,786,France,Male,37,7,165896.22,2,1,1,66977.68,0 -5602,15684211,Creel,704,Spain,Female,44,9,153656.85,1,1,0,158742.81,0 -5603,15760521,Thompson,796,France,Female,50,1,94164,1,1,1,189414.74,0 -5604,15608408,Lazareva,598,Spain,Male,39,1,0,2,1,0,159130.32,0 -5605,15804721,Boni,602,France,Male,49,0,191808.73,1,0,0,97640.2,0 -5606,15730272,Evseev,619,France,Male,58,5,152199.33,1,1,1,86022.09,0 -5607,15741988,Marino,492,Germany,Female,52,8,125396.24,1,1,0,10014.72,1 -5608,15771728,Mackenzie,641,Germany,Male,41,7,104405.54,3,1,0,17384.21,0 -5609,15605113,Sutherland,518,France,Female,27,1,133801.49,1,1,1,143315.57,0 -5610,15661945,Nicolay,623,Spain,Female,40,4,0,3,1,0,31669.18,0 -5611,15783816,Lori,733,France,Female,28,5,0,2,0,0,12761.16,0 -5612,15721207,Piazza,625,Germany,Male,42,6,100047.33,1,1,0,93429.95,0 -5613,15764072,Somerville,759,France,Female,31,1,109848.6,1,1,1,42012.55,0 -5614,15689412,Christie,604,France,Female,32,7,127849.38,1,1,0,15798.7,0 -5615,15798385,Grave,512,Spain,Female,46,3,0,2,1,1,56408.14,0 -5616,15775339,Lori,520,France,Female,29,8,95947.76,1,1,0,4696.44,0 -5617,15585256,Iloerika,805,Spain,Male,26,2,0,2,1,1,25042.1,0 -5618,15797329,Muir,626,France,Male,43,4,137638.69,1,1,0,130442.08,1 -5619,15780220,Pauley,656,France,Male,38,10,0,1,1,1,136521.82,0 -5620,15648951,Kao,785,Spain,Male,41,7,0,2,1,1,199108.88,0 -5621,15752409,Grant,553,France,Male,31,6,0,2,0,0,124596.63,0 -5622,15807524,Chukwuma,569,France,Female,44,4,0,2,0,0,134394.78,0 -5623,15766649,Vincent,670,France,Male,38,10,89416.99,1,0,0,144275.39,0 -5624,15696812,Lazareva,586,Spain,Male,42,6,0,2,1,1,123410.23,0 -5625,15581295,Ch'ien,617,Spain,Female,45,1,0,1,1,0,143298.06,0 -5626,15663234,Bishop,508,France,Female,60,7,143262.04,1,1,1,129562.74,0 -5627,15741417,Chibuzo,624,Spain,Female,35,7,119656.45,2,1,1,4595.05,0 -5628,15695174,Chang,654,France,Male,29,4,132954.64,1,1,1,146715.07,0 -5629,15665168,Calabrese,681,Germany,Female,44,3,105206.7,2,1,1,163558.36,0 -5630,15601503,Tokaryev,578,Spain,Male,28,4,0,2,0,0,6947.09,0 -5631,15706131,Logan,621,Spain,Female,37,9,83061.26,2,1,0,9170.54,0 -5632,15782758,Ozerova,632,France,Male,40,5,147650.68,1,1,1,199674.83,0 -5633,15591091,Goering,644,France,Male,44,5,73348.56,1,1,0,157166.79,1 -5634,15715877,Lo,821,France,Male,28,2,0,2,1,0,46072.52,0 -5635,15756918,Simmons,754,France,Female,38,2,0,2,0,0,3524.69,0 -5636,15746662,Maduabuchim,568,Spain,Female,27,1,116320.68,1,0,1,45563.94,0 -5637,15626679,Linger,584,France,Male,33,3,0,2,0,1,59103.13,0 -5638,15793343,Yeh,549,France,Female,29,8,0,2,1,1,189558.44,0 -5639,15576774,Stevenson,729,France,Female,38,7,0,2,0,0,45779.9,0 -5640,15801316,Ifeatu,523,France,Male,61,8,66250.71,1,1,1,21859.06,0 -5641,15800514,Kenechukwu,477,Germany,Female,24,2,95675.62,2,0,0,162699.7,1 -5642,15662232,Learmonth,675,Germany,Male,42,2,92616.64,2,1,0,8567.18,0 -5643,15737778,Dickson,782,Spain,Female,41,4,0,1,1,0,132943.88,0 -5644,15782096,Volkova,616,Spain,Female,36,6,0,1,1,1,12916.32,1 -5645,15783522,Mitchell,738,Spain,Female,37,8,100565.94,1,1,1,128799.86,0 -5646,15785373,Wong,717,Spain,Female,42,5,190305.78,1,1,0,99347.8,1 -5647,15756272,James,526,Germany,Female,35,9,118536.4,1,1,0,40980.87,1 -5648,15615245,Shao,660,France,Male,19,5,127649.64,1,1,1,40368.65,0 -5649,15600174,Walton,525,France,Male,35,7,165358.77,1,0,1,94738.54,0 -5650,15752956,Stanley,629,Spain,Male,29,6,0,2,1,1,88842.8,0 -5651,15644882,Watson,616,Germany,Female,36,10,78249.53,1,1,0,136934.91,0 -5652,15766272,Folliero,521,Germany,Female,61,0,125193.96,1,1,1,109356.53,0 -5653,15800620,Fitzgerald,691,France,Female,29,9,0,2,0,0,199635.93,0 -5654,15569764,Garner,687,Germany,Female,41,2,154007.21,1,1,0,158408.23,0 -5655,15747458,Folliero,677,Spain,Female,43,3,133214.88,2,1,1,95936.84,0 -5656,15573171,Liao,695,Spain,Male,63,1,146202.93,1,1,1,126688.83,1 -5657,15736769,Lucchesi,663,France,Female,27,9,0,2,1,0,150850.29,0 -5658,15763381,Chan,496,France,Male,30,0,90963.49,1,0,1,27802,0 -5659,15814430,Ma,747,Spain,Male,41,9,0,1,1,0,32430.94,1 -5660,15638607,Nwabugwu,546,France,Female,52,2,0,1,1,0,137332.37,1 -5661,15737133,P'eng,706,Spain,Male,68,4,114386.85,1,1,1,28601.68,0 -5662,15613945,Andrews,472,France,Female,26,5,0,2,1,0,108411.66,0 -5663,15659937,Otutodilinna,703,France,Female,40,7,0,2,0,1,122518.5,0 -5664,15765287,Grant,850,France,Female,38,2,0,2,1,0,9015.07,0 -5665,15661723,Abramovich,667,Spain,Male,71,4,137260.78,1,0,1,94433.08,1 -5666,15766064,Komarova,559,France,Male,33,9,111060.05,2,1,0,110371.84,0 -5667,15649616,Otutodilichukwu,636,Spain,Male,60,7,124447.73,1,1,1,141364.62,1 -5668,15719017,Donaldson,672,France,Female,34,8,0,2,1,1,16245.25,0 -5669,15720919,Duggan,667,France,Male,42,7,0,1,0,1,108348.94,1 -5670,15706706,Chinwendu,648,Germany,Male,33,7,135310.41,2,0,1,171668.2,0 -5671,15709653,Hamilton,497,France,Male,32,8,0,2,1,0,67364.42,0 -5672,15805104,Smith,743,France,Female,73,6,0,2,0,1,107867.38,0 -5673,15622442,Mazzi,619,France,Male,29,5,0,2,1,0,194310.1,0 -5674,15572801,Krischock,639,Spain,Male,34,5,139393.19,2,0,0,33950.08,0 -5675,15767598,Kent,540,Spain,Male,28,8,0,2,0,0,197588.32,0 -5676,15757897,Binder,766,France,Female,26,3,104258.8,1,1,1,428.23,0 -5677,15568104,Zubarev,749,France,Female,26,6,0,2,0,1,34948.77,0 -5678,15763414,Degtyarev,655,Germany,Male,32,9,113447.01,1,1,0,82084.3,0 -5679,15732265,Obialo,630,France,Male,33,9,0,2,1,0,64804.59,0 -5680,15621974,Davydova,778,Germany,Female,33,4,111063.73,2,1,0,83556.65,0 -5681,15803947,Teng,757,Germany,Female,30,6,161378.02,1,0,0,71926.28,1 -5682,15720706,Hsing,529,Spain,Female,39,2,82766.43,1,1,1,122925.44,0 -5683,15759290,Coleman,620,Spain,Male,29,9,0,2,1,0,13133.88,0 -5684,15651664,Wilder,615,France,Female,61,1,104267.7,1,1,0,62845.64,1 -5685,15795132,Molineux,735,France,Female,25,3,91718.8,1,0,0,28411.23,0 -5686,15811565,Cocci,705,Spain,Female,47,3,63488.7,1,0,1,28640.92,1 -5687,15713774,Chikwendu,644,Spain,Female,46,6,12459.19,1,0,0,156787.34,1 -5688,15691840,Fraser,505,Germany,Female,37,6,159863.9,2,0,1,125307.87,0 -5689,15682021,Lai,471,Germany,Male,23,6,104592.55,2,1,0,131736.23,0 -5690,15612931,Korovin,722,Spain,Female,50,4,132088.59,1,1,1,128262.14,0 -5691,15676707,Sidorov,577,Spain,Female,39,4,0,2,1,0,91366.42,0 -5692,15601383,Ibrahimova,744,Spain,Male,44,5,120654.68,1,1,0,82290.81,0 -5693,15662662,Duigan,573,France,Female,30,6,0,2,1,0,66190.21,0 -5694,15752694,Taylor,653,France,Female,32,4,83772.95,1,0,1,23920.65,0 -5695,15590683,Donaldson,660,France,Female,31,6,172325.67,1,0,1,45438.38,0 -5696,15773591,Jobson,787,France,Male,46,7,117685.31,2,1,1,93360.35,0 -5697,15723620,Lu,617,France,Male,41,7,0,2,0,1,14496.67,0 -5698,15671779,Nebechi,567,France,Male,39,5,0,2,0,0,168521.72,0 -5699,15672966,Cross,682,Spain,Female,64,9,0,2,1,1,103318.44,0 -5700,15624667,Wallace,684,France,Male,35,6,135871.5,1,1,1,87219.41,0 -5701,15812888,Perreault,447,France,Male,41,3,0,4,1,1,197490.39,1 -5702,15724154,Manna,625,Germany,Female,49,4,128504.76,1,1,0,126812.63,1 -5703,15749540,Hsiung,585,France,Male,36,7,0,2,1,0,94283.09,0 -5704,15621063,Gibbons,516,France,Female,42,8,56228.25,1,1,0,46857.52,0 -5705,15661626,Algeranoff,732,Germany,Female,45,6,98792.4,1,1,0,81491.7,1 -5706,15698703,Doherty,628,Germany,Male,40,5,181768.32,2,1,1,129107.97,0 -5707,15801431,Rowe,682,Spain,Female,48,9,101198.01,1,1,1,49732.9,0 -5708,15649451,Yates,746,France,Male,25,9,0,2,0,1,88728.47,0 -5709,15626156,Galloway,655,France,Female,60,3,0,2,1,1,86981.45,0 -5710,15606158,Genovese,644,France,Female,39,9,0,1,1,0,3740.93,0 -5711,15589496,Arrington,778,France,Male,34,5,139064.06,2,0,0,67949.32,0 -5712,15730345,Miah,617,France,Female,35,2,104508.1,1,1,1,147636.46,0 -5713,15572038,Chijindum,660,Germany,Male,35,9,113948.58,1,1,0,188891.96,1 -5714,15643439,Ferguson,537,France,Male,47,10,0,2,0,1,25482.62,0 -5715,15604158,Smith,554,France,Female,39,10,0,2,1,1,18391.93,0 -5716,15657396,Marshall,806,France,Male,31,9,0,2,0,1,140168.36,0 -5717,15709478,P'an,611,Germany,Male,37,1,117524.72,2,0,1,161064.29,0 -5718,15628824,Burton,665,France,Female,37,5,160389.82,1,0,1,183542.08,0 -5719,15814519,Kamdibe,648,France,Female,37,7,0,2,1,0,194238.92,0 -5720,15636520,Milani,692,France,Male,27,1,125547.53,1,0,0,7900.46,0 -5721,15794414,Forbes,507,Spain,Male,46,6,92783.68,1,1,1,51424.29,0 -5722,15643671,Chiekwugo,696,Germany,Male,49,5,97036.22,2,1,0,152450.84,1 -5723,15700650,Cousens,681,France,Male,34,3,0,2,0,0,55816.2,0 -5724,15680224,Ross,687,France,Female,26,6,0,2,1,1,32909.13,0 -5725,15784286,Wood,641,Spain,Male,40,5,102145.13,1,1,1,100637.07,0 -5726,15693996,Hawks,507,France,Female,33,1,113452.66,1,0,0,142911.99,0 -5727,15764343,T'ien,688,Spain,Female,46,8,155681.72,1,1,0,26287.21,0 -5728,15704168,Ting,535,Germany,Male,38,8,127475.24,1,0,0,60775.76,1 -5729,15680197,Thynne,701,France,Male,41,10,0,2,1,1,146257.77,0 -5730,15633729,Wang,488,France,Male,43,10,112751.13,1,1,1,28332,0 -5731,15577683,Maclean,539,France,Female,29,4,0,2,1,1,100919.19,0 -5732,15800746,Watson,674,France,Male,45,7,144889.18,1,1,1,102591.9,1 -5733,15788686,Gibson,538,Spain,Male,40,8,0,2,1,1,25554.4,0 -5734,15742798,French,829,France,Female,22,7,150126.44,1,1,0,152107.93,1 -5735,15596647,Henderson,768,France,Male,54,8,69712.74,1,1,1,69381.05,0 -5736,15756070,Greenwood,585,Spain,Female,44,4,0,2,0,1,101728.46,0 -5737,15775116,Anderson,581,France,Male,31,3,0,2,0,0,89040.61,0 -5738,15575428,Mistry,682,Germany,Female,35,2,117438.92,2,1,1,16910.98,0 -5739,15654074,Tuan,653,France,Male,38,8,119315.75,1,1,0,150468.35,0 -5740,15695872,Fiorentini,712,France,Female,30,1,89571.59,1,1,1,177613.19,0 -5741,15568885,Scott,620,Germany,Female,34,8,102251.57,1,1,0,120672.09,0 -5742,15725036,Jideofor,709,France,Male,42,9,118546.71,1,0,1,77142.85,0 -5743,15632665,Yevseyev,832,France,Male,61,2,0,1,0,1,127804.66,1 -5744,15571476,Kelly,635,Spain,Male,38,0,103257.14,1,0,0,158344.63,0 -5745,15776850,Smith,749,Spain,Female,43,1,124209.02,1,1,1,167179.48,0 -5746,15623649,Ogle,629,Spain,Male,32,3,0,2,1,1,15404.64,0 -5747,15751131,Moss,836,Spain,Female,41,7,150302.84,1,1,1,156036.19,0 -5748,15688128,Loggia,542,Spain,Male,34,8,108653.93,1,0,1,144725.14,0 -5749,15678412,Nwankwo,645,France,Female,45,8,85325.93,1,0,0,22558.74,0 -5750,15770291,Allan,844,France,Female,29,8,0,2,0,0,147342.03,0 -5751,15583392,Woronoff,747,Germany,Male,37,9,135776.36,3,1,0,85470.45,1 -5752,15690731,Wolfe,645,France,Male,40,6,131411.24,1,1,1,194656.11,0 -5753,15697948,Henderson,752,Spain,Female,36,3,0,2,1,1,48505.1,0 -5754,15608328,Sutherland,760,Spain,Female,41,6,0,2,0,0,101491.23,0 -5755,15766378,Marsden,714,Germany,Female,45,9,106431.97,2,1,1,164117.69,0 -5756,15600813,Hyde,717,France,Male,50,9,90305.76,1,1,1,124626.57,0 -5757,15706217,Kao,645,Germany,Male,28,7,117466.03,2,1,1,34490.06,0 -5758,15601417,T'ang,681,France,Male,32,3,148884.47,2,1,1,90967.37,0 -5759,15610972,Crawford,681,Germany,Female,44,4,91115.76,2,0,0,24208.84,1 -5760,15674620,Dilibe,679,Germany,Female,37,8,77373.87,2,0,1,174873.09,0 -5761,15785350,Austin,528,Spain,Male,23,7,104744.89,1,1,0,170262.97,0 -5762,15749119,Santiago,710,France,Female,31,3,0,2,1,1,112289.06,0 -5763,15756535,Chibugo,733,Germany,Male,39,5,91538.51,1,1,1,93783,0 -5764,15700965,Toscano,724,France,Female,32,6,0,2,1,1,150026.79,0 -5765,15791851,Afanasyeva,726,France,Female,34,0,185734.75,1,1,1,102036.82,0 -5766,15717156,Sokolov,520,France,Male,30,3,143396.54,2,1,1,898.51,0 -5767,15740846,Wei,556,France,Male,40,5,125909.85,1,1,1,95124.4,0 -5768,15573284,Olisanugo,579,France,Female,45,2,0,2,0,0,11514.39,0 -5769,15729083,Gorman,674,France,Male,36,2,154525.7,1,0,1,27468.72,0 -5770,15611612,Priestley,570,France,Female,29,0,0,1,1,0,37092.43,0 -5771,15694381,Lloyd,631,France,Male,51,8,100654.8,1,1,0,171587.9,0 -5772,15651737,Salmond,623,Spain,Male,44,1,83325.77,1,0,1,80828.78,0 -5773,15663168,MacDonald,665,France,Male,35,8,110934.54,1,1,0,169287.99,0 -5774,15643426,Robertson,523,Spain,Female,36,8,113680.54,1,0,0,13197.44,0 -5775,15618245,Chukwumaobim,706,Germany,Male,31,1,117020.08,2,1,0,54439.53,0 -5776,15717527,Ifeanacho,619,France,Female,49,9,145359.99,1,1,0,38186.85,0 -5777,15793478,Li Fonti,593,Germany,Female,39,8,151391.68,1,1,0,27274.6,1 -5778,15642248,Ko,608,Spain,Male,66,8,123935.35,1,1,1,65758.19,0 -5779,15640377,Goloubev,526,France,Female,36,0,0,2,1,0,97767.63,0 -5780,15723950,Kruglov,684,Spain,Male,40,2,70291.02,1,1,1,115468.84,1 -5781,15590327,Liao,604,Germany,Female,42,10,166031.45,1,1,0,98293.14,0 -5782,15706199,White,636,Germany,Male,36,6,96643.32,1,0,0,182059.28,0 -5783,15671514,Sinclair,669,Spain,Female,33,8,0,2,0,1,128538.05,0 -5784,15727041,Fiorentini,624,France,Male,71,7,0,2,1,1,108841.83,0 -5785,15738063,Shen,631,France,Male,29,2,0,2,1,1,18581.84,0 -5786,15711733,Rapuokwu,753,France,Male,48,4,0,2,0,1,146821.42,0 -5787,15652320,Woronoff,588,France,Male,40,5,0,2,0,0,100727.68,0 -5788,15634180,Holden,729,Germany,Male,26,4,97268.1,2,1,0,39356.38,0 -5789,15694566,Roberts,602,France,Female,42,10,0,2,0,0,169921.11,1 -5790,15726103,Tsou,689,Germany,Female,55,1,76296.81,1,1,0,42364.75,1 -5791,15646351,Somerville,486,Spain,Male,27,7,0,2,1,0,28823.04,0 -5792,15730044,Greco,809,Germany,Female,42,6,64497.94,3,0,1,182436.81,1 -5793,15795186,Leonard,562,France,Male,38,5,0,1,1,0,115700.2,0 -5794,15784890,McKenzie,763,Spain,Female,32,8,0,2,1,0,16725.53,0 -5795,15694125,McElhone,669,France,Male,57,5,0,2,1,1,56875.76,0 -5796,15565891,Dipietro,709,France,Male,39,8,0,2,1,0,56214.09,0 -5797,15674254,Kerr,554,Spain,Female,45,4,0,2,1,1,193412.05,0 -5798,15775206,Hunter,699,France,Male,37,10,0,2,0,0,83263.04,0 -5799,15797627,Niehaus,732,Spain,Male,54,0,134249.7,1,0,1,13404.4,0 -5800,15649853,Craig,625,France,Female,45,3,0,1,1,1,184474.15,1 -5801,15610379,Barclay-Harvey,599,France,Male,30,9,105443.68,1,1,1,121124.53,0 -5802,15659800,Teng,584,Spain,Female,50,1,0,1,0,1,152567.75,1 -5803,15716236,Milani,499,France,Male,35,10,0,2,1,0,10722.54,0 -5804,15672053,Mistry,526,Spain,Male,38,2,0,2,0,0,58010.98,0 -5805,15663933,Jamieson,625,Germany,Female,35,5,86147.46,2,1,0,163440.8,1 -5806,15814236,Kay,537,Spain,Female,38,1,96939.06,1,1,1,102606.92,0 -5807,15583597,Ikedinachukwu,696,Spain,Male,47,1,106758.6,1,1,1,80591.18,0 -5808,15607395,Holt,679,France,Female,33,9,112528.65,2,1,0,177362.45,0 -5809,15694556,Nkemakolam,684,France,Male,60,2,116563.58,1,1,0,120257.7,1 -5810,15744109,Hartung,850,France,Male,32,4,0,1,1,1,180622.02,0 -5811,15800688,Ch'en,495,Spain,Female,42,7,0,2,0,0,130404.53,0 -5812,15810878,Baker,537,Spain,Female,38,6,141786.78,1,0,1,147797.54,0 -5813,15587835,Osinachi,850,France,Male,41,3,136416.82,1,0,1,57844.26,0 -5814,15763515,Shih,513,France,Male,30,5,0,2,1,0,162523.66,0 -5815,15725882,Feng,618,Germany,Female,40,1,133245.52,2,1,1,54495.82,0 -5816,15788022,Sternberg,802,Germany,Female,41,4,90757.64,2,0,1,169183.66,0 -5817,15663917,Adams,547,France,Male,43,1,92350.36,1,0,1,80262.91,0 -5818,15656865,Gray,613,Germany,Male,69,9,78778.49,1,0,1,8751.59,0 -5819,15667971,Shepherd,592,Germany,Female,34,6,102143.93,2,1,1,102628.98,0 -5820,15800366,Walton,546,France,Male,29,5,0,1,1,1,94823.95,0 -5821,15717231,Yang,721,Germany,Male,37,4,98459.6,1,0,0,90821.66,0 -5822,15643188,Barnett,671,Germany,Female,47,7,114603.76,2,1,0,153194.32,1 -5823,15671351,Romani,624,Spain,Male,35,2,0,2,1,0,87310.59,0 -5824,15573628,Greene,751,Germany,Female,51,7,148074.79,1,1,0,146411.41,1 -5825,15698953,Hart,636,Spain,Male,36,1,0,3,1,1,74048.1,1 -5826,15753888,Johnston,607,Spain,Female,62,8,108004.64,1,1,1,23386.77,1 -5827,15737961,Miller,509,Germany,Female,29,0,107712.57,2,1,1,92898.17,0 -5828,15801701,Robson,653,Spain,Male,35,9,0,2,1,1,45956.05,0 -5829,15684419,Wallace,709,Spain,Female,37,8,0,3,1,0,71738.56,0 -5830,15794266,Cross,559,France,Male,32,9,145303.52,1,1,0,103560.98,0 -5831,15810711,Marcum,684,Germany,Male,37,4,138476.41,2,1,1,52367.29,0 -5832,15771270,North,635,France,Female,27,8,127471.56,1,1,1,152916.05,1 -5833,15607786,Mao,709,France,Male,26,6,156551.63,1,0,1,4410.77,0 -5834,15624519,Calabrese,656,Germany,Female,49,9,97092.87,1,1,0,74771.22,1 -5835,15799910,Martin,793,France,Male,32,2,0,2,1,0,193817.63,1 -5836,15602479,Fleming,609,Spain,Male,37,5,129312.79,1,1,1,26793.82,0 -5837,15617419,Roberts,618,Germany,Female,29,10,100315.1,2,1,1,32526.64,0 -5838,15657603,Finch,850,France,Female,35,6,81684.97,1,1,0,824,0 -5839,15570379,Whitelegge,669,Spain,Male,51,3,88827.53,1,0,0,85250.77,1 -5840,15772996,Rooke,594,Germany,Male,40,0,152092.44,2,1,1,83508.93,0 -5841,15729574,Lu,616,Spain,Male,71,4,0,2,1,1,173599.38,0 -5842,15737267,Marcelo,676,France,Female,49,1,0,1,1,0,79342.31,1 -5843,15799128,Matthews,608,Spain,Female,38,9,102406.76,1,0,1,57600.66,0 -5844,15813327,Romani,710,France,Male,21,4,109130.96,2,1,1,56191.99,0 -5845,15711921,Scott,695,France,Male,29,5,0,2,1,1,6770.44,0 -5846,15654300,Mao,530,Germany,Male,33,9,75242.28,1,0,1,101694.67,0 -5847,15569945,Horsley,509,Spain,Male,29,1,0,2,1,0,69113.14,0 -5848,15569666,Goddard,517,France,Female,45,4,0,1,0,0,172674.36,1 -5849,15681887,Eskridge,758,Germany,Male,33,0,129142.54,2,1,1,26606.28,0 -5850,15608873,Smith,665,France,Male,51,2,0,1,0,0,53353.36,0 -5851,15762091,Simpson,631,Germany,Female,22,6,139129.92,1,1,1,63747.51,0 -5852,15722053,Oguejiofor,576,Spain,Male,33,3,0,2,0,1,190112.05,0 -5853,15782100,Holloway,544,Spain,Male,22,3,66483.32,1,0,1,110317.39,0 -5854,15765300,L?,596,Germany,Male,40,5,62389.03,3,1,0,148623.43,1 -5855,15743570,Feng,481,France,Female,34,5,0,2,1,1,125253.46,0 -5856,15608541,Claiborne,498,France,Male,46,1,91857.66,1,1,0,101954.78,1 -5857,15750671,Egobudike,512,Spain,Male,31,6,0,2,1,0,168462.26,0 -5858,15813659,Folliero,594,France,Female,56,7,0,1,1,0,26215.85,1 -5859,15757867,Bray,570,France,Female,30,10,176173.52,1,1,0,97045.32,1 -5860,15652914,Ibrahimov,721,Spain,Male,38,7,0,1,0,1,53534.8,0 -5861,15723818,Carpenter,453,France,Female,37,4,131834.76,2,1,0,8949.2,0 -5862,15713819,Walsh,562,France,Male,48,3,92347.96,1,1,1,163116.75,0 -5863,15656484,Woods,682,France,Male,40,4,0,2,1,1,140745.91,0 -5864,15778515,Wu,748,France,Male,40,3,95297.11,1,0,0,171515.84,0 -5865,15803840,Forbes,729,France,Female,32,9,0,2,0,0,150803.44,0 -5866,15735339,Lynch,663,France,Male,39,4,0,1,1,0,76884.05,0 -5867,15600392,Amaechi,735,France,Female,53,8,123845.36,2,0,1,170454.93,1 -5868,15625740,Enriquez,627,Germany,Male,62,3,143426.34,2,1,1,143104.3,0 -5869,15663817,Y?an,713,France,Male,46,5,0,1,1,1,55701.62,0 -5870,15734461,Brooks,562,Germany,Male,31,2,112708.2,1,0,1,186370.3,0 -5871,15780142,Wang,632,France,Male,43,2,100013.51,1,1,0,24275.32,0 -5872,15709920,Burke,479,France,Female,33,2,208165.53,1,0,0,50774.81,1 -5873,15684248,Meng,658,Spain,Male,21,7,0,2,0,1,154279.87,0 -5874,15643158,Chiganu,598,France,Female,40,9,0,1,1,0,68462.59,1 -5875,15693902,Hunt,597,France,Male,19,2,0,2,1,1,91036.74,0 -5876,15578307,Lucchese,512,France,Female,33,6,121685.31,2,1,1,83681.97,0 -5877,15585379,Humphries,704,France,Male,39,2,111525.02,1,1,0,199484.96,0 -5878,15758510,Frolova,474,France,Male,26,6,0,2,0,0,152491.22,0 -5879,15692918,Hsing,604,Germany,Male,36,10,113546.3,1,1,1,134875.37,0 -5880,15705301,Parkes,683,France,Male,41,6,95696.52,2,1,1,184366.14,0 -5881,15718231,Gregory,537,France,Male,28,0,88963.31,2,1,1,189839.93,0 -5882,15567991,Obiuto,794,Spain,Male,31,0,144880.34,2,0,1,175643.44,0 -5883,15772650,Longo,732,France,Male,55,9,136576.02,1,0,1,3268.17,1 -5884,15574795,Lombardo,495,France,Female,38,2,63093.01,1,1,1,47089.72,0 -5885,15706036,Lombardo,552,Germany,Male,38,10,132271.12,2,1,1,46562.02,0 -5886,15723856,Gonzalez,602,France,Female,29,3,88814.4,2,1,1,62487.97,0 -5887,15812920,Nwabugwu,607,Germany,Male,40,5,90594.55,1,0,1,181598.25,0 -5888,15691287,Ford,675,Germany,Female,33,0,141816.25,1,1,0,64815.05,1 -5889,15804797,Gilleland,443,France,Female,54,3,138547.97,1,1,1,70196.23,1 -5890,15708650,Fullwood,727,France,Female,31,2,52192.08,2,0,1,160383.47,0 -5891,15712777,Kao,482,France,Male,38,4,124976.19,1,1,0,35848.12,0 -5892,15786469,Montalvo,686,France,Female,34,1,0,2,1,0,87278.48,0 -5893,15669219,Wilson,588,Germany,Male,35,3,104356.38,1,1,0,94498.82,0 -5894,15641004,Doyne,605,Spain,Female,48,10,150315.92,1,0,1,133486.36,0 -5895,15648067,Onwuamaeze,583,France,Male,39,1,129299.28,2,1,0,73107.6,0 -5896,15704014,K'ung,738,Germany,Male,37,7,140950.92,2,1,0,195333.98,0 -5897,15645136,O'Donnell,744,Spain,Male,30,1,128065.12,1,1,0,121525.48,0 -5898,15709604,McMillan,781,France,Male,23,2,107433.48,1,1,0,173843.21,0 -5899,15713637,Chinedum,699,France,Male,34,2,117468.67,1,1,0,185227.42,0 -5900,15793901,Capon,639,France,Female,27,2,0,2,0,0,125244.18,0 -5901,15569759,Rawling,583,France,Female,27,4,0,3,1,0,163113.41,0 -5902,15712930,Duncan,587,France,Male,42,1,0,1,0,0,123006.91,0 -5903,15586504,Trevisani,694,France,Male,40,9,0,2,1,0,40463.03,0 -5904,15677317,Ankudinova,570,France,Female,29,4,153040.03,1,1,1,131363.57,1 -5905,15664270,Balsillie,692,Germany,Male,45,6,142084.04,4,1,0,188305.85,1 -5906,15731519,Kerr,511,France,Female,30,5,0,2,1,0,143994.86,0 -5907,15745623,Worsnop,788,France,Male,32,4,112079.58,1,0,0,89368.59,0 -5908,15813862,Yevseyev,526,Spain,Male,66,7,132044.6,2,1,1,158365.89,0 -5909,15641934,Manna,749,Spain,Female,46,9,66582.81,1,1,0,78753.12,1 -5910,15713043,Siciliani,691,France,Female,33,6,0,2,1,1,100408.31,0 -5911,15700749,Powell,481,France,Female,39,6,0,1,1,1,24677.54,0 -5912,15697567,Bazarova,752,France,Male,33,4,0,2,1,1,39570.78,0 -5913,15715414,White,658,France,Female,38,6,102895.1,1,0,0,155665.76,0 -5914,15639530,Buda,679,Spain,Male,42,2,0,1,1,1,168294.27,0 -5915,15726058,Cattaneo,754,Germany,Male,27,7,117578.35,2,0,1,87908.01,0 -5916,15725665,Lo,679,France,Male,47,10,198546.1,2,1,0,191198.92,1 -5917,15698872,Brown,633,Spain,Female,39,2,0,2,0,0,191207.03,0 -5918,15812184,Rose,674,France,Female,31,1,0,1,1,0,128954.05,0 -5919,15742609,Lombardo,600,Germany,Male,28,2,116623.31,1,0,1,59905.29,0 -5920,15815043,McMillan,645,Spain,Male,49,8,0,2,1,0,162012.6,0 -5921,15640648,Howe,698,France,Male,36,6,0,2,0,1,19231.98,0 -5922,15627203,Hsu,508,Spain,Male,54,10,0,1,1,1,175749.36,0 -5923,15786196,Han,555,France,Female,44,3,105770.7,3,1,0,60533.96,1 -5924,15612095,Calabrese,751,France,Female,48,9,0,1,1,0,137508.42,1 -5925,15674368,Riley,738,France,Female,39,1,94435.45,2,0,1,189430.86,0 -5926,15783477,Biryukov,706,Germany,Female,39,8,112889.91,1,0,1,6723.66,0 -5927,15757559,Broadhurst,595,France,Female,53,7,0,2,1,0,41371.68,1 -5928,15591036,Genovesi,577,Germany,Female,43,3,127940.47,1,0,0,125140.72,1 -5929,15761241,Hsieh,578,Germany,Female,36,8,129745.1,1,1,1,143683.75,0 -5930,15695078,Kemp,699,France,Male,32,3,0,2,1,1,170770.44,0 -5931,15645744,Chukwudi,826,France,Female,30,5,0,2,0,1,157397.57,0 -5932,15566988,Iqbal,656,Germany,Female,46,7,141535.52,1,1,0,50595.15,1 -5933,15749300,Teng,556,France,Female,47,2,139914.27,1,1,1,50390.98,0 -5934,15594340,Tao,569,France,Male,41,4,120243.49,1,1,0,163150.03,1 -5935,15607065,Chinedum,765,France,Male,34,9,91835.16,1,0,0,138280.17,0 -5936,15778089,Stevenson,544,Spain,Male,37,2,0,2,0,0,135067.02,0 -5937,15773723,Duncan,588,Spain,Female,22,9,67178.19,1,1,1,163534.75,1 -5938,15697035,Garrett,740,Spain,Female,31,8,0,2,0,0,86657.48,0 -5939,15679668,Yao,850,Spain,Male,38,7,115378.94,1,0,1,162087.82,0 -5940,15709861,He,766,Germany,Male,30,4,127786.28,2,1,1,28879.3,0 -5941,15791958,Mazzi,849,France,Female,41,6,0,2,1,1,169203.51,1 -5942,15791030,Edwards,612,France,Female,33,0,64900.32,2,1,0,102426.12,0 -5943,15695339,Lucchesi,517,Germany,Male,53,0,109172.88,1,1,0,54676.1,1 -5944,15658813,Siciliani,645,France,Female,55,7,0,2,1,1,18369.33,0 -5945,15715709,Shih,696,Germany,Male,43,4,114091.38,1,0,1,159888.1,0 -5946,15722533,Logue,716,France,Female,40,3,0,2,0,1,167636.15,0 -5947,15683118,Rechner,590,France,Male,32,9,0,2,1,0,138889.15,0 -5948,15672798,O'Brien,656,France,Female,45,7,145933.27,1,1,1,199392.14,0 -5949,15680112,Stewart,473,Germany,Female,35,7,131504.73,1,1,0,189560.43,0 -5950,15714575,Batt,742,Germany,Female,44,8,107926.02,1,0,1,17375.27,1 -5951,15806808,Hope,834,Germany,Female,57,8,112281.6,3,1,0,140225.14,1 -5952,15590637,Ahmed,721,France,Male,41,7,0,2,0,1,61018.85,0 -5953,15657535,Pearson,590,Spain,Male,29,10,0,1,1,1,51907.72,1 -5954,15696141,Kruglov,516,Spain,Female,31,7,0,1,1,0,47018.75,0 -5955,15811947,Gordon,850,France,Male,33,0,124781.67,1,0,1,33700.52,0 -5956,15649024,Trujillo,748,France,Female,39,9,132865.56,1,1,1,59636.43,1 -5957,15594928,Pagnotto,798,Germany,Female,38,4,129055.13,1,1,0,157147.59,0 -5958,15765532,Horton,612,Germany,Male,76,6,96166.88,1,1,1,191393.26,0 -5959,15741719,DeRose,540,France,Female,40,3,165298.12,1,0,1,199862.75,0 -5960,15665629,Chiang,719,Spain,Female,33,7,0,2,1,0,20016.59,0 -5961,15728917,Gill,598,France,Male,48,6,120682.53,1,1,0,30635.52,1 -5962,15762993,Trevisano,796,Spain,Male,32,5,102773.15,2,0,1,117832.88,0 -5963,15571193,Morrison,579,Germany,Male,42,0,144386.32,1,1,1,22497.1,1 -5964,15653521,Onuora,850,Germany,Female,40,7,104449.8,1,1,1,747.88,0 -5965,15802220,Ikenna,599,Spain,Male,35,6,137102.65,1,0,0,76870.81,0 -5966,15644132,Mancini,724,France,Female,30,9,142475.87,1,1,1,107848.24,0 -5967,15600832,Moss,508,France,Female,43,9,0,1,1,0,103726.71,0 -5968,15797919,Ting,773,Spain,Male,37,2,103195.2,2,1,0,178268.36,0 -5969,15603743,Tai,526,France,Male,28,1,112070.44,1,0,1,126281.83,0 -5970,15579714,Pan,542,France,Female,29,7,0,2,0,1,196651.72,0 -5971,15634295,Wilson,470,France,Male,35,1,96473.59,1,0,0,5962.3,0 -5972,15786680,Bianchi,805,Spain,Male,37,5,0,2,1,0,21928.81,0 -5973,15623499,Holman,548,Germany,Male,49,9,108437.89,1,0,0,127022.87,1 -5974,15691823,Obidimkpa,672,France,Male,37,5,153195.59,1,1,1,162763.01,0 -5975,15809279,Wallace,773,France,Male,45,8,96877.21,1,1,1,113950.51,0 -5976,15758039,Ash,614,France,Male,44,6,0,2,0,1,104930.46,0 -5977,15807163,Ku,537,France,Female,38,10,0,1,0,0,52337.97,1 -5978,15631639,Uspensky,704,France,Female,40,6,95452.89,1,0,1,179964.55,0 -5979,15713770,Shih,586,Spain,Male,41,3,63873.56,1,1,0,83753.64,0 -5980,15698167,Kumm,677,France,Female,24,0,148298.59,2,0,0,182913.95,0 -5981,15781710,Carey,558,Spain,Female,31,7,0,2,1,0,166720.28,0 -5982,15801296,Farber,634,Germany,Female,37,7,143258.85,2,1,0,192721.98,0 -5983,15704378,Calabrese,655,Germany,Male,37,9,121342.24,1,1,1,180241.44,0 -5984,15767891,Findlay,619,Germany,Female,28,6,99152.73,2,1,0,48475.12,0 -5985,15640667,Yu,662,France,Female,41,4,0,2,1,0,126551.48,0 -5986,15702145,Edments,705,Spain,Male,33,7,68423.89,1,1,1,64872.55,0 -5987,15679738,Brown,527,Spain,Female,35,8,0,1,1,0,98031.53,1 -5988,15636634,Lindon,630,Germany,Female,25,7,79656.81,1,1,0,93524.22,0 -5989,15809227,Chukwudi,850,France,Male,35,2,0,2,1,1,56991.66,0 -5990,15601811,Caldwell,668,France,Female,53,10,110240.04,1,0,0,183980.56,1 -5991,15625494,Li Fonti,573,France,Female,32,9,125321.84,2,1,1,130234.63,0 -5992,15723737,Pitcher,680,France,Male,27,3,0,1,1,0,32454.26,0 -5993,15682955,Capon,758,France,Female,32,2,84378.9,1,1,1,75396.43,0 -5994,15758856,Kable,597,France,Male,45,7,0,2,0,0,167756.45,0 -5995,15746065,Lo Duca,580,Germany,Male,35,10,136281.41,2,1,1,24799.47,0 -5996,15783865,Kulikova,622,France,Male,59,5,119380.37,1,1,1,60429.43,0 -5997,15745455,Navarrete,638,Germany,Male,62,4,108716.59,2,1,1,74241.09,0 -5998,15583033,Huguley,640,France,Female,20,4,0,2,0,1,78310.82,0 -5999,15644212,Han,644,Spain,Male,28,0,0,2,1,0,119419.37,0 -6000,15735688,Horsley,753,France,Female,31,6,106596.29,1,0,0,91305.77,0 -6001,15658577,Massie,629,France,Female,37,10,99546.25,3,0,1,25136.95,1 -6002,15606887,Singh,775,France,Female,30,5,0,1,1,0,193880.6,1 -6003,15783026,H?,701,France,Female,41,2,0,1,1,0,47856.78,0 -6004,15579892,Doyle,708,Spain,Male,19,7,112615.86,1,1,1,4491.77,0 -6005,15802088,Grant,521,Spain,Female,22,10,0,1,1,1,101311.95,0 -6006,15589323,Law,636,France,Female,24,9,0,2,0,1,38830.72,0 -6007,15636395,King,529,France,Female,31,5,0,2,1,0,26817.23,0 -6008,15712772,Onwubiko,757,France,Male,28,3,75381.15,1,1,1,199727.72,0 -6009,15700937,Romano,767,Spain,Female,24,5,0,2,1,1,67445.85,0 -6010,15766659,Okwudilichukwu,525,Spain,Male,33,5,0,2,1,0,161002.29,0 -6011,15814033,Milano,759,Spain,Male,38,1,0,2,1,0,20778.39,0 -6012,15783007,Parker,520,Germany,Female,45,1,123086.39,1,1,1,41042.4,1 -6013,15654183,Aitken,738,France,Female,26,3,0,2,1,0,67484.16,0 -6014,15609899,Obiora,548,Spain,Male,37,4,0,1,1,0,121763.68,0 -6015,15747323,Vasilyeva,535,Spain,Male,48,9,109472.47,1,1,0,157358.43,1 -6016,15582591,Chiabuotu,615,Spain,Male,59,4,155766.05,1,1,1,110275.17,0 -6017,15738835,Slater,850,Germany,Male,38,7,101985.81,2,0,0,43801.27,0 -6018,15782404,Hughes,487,France,Female,34,2,96019.5,1,0,0,9085,0 -6019,15697480,Menkens,731,France,Male,30,7,0,2,0,1,143086.09,0 -6020,15697045,Pisani,726,Spain,Female,35,9,0,2,0,1,100556.98,0 -6021,15781234,Y?an,609,France,Female,35,2,147900.43,1,1,0,140000.29,0 -6022,15579891,Milani,714,France,Male,52,4,100755.66,1,1,1,186775.25,0 -6023,15805690,Chin,694,Spain,Female,35,7,0,1,1,0,133570.43,1 -6024,15612139,Fu,786,France,Female,33,0,83036.05,1,0,1,154990.58,1 -6025,15568834,Howells,698,Spain,Male,27,6,125427.37,2,0,0,27654.44,0 -6026,15709917,Ni,601,France,Female,46,3,98202.76,1,0,0,137763.93,0 -6027,15718843,Maslova,769,Spain,Male,41,1,72509.91,1,1,0,25723.73,0 -6028,15799494,Forster,850,Germany,Male,44,3,140393.65,2,0,1,186285.52,0 -6029,15673439,Sun,646,Spain,Female,50,5,142644.64,2,1,1,142208.5,1 -6030,15669011,Bocharova,659,France,Female,44,9,23503.31,1,0,1,169862.01,1 -6031,15581388,Y?an,487,Spain,Male,33,8,145729.71,1,1,0,41365.85,0 -6032,15743153,Singh,740,Germany,Female,40,2,122295.17,2,1,1,30812.84,0 -6033,15579787,Nkemakonam,686,France,Male,39,4,0,2,1,0,155023.93,0 -6034,15759966,Chiemenam,612,Spain,Female,36,5,119799.27,2,1,0,159416.58,0 -6035,15601045,Angelo,655,Spain,Male,37,8,163708.58,2,0,0,76259.23,0 -6036,15764021,Frolov,617,France,Male,34,1,61687.33,2,1,0,105965.25,0 -6037,15687218,West,674,France,Female,27,4,79144.34,1,0,1,50743.83,0 -6038,15626452,Beatham,711,Spain,Male,32,5,0,2,1,1,147720.27,0 -6039,15700964,Pollard,624,Germany,Female,27,7,104848.68,1,1,1,167387.36,0 -6040,15768887,Hsing,597,Spain,Male,26,5,0,2,0,1,95159.13,0 -6041,15735358,Dowse,682,Spain,Male,46,4,0,1,1,1,4654.28,0 -6042,15749472,Lucciano,775,France,Male,45,8,0,1,1,0,130376.68,0 -6043,15685872,Godfrey,727,France,Female,29,1,146652.01,1,1,1,173486.39,0 -6044,15760851,Gratton,629,France,Male,31,6,0,2,1,0,93881.75,0 -6045,15734588,Manning,684,France,Male,46,0,0,2,1,1,36376.97,0 -6046,15784594,Mazzi,549,Germany,Female,37,1,130622.34,2,1,1,128499.94,0 -6047,15606435,Wall,593,Germany,Male,69,2,187013.13,2,0,1,105898.69,0 -6048,15790247,Sims,536,Spain,Male,40,9,0,2,1,1,11959.03,0 -6049,15676433,Allan,707,France,Female,36,6,0,1,0,0,98810.78,0 -6050,15625905,Griffen,592,Spain,Male,41,0,0,2,1,0,65906.07,0 -6051,15626414,Russell,703,France,Male,44,6,98862.54,1,1,0,151516.7,0 -6052,15623220,Brown,723,Spain,Female,45,4,0,2,1,0,37214.39,0 -6053,15752857,Palerma,452,Germany,Male,52,1,98443.14,2,0,0,92033.98,0 -6054,15677908,Gilbert,552,Spain,Male,42,4,0,2,0,0,195692.3,0 -6055,15773013,Uvarov,633,France,Female,47,0,0,1,1,1,6342.84,1 -6056,15623972,Wisdom,479,Germany,Female,23,9,123575.51,1,0,1,95148.28,0 -6057,15738627,Hussain,768,France,Male,25,6,0,2,1,1,21215.67,0 -6058,15643392,Woods,742,France,Male,31,4,105239.1,1,1,1,19700.24,0 -6059,15684868,Cameron,668,Germany,Male,56,9,110993.79,1,1,0,134396.64,1 -6060,15627854,Mai,707,Spain,Male,44,3,0,2,1,1,135077.01,0 -6061,15669253,Gibson,754,Spain,Male,39,7,157691.98,2,1,0,133600.89,1 -6062,15758023,Grigoryeva,544,Germany,Male,47,5,105245.21,1,0,0,99922.08,1 -6063,15574558,Gunter,718,Spain,Male,32,8,0,2,1,1,41399.33,0 -6064,15635256,Arcuri,762,France,Male,31,7,117687.35,1,1,1,159344.43,0 -6065,15680399,Tung,772,France,Male,23,2,0,2,1,0,18364.19,0 -6066,15674720,Smith,691,Germany,Female,37,7,123067.63,1,1,1,98162.44,1 -6067,15580249,Lori,502,France,Male,45,0,0,1,0,0,84663.21,0 -6068,15675431,Chidimma,563,France,Female,34,6,0,2,0,0,36536.93,0 -6069,15698285,Ting,676,France,Female,41,4,101457.14,1,1,1,79101.67,0 -6070,15810775,Tsao,576,Spain,Male,52,2,100549.43,2,1,1,16644.16,0 -6071,15678173,Collee,629,Spain,Male,35,4,174588.8,2,0,1,158420.14,0 -6072,15665222,Lettiere,625,Spain,Male,52,8,121161.57,1,1,0,48988.28,0 -6073,15803908,Fu,628,France,Male,45,9,0,2,1,1,96862.56,0 -6074,15586039,Bergamaschi,471,Germany,Female,36,5,90063.74,2,1,1,96366.7,0 -6075,15802570,Dyer,811,France,Female,45,5,0,2,1,1,146123.19,0 -6076,15781451,Buccho,504,France,Male,42,3,134936.97,2,0,0,135178.91,0 -6077,15721019,Jones,687,France,Female,24,3,110495.27,1,1,0,158615.41,0 -6078,15738588,Nebechi,660,Germany,Female,37,2,133200.09,1,0,0,71433.88,0 -6079,15730657,Ibekwe,548,France,Female,41,4,82596.8,1,0,1,55672.09,0 -6080,15739292,Gorshkov,609,Germany,Male,31,9,103837.75,1,1,1,150218.11,0 -6081,15725945,Nweke,659,Spain,Female,42,2,0,1,0,0,162734.31,1 -6082,15813159,Hairston,526,France,Male,52,8,93590.47,1,0,1,21228.71,1 -6083,15636820,Loggia,725,Germany,Male,40,8,104149.66,1,1,0,62027.9,0 -6084,15603880,Morgan,519,Germany,Male,38,1,114141.64,1,1,1,60988.21,1 -6085,15619494,Abdulov,562,Germany,Female,31,9,117153,1,1,1,108675.01,0 -6086,15596992,Norris,482,Germany,Male,45,7,156353.46,1,1,0,72643.95,1 -6087,15735025,Clark,535,Spain,Male,37,3,175534.78,2,1,1,9241.52,0 -6088,15730759,Chukwudi,561,France,Female,27,9,135637,1,1,0,153080.4,1 -6089,15752912,Perkin,661,France,Female,30,7,0,2,1,0,72196.57,0 -6090,15711316,Ch'ang,771,France,Male,27,2,0,2,1,1,199527.34,0 -6091,15738785,Kang,545,France,Male,26,7,0,2,0,1,156598.23,0 -6092,15777896,Chukwudi,850,Germany,Female,33,2,83415.04,1,0,1,74917.64,0 -6093,15628963,Frolova,601,Germany,Male,43,3,141859.12,2,1,1,111249.62,0 -6094,15742126,Chiu,712,Germany,Male,38,7,132767.66,2,1,1,59115.77,0 -6095,15575623,Simpson,589,France,Female,31,10,110635.32,1,1,0,148218.86,0 -6096,15741652,McLean,600,Spain,Male,37,8,177657.35,1,1,1,77142.32,0 -6097,15738884,Hu,642,Germany,Male,41,4,157777.58,1,1,0,67484.6,0 -6098,15615050,Savage,575,Germany,Male,47,9,107915.94,2,1,1,63452.18,1 -6099,15803005,Wallace,570,Germany,Female,57,5,86568.75,1,0,1,103660.31,0 -6100,15743498,Winter,532,Germany,Male,52,9,137755.76,1,1,0,163191.99,1 -6101,15720463,Ho,796,France,Male,30,2,137262.71,2,1,0,62905.29,0 -6102,15588695,Su,833,Spain,Male,32,6,0,1,1,1,44323.22,1 -6103,15665802,Li Fonti,642,Spain,Female,36,6,0,2,1,1,97938.59,0 -6104,15571144,Ives,655,France,Male,28,10,0,2,0,1,126565.21,0 -6105,15750731,Trevisani,736,Germany,Male,50,9,116309.01,1,1,0,185360.4,1 -6106,15605134,Bond,617,France,Female,34,0,131244.65,2,1,0,183229.02,0 -6107,15626044,Lettiere,762,Germany,Male,28,3,125155.83,2,1,1,106024.02,0 -6108,15737910,Houghton,703,Germany,Male,35,5,140691.08,2,1,0,167810.26,0 -6109,15761076,Lei,507,France,Male,41,3,58820.32,2,1,1,138536.09,0 -6110,15710105,Stirling,581,Germany,Female,26,3,105099.45,1,1,1,184520,1 -6111,15577402,Grant,593,France,Male,31,9,0,2,0,1,20492.16,0 -6112,15803337,Baresi,648,France,Male,23,9,168372.52,1,1,0,134676.72,0 -6113,15654372,Pearce,462,Germany,Male,34,1,94682.56,2,1,0,138478.2,0 -6114,15585867,Rutledge,596,Spain,Male,36,2,0,2,0,1,125557.95,0 -6115,15662488,Udegbunam,627,France,Female,44,5,0,2,1,0,82969.61,1 -6116,15604813,Zaytseva,494,France,Male,40,7,0,2,0,1,158071.69,0 -6117,15611644,Onyemauchechukwu,627,France,Male,73,0,146329.73,1,0,1,43615.67,0 -6118,15674928,Mullah,850,Spain,Male,37,2,0,2,1,0,119969.99,0 -6119,15656100,Candler,632,France,Female,49,5,167962.7,1,0,0,140201.21,0 -6120,15764293,Konovalova,490,France,Male,33,1,0,2,1,1,80792.83,0 -6121,15636423,Lei,715,France,Male,40,7,0,1,1,1,141359.11,0 -6122,15607629,Hollis,679,France,Male,48,8,0,2,1,0,23344.94,0 -6123,15577313,Lionel,619,France,Male,44,3,116967.68,1,1,0,5075.17,1 -6124,15714493,Francis,465,Spain,Female,33,6,0,2,1,1,95500.98,0 -6125,15643359,Carter,736,Spain,Male,32,7,0,1,0,1,79082.62,0 -6126,15687913,Mai,501,Germany,Female,34,7,93244.42,1,0,1,199805.63,0 -6127,15790935,Johnson,535,France,Female,29,5,0,2,0,1,52709.55,0 -6128,15708693,Sherman,759,France,Female,33,2,0,2,1,0,56583.88,0 -6129,15672016,Sabbatini,819,France,Male,35,1,0,2,0,1,3385.04,0 -6130,15727605,Shih,533,Germany,Male,43,4,80442.06,2,0,1,12537.42,0 -6131,15651144,Yao,632,Germany,Female,35,2,150561.03,2,0,0,64722.61,0 -6132,15749401,Ko,686,France,Male,60,9,0,3,1,1,75246.21,1 -6133,15691874,Kazakova,687,France,Female,34,9,125474.44,1,1,0,198929.84,0 -6134,15620735,Chiganu,667,Germany,Female,33,4,127076.68,2,1,0,69011.66,0 -6135,15769781,Nucci,699,Spain,Female,25,8,0,2,1,1,52404.47,0 -6136,15624611,Marsden,497,Spain,Male,37,8,128650.11,2,1,1,163641.53,0 -6137,15773071,Serena,780,Spain,Female,33,6,145580.61,1,1,1,154598.56,0 -6138,15720371,McLean,652,France,Female,51,3,0,1,1,0,173989.47,1 -6139,15717984,Longo,477,France,Male,47,9,144900.58,1,1,0,61315.37,1 -6140,15806407,Wilson,652,France,Female,37,4,0,2,1,0,143393.24,0 -6141,15785042,Hsiung,488,France,Female,31,8,97588.6,1,0,0,124210.53,0 -6142,15809302,Wright,572,France,Male,24,1,0,2,1,1,151460.84,0 -6143,15677550,Folliero,755,France,Female,38,1,0,2,1,0,20734.81,0 -6144,15654096,Johnston,779,Germany,Female,24,10,122200.31,2,1,0,43705.56,0 -6145,15617320,Palermo,693,Spain,Female,46,3,151709.33,1,1,0,180736.24,0 -6146,15653065,Nwabugwu,530,Spain,Female,22,7,0,2,1,0,104170.48,0 -6147,15649112,Endrizzi,738,Spain,Female,33,3,122134.4,2,0,1,27867.59,0 -6148,15690526,Tuan,690,Germany,Male,31,2,137260.45,2,1,0,55387.28,0 -6149,15806945,Udobata,611,France,Female,30,9,88594.14,1,1,0,196332.45,0 -6150,15670066,Ibezimako,643,Spain,Male,34,6,0,2,1,1,116046.22,0 -6151,15625761,Maclean,632,Germany,Male,41,8,127205.32,4,1,0,93874.87,1 -6152,15761525,Shaw,727,Spain,Female,31,10,96997.09,2,0,0,76614.04,0 -6153,15735080,Cummins,508,France,Female,64,2,0,1,1,1,6076.62,0 -6154,15619537,Lavrentiev,550,France,Male,31,5,142200.19,2,1,1,122221.71,0 -6155,15598162,Saunders,754,Germany,Female,39,3,160761.41,1,1,1,24156.03,0 -6156,15694300,Fiorentino,759,France,Male,26,4,0,2,1,0,135394.62,0 -6157,15637235,Knight,794,Spain,Male,33,8,0,2,0,0,91340.02,0 -6158,15612444,Manfrin,549,France,Male,29,3,0,2,1,0,146090.38,0 -6159,15626457,Zetticci,671,France,Male,31,0,116234.61,1,1,0,172096.08,0 -6160,15627995,Angelo,756,Germany,Female,26,5,155143.52,1,0,1,135034.57,1 -6161,15706128,Zhdanov,632,France,Female,21,1,0,2,1,0,84008.66,0 -6162,15666430,Peck,579,France,Male,38,8,0,2,0,0,91763.67,0 -6163,15627385,Uwaezuoke,748,France,Male,34,5,84009.47,1,1,1,137001.1,0 -6164,15581323,White,488,Germany,Female,28,7,139246.22,2,1,0,106799.49,0 -6165,15608109,Greco,710,Germany,Male,58,7,170113,2,0,1,10494.64,0 -6166,15801942,Chu,619,Spain,Female,41,8,0,3,1,1,79866.73,1 -6167,15567431,Kodilinyechukwu,773,France,Male,64,2,145578.28,1,0,1,186172.85,0 -6168,15810167,Scott,657,Spain,Male,75,7,126273.95,1,0,1,91673.6,0 -6169,15644501,Enyinnaya,579,France,Female,26,10,162482.76,1,1,1,18458.2,0 -6170,15785290,Hao,542,France,Male,29,9,0,1,1,0,8342.35,0 -6171,15611157,McElhone,709,France,Female,32,2,87814.89,1,1,0,138578.37,0 -6172,15673837,Ko,617,Spain,Male,61,3,113858.95,1,1,1,38129.22,0 -6173,15656822,Day,568,Germany,Male,43,5,87612.64,4,1,1,107155.4,1 -6174,15580560,Harris,769,France,Female,73,1,0,1,1,1,29792.11,0 -6175,15760641,Gerald,608,Germany,Male,26,1,106648.98,1,0,1,7063.6,0 -6176,15587584,Nebeuwa,503,Spain,Male,31,4,0,2,1,1,21645.06,0 -6177,15604146,Kaodilinakachukwu,608,Germany,Female,38,8,103653.51,2,1,1,137079.86,0 -6178,15813974,Maruff,731,Germany,Male,37,3,116880.53,1,0,0,172718.35,1 -6179,15746986,Howe,850,Germany,Female,40,4,97990.49,2,0,0,106691.02,0 -6180,15759741,Knepper,591,Germany,Female,34,4,150635.3,1,1,1,72274.84,0 -6181,15734892,Fennell,579,Spain,Male,37,4,0,2,1,1,32246.63,0 -6182,15797194,T'ao,570,France,Male,39,10,129674.89,2,1,0,80552.36,0 -6183,15723786,Morris,709,France,Female,37,9,0,2,1,0,16733.59,0 -6184,15642726,Holmes,611,France,Male,53,3,83568.26,1,0,0,1235.49,0 -6185,15664339,Yu,775,Spain,Male,48,4,178144.91,2,0,0,50168.41,1 -6186,15754526,Walker,699,Germany,Male,36,6,147137.74,1,1,1,33687.9,0 -6187,15703037,Edwards,618,France,Male,37,5,0,1,0,1,178705.45,1 -6188,15751412,Harvey,704,France,Male,36,3,114370.41,1,0,1,66810.48,0 -6189,15609558,McDonald,835,Germany,Female,47,5,108289.28,2,1,1,45859.55,1 -6190,15572408,Chambers,714,Germany,Male,39,3,149887.49,2,1,0,63846.36,0 -6191,15613923,Reed,581,Spain,Female,43,4,170172.9,1,0,1,100236.02,0 -6192,15747000,Shih,592,France,Male,27,3,0,2,1,1,19645.65,0 -6193,15731781,Onyemachukwu,551,France,Male,43,7,0,2,1,0,178393.68,0 -6194,15727198,Teng,689,Germany,Female,28,2,64808.32,2,0,0,78591.15,0 -6195,15794273,Hand,604,France,Female,56,0,62732.65,1,0,1,124954.56,0 -6196,15804950,Onyemauchechukwu,514,France,Female,41,7,0,2,1,1,3756.65,0 -6197,15576304,Bailey,698,France,Male,29,5,95167.55,1,1,1,152723.23,0 -6198,15645200,Chiang,581,Germany,Female,54,2,152508.99,1,1,0,187597.98,1 -6199,15779627,Maclean,573,Germany,Male,31,0,134644.19,1,1,1,70381.49,0 -6200,15750755,Yobachi,449,Spain,Female,33,8,0,2,0,0,156792.89,0 -6201,15569654,Munro,850,Germany,Female,31,3,51293.47,1,0,0,35534.68,0 -6202,15753079,Chidi,612,France,Male,41,5,0,3,0,0,151256.22,0 -6203,15684995,Chamberlain,690,Spain,Male,49,8,116622.73,1,0,1,51011.29,0 -6204,15790763,Trujillo,599,Spain,Female,49,2,0,2,1,0,111190.53,0 -6205,15766458,Tang,498,France,Male,33,1,198113.86,1,1,0,69664.35,0 -6206,15616221,Wilson,497,France,Female,29,4,85646.81,1,0,0,63233.02,1 -6207,15776124,Mann,802,Spain,Male,51,7,0,1,0,1,40855.79,0 -6208,15665811,Parry,644,France,Male,33,9,141234.98,1,1,0,95673.05,0 -6209,15729804,Manfrin,714,France,Male,34,10,0,2,1,1,80234.14,0 -6210,15714062,Millar,690,France,Female,40,9,77641.99,1,0,0,189051.59,1 -6211,15592197,Simmons,522,Spain,Male,30,3,0,2,1,0,145490.85,0 -6212,15793116,Beneventi,502,Germany,Female,40,7,117304.29,1,0,0,196278.32,0 -6213,15638231,Chung,730,Spain,Female,62,2,0,2,1,1,162889.1,0 -6214,15697678,Maxwell,590,Germany,Male,36,6,92340.69,2,1,1,174667.58,0 -6215,15800412,Dale,458,Germany,Male,35,9,146780.52,2,1,1,3476.38,0 -6216,15597610,Stevens,553,Spain,Male,41,6,144974.55,1,1,1,19344.92,0 -6217,15726634,Wei,479,France,Male,47,1,0,1,1,0,95270.83,0 -6218,15670866,Chiu,693,France,Male,31,2,0,2,1,1,107759.31,0 -6219,15667462,Duncan,707,Spain,Male,43,10,0,2,1,0,118368.2,0 -6220,15662574,Brady,636,Spain,Male,37,1,115137.26,1,1,0,52484.01,0 -6221,15716926,Macleod,807,France,Male,33,10,101952.97,2,1,0,178153.65,0 -6222,15603554,Berkeley,513,France,Female,45,0,164649.52,3,1,0,49915.52,1 -6223,15716800,Kaur,582,France,Male,31,2,0,2,1,1,33747.03,0 -6224,15679429,Bell,694,France,Male,32,0,91956.49,1,1,1,59961.81,0 -6225,15616122,Nwokike,777,France,Male,39,8,0,2,1,1,18613.52,0 -6226,15742172,Williamson,598,Germany,Male,32,9,123938.6,2,1,0,198894.42,0 -6227,15792305,Mountgarrett,762,Germany,Male,46,6,123571.77,3,0,1,57014.17,1 -6228,15636016,Wreford,588,France,Female,34,3,120777.88,1,1,1,131729.52,0 -6229,15733138,Paterson,663,Germany,Male,42,5,90248.79,1,1,1,79169.73,0 -6230,15669741,Hou,777,France,Male,36,7,0,1,1,0,106472.34,0 -6231,15616954,Smith,592,France,Male,71,4,0,2,0,1,17013.54,0 -6232,15729238,Peng,631,Germany,Male,48,1,106396.48,1,1,1,150661.42,1 -6233,15718242,Wollstonecraft,725,Germany,Female,47,1,104887.43,1,0,0,86622.56,1 -6234,15682914,Bolton,850,France,Male,34,2,72079.71,1,1,1,115767.93,0 -6235,15654274,Corrie,540,France,Male,37,6,0,2,1,0,141998.89,0 -6236,15691457,Boyle,674,Spain,Male,36,2,0,2,1,1,182787.17,0 -6237,15719649,Lambie,553,France,Male,38,3,99844.68,1,0,0,187915.7,0 -6238,15778897,Cartwright,630,France,Female,28,1,0,2,1,1,133267.78,0 -6239,15589437,Lu,466,France,Male,26,3,156815.71,1,1,1,137476.09,0 -6240,15682369,Pisano,613,France,Male,47,6,146034.74,1,1,1,77146.14,0 -6241,15626507,Chukwubuikem,558,France,Male,27,1,152283.39,1,1,0,183271.15,0 -6242,15571995,Harper,775,Germany,Female,33,1,118897.1,2,1,1,26362.4,0 -6243,15673333,Wilson,698,Germany,Male,52,8,96781.39,1,1,1,153373.71,0 -6244,15748752,Ch'in,608,Germany,Male,33,1,102772.67,2,1,0,70705.58,0 -6245,15725302,Streeton,670,Spain,Female,20,4,0,2,1,0,119759.24,0 -6246,15722083,Ch'ang,591,Spain,Male,39,8,0,2,0,0,42392.24,0 -6247,15771442,Pennington,633,France,Male,40,4,150578,1,0,1,34670.62,1 -6248,15803633,T'ien,678,France,Female,46,1,0,2,0,0,82106.19,0 -6249,15672185,Liu,590,France,Male,47,3,0,2,1,0,171774.5,0 -6250,15806486,Cunningham,705,France,Female,48,0,0,2,0,0,149772.61,0 -6251,15570895,Ch'in,608,France,Male,42,10,163548.07,1,1,0,38866.85,0 -6252,15614520,Smith,682,France,Female,37,8,148580.12,1,1,0,35179.18,0 -6253,15687492,Anderson,596,Germany,Male,32,3,96709.07,2,0,0,41788.37,0 -6254,15675337,Forbes,395,Germany,Female,34,5,106011.59,1,1,1,17376.57,1 -6255,15721047,Ansell,578,Germany,Male,37,1,135650.88,1,1,0,199428.19,0 -6256,15589017,Chiu,547,Germany,Male,55,4,111362.76,3,1,0,16922.28,1 -6257,15611186,Yevdokimova,609,France,Male,37,1,39344.83,1,1,1,178291.89,1 -6258,15617301,Chamberlin,774,Germany,Male,36,9,130809.77,1,1,0,152290.28,0 -6259,15726046,Johnston,712,France,Female,27,2,133009.51,1,1,0,126809.15,0 -6260,15585748,McDonald,585,Germany,Female,28,9,135337.49,2,1,1,40385.61,0 -6261,15672826,Chen,666,France,Female,32,10,112536.57,2,1,1,34350.54,0 -6262,15595162,Cattaneo,708,Spain,Female,35,8,122570.69,1,0,0,199005.88,0 -6263,15650026,Barclay-Harvey,513,France,Male,44,1,63562.02,2,0,1,52629.73,1 -6264,15745826,Dawson,445,France,Male,37,3,0,2,1,1,180012.39,0 -6265,15708610,Costa,690,Germany,Male,44,9,100368.63,2,0,0,35342.33,0 -6266,15624471,Chikwado,850,France,Male,37,6,0,2,1,0,109291.22,0 -6267,15590097,Ch'eng,537,Spain,Female,33,7,136082,1,1,0,62746.54,0 -6268,15689328,Harrison,705,Germany,Male,48,9,114169.16,1,0,0,173273.2,1 -6269,15582154,Crawford,670,France,Female,45,5,47884.92,1,1,1,54340.24,0 -6270,15734626,Gibson,652,Spain,Female,36,1,0,2,1,1,19302.78,0 -6271,15702806,Martin,696,Spain,Male,24,9,0,1,0,0,10883.52,0 -6272,15620756,Stokes,747,France,Male,49,6,202904.64,1,1,1,17298.72,1 -6273,15611331,Niu,511,France,Female,46,1,0,1,1,1,115779.48,1 -6274,15576935,Ampt,743,Spain,Male,43,2,161807.18,2,0,1,93228.86,1 -6275,15661275,Wynn,532,Germany,Male,52,3,110791.97,1,1,0,148704.77,1 -6276,15814940,Lawrence,642,Spain,Female,33,9,0,2,1,1,150475.14,0 -6277,15768471,Wagner,554,Germany,Female,54,6,108755,1,1,0,40914.32,1 -6278,15697391,Argyle,604,Spain,Female,34,3,0,2,1,0,38587.7,0 -6279,15793346,Ofodile,602,France,Female,72,3,0,2,1,1,171260.66,0 -6280,15608338,Chiemenam,757,Spain,Female,55,9,117294.12,4,1,0,94187.47,1 -6281,15578546,Akobundu,491,Germany,Male,26,4,102251.14,1,1,1,145900.89,0 -6282,15656921,Locke,850,France,Male,31,4,0,2,0,0,152298.28,0 -6283,15761340,Bullen,521,France,Male,22,5,0,2,1,1,99828.45,0 -6284,15591135,Forster,726,France,Male,37,2,132057.92,2,1,0,34743.98,0 -6285,15623219,Smith,596,France,Male,33,8,0,1,1,0,121189.3,1 -6286,15655229,Craig,850,Germany,Female,35,7,114285.2,1,0,1,129660.59,0 -6287,15805884,Archer,637,France,Female,41,9,0,2,1,0,145477.36,0 -6288,15668289,McWilliams,690,Spain,Male,32,2,76087.98,1,0,1,151822.66,0 -6289,15568562,Moss,689,France,Male,40,8,160272.27,1,1,0,49656.24,0 -6290,15773276,Townsend,633,Spain,Male,63,4,114552.6,1,1,0,73856.28,1 -6291,15622801,Brown,555,France,Female,27,8,102000.17,1,1,1,116757,0 -6292,15779886,Munson,563,Spain,Male,24,7,0,2,0,0,16319.56,0 -6293,15713673,T'ien,494,France,Female,33,1,137853,1,0,1,90273.85,0 -6294,15783083,Shubin,534,France,Male,27,9,0,2,1,0,161344.13,0 -6295,15742824,Isayeva,696,Germany,Male,42,7,162318.61,1,1,0,121061.89,0 -6296,15621550,Hung,535,Spain,Female,50,1,140292.58,3,0,0,69531.22,1 -6297,15799480,Webb,600,France,Male,34,0,0,2,0,1,3756.23,0 -6298,15625247,Scott,807,France,Female,34,1,0,1,0,0,114448.13,0 -6299,15755241,Rahman,714,France,Female,52,2,0,1,0,1,144045.08,1 -6300,15575679,Lori,590,France,Male,24,7,126431.54,1,1,0,58781.11,0 -6301,15668235,Cooke,614,France,Female,41,3,123475.04,1,1,1,179227.52,0 -6302,15683183,Volkova,766,Germany,Female,45,6,97652.96,1,1,0,127332.33,0 -6303,15684592,Lamb,557,Spain,Male,42,4,0,2,0,1,86642.38,0 -6304,15591169,Hawes,788,Germany,Female,49,4,137455.99,1,1,0,184178.29,1 -6305,15653455,Smith,648,France,Female,38,2,0,2,0,1,9551.49,0 -6306,15732563,Swanton,726,Germany,Female,33,7,99046.31,2,1,1,56053.06,0 -6307,15656471,Mitchell,773,France,Male,33,9,0,2,1,1,1118.31,0 -6308,15598510,Colombo,583,Germany,Male,27,4,105907.42,2,1,1,195732.04,0 -6309,15766427,Shaw,565,Germany,Male,52,5,97720.35,2,1,0,175070.94,1 -6310,15785342,Shipp,705,France,Male,25,9,0,2,0,1,112331.19,0 -6311,15641595,Jonathan,685,Spain,Male,43,4,97392.18,2,1,0,43956.83,0 -6312,15798429,Hernandez,741,France,Male,29,8,0,2,1,1,115994.52,0 -6313,15648136,Green,658,Germany,Female,28,9,152812.58,1,1,0,166682.57,0 -6314,15812482,Young,575,France,Male,27,3,139301.68,1,1,0,99843.98,0 -6315,15790810,Han,844,France,Female,41,10,76319.64,1,1,1,141175.18,1 -6316,15687421,Highland,559,Spain,Male,67,9,125919.35,1,1,0,175910.95,1 -6317,15765643,Hamilton,725,France,Male,37,6,124348.38,2,0,1,176984.34,0 -6318,15654878,Yobanna,450,France,Male,29,7,117199.8,1,1,1,43480.63,0 -6319,15686835,Crawford,738,Germany,Female,57,9,148384.64,1,0,0,155047.11,1 -6320,15768340,Beavers,642,Germany,Female,19,3,113905.48,1,1,1,176137.2,0 -6321,15673599,Williamson,618,Spain,Male,32,5,133476.09,1,0,1,154843.4,0 -6322,15689096,Beneventi,590,France,Male,47,0,117879.32,1,1,1,8214.46,0 -6323,15684294,Chidumaga,735,France,Male,50,2,0,2,0,1,147075.69,0 -6324,15615828,Mitchell,550,France,Male,34,8,122359.5,1,0,0,116495.55,0 -6325,15746012,Chibugo,729,Spain,Female,28,0,0,2,1,1,31165.06,1 -6326,15615797,Hyde,743,Germany,Male,59,5,108585.35,1,1,1,192127.22,1 -6327,15788494,Alekseeva,555,France,Male,31,8,145875.74,1,1,0,137491.23,0 -6328,15793856,Abdulov,667,Spain,Female,36,3,121542.57,2,1,1,186841.71,0 -6329,15629545,Buckley,790,Spain,Female,41,7,109508.68,1,0,0,86776.38,0 -6330,15661198,Howard,727,Germany,Male,34,2,146407.11,1,1,1,72073.72,0 -6331,15715117,Peel,744,France,Female,39,6,0,1,0,0,10662.58,0 -6332,15701074,Herz,629,Germany,Male,35,8,112330.83,1,1,1,91001.02,0 -6333,15793046,Holden,619,France,Female,35,4,90413.12,1,1,1,20555.21,0 -6334,15623744,McLean,634,France,Male,34,8,105302.66,1,1,1,123164.97,0 -6335,15611329,Findlay,608,Spain,Female,35,6,0,2,1,1,143463.28,0 -6336,15740428,Wyatt,507,France,Female,35,1,0,2,0,0,92131.54,0 -6337,15781534,Rapuluolisa,536,Germany,Female,35,4,121520.36,1,0,0,77178.42,0 -6338,15618243,Buckland,730,Spain,Female,43,1,103960.38,1,1,1,193650.16,0 -6339,15784161,Hargreaves,583,Germany,Male,39,8,102945.01,1,0,0,52861.89,0 -6340,15700325,Onyeoruru,644,France,Female,24,8,92760.55,1,1,0,35896.75,0 -6341,15659064,Salas,790,Spain,Male,37,8,0,2,1,1,149418.41,0 -6342,15658364,Laney,807,Germany,Female,40,1,134590.21,1,1,1,46253.65,0 -6343,15704340,Fu,581,France,Female,37,10,104255.03,1,1,0,86609.37,0 -6344,15793455,Tien,627,Spain,Female,55,6,0,1,0,0,91943.94,1 -6345,15579777,Sazonova,850,France,Male,41,3,0,2,1,0,128892.36,0 -6346,15632345,Tuan,754,France,Female,35,4,0,2,1,0,44830.71,0 -6347,15814468,Wei,551,Germany,Male,50,1,121399.98,1,0,1,84508.44,1 -6348,15754820,Bergamaschi,637,Germany,Male,35,8,147127.81,2,1,1,84760.7,0 -6349,15707505,Taylor,699,Spain,Male,31,8,125927.51,2,1,0,147661.47,0 -6350,15699507,Messersmith,542,France,Female,25,7,0,2,0,1,82393.08,0 -6351,15799600,Coles,640,Germany,Male,48,1,111599.32,1,0,1,135995.58,0 -6352,15794472,Brookes,553,France,Female,27,3,0,2,0,0,159800.16,0 -6353,15646632,Reid,741,France,Male,38,9,0,2,1,0,14379.01,0 -6354,15676353,Etheridge,598,France,Male,35,8,114212.6,1,1,1,74322.85,0 -6355,15566312,Jolly,660,Spain,Female,42,5,0,3,1,1,189016.24,1 -6356,15570414,Chizoba,618,Spain,Male,41,4,115251.64,1,0,0,136435.75,0 -6357,15776743,Eberegbulam,647,France,Male,43,9,0,2,1,1,78488.39,0 -6358,15674637,Pagnotto,491,France,Female,68,3,107571.61,1,0,1,113695.99,0 -6359,15730418,Lucchesi,652,France,Female,32,2,0,2,1,0,54628.11,0 -6360,15739972,Hughes,650,Germany,Female,45,9,152367.21,3,1,0,150835.21,1 -6361,15661591,Panicucci,413,Germany,Male,39,1,130969.77,2,1,1,158891.79,0 -6362,15675585,Burns,416,Germany,Female,25,0,97738.97,2,1,1,160523.33,0 -6363,15814750,Ricci,629,Spain,Male,34,8,0,2,1,1,180595.02,0 -6364,15593454,Lambert,678,Spain,Female,40,4,113794.22,1,1,0,16618.76,0 -6365,15663421,Esposito,527,Spain,Male,28,6,128396.33,2,1,0,79919.97,0 -6366,15576196,Benson,743,Spain,Female,48,5,118207.69,2,0,0,186489.14,1 -6367,15677324,Botts,683,Germany,Male,73,9,124730.26,1,1,1,51999.5,0 -6368,15568742,Parkes,536,France,Female,41,9,0,1,1,0,121299.14,0 -6369,15693764,Mai,663,Spain,Male,52,0,136298.65,1,1,0,144593.3,1 -6370,15714260,Castiglione,646,France,Female,38,2,0,2,0,0,178752.73,0 -6371,15798200,Manna,707,France,Male,35,2,0,3,1,1,94148.3,0 -6372,15656627,Lin,602,France,Male,34,5,0,2,1,1,77414.45,0 -6373,15791111,Fink,635,France,Female,47,2,125724.95,2,1,0,63236.97,0 -6374,15638269,Baresi,597,France,Male,67,2,0,2,0,1,108645.85,0 -6375,15807473,Morehead,503,France,Male,38,1,0,2,1,1,95153.24,0 -6376,15708534,Afamefuna,524,Spain,Female,64,5,0,1,1,0,136079.64,1 -6377,15640686,Greco,700,France,Male,46,5,95872.86,1,1,0,98273.01,1 -6378,15588904,Balashova,692,France,Male,33,9,0,1,1,0,113505.93,1 -6379,15768763,Bogdanov,562,France,Male,37,2,0,1,0,1,52525.15,1 -6380,15770543,Lowe,679,France,Male,37,7,74260.03,1,1,0,194617.98,0 -6381,15642162,Ponce,603,Germany,Male,35,1,123407.69,1,1,0,152541.89,1 -6382,15714046,Trevisano,720,Spain,Male,33,3,123783.91,2,1,1,142903.44,0 -6383,15575060,Gardner,797,France,Male,24,5,0,2,1,0,182257.61,0 -6384,15812040,Lorenzo,594,France,Male,36,6,153880.15,1,0,0,135431.72,0 -6385,15812073,Palmer,529,France,Female,31,7,0,2,1,1,175697.87,0 -6386,15706810,Zuyeva,606,Germany,Female,32,1,106301.85,2,0,1,59061.25,0 -6387,15584090,Jen,621,Spain,Female,40,7,0,2,0,1,131283.6,1 -6388,15810807,Alekseeva,513,France,Female,43,9,0,2,1,0,152499.8,0 -6389,15582033,Manfrin,753,Germany,Male,44,3,138076.47,1,1,0,15523.09,1 -6390,15687607,Chiemenam,605,France,Female,30,9,135422.31,1,0,1,186418.85,0 -6391,15588406,Chiemenam,574,Spain,Female,37,7,0,2,1,0,32262.28,0 -6392,15784099,Clark,726,France,Female,38,5,126875.62,1,1,0,128052.29,0 -6393,15701352,Fanucci,611,Spain,Female,28,3,96381.68,2,1,0,181419.29,0 -6394,15789371,Cattaneo,593,Germany,Female,41,4,119703.1,2,1,1,109783.29,0 -6395,15602845,Udinesi,466,Germany,Male,41,2,152102.18,2,1,0,181879.56,0 -6396,15707918,Bentley,741,Germany,Female,36,0,127675.39,2,1,0,74260.16,0 -6397,15602812,Holmes,684,Germany,Female,44,2,133776.86,2,0,1,49865.04,0 -6398,15675888,Austin,550,Spain,Female,33,9,72788.03,1,1,1,103608.06,0 -6399,15591822,Mackenzie,593,Spain,Male,26,9,76226.9,1,1,0,167564.82,0 -6400,15738501,Booth,601,Germany,Male,48,9,163630.76,1,0,1,41816.49,1 -6401,15585907,Collier,676,Spain,Female,30,5,0,2,0,0,179066.58,0 -6402,15579040,Hs?,556,France,Female,46,10,0,2,0,0,109184.24,0 -6403,15804211,Oluchukwu,719,France,Male,36,3,155423.17,1,1,1,199841.32,0 -6404,15736126,Sung,850,Germany,Male,55,0,98710.89,1,1,1,83617.17,1 -6405,15745399,Marino,649,Spain,Female,49,2,0,1,1,0,84863.85,1 -6406,15760749,Vinogradov,509,Spain,Male,41,7,126683.8,1,0,1,114775.53,0 -6407,15637118,Burns,684,France,Male,33,4,140700.61,1,1,0,103557.93,0 -6408,15657829,Fanucci,806,Germany,Male,30,8,168078.83,1,1,0,85028.36,1 -6409,15738497,Chukwujamuike,729,Spain,Male,44,4,107726.93,2,1,0,153064.87,0 -6410,15690695,Flynn,683,France,Female,33,9,0,2,1,1,38784.42,0 -6411,15762351,Chao,689,Spain,Female,63,1,0,2,1,1,186526.12,0 -6412,15791172,Yeh,672,Germany,Female,21,1,35741.69,1,1,0,28789.94,0 -6413,15598982,Klein,602,Germany,Female,53,5,98268.84,1,0,1,45038.29,1 -6414,15734765,Mahmood,739,France,Female,20,4,133800.98,1,0,1,150245.81,0 -6415,15642912,Tu,618,France,Female,21,2,125682.79,1,0,0,57762,0 -6416,15769516,Shcherbakov,674,France,Female,42,9,0,2,1,0,4292.72,0 -6417,15789379,Zetticci,762,France,Male,26,6,130428.78,1,1,0,173365.89,0 -6418,15695103,Carr,790,Spain,Male,37,6,0,2,1,1,119484.01,0 -6419,15801924,Browne,754,Spain,Female,27,8,0,2,0,0,121821.16,0 -6420,15767804,Feng,729,France,Male,44,6,0,2,1,0,151733.43,0 -6421,15718039,Ferguson,606,Germany,Female,47,0,137138.2,2,0,1,53784.22,0 -6422,15579994,Shaw,616,France,Male,23,8,73112.95,1,1,1,62733.05,0 -6423,15595037,Palermo,772,France,Male,47,9,152347.01,1,0,1,17671.78,0 -6424,15600720,Moore,652,Spain,Male,41,8,115144.68,1,1,0,188905.43,0 -6425,15782608,Huang,743,France,Male,43,5,0,2,0,0,113079.19,1 -6426,15566894,Gray,793,France,Male,39,3,137817.52,1,0,0,83997.79,0 -6427,15749123,Sokolova,743,Spain,Male,45,7,157332.26,1,1,0,125424.42,0 -6428,15668943,Henderson,746,France,Male,37,2,0,2,1,0,143194.05,0 -6429,15577423,Mosley,627,Germany,Female,39,5,124586.93,1,1,0,93132.61,1 -6430,15623102,Nnaemeka,713,Spain,Male,38,6,116980.78,2,0,1,76038.38,0 -6431,15728012,Everett,678,Spain,Female,40,3,128398.38,1,1,0,168658.3,0 -6432,15683363,Goddard,540,Spain,Male,39,1,0,1,0,1,108419.41,0 -6433,15699335,Kuo,615,Germany,Female,33,3,137657.25,2,1,1,171657.57,0 -6434,15574369,Bianchi,415,Spain,Male,53,5,167259.44,1,1,1,22357.25,0 -6435,15703167,Rouse,628,France,Female,45,8,0,2,1,0,193903.06,0 -6436,15754874,Nwoye,700,France,Male,26,4,119009.57,1,1,0,141926.43,0 -6437,15723216,Greco,623,Germany,Male,33,2,80002.33,1,1,1,104079.62,0 -6438,15725094,Fang,623,France,Female,37,4,140211.88,1,1,1,93832.33,0 -6439,15647974,Chiemenam,679,France,Female,44,3,118742.74,2,1,0,1568.91,0 -6440,15583371,Artemiev,632,Spain,Male,37,1,138207.08,1,1,0,60778.11,1 -6441,15772559,Burrows,790,France,Female,47,10,148636.21,1,0,1,16119.96,1 -6442,15711251,Chizuoke,514,France,Male,45,1,178827.79,1,1,0,60375.18,0 -6443,15719212,T'ien,491,France,Male,33,5,83134.3,1,1,0,187946.55,0 -6444,15764927,Rogova,753,France,Male,92,3,121513.31,1,0,1,195563.99,0 -6445,15731412,Trevisano,693,Germany,Female,37,6,95900.04,1,1,1,38196.24,0 -6446,15719170,Sagese,679,France,Female,30,1,112543.42,1,1,1,179435.21,0 -6447,15596011,Artyomova,529,Spain,Male,34,9,0,1,1,1,93208.22,0 -6448,15614834,Long,619,Spain,Female,31,3,141751.82,1,0,1,61531.86,0 -6449,15600510,Hsueh,680,Spain,Female,37,6,124140.57,2,1,0,92826.35,0 -6450,15625706,White,693,Germany,Male,45,2,116546.59,2,0,0,23140.28,1 -6451,15781409,Lazarev,834,France,Female,28,6,0,1,1,0,74287.53,0 -6452,15722583,Benjamin,636,Spain,Female,29,6,157576.47,2,1,1,101102.39,0 -6453,15677243,Wan,538,Spain,Male,43,5,0,2,1,0,126933.73,0 -6454,15815070,Romano,566,Germany,Female,44,5,141428.99,2,0,0,68408.74,0 -6455,15705899,Craig,597,Spain,Male,35,0,127510.99,1,1,1,155356.34,0 -6456,15701522,Yermolayeva,711,France,Female,29,9,0,2,0,1,3234.8,0 -6457,15755978,Tseng,606,France,Male,31,10,0,2,1,0,195209.4,0 -6458,15722090,Tseng,615,Spain,Male,51,6,81818.49,1,1,1,169149.38,0 -6459,15783526,Le Hunte,589,France,Male,36,1,100895.54,1,1,1,68075.14,0 -6460,15632125,Blake,606,Germany,Male,45,5,63832.43,1,1,1,93707.8,0 -6461,15688395,Lane,582,France,Male,29,4,0,2,0,0,156153.27,0 -6462,15666975,Sparks,710,France,Female,36,4,116085.06,1,1,0,58601.61,0 -6463,15682211,Tu,467,France,Male,57,1,0,2,1,1,114448.77,0 -6464,15637411,Tochukwu,749,France,Male,30,1,0,2,0,1,126551.65,0 -6465,15591512,Whittaker,564,Germany,Female,33,2,115761.51,1,0,1,112350.21,1 -6466,15606855,Wang,730,Spain,Male,26,6,0,2,1,1,185808.7,0 -6467,15763683,Northern,678,Germany,Male,32,4,139626.01,1,1,1,118235.52,1 -6468,15641782,Humphries,540,France,Female,31,7,0,1,0,1,183051.6,1 -6469,15677184,Cremonesi,767,France,Female,35,6,115576.44,1,0,1,27922.45,0 -6470,15775042,Ku,615,France,Female,23,4,0,2,1,0,196476.19,0 -6471,15616630,Tobenna,583,Germany,Female,41,5,77647.6,1,1,0,190429.52,0 -6472,15800233,Okwuadigbo,850,France,Female,40,5,0,2,1,0,35034.15,0 -6473,15588419,Johnston,651,Germany,Female,34,10,148962.46,1,1,0,66389.43,1 -6474,15595557,Li,798,France,Male,22,8,0,2,1,0,107615.43,0 -6475,15626143,Talbot,695,France,Male,37,2,0,2,1,1,99692.65,0 -6476,15566030,Tu,497,Germany,Male,41,5,80542.81,1,0,0,88729.22,1 -6477,15701412,T'ien,739,France,Male,40,4,0,2,0,0,173321.65,0 -6478,15702464,Ross,549,France,Female,34,4,0,2,0,0,139463.57,0 -6479,15573348,Maclean,850,France,Male,35,9,102050.47,1,1,1,3769.71,0 -6480,15704160,Wan,648,Spain,Male,49,5,0,1,1,0,149946.43,1 -6481,15693704,Tsou,679,France,Female,24,6,114948.76,2,0,1,135768.25,0 -6482,15664752,Jack,606,Germany,Male,39,8,136000.45,2,1,0,31708.53,0 -6483,15628292,Lucchesi,850,France,Male,32,4,156001.68,2,1,1,151677.31,0 -6484,15621195,Ch'eng,619,Germany,Male,41,3,147974.16,2,1,0,170518.83,0 -6485,15668629,Saunders,719,Spain,Male,44,2,0,2,1,0,196582.19,0 -6486,15635197,Glover,640,Germany,Male,26,5,90402.77,1,1,1,3298.65,0 -6487,15592761,Tung,710,France,Male,40,5,0,2,0,0,162878.96,0 -6488,15574283,Padovano,580,France,Male,31,2,0,2,0,1,64014.24,0 -6489,15598097,Johnstone,550,France,Male,44,9,0,2,1,0,26257.01,0 -6490,15711352,Endrizzi,841,France,Female,31,3,162701.65,2,1,1,126794.56,0 -6491,15620751,Secombe,760,France,Male,34,2,0,2,1,0,164162.44,0 -6492,15656717,Elewechi,687,France,Female,30,6,0,2,0,0,179206.92,0 -6493,15643121,Chu,753,Germany,Female,35,5,82453.96,2,0,0,18254.75,0 -6494,15723671,Lucciano,661,France,Male,35,9,100107.99,1,1,0,83949.68,0 -6495,15752846,Pinto,699,France,Male,28,7,0,2,1,1,22684.78,0 -6496,15640852,McGregor,617,Germany,Female,39,5,83348.89,3,1,0,7953.62,1 -6497,15789313,Ugorji,595,Germany,Female,44,4,96553.52,2,1,0,143952.24,1 -6498,15793688,Bancks,669,France,Male,50,9,201009.64,1,1,0,158032.5,1 -6499,15770405,Warlow-Davies,613,France,Female,27,5,125167.74,1,1,0,199104.52,0 -6500,15702561,Dale,782,France,Male,32,9,0,1,1,1,87566.97,0 -6501,15625964,Buckley,582,France,Female,43,5,153313.67,1,0,0,170563.73,0 -6502,15761364,Nkemjika,679,France,Male,30,9,0,2,1,0,157871.55,0 -6503,15590286,Fairley,611,France,Female,40,2,125879.29,1,1,0,93203.43,0 -6504,15587978,Boothby,455,Germany,Female,37,6,170057.62,1,0,1,54398.56,0 -6505,15773242,Chukwuhaenye,621,France,Male,32,1,0,2,1,1,168779.47,0 -6506,15761053,Lock,596,Germany,Male,48,2,131326.47,1,0,0,1140.02,1 -6507,15702095,Clarke,585,Spain,Female,56,1,128472.8,1,1,0,186476.91,1 -6508,15764253,Ramsey,742,France,Male,32,6,160485.16,1,1,0,29023.03,0 -6509,15700801,Eipper,850,Germany,Male,42,6,84445.68,3,0,1,60021.34,1 -6510,15730590,Ko,738,Germany,Female,40,1,115409.18,2,0,0,180456.8,0 -6511,15643916,Munro,619,Spain,Male,46,8,62400.48,1,1,1,132498.39,1 -6512,15720636,McGregor,628,France,Female,50,4,143054.56,1,0,1,109608.81,1 -6513,15795429,Henderson,487,France,Male,24,7,133628.09,2,1,1,98570.01,0 -6514,15609254,Fernandez,513,Spain,Female,41,9,107135.04,2,1,1,160546.58,0 -6515,15625141,Porter,563,Spain,Male,26,7,0,2,0,0,6139.74,0 -6516,15810898,Pan,803,France,Female,65,2,151659.52,2,0,1,6930.17,0 -6517,15775797,Esposito,607,Spain,Female,32,7,0,3,0,1,10674.62,0 -6518,15795246,Kaeppel,628,Germany,Female,51,9,155903.82,2,1,1,71159.84,0 -6519,15795275,Lamb,521,Spain,Female,49,4,82940.25,2,0,0,62413.01,1 -6520,15571869,Lei,669,Germany,Female,50,4,112650.89,1,0,0,166386.22,1 -6521,15694143,Conti,686,France,Female,41,10,0,1,1,0,133086.45,0 -6522,15748231,Hargreaves,700,Germany,Male,35,4,95853.39,2,1,0,192933.37,0 -6523,15632185,Yermolayev,663,France,Female,42,1,82228.67,2,1,0,71359.78,0 -6524,15806249,Kerr,671,Spain,Female,31,4,0,2,0,1,79270.02,0 -6525,15743293,Waters,651,Germany,Female,35,1,163700.78,3,1,1,29583.48,1 -6526,15598157,Onyeorulu,728,France,Male,34,4,106328.08,1,1,0,88680.65,0 -6527,15700946,Kolesnikova,574,France,Female,34,7,152992.91,1,1,1,134691.2,0 -6528,15722692,Kazakova,464,France,Male,38,3,116439.65,1,1,0,75574.48,0 -6529,15696506,MacDonald,604,Spain,Male,27,9,101352.78,1,0,0,30252.3,0 -6530,15728823,Sharwood,836,Spain,Female,37,10,0,2,1,0,111324.41,0 -6531,15808851,Bufkin,511,Germany,Female,75,9,105609.17,1,0,1,105425.18,0 -6532,15675231,Nwankwo,518,France,Female,45,8,0,2,1,1,36193.07,0 -6533,15732299,Boniwell,756,France,Male,67,4,0,3,1,1,93081.87,0 -6534,15706269,Willis,489,France,Female,47,8,103894.38,2,1,1,107625.46,0 -6535,15590078,Burns,622,Spain,Male,27,9,139834.93,1,1,1,152733.89,0 -6536,15776985,Kung,652,France,Female,36,6,112518.71,2,0,1,110421.31,0 -6537,15756743,Howells,625,France,Female,37,7,115895.42,1,1,0,48486.25,0 -6538,15782364,Bevan,521,Spain,Female,39,3,146408.68,1,0,0,72993.67,0 -6539,15604093,Neitenstein,546,France,Male,34,4,165363.31,2,1,1,25744.13,1 -6540,15749328,Johnson,697,France,Female,45,1,0,2,1,0,46807.62,1 -6541,15656322,Sandover,571,Germany,Male,33,3,71843.15,1,1,0,26772.04,0 -6542,15685564,Nnamutaezinwa,748,Spain,Male,35,5,105492.53,1,1,1,150057.2,0 -6543,15785831,Sinclair,591,France,Male,35,7,183027.25,1,1,1,56028.79,0 -6544,15796218,Wei,814,Germany,Male,29,1,131968.57,2,1,1,147693.92,0 -6545,15716218,Higgins,709,France,Female,45,3,104118.5,1,0,1,174032,0 -6546,15572735,Chang,433,Spain,Male,27,2,0,2,1,1,153698.65,0 -6547,15633840,Henderson,781,France,Male,20,0,125023.1,2,1,1,108301.45,0 -6548,15608760,Cox,656,France,Female,30,4,74323.2,1,1,1,22929.08,0 -6549,15627848,Tsui,683,France,Male,38,7,109346.13,2,1,0,102665.92,0 -6550,15792029,Lee,620,France,Male,32,6,0,2,1,0,56139.09,0 -6551,15617331,Sergeyeva,637,Germany,Female,39,3,109698.41,1,1,1,88391.29,1 -6552,15651740,Napolitani,525,Spain,Female,30,5,0,2,0,1,149195.44,0 -6553,15636407,Beatham,793,Germany,Female,34,5,127758.09,1,1,0,143357.03,0 -6554,15607526,Lu,638,Germany,Male,50,1,102645.48,1,1,0,168359.98,1 -6555,15632576,Yashina,520,France,Male,31,4,93249.4,1,1,0,77335.75,0 -6556,15581505,Bales,641,France,Male,35,5,0,2,1,0,93148.93,0 -6557,15612207,Hill,840,Germany,Female,51,1,87779.83,1,0,1,36687.11,1 -6558,15707242,Ibeamaka,504,Spain,Male,40,5,0,2,0,0,146703.36,0 -6559,15721937,Romilly,686,France,Male,38,0,138131.34,1,0,1,115927.85,0 -6560,15773852,Hayes,533,Germany,Male,38,4,70362.52,2,1,1,104189.46,0 -6561,15719778,Chiu,577,France,Female,32,1,0,2,1,0,9902.39,0 -6562,15650538,Sun,445,Germany,Female,48,7,168286.58,1,1,0,16645.77,1 -6563,15797475,Brennan,720,France,Male,44,3,86102.27,1,1,0,180134.88,1 -6564,15780359,Storey,643,Germany,Male,25,4,115142.9,1,1,1,148098.95,0 -6565,15737104,Lawson,652,Germany,Female,47,0,126597.89,2,1,1,38798.79,1 -6566,15789936,T'ao,663,France,Female,33,2,0,2,1,0,153295,0 -6567,15709523,Yao,525,Germany,Female,30,0,157989.21,2,1,1,100687.67,0 -6568,15593425,Bracewell,662,Spain,Female,54,1,187997.15,1,0,0,111442.71,1 -6569,15776725,Kerr,724,Germany,Male,54,8,172192.49,1,1,1,136902.01,0 -6570,15604706,Blake,581,Germany,Male,38,1,133105.47,1,1,0,105732.9,1 -6571,15790958,Sanders,685,Spain,Male,38,4,0,2,1,1,35884.91,0 -6572,15747534,Torkelson,595,France,Male,46,10,0,1,1,0,73489.15,1 -6573,15574237,Hsueh,588,France,Female,21,8,0,2,1,1,110114.19,0 -6574,15690332,Wang,647,Germany,Male,35,3,192407.97,1,1,1,40145.28,0 -6575,15661290,Hightower,785,Germany,Female,38,9,107199.75,1,0,0,146398.51,0 -6576,15651883,Genovesi,794,Germany,Female,55,6,115796.7,1,1,0,160526.36,1 -6577,15808905,Levan,823,France,Male,37,5,164858.18,1,1,1,173516.71,0 -6578,15715532,Lai,687,Germany,Male,38,4,117633.28,1,0,1,88396.6,0 -6579,15786078,Loginov,850,France,Female,28,9,0,2,1,0,185821.41,0 -6580,15652401,Lafleur,496,France,Female,36,7,0,2,0,0,108098.28,0 -6581,15673074,Obidimkpa,527,Germany,Female,30,6,126663.51,1,1,1,162267.91,0 -6582,15598744,Ch'ang,576,Germany,Female,71,6,140273.47,1,1,1,193135.25,1 -6583,15785975,Mason,525,Spain,Female,60,7,0,2,0,1,168034.9,0 -6584,15613180,Miranda,727,Germany,Male,21,8,153344.72,1,1,1,163295.87,0 -6585,15584229,Simon,671,Germany,Female,23,9,123943.18,1,1,1,159553.27,0 -6586,15773804,Golubeva,625,France,Male,39,5,0,1,1,0,99800.87,0 -6587,15699515,Manfrin,643,Germany,Male,33,7,98630.31,2,1,1,40250.82,0 -6588,15705313,Stange,707,France,Female,33,2,58036.33,1,1,1,83335.78,0 -6589,15693817,Ferrari,539,Spain,Male,28,5,0,2,1,0,48382.4,0 -6590,15673790,Taylor,498,Germany,Male,45,7,109200.74,2,0,1,165990.44,0 -6591,15674868,Wei,696,Spain,Female,30,0,0,2,1,1,9002.8,0 -6592,15692110,Ch'eng,758,France,Female,33,7,0,1,1,0,188156.34,0 -6593,15645904,Parsons,685,France,Female,33,6,0,2,0,1,186785.01,0 -6594,15581332,Pan,655,Germany,Female,30,1,83173.98,2,1,1,184259.6,0 -6595,15808544,Cameron,747,France,Female,40,3,0,1,0,0,57817.84,1 -6596,15734948,Igwebuike,601,Spain,Male,24,7,0,2,0,0,144660.42,0 -6597,15654531,Tuan,477,France,Male,22,5,82559.42,2,0,0,163112.9,1 -6598,15637774,Fraser,558,France,Male,32,5,73494.21,1,0,0,136301.1,0 -6599,15677141,Turnbull,586,Spain,Male,29,2,132450.24,1,1,1,36176.63,0 -6600,15739578,Chiazagomekpere,850,France,Male,49,6,128663.9,1,1,0,65769.3,1 -6601,15697360,Yudina,505,France,Female,36,2,79951.9,1,0,1,174123.16,1 -6602,15655213,Udinese,591,Germany,Female,51,8,132508.3,1,1,1,161304.68,1 -6603,15580872,Chinweike,761,Germany,Female,38,1,120530.13,2,1,0,109394.62,0 -6604,15683213,Bergamaschi,554,France,Female,35,10,74988.59,2,0,1,190155.13,0 -6605,15801188,Milliner,774,France,Female,47,6,94722.88,1,0,1,61450.96,0 -6606,15645029,Knowles,771,Spain,Female,33,5,0,2,1,0,8673.43,0 -6607,15633181,Swinton,792,France,Male,31,6,71269.89,2,0,1,125912.77,0 -6608,15598259,Gregory,673,Germany,Female,41,9,98612.1,1,1,0,151349.35,0 -6609,15576000,Chibueze,765,France,Male,40,6,138033.55,1,1,1,67972.45,0 -6610,15766047,Sukhorukova,748,France,Female,41,2,91621.69,1,1,1,71139.31,0 -6611,15596339,French,422,France,Male,54,3,140014.42,1,0,1,86350.97,0 -6612,15715199,Estrada,568,Spain,Male,27,5,126815.97,2,0,1,118648.12,0 -6613,15615938,Fleming,502,France,Female,64,3,139663.37,1,0,1,100995.11,0 -6614,15679991,Kennedy,524,France,Female,28,7,0,2,0,1,147100.72,0 -6615,15626135,Combes,689,France,Male,34,1,165312.27,1,1,0,155495.63,0 -6616,15792934,Carruthers,661,France,Male,26,8,0,2,0,0,196875.87,0 -6617,15744046,Andrejew,606,Spain,Male,33,8,0,2,1,1,63176.77,0 -6618,15700826,Ko,678,Germany,Female,54,1,123699.28,2,0,1,105221.76,0 -6619,15756301,Daniels,636,Germany,Female,29,3,97325.15,1,0,1,131924.38,0 -6620,15586517,Toscano,647,France,Male,32,5,97041.16,1,1,1,23132.73,0 -6621,15751297,Wilson,732,France,Male,36,5,0,2,1,0,161428.25,0 -6622,15710365,Thomson,646,France,Male,50,0,104129.24,2,1,0,181794.86,1 -6623,15679307,Kazantseva,559,France,Female,43,1,0,1,0,1,86634.3,0 -6624,15610753,Cremonesi,581,France,Male,28,3,104367.5,1,1,1,29937.75,0 -6625,15811036,Ferri,565,France,Male,46,7,135369.71,1,0,1,140130.22,0 -6626,15610912,Ferri,657,Spain,Female,41,6,112119.48,1,1,0,17536.82,0 -6627,15619932,Lombardi,847,France,Male,66,7,123760.68,1,0,1,53157.16,0 -6628,15746199,Eluemuno,558,France,Female,41,6,0,1,1,1,143585.29,1 -6629,15584967,Chiganu,596,Spain,Male,57,6,0,2,1,1,72402,0 -6630,15734365,Hsueh,579,France,Male,39,5,0,2,0,1,39891.84,0 -6631,15726960,O'Brien,741,France,Female,36,3,0,2,1,1,89804.83,0 -6632,15665177,Booth,613,France,Male,44,3,0,2,0,1,136491.72,0 -6633,15779915,O'Loghlin,694,Spain,Male,31,5,0,1,1,0,35593.18,0 -6634,15729110,Lavrov,729,Spain,Female,42,7,0,2,1,0,58268.2,1 -6635,15575399,Somadina,480,France,Female,42,1,152160.21,2,1,0,101778.9,0 -6636,15678374,Colombo,666,France,Female,59,5,0,2,1,1,185123.09,0 -6637,15792679,Troupe,575,France,Male,24,2,0,2,1,1,119927.81,0 -6638,15668767,Kenenna,850,France,Male,36,3,0,2,1,0,195033.07,0 -6639,15761886,Franklin,740,France,Male,36,4,172381.8,1,1,1,86480.29,0 -6640,15583076,Deleon,588,Germany,Male,41,6,106116.56,2,1,0,198766.61,0 -6641,15815615,Kung,681,France,Male,36,5,141952.07,1,1,1,185144.08,0 -6642,15591942,Zito,611,Spain,Female,33,7,0,2,1,1,3729.89,0 -6643,15724924,Giordano,589,France,Female,37,6,138497.84,1,0,1,18988.58,0 -6644,15762123,Davide,717,Spain,Female,34,1,0,2,1,0,119313.74,0 -6645,15567893,Lei,556,Germany,Male,33,3,124213.36,2,1,0,62627.55,0 -6646,15648989,Moss,850,France,Male,37,4,126872.6,1,1,0,197266.58,0 -6647,15662021,Lucciano,685,Spain,Female,42,2,0,2,0,0,199992.48,0 -6648,15691627,Tai,713,France,Female,37,8,0,1,1,1,16403.41,0 -6649,15731751,Osinachi,437,France,Female,26,1,120923.52,1,0,1,78854.57,0 -6650,15635277,Coates,605,Spain,Male,47,7,142643.54,1,1,0,189310.27,0 -6651,15655252,Larionova,758,Germany,Male,41,10,79857.64,1,1,1,78088.17,0 -6652,15803941,Seleznev,600,France,Male,46,10,95502.21,1,0,0,19842.18,0 -6653,15714380,Butcher,827,France,Male,38,5,0,2,0,0,103305.01,0 -6654,15666559,Gould,608,Germany,Male,23,8,197715.93,2,1,1,116124.28,0 -6655,15799998,Cunningham,608,France,Female,30,8,85859.76,1,0,0,142730.27,0 -6656,15703763,Sanderson,554,France,Male,44,7,85304.27,1,1,1,58076.52,0 -6657,15795640,Mai,683,Germany,Female,35,1,132371.3,2,0,0,186123.57,0 -6658,15780056,Reid,660,Spain,Male,33,4,0,1,1,0,29664.45,0 -6659,15777873,Downer,628,France,Female,31,5,0,1,0,0,147963.07,1 -6660,15584749,Humphries,668,Germany,Male,39,4,79896,1,1,0,38466.39,0 -6661,15765258,Bochsa,776,France,Female,29,5,0,2,1,1,143301.49,0 -6662,15623346,Czajkowski,820,France,Male,36,4,0,2,1,0,31422.69,0 -6663,15614054,Pankhurst,665,France,Male,36,1,0,2,0,1,121505.61,0 -6664,15766185,She,850,Germany,Male,31,4,146587.3,1,1,1,89874.82,0 -6665,15667632,Birdseye,703,France,Female,42,7,0,2,0,1,72500.68,0 -6666,15599024,Hope,506,Spain,Male,32,8,0,2,0,1,182692.8,0 -6667,15798709,Gill,588,Spain,Male,32,3,109109.33,1,0,1,4993.94,0 -6668,15741921,Moon,622,Spain,Female,26,8,0,2,1,1,124964.82,0 -6669,15793671,Watt,606,France,Male,34,5,0,1,1,0,161971.42,0 -6670,15797900,Chinomso,517,France,Male,56,9,142147.32,1,0,0,39488.04,1 -6671,15667932,Bellucci,758,Spain,Female,43,10,0,2,1,1,55313.44,0 -6672,15795933,Barese,677,France,Female,49,3,0,2,1,1,187811.71,0 -6673,15660403,Fleming,827,Spain,Female,35,0,0,2,0,1,184514.01,0 -6674,15736299,Bell,729,France,Female,36,8,109106.8,1,0,0,121311.12,0 -6675,15759034,Li Fonti,654,France,Male,36,2,112262.84,1,1,0,12873.39,0 -6676,15724663,Christmas,654,Spain,Female,36,5,0,2,0,0,157238.05,0 -6677,15594556,Chuter,619,Spain,Male,52,8,0,2,1,1,123242.11,0 -6678,15737169,Johnson,642,Spain,Male,26,8,144238.7,1,1,1,184399.76,0 -6679,15632472,Scott,472,Spain,Female,32,1,159397.75,1,0,1,57323.18,0 -6680,15722813,Byrne,470,Spain,Male,30,4,125385.01,1,1,0,68293.93,0 -6681,15588450,Chukwudi,633,France,Female,60,8,69365.25,1,1,1,10288.24,0 -6682,15736717,Ma,602,France,Male,31,7,155271.83,1,1,1,179446.31,0 -6683,15680683,Simmons,640,Spain,Male,29,5,197200.04,2,1,0,141453.62,0 -6684,15710316,Fang,454,Spain,Female,48,5,144837.79,1,1,1,93151.77,0 -6685,15746333,Blake,562,France,Female,57,3,0,3,1,0,6554.97,1 -6686,15606861,Tien,636,France,Male,34,8,0,2,1,0,38570.13,0 -6687,15641285,Yusupova,621,Spain,Male,50,3,163085.79,1,0,1,131048.36,0 -6688,15662908,Davidson,795,Germany,Male,38,7,125903.22,2,1,1,127068.92,0 -6689,15814267,Zhdanova,550,France,Male,22,6,154377.3,1,1,1,51721.52,0 -6690,15614923,Nielson,630,Spain,Male,41,7,107511.52,1,0,1,46156.87,0 -6691,15579223,Niu,573,Germany,Male,30,8,127406.5,1,1,0,192950.6,0 -6692,15651389,Kay,561,Spain,Male,24,8,143656.55,1,0,1,180932.46,0 -6693,15677087,Green,662,France,Female,39,5,138106.75,1,0,0,19596.73,0 -6694,15665784,She,637,France,Male,27,9,128940.24,1,1,0,46786.92,0 -6695,15576706,Ajuluchukwu,651,Germany,Male,37,9,114453.58,1,0,1,175820.91,0 -6696,15615473,Sabbatini,646,France,Female,33,2,0,2,0,0,198208,0 -6697,15587299,Board,567,France,Female,48,3,0,1,1,0,55362.45,0 -6698,15655389,Leckie,638,France,Male,41,1,131762.94,1,1,1,47675.29,0 -6699,15784491,Ho,725,France,Female,31,6,0,1,0,0,61326.43,0 -6700,15809999,Gordon,709,France,Female,41,3,150300.65,2,1,0,71672.86,0 -6701,15681115,Iroawuchi,787,Spain,Male,39,10,108935.39,1,1,1,101168.3,0 -6702,15629390,Liao,653,France,Male,37,7,135847.47,1,1,0,144880.81,0 -6703,15792668,Hamilton,661,Germany,Male,37,7,109908.06,2,1,0,115037.67,1 -6704,15583863,Chimaobim,681,Germany,Male,49,8,142946.18,1,0,0,187280.51,1 -6705,15681878,Fan,436,Germany,Male,45,3,104339.11,2,1,1,183540.22,1 -6706,15782875,Cayley,663,France,Male,33,5,157274.36,2,1,1,28531.81,0 -6707,15732235,Kuykendall,662,France,Male,64,0,98848.19,1,0,1,42730.12,0 -6708,15735909,McDonald,607,Germany,Female,39,8,105103.33,1,1,0,104721.5,1 -6709,15653448,Duncan,754,France,Male,34,7,0,2,1,1,65219.85,0 -6710,15587647,Browne,850,Germany,Female,66,0,127120.62,1,0,1,118929.64,1 -6711,15701037,Barton,578,France,Male,39,2,0,2,1,0,70563.9,0 -6712,15727499,Boyle,666,Germany,Female,36,3,129118.5,2,0,0,139435.12,0 -6713,15724838,Moretti,599,France,Female,43,4,0,1,1,0,170347.1,0 -6714,15666711,Ukaegbulam,586,France,Female,46,0,0,3,0,1,131553.82,1 -6715,15588933,Nwankwo,825,France,Female,36,3,146053.66,1,1,1,138344.7,0 -6716,15763111,Niu,808,Spain,Female,67,10,124577.15,1,0,1,169894.4,0 -6717,15805676,Hsu,515,Spain,Male,29,4,151012.55,2,1,0,9770.97,0 -6718,15586674,Shaw,663,Spain,Female,58,5,216109.88,1,0,1,74176.71,1 -6719,15744553,Ho,444,France,Male,34,2,144318.97,1,1,0,112668.06,0 -6720,15776629,Christie,650,France,Female,39,4,0,2,0,0,186275.7,0 -6721,15647207,Onwuemelie,609,France,Male,26,7,0,2,1,0,98463.99,0 -6722,15715638,Ch'ang,824,Germany,Male,77,3,27517.15,2,0,1,2746.41,0 -6723,15750602,Clendinnen,662,France,Male,29,5,147092.65,1,1,0,10928.3,0 -6724,15766810,Onyemauchechi,699,Germany,Female,51,2,92246.14,2,0,1,91346.03,0 -6725,15756625,Crawford,752,France,Female,41,8,0,2,1,0,139844.04,1 -6726,15639552,Mellor,603,Germany,Female,40,8,148897.02,1,0,0,105052.9,0 -6727,15633213,Rizzo,628,Spain,Male,50,8,0,1,0,0,144366.83,1 -6728,15610416,Christie,745,France,Female,36,9,0,1,1,0,19605.18,1 -6729,15715208,Watkins,804,Germany,Female,33,10,138335.96,1,1,1,80483.76,0 -6730,15619608,Ojiofor,454,Germany,Female,50,10,92895.56,1,1,0,154344,1 -6731,15628697,Tung,631,Spain,Male,46,9,160736.63,1,0,1,93503.02,0 -6732,15643826,McKay,503,France,Male,32,4,0,2,1,1,153036.97,0 -6733,15718588,Meng,548,France,Female,37,9,0,2,0,0,98029.58,0 -6734,15709741,Hussain,668,France,Male,28,4,107141.27,1,1,0,193018.71,0 -6735,15723318,Mactier,619,France,Female,55,0,0,3,0,0,60810.64,1 -6736,15717328,Hsueh,842,France,Female,37,4,132446.08,2,1,0,87071.18,1 -6737,15771299,Nnachetam,707,France,Female,57,1,92053,1,1,1,164064.44,1 -6738,15706223,Barnes,715,Spain,Male,38,2,96798.79,2,1,1,4554.67,0 -6739,15612358,Christie,573,Germany,Male,35,9,134498.54,2,1,1,119924.8,0 -6740,15769191,Lipton,509,France,Male,55,8,132387.91,2,1,1,170360.11,0 -6741,15618816,Yu,670,Germany,Female,40,2,147171.2,1,0,1,69850.04,0 -6742,15730810,Storey,613,Spain,Male,44,9,100524.69,1,1,1,47298.95,0 -6743,15783463,Read,678,France,Female,26,1,0,2,1,0,45443.68,0 -6744,15616213,Levy,555,Germany,Female,51,9,138214.5,1,1,0,198715.27,1 -6745,15611287,Chiu,777,France,Female,30,4,0,2,0,1,115611.97,0 -6746,15786454,Moore,552,Spain,Male,55,3,0,1,1,1,40333.94,0 -6747,15768682,Amies,640,Spain,Male,39,3,0,1,1,1,105997.25,0 -6748,15766172,Tsao,541,France,Male,34,3,128743.55,1,1,0,134851.12,0 -6749,15637646,Rowley,756,France,Male,31,10,122647.32,1,0,0,61666.87,0 -6750,15653404,Aliyev,684,Spain,Female,24,9,79263.9,1,0,1,196574.48,0 -6751,15690546,Riley,618,France,Female,42,2,0,4,0,0,111097.39,1 -6752,15735636,Toscano,604,France,Female,53,2,121389.78,1,1,1,48201.64,1 -6753,15605424,Oluchukwu,624,Spain,Male,38,7,123906.55,1,1,0,135096.78,0 -6754,15568449,Fu,661,Spain,Male,38,7,143006.7,1,1,1,15650.89,0 -6755,15688085,Warner,627,Spain,Female,28,3,157597.61,1,0,1,34097.22,0 -6756,15683483,Fleming,812,Spain,Male,38,3,127117.8,2,1,1,174822.74,0 -6757,15659567,Ch'iu,473,France,Female,39,9,117103.26,2,1,1,85937.52,1 -6758,15766667,Langler,717,Spain,Male,36,2,102989.83,2,0,1,49185.57,0 -6759,15624975,Angelo,693,Spain,Male,28,1,145118.83,1,0,1,77742.38,0 -6760,15660878,T'ien,705,France,Male,92,1,126076.24,2,1,1,34436.83,0 -6761,15586557,Milani,661,France,Male,41,5,0,1,0,1,88279.6,0 -6762,15746183,Pye,573,France,Female,27,4,0,2,1,1,157549.6,0 -6763,15631457,Asher,639,France,Male,37,5,98186.7,1,0,1,173386.95,0 -6764,15754053,Chung,718,France,Female,67,7,0,3,1,1,82782.08,0 -6765,15645839,Yudin,570,France,Male,37,6,0,1,1,1,187758.5,0 -6766,15689955,Arcuri,461,France,Female,40,7,0,2,1,0,176547.8,0 -6767,15593510,Capon,638,Germany,Female,33,5,129335.65,1,1,1,56585.2,1 -6768,15654964,Piccio,608,Spain,Male,48,7,75801.74,1,1,0,125762.95,0 -6769,15594039,Lung,599,Spain,Male,42,6,0,2,1,0,113868.4,0 -6770,15625929,Trevisan,762,France,Female,44,7,159316.64,1,0,0,24780.13,0 -6771,15815295,John,662,France,Female,38,2,96479.81,1,1,0,120259.41,0 -6772,15621818,Anayolisa,747,Germany,Male,29,7,117726.33,1,1,1,175398.34,0 -6773,15652700,Ritchie,539,France,Male,39,6,0,2,1,1,86767.48,0 -6774,15636860,Ch'eng,625,France,Male,43,4,122351.29,1,1,0,71216.6,0 -6775,15569432,Macleod,656,France,Female,48,9,0,2,1,1,85240.61,1 -6776,15751455,Boyle,469,France,Female,48,5,0,1,1,0,160529.71,1 -6777,15800583,Chukwuemeka,621,Spain,Female,43,8,0,1,0,0,102806.6,0 -6778,15770214,Bryant,754,France,Female,27,7,0,2,1,0,144134.64,0 -6779,15613463,Hackett,679,Germany,Female,50,6,132598.38,2,1,1,184017.98,0 -6780,15587066,Kovaleva,535,France,Male,38,2,119272.29,1,0,0,195896.59,1 -6781,15693752,Reed,487,France,Male,37,2,0,2,1,1,126722.57,0 -6782,15714874,Major,850,France,Female,42,3,0,2,1,1,176883.42,0 -6783,15657809,Lo,585,France,Male,55,10,106415.57,3,1,1,122960.98,1 -6784,15651955,Hanson,603,France,Male,31,4,0,2,0,1,9607.1,0 -6785,15570912,Ogbonnaya,728,Germany,Female,32,9,127772.1,2,1,1,152643.48,0 -6786,15640266,Windsor,621,Spain,Male,41,5,104631.67,1,1,1,95551.22,0 -6787,15652069,Calabrese,833,France,Male,30,1,0,2,1,0,141860.62,0 -6788,15596074,Keating,502,France,Male,37,10,0,1,1,1,76642.68,0 -6789,15800268,Costa,825,Germany,Male,37,6,118050.79,1,0,1,52301.15,0 -6790,15809847,Tan,668,France,Male,46,0,0,2,0,0,29388.02,0 -6791,15599074,Ma,487,Spain,Female,40,6,136093.74,1,0,1,193408.43,0 -6792,15599591,Martin,600,Germany,Female,39,7,88477.36,2,1,0,58632.37,0 -6793,15776096,Halpern,606,Spain,Male,34,3,161572.24,1,0,1,191076.22,0 -6794,15611669,Nyhan,623,Germany,Male,50,7,126608.37,1,0,1,645.61,1 -6795,15694098,Jackson,575,France,Female,54,9,68332.96,1,1,1,144390.75,0 -6796,15713347,Reynolds,577,Spain,Male,48,6,179852.26,1,1,0,193580.32,0 -6797,15713094,Tai,651,France,Female,25,8,0,2,1,1,126761.2,0 -6798,15811978,Trevisani,693,Germany,Male,46,2,104763.41,1,1,1,62368.33,0 -6799,15799925,Uwakwe,800,France,Male,60,6,88541.57,2,1,1,131718.12,0 -6800,15692575,Kerr,760,France,Male,38,6,162888.73,1,1,0,91098.76,1 -6801,15743149,Findlay,711,France,Female,35,8,0,1,1,1,67508.01,0 -6802,15776947,Ugorji,637,Spain,Male,43,8,0,1,1,0,12156.93,1 -6803,15700656,Balashova,662,France,Male,32,9,0,2,0,0,65089.38,0 -6804,15594515,Cheng,568,France,Female,44,7,0,2,0,0,62370.67,1 -6805,15787884,Martin,692,France,Female,30,7,0,2,1,1,18826.34,0 -6806,15577988,Skinner,614,France,Female,35,1,0,2,1,1,3342.62,0 -6807,15795586,McDonald,478,France,Male,35,1,92474.05,1,1,0,178626.07,0 -6808,15677739,Dellucci,562,France,Male,36,6,0,2,1,0,32845.32,0 -6809,15720134,Reynolds,709,Germany,Male,30,9,115479.48,2,1,1,134732.99,0 -6810,15688868,Birdsall,684,France,Female,26,5,87098.91,1,0,0,106095.82,0 -6811,15642996,Tsai,546,Germany,Female,42,9,86351.85,2,1,0,57380.13,0 -6812,15771222,Oguejiofor,779,France,Female,42,5,0,2,0,0,25951.91,0 -6813,15605059,Mackie,576,Germany,Male,63,3,148843.56,1,1,0,69414.13,1 -6814,15568088,Jamieson,481,Germany,Male,44,3,163714.52,1,1,0,96123.72,0 -6815,15665943,Mai,445,France,Male,25,6,0,2,1,0,119425.94,0 -6816,15795571,Patterson,606,Spain,Male,36,0,94153.56,1,0,1,120138.27,0 -6817,15662243,Taylor,559,France,Male,50,5,162702.35,1,0,0,150548.5,1 -6818,15593128,Vinogradoff,608,France,Female,56,10,129255.2,2,1,0,142492.04,1 -6819,15589739,North,698,France,Male,41,3,90605.29,1,1,1,14357,0 -6820,15787602,Carter,568,Spain,Male,39,5,0,2,1,1,129569.92,0 -6821,15685019,Graham,528,France,Male,29,3,102787.42,1,1,0,55972.56,0 -6822,15704209,Noble,802,France,Female,39,7,120145.96,2,0,1,59497.01,1 -6823,15605264,Walker,669,Germany,Male,47,0,63723.78,2,1,1,181928.25,0 -6824,15708265,Chibugo,581,Spain,Female,24,10,159203.71,1,1,1,102517.83,1 -6825,15740264,Yobachi,640,France,Male,38,9,0,2,1,0,88827.67,0 -6826,15615477,Ignatyeva,529,Spain,Female,44,1,0,2,0,0,14161.3,0 -6827,15727361,Chiemela,547,France,Female,51,1,0,2,1,1,56908.41,0 -6828,15760216,Pokrovskaya,718,France,Female,49,10,0,1,1,0,184474.72,1 -6829,15806134,Storey,707,Germany,Male,34,9,162691.16,2,1,0,94912.78,0 -6830,15601351,Moroney,735,France,Male,43,9,127806.91,1,1,1,73069.59,0 -6831,15669262,Maslov,765,France,Male,43,9,157960.49,2,0,0,136602.8,0 -6832,15696989,Chukwueloka,469,Germany,Female,52,8,139493.25,3,0,0,150093.32,1 -6833,15688498,Chu,594,Germany,Female,21,2,87096.82,2,1,0,168186.11,0 -6834,15686964,Spence,675,France,Female,34,10,84944.58,1,0,0,146230.63,0 -6835,15625035,Mills,703,France,Male,50,8,160139.59,2,1,1,79314.1,0 -6836,15618391,Doyle,810,France,Male,33,6,0,2,1,1,77965.67,0 -6837,15591344,Donnelly,715,Spain,Male,42,6,0,2,1,1,128745.69,0 -6838,15605455,Tai,664,France,Male,40,9,0,2,1,0,194767.3,0 -6839,15680804,Abbott,850,France,Male,29,6,0,2,1,1,10672.54,0 -6840,15768282,Perez,724,Germany,Male,36,6,94615.11,2,1,1,10627.21,0 -6841,15685826,Hsiung,563,France,Male,30,7,90727.79,1,1,0,122268.75,0 -6842,15793491,Cherkasova,714,Germany,Male,26,3,119545.48,2,1,0,65482.94,0 -6843,15797787,Denisov,614,France,Male,36,1,118311.76,1,1,0,146134.68,0 -6844,15611171,Fowler,740,France,Male,33,1,129574.98,1,1,1,123300.38,0 -6845,15601627,Siciliano,587,France,Male,33,8,148163.57,1,0,0,122925.4,0 -6846,15734085,Crocker,465,Germany,Male,24,5,117154.9,1,1,1,127744.02,0 -6847,15809309,Longo,689,Spain,Female,40,5,154251.67,1,0,1,118319.5,0 -6848,15809462,Polyakova,656,France,Male,30,3,0,2,0,1,17104,0 -6849,15634628,Brown,579,France,Female,33,1,65667.79,2,0,0,164608.98,0 -6850,15775678,Uspensky,716,France,Female,44,1,0,1,1,1,152108.47,0 -6851,15579526,O'Meara,551,France,Male,42,1,50194.59,1,1,1,23399.58,0 -6852,15779103,Cantamessa,527,Germany,Female,39,9,96748.89,2,1,0,94711.43,0 -6853,15738715,Alexander,600,France,Female,37,4,0,3,1,0,7312.25,1 -6854,15593943,Chinagorom,685,France,Female,43,1,132667.17,1,1,1,41876.98,0 -6855,15754574,Tomlinson,738,Spain,Male,36,5,0,2,1,1,96881.32,0 -6856,15737814,Lo,622,France,Male,41,2,127087.06,1,1,0,102402.91,1 -6857,15670889,Nwachukwu,528,France,Male,34,1,125566.9,1,1,1,176763.27,0 -6858,15629299,Yang,546,Germany,Female,52,1,106074.89,1,1,1,23548.45,1 -6859,15771569,Bage,576,Germany,Male,46,4,137367.94,1,1,1,33450.11,0 -6860,15811927,Marcelo,733,France,Female,38,3,157658.36,1,0,0,19658.43,0 -6861,15785654,Ofodile,727,Germany,Male,45,6,114422.85,2,1,1,104678.78,1 -6862,15665524,Savage,605,Spain,Male,41,5,103154.66,1,0,0,143203.78,0 -6863,15736287,Piccio,586,France,Male,33,9,0,1,1,0,6975.02,0 -6864,15765732,Simmons,564,Spain,Female,24,6,149592.14,1,1,1,153771.8,0 -6865,15797381,DeRose,593,Germany,Female,48,3,133903.12,2,1,1,85902.39,1 -6866,15598536,Onuchukwu,736,Germany,Female,26,0,84587.9,1,0,1,188037.76,0 -6867,15664506,Goodwin,675,Spain,Male,32,8,197436.82,1,1,1,52710.7,0 -6868,15575619,Teakle,656,Spain,Female,32,1,104254.27,1,1,1,17034.37,0 -6869,15587394,Thomson,462,France,Male,39,4,140133.08,2,0,0,131304.45,0 -6870,15654457,Cross,685,Spain,Female,30,2,0,3,1,1,172576.43,1 -6871,15762793,Jones,850,Germany,Female,36,0,136980.23,2,1,1,99019.65,0 -6872,15658067,Walker,636,Germany,Female,48,3,120568.41,1,1,0,190160.04,1 -6873,15642816,De Salis,850,France,Female,27,7,43658.33,2,1,1,3025.49,0 -6874,15693088,Oliver,628,France,Female,37,9,0,2,1,1,34689.77,0 -6875,15793883,Lo Duca,798,France,Male,28,3,0,2,1,0,2305.27,0 -6876,15665283,Brookes,610,France,Female,57,7,72092.95,4,0,1,113228.82,1 -6877,15680421,Challis,591,France,Female,42,10,0,2,0,0,171099.22,0 -6878,15695148,Ibeabuchi,614,Spain,Female,37,9,0,2,1,1,62023.1,0 -6879,15636592,Iroawuchi,651,France,Male,35,0,181821.96,2,0,1,36923.67,1 -6880,15772618,Tyler,665,France,Male,25,7,90920.75,1,0,1,112256.57,0 -6881,15724453,Fan,570,France,Male,23,2,0,1,0,0,198830.98,0 -6882,15565878,Bates,631,Spain,Male,29,3,0,2,1,1,197963.46,0 -6883,15609160,Marsden,586,France,Male,32,1,0,2,0,0,31635.99,0 -6884,15678460,Dodgshun,691,France,Male,30,9,0,1,1,0,49594.02,0 -6885,15662571,Maclean,639,France,Male,35,8,0,2,1,0,170483.9,0 -6886,15606849,Blackall,698,France,Female,27,1,94920.71,1,1,1,40339.9,0 -6887,15670738,Mazzanti,733,Germany,Male,45,2,113939.36,2,1,0,3218.71,0 -6888,15662641,Amadi,850,France,Male,19,8,0,1,1,1,68569.89,0 -6889,15727539,Schoenheimer,618,France,Female,31,4,0,2,1,0,29176.04,0 -6890,15651020,Fiorentino,473,France,Female,25,6,110666.42,2,0,0,46758.42,0 -6891,15673877,Murray,490,France,Male,39,1,0,3,1,0,171060.01,1 -6892,15760865,Fan,754,Germany,Female,48,7,141819.02,1,1,0,93550.53,1 -6893,15705009,Cartwright,649,France,Female,56,8,156974.26,1,1,0,89405.26,1 -6894,15657540,Cremonesi,578,France,Male,50,5,151215.34,2,1,0,169804.4,0 -6895,15707441,White,690,Spain,Male,26,8,116318.23,1,1,1,83253.05,0 -6896,15694765,Sabbatini,610,Germany,Male,49,6,113882.33,1,1,0,195813.81,1 -6897,15649086,Patterson,596,France,Male,42,7,0,2,1,1,121568.37,0 -6898,15650488,Bromley,492,France,Female,48,6,127253.98,1,1,1,92144.09,1 -6899,15760924,Doherty,575,Spain,Male,41,2,100062.39,1,0,0,126307.25,0 -6900,15700263,Ifeatu,569,France,Male,66,2,0,1,1,0,130784.2,1 -6901,15806922,Bergamaschi,674,Spain,Female,41,4,126605.14,1,1,1,166694.93,0 -6902,15637522,Shubina,507,France,Female,31,0,106942.08,1,0,1,44001.11,0 -6903,15636548,Lung,457,Spain,Male,44,7,0,2,0,0,185992.36,0 -6904,15566891,Kinder,584,Germany,Female,41,3,88594.93,1,1,0,178997.89,0 -6905,15627185,Terry,744,Germany,Male,29,6,123737.04,2,1,0,141558.04,0 -6906,15754012,Shepherdson,687,France,Female,35,1,110752.15,2,1,1,47921.22,0 -6907,15627514,Short,688,Spain,Female,46,3,0,2,0,1,104902.68,0 -6908,15661433,Zetticci,519,France,Male,34,5,0,1,1,0,68479.6,0 -6909,15610653,Belov,733,Spain,Female,38,5,0,2,1,1,1271.51,0 -6910,15667002,Knight,666,Spain,Male,43,5,0,2,1,0,29346.1,0 -6911,15709199,Burson,511,Spain,Female,40,1,0,1,1,1,184118.73,0 -6912,15710087,Nicholls,705,Germany,Female,54,3,125889.3,3,1,0,96013.5,1 -6913,15679884,Hs?eh,544,France,Male,48,10,78314.63,3,1,1,103713.93,1 -6914,15784180,Ku,564,France,Female,36,7,206329.65,1,1,1,46632.87,1 -6915,15808849,T'ien,702,France,Male,40,7,145536.9,1,0,1,135334.24,0 -6916,15751549,H?,658,Germany,Male,31,2,77082.65,2,0,0,13482.28,0 -6917,15588235,Vasilieva,654,France,Female,24,8,145081.73,1,1,1,130075.07,0 -6918,15640418,Omeokachie,649,Germany,Female,41,4,115897.73,1,1,0,143544.48,0 -6919,15721116,Napolitano,597,Spain,Male,24,0,108058.07,2,1,1,187826.11,0 -6920,15599084,Hopwood,782,France,Male,33,7,191523.09,1,1,1,167058.75,0 -6921,15773394,Bergamaschi,644,France,Male,38,3,0,2,1,1,79928.41,0 -6922,15625713,Lindeman,679,Spain,Female,39,7,91187.9,1,0,1,6075.36,0 -6923,15766417,McKinley,678,France,Female,60,2,0,2,1,1,43821.56,0 -6924,15622578,Sergeyev,806,France,Male,34,5,113958.55,1,0,1,32125.98,0 -6925,15799924,Sanchez,668,Spain,Male,43,1,147167.25,1,0,0,141679.73,0 -6926,15618363,Muomelu,659,Germany,Male,29,9,82916.48,1,1,1,84133.48,0 -6927,15637138,Murray,660,France,Male,34,1,0,2,1,0,9692.58,0 -6928,15781665,Ibekwe,601,France,Female,37,5,0,1,0,0,20708.6,0 -6929,15804853,McVey,781,France,Female,48,0,57098.96,1,1,0,85644.06,1 -6930,15651627,White,628,Germany,Male,39,1,115341.19,1,1,1,107674.3,1 -6931,15680685,Patterson,751,France,Male,30,3,165257.2,1,0,0,134822.05,0 -6932,15808930,Mai,531,France,Female,37,1,0,1,1,0,4606.97,0 -6933,15570970,Han,647,France,Female,42,9,0,2,1,1,51362.82,0 -6934,15679961,Davidson,708,Spain,Male,46,7,68799.72,1,1,1,39704.14,0 -6935,15705458,Parkin,550,Spain,Male,39,2,116120.19,2,1,1,195638.13,0 -6936,15750396,McKissick,670,France,Male,33,1,0,2,1,1,86413.11,0 -6937,15679928,Horsfall,592,France,Female,31,2,84102.11,2,0,1,116385.24,0 -6938,15711181,Clapp,589,France,Female,50,4,0,2,0,1,182076.97,0 -6939,15698324,Azikiwe,725,France,Female,33,4,0,1,1,1,67879.8,0 -6940,15807433,Zubarev,570,France,Female,43,9,0,2,0,1,11417.26,0 -6941,15636590,Pisano,575,France,Male,46,1,0,2,1,1,65998.26,0 -6942,15628950,Coates,501,Germany,Male,25,6,104013.79,1,1,0,114774.35,0 -6943,15617206,Trentino,431,Germany,Male,42,8,120822.86,2,1,0,126153.24,0 -6944,15603741,MacDonnell,719,Spain,Male,40,4,128389.12,1,1,1,176091.31,0 -6945,15742607,Ermakov,850,Germany,Male,36,7,102800.72,1,1,1,87352.43,0 -6946,15747821,K?,554,Germany,Female,31,6,135470.9,1,1,0,107074.81,0 -6947,15612043,Hammonds,418,France,Male,36,7,90145.04,1,1,1,69157.93,0 -6948,15809558,Peppin,715,Spain,Male,31,7,0,1,1,1,149970.59,0 -6949,15803750,Ball,750,Spain,Female,33,3,161801.47,1,0,1,153288.97,1 -6950,15704681,Yeh,766,Germany,Male,37,2,99660.13,2,0,1,147700.78,0 -6951,15667392,L?,652,Spain,Female,38,6,123081.84,2,1,1,188657.97,0 -6952,15738889,Shih,658,France,Male,42,8,102870.93,1,0,1,103764.55,1 -6953,15598838,Greco,659,France,Female,37,1,151105.68,1,1,1,140934.57,0 -6954,15579109,Napolitano,574,Germany,Male,35,5,163856.76,1,1,1,15118.2,0 -6955,15799042,Zaytseva,611,France,Male,38,7,0,1,1,1,63202,0 -6956,15697042,Genovesi,738,Spain,Male,35,8,127290.61,1,1,0,16081.62,0 -6957,15696605,Angelo,571,France,Male,49,4,180614.04,1,0,0,523,0 -6958,15802274,Waters,686,France,Female,44,7,55053.62,1,1,0,181757.19,0 -6959,15596808,Maclean,679,Spain,Male,33,4,96110.22,1,1,0,1173.23,0 -6960,15705403,Seleznyova,617,Spain,Female,46,3,106521.49,1,0,1,86587.37,0 -6961,15732903,Fontenot,673,France,Male,39,7,82255.51,2,1,0,109545.56,0 -6962,15581968,Reid,745,France,Female,33,1,0,2,1,1,174431.01,0 -6963,15683892,Fraser,677,Germany,Female,26,3,102395.79,1,1,0,119368.99,0 -6964,15595447,Tuan,613,Spain,Male,39,8,118201.41,1,1,0,23315.59,0 -6965,15569249,Howarth,576,France,Female,55,6,44582.07,3,0,1,67539.85,1 -6966,15656188,Davis,584,Spain,Female,30,5,0,2,1,1,185201.58,0 -6967,15689661,Gorbunov,663,France,Male,22,6,0,2,0,1,131827.15,0 -6968,15644934,Gentry,466,France,Male,26,9,105522.06,1,1,0,10842.46,0 -6969,15721793,Chiu,510,Germany,Female,50,7,123936.54,1,1,1,23768.01,0 -6970,15687413,Sunderland,619,Spain,Female,38,6,0,2,1,1,117616.29,0 -6971,15761286,Fan,696,Germany,Female,66,7,119499.42,2,1,1,174027.3,0 -6972,15658240,Parry,554,France,Female,44,9,135814.7,2,0,0,115091.38,0 -6973,15706232,Niu,595,France,Male,52,9,0,1,1,1,106340.66,1 -6974,15583394,Zuyev,659,Germany,Male,39,8,106259.63,2,1,1,198103.32,0 -6975,15715643,Ijendu,662,France,Male,44,8,0,2,1,1,175314.87,0 -6976,15644856,Bird,556,Spain,Male,38,2,115463.16,1,1,0,150679.65,0 -6977,15785488,Palmer,701,Spain,Female,39,9,0,2,1,1,110043.88,0 -6978,15711571,Y?,587,Spain,Male,42,5,120233.83,1,1,0,194890.33,0 -6979,15778604,Nicholson,571,France,Female,47,7,0,2,0,0,112366.98,0 -6980,15751180,Adams,539,France,Female,40,7,81132.21,1,1,0,167289.82,0 -6981,15748360,Cocci,644,Germany,Female,34,10,122196.99,2,1,1,182099.71,0 -6982,15770039,Kuo,572,Germany,Male,39,4,112290.22,1,1,0,49373.97,1 -6983,15685096,Trevisani,753,France,Female,50,4,0,2,1,1,861.4,0 -6984,15669501,Kuo,706,France,Male,35,5,0,2,1,1,81718.37,0 -6985,15622631,H?,588,France,Male,44,8,154409.74,1,1,0,49324.03,1 -6986,15586699,Thomson,825,France,Male,32,9,0,2,0,0,9751.03,0 -6987,15702377,Knorr,627,Spain,Male,48,1,132759.8,1,1,0,78899.22,0 -6988,15577170,Manfrin,532,France,Male,60,5,76705.87,2,0,1,13889.73,0 -6989,15769451,Hayes,764,France,Female,44,1,0,2,1,1,11467.38,0 -6990,15811877,Shao,700,France,Female,36,4,0,2,1,0,130789.15,0 -6991,15648725,Sinclair,660,France,Male,41,3,0,2,1,1,108665.89,0 -6992,15752801,Bradshaw,518,Germany,Male,29,9,125961.74,2,1,0,160303.08,1 -6993,15808175,Castiglione,557,France,Female,39,7,49572.73,1,1,0,115287.99,1 -6994,15681342,Hurst,639,France,Female,35,1,103015.12,2,1,1,139094.12,0 -6995,15589210,Adamson,557,France,Female,24,4,0,1,0,0,20515.72,0 -6996,15696826,James,633,France,Female,32,1,104001.38,1,0,1,36642.65,0 -6997,15614962,Pavlova,623,Spain,Female,50,2,87116.71,1,1,1,104382.11,0 -6998,15689061,Davey,611,France,Male,68,5,82547.11,2,1,1,146448.01,0 -6999,15640074,Barrett,666,Spain,Female,47,5,0,1,0,0,166650.9,1 -7000,15776156,Dolgorukova,521,France,Male,27,4,121325.84,1,1,1,164223.7,1 -7001,15739548,Johnson,775,France,Male,28,9,111167.7,1,1,0,149331.01,0 -7002,15662854,Manna,681,Germany,Male,48,5,139714.4,2,0,0,73066.72,0 -7003,15687688,Hou,564,Germany,Female,32,10,139875.2,2,1,0,15378.23,0 -7004,15715750,Okeke,646,Germany,Female,44,2,113063.83,1,0,0,53072.49,1 -7005,15571121,Kodilinyechukwu,670,France,Female,50,8,138340.06,1,0,1,3159.15,0 -7006,15726466,Esposito,751,France,Male,43,1,114974.24,1,1,0,125920.54,0 -7007,15660390,Boyle,544,France,Female,33,6,0,2,1,1,124113.04,0 -7008,15663942,Hsiung,639,France,Female,38,5,0,2,0,0,93716.38,0 -7009,15638610,Kennedy,635,Germany,Female,65,5,117325.54,1,1,0,155799.86,1 -7010,15644446,Norton,672,France,Female,28,6,0,1,0,1,8814.69,0 -7011,15585892,Zakharov,639,France,Female,35,8,0,1,0,0,164453.98,0 -7012,15609356,Chimaraoke,697,France,Female,25,1,0,2,0,0,87803.32,0 -7013,15803378,Small,850,Spain,Male,44,8,0,2,1,1,183617.32,0 -7014,15599440,McGregor,748,France,Female,34,8,0,2,1,0,53584.03,0 -7015,15692408,Brown,463,Spain,Female,35,2,0,2,1,1,1950.93,0 -7016,15683168,Frederickson,572,France,Female,30,6,0,1,0,1,175025.27,0 -7017,15790254,Wood,741,Spain,Male,50,1,78737.61,1,1,1,13018.96,0 -7018,15767729,Smith,646,Spain,Male,25,5,182876.88,2,1,1,42537.59,1 -7019,15768600,Harris,805,Germany,Male,50,9,130023.38,1,1,0,62989.82,1 -7020,15699839,Hall,637,France,Male,36,2,152606.82,1,1,1,71692.8,0 -7021,15786237,Pickworth,651,France,Male,28,7,0,2,1,0,823.96,0 -7022,15694530,Porter,672,France,Male,28,4,167268.98,1,1,1,169469.3,0 -7023,15796813,Storey,493,France,Male,54,3,167831.88,2,1,0,150159.95,1 -7024,15605791,Li,524,Germany,Male,29,9,144287.6,2,1,0,32063.3,0 -7025,15714087,McGill,624,Germany,Female,45,5,151855.33,1,1,0,68794.15,0 -7026,15711446,Sinclair,569,Spain,Female,51,3,0,3,1,0,75084.96,1 -7027,15588123,Horton,677,France,Female,27,2,0,2,0,1,114685.92,0 -7028,15748552,Sal,464,Germany,Male,37,4,155994.15,1,0,0,143665.44,0 -7029,15618410,Murray,718,Germany,Male,26,7,147527.03,1,0,0,51099.56,0 -7030,15672432,Giles,594,France,Female,53,4,0,1,1,0,5408.74,1 -7031,15610042,Brown,574,France,Male,33,8,100267.03,1,1,0,103006.27,0 -7032,15580914,Okechukwu,478,Spain,Male,48,0,83287.05,2,0,1,44147.95,1 -7033,15583680,White,615,Spain,Male,41,4,0,1,0,1,149278.96,0 -7034,15813718,Kirillova,651,Spain,Male,45,4,0,2,0,0,193009.21,0 -7035,15767264,Lawson,465,Germany,Male,53,1,117438.17,1,0,0,74898.8,1 -7036,15686461,Sarratt,558,France,Female,56,7,121235.05,2,1,1,116253.1,0 -7037,15678882,Hay,540,Germany,Male,37,3,129965.18,1,0,0,19374.08,0 -7038,15789611,Lin,568,Germany,Male,46,8,150836.92,1,0,0,64516.8,1 -7039,15668679,Ozerova,630,France,Male,31,0,0,2,1,1,34475.14,0 -7040,15631685,Lambert,523,Germany,Male,60,1,163894.35,1,0,1,57061.71,0 -7041,15655658,Bulgakov,678,France,Female,48,2,0,2,1,1,32301.88,0 -7042,15753591,He,438,France,Male,38,2,0,2,1,0,136859.55,0 -7043,15617348,Uchechukwu,544,France,Male,44,1,0,2,0,0,69244.24,0 -7044,15704581,Robertson,595,Germany,Male,34,2,87967.42,2,0,1,156309.52,0 -7045,15738487,Leworthy,678,France,Male,26,3,0,2,1,0,4989.33,0 -7046,15648069,Onyemachukwu,850,France,Female,36,6,0,2,1,1,190194.95,0 -7047,15737627,Rivero,589,Germany,Female,20,2,121093.29,2,1,0,3529.72,0 -7048,15731586,Lai,785,Spain,Female,31,2,121691.54,2,0,0,81778.72,0 -7049,15757467,Feng,563,Spain,Male,57,6,0,2,1,1,39297.48,0 -7050,15597709,Hornung,602,France,Female,39,6,154121.32,2,1,0,176614.86,1 -7051,15720529,Schiavone,591,France,Male,29,6,0,2,1,1,108684.65,0 -7052,15596797,Barnet,643,Spain,Male,43,1,0,2,1,1,145764.4,0 -7053,15681755,Dennys,605,France,Female,32,5,0,2,1,1,42135.28,0 -7054,15815271,Ritchie,755,Germany,Male,43,6,165048.5,3,1,0,16929.41,1 -7055,15682860,Lo,769,Spain,Male,38,6,0,2,0,0,104393.78,0 -7056,15621546,Yuriev,620,France,Female,33,9,127638.35,1,1,1,192717.57,0 -7057,15705918,Howarth,725,France,Male,31,8,0,2,1,1,59650.42,0 -7058,15684512,Gibson,818,Germany,Female,72,8,135290.42,2,1,1,63729.72,0 -7059,15671769,Zikoranachidimma,624,France,Female,71,4,170252.05,3,1,1,73679.59,1 -7060,15642934,Mason,669,Germany,Female,35,4,108269.2,2,1,0,174969.92,0 -7061,15594305,Rizzo,712,France,Female,32,1,0,2,1,0,1703.58,0 -7062,15789201,Thomson,603,Germany,Female,35,9,145623.36,1,1,0,163181.62,0 -7063,15706762,Ignatyev,597,France,Female,41,4,145809.53,2,1,1,52319.26,0 -7064,15766183,Ferguson,580,Germany,Male,76,2,130334.84,2,1,1,51672.08,0 -7065,15777994,Woods,718,France,Female,39,3,0,2,1,1,145355.11,0 -7066,15568162,Sung,527,Spain,Male,53,8,0,1,1,1,51711.57,0 -7067,15680643,Lo,729,Spain,Female,42,1,0,2,1,1,149535.97,0 -7068,15761854,Burn,746,France,Female,24,4,0,1,0,1,94105,0 -7069,15730793,Russell,699,Germany,Female,54,3,111009.32,1,1,1,155905.79,1 -7070,15692137,Jen,759,France,Female,46,2,0,1,1,1,138380.11,0 -7071,15608595,Lo Duca,748,France,Female,39,3,157371.54,1,0,1,97734.3,0 -7072,15709459,Oluchi,698,Spain,Female,63,5,0,1,1,1,173576.71,0 -7073,15775750,Yao,686,France,Male,37,9,134560.62,1,1,0,27596.39,0 -7074,15585855,Gould,679,France,Male,40,1,0,1,1,1,16897.19,0 -7075,15752139,Salter,682,Germany,Male,36,5,72373.62,2,1,0,36895.99,0 -7076,15768295,Warner,778,France,Female,34,7,109564.1,1,0,1,113046.81,0 -7077,15766906,Salier,742,France,Female,25,4,132116.13,2,1,0,129933.5,0 -7078,15725776,Lazar,649,Germany,Male,24,7,101195.23,1,0,0,133091.32,0 -7079,15682576,Onyenachiya,763,France,Male,67,1,149436.73,2,0,1,106282.74,0 -7080,15704081,Findlay,595,Germany,Male,30,9,130682.11,2,1,1,57862.88,0 -7081,15719940,Gibbons,628,Germany,Female,51,10,115280.49,2,0,0,12628.61,1 -7082,15672894,McCawley,625,France,Female,36,8,129944.39,2,0,0,198914.8,0 -7083,15667451,Taylor,733,France,Male,36,5,0,2,1,1,109127.54,0 -7084,15636767,Yang,665,Spain,Female,32,10,0,1,1,1,22487.45,0 -7085,15571415,Okwudiliolisa,805,Germany,Male,56,6,151802.29,1,1,0,46791.09,1 -7086,15575605,Napolitano,725,France,Male,38,6,0,2,1,1,158697.28,0 -7087,15649160,Vavilov,554,France,Female,38,3,138731.95,1,1,1,194138.36,0 -7088,15615832,Teague,675,Spain,Female,35,8,155621.08,1,0,1,35177.31,0 -7089,15600975,Chiemenam,556,France,Female,54,4,150005.38,1,1,0,157015.5,1 -7090,15690772,Hughes,635,Spain,Female,48,2,0,2,1,1,136551.25,0 -7091,15565714,Cattaneo,601,France,Male,47,1,64430.06,2,0,1,96517.97,0 -7092,15763108,Davis,600,Germany,Male,53,7,106261.63,1,1,0,93629.66,1 -7093,15723884,Nekrasova,758,Spain,Male,40,3,0,2,0,0,96097.65,0 -7094,15644453,Loggia,606,Germany,Female,41,4,132670.53,1,1,0,156476.36,1 -7095,15655464,Combes,640,France,Female,67,3,0,1,0,1,42964.63,0 -7096,15783883,Onwuka,753,Germany,Female,38,1,117314.92,1,1,0,122021.33,1 -7097,15787693,Kharlamov,559,Spain,Male,38,3,145874.35,1,1,0,56311.39,1 -7098,15664793,Scott,754,Spain,Female,50,7,146777.44,2,0,1,150685.52,0 -7099,15642391,Lettiere,621,Germany,Male,51,4,109978.83,1,0,0,177740.58,1 -7100,15756538,Osonduagwuike,654,France,Female,37,5,0,1,0,1,71492.28,0 -7101,15668830,Wan,650,Spain,Male,24,8,108881.73,1,1,0,104492.83,0 -7102,15796569,Donaldson,831,Spain,Female,44,10,0,1,0,1,47729.33,0 -7103,15677112,Chukwufumnanya,519,France,Male,39,2,112957.26,2,1,0,97593.16,0 -7104,15815040,Ma,552,Germany,Female,42,8,103362.14,1,0,1,186869.58,1 -7105,15590434,Alexander,577,Spain,Male,41,4,89015.61,1,0,1,135227.23,0 -7106,15597536,Nkemjika,576,Spain,Male,45,5,133618.01,1,0,0,135244.87,0 -7107,15723989,Carroll,646,France,Male,40,5,93680.43,2,1,1,179473.26,0 -7108,15767358,Obioma,711,Germany,Female,45,1,97486.15,2,1,0,50610.62,0 -7109,15594812,Campbell,806,Spain,Female,37,2,137794.18,2,0,1,75232.02,0 -7110,15688210,Sims,670,France,Female,39,8,101928.51,1,0,0,89205.54,0 -7111,15681509,McKay,679,Spain,Female,28,9,0,2,0,1,61761.77,0 -7112,15572390,Huang,850,Spain,Female,39,6,0,2,1,0,103921.43,0 -7113,15801441,Campbell,670,Germany,Female,35,2,79585.96,1,0,1,198802.9,0 -7114,15783859,Boni,733,France,Female,24,3,161884.99,1,1,1,9617.24,0 -7115,15575243,Gorbunova,764,France,Female,39,1,129068.54,2,1,1,187905.12,0 -7116,15773421,Genovese,673,France,Female,42,4,0,2,1,0,121440.8,0 -7117,15788776,Landor,588,Germany,Male,49,6,132623.76,3,1,0,36292.94,1 -7118,15765257,Meng,564,Spain,Male,31,5,121461.87,1,1,1,20432.09,1 -7119,15661412,Wardell,715,France,Male,32,8,175307.32,1,1,0,187051.23,0 -7120,15636478,Williams,621,France,Male,31,7,136658.61,1,1,1,148689.13,0 -7121,15603683,Ofodile,796,Spain,Female,23,3,146584.19,2,0,0,125445.8,0 -7122,15651868,Clark,672,France,Male,34,6,0,1,0,0,22736.06,0 -7123,15815443,Lo,527,Spain,Female,46,10,131414.76,1,1,0,54947.51,0 -7124,15682686,Chukwuemeka,722,France,Female,38,3,0,2,0,1,167984.72,0 -7125,15697460,Lai,596,Germany,Male,34,4,99441.21,2,0,1,4802.27,0 -7126,15748432,Arcuri,746,France,Female,32,4,0,2,1,1,72909.75,0 -7127,15698271,Graham,523,France,Female,26,4,0,2,1,0,185488.81,0 -7128,15808662,Krylov,624,France,Male,44,3,0,2,1,0,88407.51,0 -7129,15690372,Henry,553,Spain,Male,38,1,181110.13,2,1,0,184544.59,0 -7130,15781875,Jamieson,850,Spain,Male,33,3,100476.46,2,1,1,136539.13,0 -7131,15801473,Moore,599,Germany,Male,33,2,51949.95,2,1,0,85045.92,0 -7132,15704509,Tan,492,France,Male,35,8,121063.49,1,0,0,85421.48,0 -7133,15694666,Thornton,707,Spain,Male,48,8,88441.64,1,1,1,119903.2,1 -7134,15731166,Macleod,743,France,Female,30,1,127023.39,1,1,1,138780.89,0 -7135,15728523,Rizzo,522,France,Male,41,5,144147.68,1,1,1,14789.9,0 -7136,15788442,Chukwukadibia,681,Spain,Female,57,2,173306.13,1,0,1,131964.66,0 -7137,15689781,Ts'ai,826,France,Female,49,0,0,1,0,0,178709.98,1 -7138,15764226,Lu,630,Germany,Female,28,8,106425.75,1,1,1,20344.84,0 -7139,15809837,Kent,430,Germany,Female,66,6,135392.31,2,1,1,172852.06,1 -7140,15805212,Black,806,France,Female,67,1,0,2,0,1,103945.58,0 -7141,15716082,Chukwubuikem,703,Spain,Male,39,6,152685.4,1,0,0,183656.12,0 -7142,15643056,McMillan,755,Germany,Female,38,1,82083.52,1,0,1,10333.78,0 -7143,15654859,Ngozichukwuka,612,Spain,Female,63,2,131629.17,2,1,0,122109.58,1 -7144,15761158,Y?an,719,France,Female,54,7,0,2,1,1,125041.52,0 -7145,15577515,Sung,554,Germany,Female,55,0,108477.27,1,0,1,140003,1 -7146,15723827,Macartney,683,France,Male,30,4,114779.35,1,0,0,183171.47,0 -7147,15646594,Ali,749,France,Male,41,5,57568.94,1,1,1,61128.29,0 -7148,15712877,Morley,724,Spain,Male,36,1,0,2,1,0,52462.25,0 -7149,15598802,Martin,770,Spain,Male,30,8,0,2,0,1,50839.85,0 -7150,15699340,Okorie,680,France,Male,37,4,0,2,1,0,61240.87,0 -7151,15691150,Ku,699,France,Female,32,4,110559.46,1,1,1,127429.56,0 -7152,15608688,Andreyeva,442,France,Male,34,4,0,2,1,0,68343.08,0 -7153,15737998,Cheng,529,France,Male,46,8,0,1,0,0,126511.94,1 -7154,15735837,Hsia,574,Spain,Male,36,3,0,2,1,1,8559.66,0 -7155,15659100,Lane,605,France,Male,33,9,128152.82,1,0,0,147822.81,0 -7156,15609070,Findlay,515,Germany,Male,45,7,120961.5,3,1,1,39288.11,1 -7157,15650313,Okonkwo,632,Germany,Male,65,6,129472.33,1,1,1,85179.48,0 -7158,15627699,Pirogova,558,France,Male,32,10,105000.23,1,1,0,190019.61,0 -7159,15591010,McDonald,434,Germany,Male,55,8,109339.17,2,1,0,96405.88,1 -7160,15798895,Okonkwo,525,France,Female,59,6,55328.4,1,1,0,83342.73,1 -7161,15745375,Nnanna,640,Germany,Male,23,3,72012.76,1,1,0,161333.13,0 -7162,15775235,Ku,690,France,Female,36,6,110480.48,1,0,0,81292.33,0 -7163,15780088,Porter,607,Spain,Male,34,9,132439.99,1,1,0,177747.72,0 -7164,15649379,Somayina,850,France,Female,46,3,0,2,1,1,187980.21,0 -7165,15713983,Mao,780,Germany,Male,34,5,94108.54,2,1,0,177235.21,0 -7166,15709252,Fuller,616,Germany,Female,28,10,105173.99,1,0,1,29835.37,1 -7167,15699238,Craig,618,Spain,Female,40,8,0,2,1,0,80204.38,0 -7168,15732884,Trevisano,676,France,Male,29,7,131959.86,1,0,0,189268.81,0 -7169,15587297,Ruiz,507,France,Male,33,7,0,2,1,1,85411.01,0 -7170,15684722,Fraser,490,France,Male,34,5,122952.9,2,0,0,154360.97,0 -7171,15621244,Gallo,678,France,Male,36,0,107379.68,1,1,1,84460.18,0 -7172,15744273,Waterhouse,637,Germany,Male,30,6,122641.56,2,1,0,65618.01,0 -7173,15682540,Cremonesi,602,France,Female,33,8,0,2,1,1,112928.74,0 -7174,15636521,Feng,744,Spain,Female,30,1,124037.28,1,1,1,142210.94,0 -7175,15785339,H?,640,France,Female,50,9,117565.03,2,0,0,82559.77,0 -7176,15638983,Jara,684,France,Female,38,5,133189.4,1,0,0,127388.06,0 -7177,15654625,Wilson,495,Germany,Male,39,8,120252.02,2,1,1,10160.23,0 -7178,15697310,O'Callaghan,559,Germany,Female,28,3,152264.81,1,0,0,64242.31,0 -7179,15678210,Robson,684,France,Male,38,5,105069.98,2,1,1,198355.28,0 -7180,15575438,Pease,613,France,Male,42,7,115076.06,1,1,1,79323.61,0 -7181,15632789,Maclean,794,France,Male,30,8,0,2,1,1,24113.91,0 -7182,15621423,Lavrentyev,736,France,Female,42,7,117280.23,3,0,0,41921.06,1 -7183,15573520,Rhodes,692,Germany,Male,49,6,110540.43,2,0,1,107472.99,0 -7184,15740458,Murphy,703,Spain,Male,36,7,135095.47,1,1,0,143859.66,0 -7185,15762799,Alexander,720,Germany,Male,23,0,187861.18,2,1,1,104120.17,0 -7186,15686885,Nekrasov,777,Germany,Male,44,3,124655.59,2,0,1,79792.3,0 -7187,15565996,Arnold,653,France,Male,44,8,0,2,1,1,154639.72,0 -7188,15662152,Trevisan,552,France,Female,38,9,134105.01,1,0,0,57850.1,0 -7189,15711742,Mason,708,France,Female,34,4,0,1,1,1,62868.33,0 -7190,15701885,Tucker,647,France,Female,40,9,0,2,0,1,92357.21,0 -7191,15774262,Hobson,597,Germany,Male,52,8,83693.34,2,1,1,161083.53,0 -7192,15567839,Gordon,501,France,Male,42,9,114631.23,1,0,1,91429.74,0 -7193,15644400,Anderson,709,France,Male,44,9,128601.98,1,1,0,117031.2,0 -7194,15797246,Terry,621,Germany,Female,34,2,91258.52,2,1,0,44857.4,0 -7195,15778290,Lappin,799,France,Male,70,8,70416.75,1,1,1,36483.52,0 -7196,15708714,Santiago,675,France,Female,33,6,0,2,1,0,34045.61,0 -7197,15586183,Wallace,561,France,Female,35,5,0,2,1,0,59981.62,0 -7198,15761733,King,707,France,Female,42,10,0,2,1,1,152944.39,0 -7199,15773934,Fang,670,France,Male,33,6,88294.6,1,1,0,66979.06,0 -7200,15705343,May,649,Spain,Female,32,7,0,1,1,0,28797.32,0 -7201,15593959,Travis,524,France,Male,28,1,93577.3,1,1,1,51670.82,0 -7202,15664615,Nnachetam,689,Germany,Female,30,5,136650.89,1,1,1,41865.72,1 -7203,15671014,Zhdanova,573,Spain,Female,72,8,98765.84,1,1,1,96015.53,0 -7204,15657778,Jefferson,657,France,Male,33,1,84309.57,2,0,0,103914.4,0 -7205,15585192,Cremonesi,686,Spain,Male,39,10,136258.06,1,0,0,89199.51,0 -7206,15592914,Fang,683,France,Female,29,9,0,2,1,1,48849.89,0 -7207,15770995,Sinclair,753,Germany,Female,47,1,131160.85,1,1,0,197444.69,0 -7208,15570990,Begley,520,Spain,Female,30,4,145222.99,2,0,0,145160.96,0 -7209,15596165,Degtyarev,547,Germany,Male,25,4,98141.57,2,1,1,52309.8,0 -7210,15788131,Atkins,653,France,Male,47,6,0,1,1,0,50695.93,1 -7211,15800773,Ikenna,648,Spain,Female,28,9,102282.61,1,1,1,157891.11,0 -7212,15690153,Sun,639,France,Female,37,4,116121.84,2,0,1,181850.74,0 -7213,15638989,Lettiere,711,France,Female,25,5,190066.54,1,0,0,51345.39,1 -7214,15623210,Smith,484,Germany,Female,55,8,149349.58,3,0,0,137519.92,1 -7215,15652658,Finch,721,France,Male,36,1,155176.83,2,1,1,49653.37,0 -7216,15684440,Monaldo,548,Germany,Male,32,2,98986.28,1,1,1,55867.38,0 -7217,15730287,Ugonna,679,France,Male,41,8,147726.98,3,1,0,172749.4,1 -7218,15720353,Chiang,553,France,Male,41,1,0,2,1,0,90607.31,0 -7219,15767231,Sun,757,France,Male,36,7,144852.06,1,0,0,130861.95,0 -7220,15761554,Blackburn,581,France,Male,54,4,89299.81,1,0,0,5558.47,1 -7221,15706637,Chang,718,Spain,Male,40,9,0,2,0,0,121537.91,0 -7222,15690492,Palermo,625,France,Male,41,6,97663.16,2,1,0,57128.78,0 -7223,15694237,McEwan,744,Spain,Male,39,4,95161.75,1,1,0,19409.77,0 -7224,15729771,Davide,799,Germany,Male,31,9,154586.92,1,0,1,88604.89,1 -7225,15609823,Chieloka,751,Spain,Female,34,8,127095.14,2,0,0,479.54,0 -7226,15793366,Humphreys,781,Germany,Male,35,7,92526.15,2,1,1,173837.54,0 -7227,15614813,Cocci,777,Germany,Female,46,0,107362.8,1,1,0,487.3,0 -7228,15566495,Hanson,704,Spain,Female,24,2,0,1,1,0,35600.25,1 -7229,15707602,Macleod,539,France,Female,47,2,127286.04,2,1,1,166929.43,1 -7230,15635244,Ritchie,716,France,Female,29,6,0,2,1,1,98998.61,0 -7231,15805627,Nebechukwu,670,France,Male,37,2,0,2,1,1,54229.74,0 -7232,15607986,Nnamutaezinwa,555,France,Male,40,10,139930.18,1,1,1,105720.09,0 -7233,15799785,Ikemefuna,679,Germany,Female,30,4,77949.69,1,1,1,121151.46,0 -7234,15699963,Scott,571,France,Male,38,1,121405.04,1,1,1,154844.22,0 -7235,15624595,Chiang,512,Spain,Female,35,5,124580.69,1,1,1,18785.48,0 -7236,15629750,Artyomova,697,France,Male,35,5,133087.76,1,1,0,64771.61,0 -7237,15651460,Hsieh,424,Spain,Male,34,7,0,1,1,1,16250.61,0 -7238,15753550,Levien,684,France,Female,43,7,0,2,1,0,131093.99,0 -7239,15594133,Erskine,697,Spain,Male,62,7,0,1,1,0,129188.18,1 -7240,15772329,Fiorentino,580,Germany,Male,45,8,103741.14,1,1,0,47428.73,1 -7241,15591552,Okonkwo,600,France,Female,32,7,98877.95,1,1,0,132973.21,0 -7242,15750921,Monds,521,France,Male,37,5,105843.26,2,1,1,84908.2,0 -7243,15701687,Campbell,664,Spain,Male,44,7,77526.66,3,0,0,57338.56,1 -7244,15728906,Ibekwe,634,France,Male,77,5,0,2,1,1,161579.85,0 -7245,15670029,Marcelo,445,France,Female,33,7,0,2,1,0,122625.68,0 -7246,15763579,Castro,702,Germany,Female,36,2,105264.88,2,1,1,52909.87,0 -7247,15728010,Capon,485,France,Male,37,5,0,2,0,1,170226.47,0 -7248,15663194,Voronova,582,Germany,Female,40,3,110150.43,1,1,1,191757.65,1 -7249,15736510,Loggia,605,Spain,Female,57,2,0,3,1,0,66652.75,1 -7250,15745804,Law,628,France,Male,25,7,0,2,1,1,195977.75,0 -7251,15631451,Grant,604,Spain,Female,28,6,0,2,1,1,69056.26,0 -7252,15746995,Greco,724,Germany,Male,31,9,138166.3,1,1,0,12920.43,0 -7253,15730673,Dietz,567,Germany,Male,40,7,122265.24,1,1,0,138552.74,0 -7254,15734649,Martel,779,Spain,Female,55,0,133295.98,1,1,0,22832.71,1 -7255,15701081,Jarvis,785,France,Male,36,2,0,1,0,1,61811.1,0 -7256,15632503,Meng,563,France,Female,32,0,148326.09,1,1,0,191604.27,1 -7257,15585928,Hay,821,Germany,Female,31,2,68927.57,1,1,1,25445,0 -7258,15648681,Voronoff,747,France,Female,47,5,139914.6,4,0,1,129964.56,1 -7259,15747757,Trevascus,600,Germany,Female,58,8,118723.11,1,0,0,6209.51,1 -7260,15718921,Ho,625,Spain,Male,32,7,106957.28,1,1,1,134794.02,0 -7261,15571081,Hansen,773,France,Female,41,7,190238.93,1,1,1,57549.65,0 -7262,15734578,Craig,726,France,Female,53,1,113537.73,1,0,1,28367.21,0 -7263,15579583,Hall,641,Spain,Female,40,4,101090.27,1,1,1,51703.09,0 -7264,15622729,Sun,649,France,Female,46,2,0,2,1,1,66602.7,0 -7265,15662189,Durant,434,Spain,Male,33,3,0,1,1,1,2739.71,0 -7266,15692718,Jackson,738,France,Female,38,7,0,2,0,0,69227.42,0 -7267,15762716,Chigozie,762,Spain,Female,60,10,168920.75,1,1,0,31445.03,1 -7268,15724851,Farmer,507,Germany,Male,31,9,111589.67,1,1,0,150037.19,0 -7269,15587266,Douglas,606,Germany,Female,27,6,172310.33,1,0,1,111448.92,0 -7270,15675926,Ardis,655,Germany,Male,34,7,118028.35,1,1,0,51226.32,1 -7271,15706268,Smith,697,Germany,Male,51,1,147910.3,1,1,1,53581.14,0 -7272,15581871,Butler,504,Germany,Male,42,7,131287.36,2,1,1,149697.78,0 -7273,15666166,Pettry,653,France,Female,74,0,121276.32,1,1,1,160348.31,0 -7274,15671582,John,660,Spain,Male,38,6,109869.32,1,1,1,154641.91,0 -7275,15680901,Potter,652,France,Female,34,6,97435.85,2,1,1,104331.76,0 -7276,15642336,Shaw,669,France,Female,42,9,0,2,0,0,135630.32,0 -7277,15653147,Boyle,594,France,Male,35,2,133853.27,1,1,1,65361.66,0 -7278,15571284,Elmore,756,Germany,Male,32,0,109528.16,2,1,1,56176.31,0 -7279,15591360,Udinesi,642,France,Female,33,4,84607.34,2,0,1,60059.47,0 -7280,15810485,Sun,486,Germany,Male,37,1,101438,1,0,0,51364.56,0 -7281,15611973,Tuan,804,France,Male,55,7,0,2,1,1,118752.6,0 -7282,15735572,Lawrence,629,France,Male,59,9,113657.83,1,1,1,116848.79,1 -7283,15567860,Burrows,581,Spain,Female,44,7,189318.16,2,1,0,45026.23,1 -7284,15795690,Shao,667,France,Male,31,3,99513.91,1,1,1,189657.26,0 -7285,15706464,White,667,Spain,Male,35,4,97585.32,2,0,0,57213.46,0 -7286,15725028,Chialuka,679,France,Male,29,3,0,2,1,1,63687.06,0 -7287,15751167,Toscano,680,France,Female,43,4,0,2,1,1,58761.33,0 -7288,15633944,McKay,644,Spain,Male,32,3,136659.74,1,1,1,14187.78,0 -7289,15672637,Voronkov,571,France,Female,30,4,85755.86,1,1,0,145115.95,0 -7290,15680895,Sal,627,Spain,Female,35,7,0,1,1,0,187718.26,0 -7291,15793825,Ikechukwu,536,France,Male,39,4,0,2,1,0,27150.35,0 -7292,15611318,Kruglova,599,Spain,Male,33,4,51690.89,1,1,0,111622.76,1 -7293,15768474,Clements,744,Spain,Male,34,3,0,2,1,0,27244.35,0 -7294,15716276,Kennedy,709,France,Female,34,2,111669.68,1,1,0,57029.66,0 -7295,15623668,Johnson,653,Germany,Male,31,2,154741.45,2,0,0,25183.01,0 -7296,15696361,Chung,648,Germany,Male,31,7,125681.51,1,0,1,129980.93,0 -7297,15607988,Garland,663,Germany,Female,37,8,155303.71,1,1,0,118716.63,0 -7298,15637891,Docherty,613,Germany,Female,43,4,140681.68,1,0,1,20134.07,0 -7299,15789865,Nnaife,620,France,Male,28,9,71902.52,1,0,1,190208.23,0 -7300,15627190,Lettiere,661,France,Male,51,6,146606.6,1,1,1,68021.9,0 -7301,15788224,Sanderson,669,Germany,Male,45,1,123949.75,1,0,0,110881.56,0 -7302,15702149,Fomin,767,Germany,Female,33,1,144753.21,1,1,1,132480.75,0 -7303,15708236,Wright,491,France,Female,72,6,91285.22,1,1,1,7032.95,0 -7304,15568469,Buckley,653,France,Male,43,0,0,2,1,0,27862.58,0 -7305,15764444,Pan,679,Germany,Male,58,8,125850.53,2,1,1,87008.17,0 -7306,15794204,Manna,687,France,Male,28,7,108116.66,1,1,1,27411.19,0 -7307,15807546,Chinwendu,837,France,Female,38,2,0,2,1,1,46395.21,0 -7308,15782159,Ndubuagha,850,France,Male,28,8,67639.56,2,1,1,194245.29,0 -7309,15618703,White,663,Spain,Female,53,6,150200.23,1,0,1,151317.27,1 -7310,15793317,Hale,547,Spain,Female,22,7,141287.15,1,1,0,118142.79,0 -7311,15740487,Ross,627,France,Female,41,6,0,3,1,1,138700.75,1 -7312,15722479,Ikenna,707,France,Male,37,1,0,2,0,1,6035.51,0 -7313,15688264,Nkemdilim,629,France,Female,43,0,0,2,1,1,41263.69,0 -7314,15583067,McMillan,687,France,Female,36,4,97157.96,1,0,1,63185.05,0 -7315,15686670,Duke,588,France,Female,36,2,0,2,1,0,92536,1 -7316,15593345,Bradbury,502,Germany,Female,33,6,125241.17,2,1,1,158736.07,0 -7317,15811690,Bayley,793,Germany,Male,54,2,128966.13,1,0,0,18633.4,1 -7318,15734008,Bartlett,727,Germany,Male,59,5,152581.06,1,1,0,71830.1,1 -7319,15771856,Cremin,632,Spain,Female,32,1,0,2,1,0,19525.65,0 -7320,15762045,Gilchrist,474,Germany,Female,37,5,142688.57,2,1,1,110953.33,0 -7321,15778142,Shih,850,Germany,Female,31,1,130089.56,2,1,1,4466.21,0 -7322,15689268,Fitzpatrick,584,France,Male,36,9,0,1,1,1,105818.51,0 -7323,15721507,Pagan,713,France,Female,32,1,117094.02,1,0,0,149558.83,1 -7324,15750476,Hendrick,742,Spain,Male,24,8,0,2,1,0,4070.28,0 -7325,15810723,Sanderson,607,France,Female,39,10,0,3,1,0,132741.13,1 -7326,15787229,Samsonova,761,Spain,Female,34,2,0,2,1,0,61251.25,0 -7327,15570508,Azubuike,600,France,Male,49,7,90218.9,1,1,0,91347.76,0 -7328,15617065,Pan,650,Spain,Male,42,4,194532.66,1,1,0,171045.31,1 -7329,15689786,Massie,850,Germany,Male,56,1,169743.83,1,0,0,155850.4,1 -7330,15648876,Sandover,501,France,Female,34,5,0,1,1,0,27380.99,0 -7331,15802106,Craig,418,France,Male,34,8,155973.88,1,1,0,154208.96,0 -7332,15773869,Onwudiwe,797,Spain,Male,59,4,129321.44,1,1,1,93624.55,0 -7333,15711635,Chu,788,Germany,Female,42,6,138650.49,2,1,0,64746.07,0 -7334,15795527,Zetticci,699,Spain,Male,43,2,136487.86,2,1,0,82815.93,0 -7335,15759133,Vaguine,616,France,Male,18,6,0,2,1,1,27308.58,0 -7336,15679394,Owen,651,France,Female,41,4,38617.2,1,1,1,104876.8,0 -7337,15801072,Hurst,654,France,Female,28,7,0,2,1,0,151316.37,0 -7338,15646082,Harding,676,France,Female,34,8,82909.14,1,1,0,91817.38,1 -7339,15796111,Smith,708,Germany,Female,54,8,145151.4,1,0,1,125311.17,1 -7340,15670646,Moore,499,Spain,Female,42,0,147187.84,1,1,1,14868.94,1 -7341,15578722,Bradley,689,France,Male,39,4,0,2,1,0,196112.45,0 -7342,15815095,Burfitt,850,Spain,Male,54,7,108185.81,2,0,0,24093.4,1 -7343,15730360,Mackenzie,502,France,Male,30,4,0,2,1,1,66263.87,0 -7344,15763194,Milanesi,643,France,Male,34,7,0,2,0,1,100304.13,0 -7345,15720725,Shubin,762,France,Male,28,2,0,2,1,0,167909.52,0 -7346,15567834,Nieves,719,France,Male,49,5,105918.1,1,1,1,16246.59,0 -7347,15720644,Martin,789,France,Male,27,6,0,2,1,0,103603.65,0 -7348,15811742,Jen,553,Spain,Male,42,7,0,2,1,0,7680.23,0 -7349,15813363,Woods,448,Spain,Male,25,2,0,2,0,0,95215.73,0 -7350,15717629,Docherty,632,Germany,Male,42,6,59972.26,2,0,1,148172.94,0 -7351,15713160,Lin,669,Spain,Male,25,7,157228.61,2,1,0,124382.9,0 -7352,15568878,Cheng,654,Spain,Male,34,5,0,2,1,0,159311.46,0 -7353,15809800,Korovina,726,France,Female,38,4,0,2,0,0,6787.48,0 -7354,15736420,Macdonald,596,France,Male,21,4,210433.08,2,0,1,197297.77,1 -7355,15757933,Hardy,733,Germany,Female,30,1,102452.71,1,1,0,21556.95,0 -7356,15623072,Shaw,529,Spain,Female,35,5,0,2,1,0,56518,0 -7357,15683993,Knight,493,France,Female,37,8,142987.46,2,1,0,158840.99,0 -7358,15570947,Bruny,615,Spain,Female,29,7,143330.56,2,1,1,126396.01,0 -7359,15797767,Ikedinachukwu,600,France,Female,49,6,0,1,0,1,148087.88,1 -7360,15731989,Moran,666,France,Male,36,4,120165.4,2,1,0,33701.5,0 -7361,15591035,Macleod,644,Spain,Male,54,6,0,1,0,1,84622.37,0 -7362,15586479,Yin,692,France,Female,36,4,0,1,1,0,185580.89,1 -7363,15605872,Felix,707,France,Male,73,6,66573.17,1,1,1,62768.8,0 -7364,15666012,Rippey,603,France,Male,40,4,102833.46,2,1,1,38829.11,0 -7365,15641733,Mishina,671,France,Female,34,5,164757.56,1,1,0,110748.88,0 -7366,15593178,Graham,568,Spain,Female,36,10,153610.61,1,1,1,54083.8,1 -7367,15649183,Johnston,598,Spain,Female,35,8,0,3,0,1,88658.73,0 -7368,15736399,Korovin,606,Spain,Male,42,10,0,2,1,0,177938.52,0 -7369,15751137,Lei,850,Germany,Female,36,3,169025.83,1,1,0,174235.06,0 -7370,15757188,Chimaijem,644,Spain,Female,26,4,153455.72,2,1,1,82696.84,0 -7371,15726167,Scott,655,France,Male,37,4,0,2,1,1,142415.97,0 -7372,15624850,Grant,850,France,Male,30,10,153972.89,2,1,0,62811.03,0 -7373,15717700,McIntyre,683,Spain,Male,34,9,114609.55,2,0,1,25339.29,0 -7374,15716347,Griffin,663,Germany,Male,37,7,143625.83,2,0,1,176487.05,0 -7375,15696287,Converse,682,Germany,Female,38,1,116520.28,1,1,1,49833.5,1 -7376,15638871,Ch'ang,639,France,Male,77,6,80926.02,2,1,1,55829.25,0 -7377,15765093,Coates,704,France,Male,23,6,166594.78,1,1,1,155823.2,0 -7378,15592999,Reid,691,France,Female,40,0,115465.98,1,1,1,60622.61,0 -7379,15641715,Ts'ui,599,France,Male,34,8,0,2,1,1,174196.68,0 -7380,15607746,Belstead,573,France,Female,36,1,0,1,1,1,56905.38,0 -7381,15625311,Dickinson,589,Germany,Female,41,7,92618.62,1,1,1,101178.85,0 -7382,15573077,Nwora,620,Germany,Female,25,8,141825.88,1,1,1,73857.94,1 -7383,15735106,Bishop,647,Spain,Male,28,6,149594.02,2,1,0,102325.19,0 -7384,15672912,Loggia,737,Spain,Female,39,7,130051.66,2,0,0,55356.39,1 -7385,15589881,Rowe,634,France,Female,41,7,0,2,1,1,131284.93,0 -7386,15660144,Balashov,660,France,Male,38,4,0,2,0,0,88080.43,0 -7387,15664083,Ulyanova,666,Germany,Female,37,2,158468.76,1,0,1,93266.01,0 -7388,15690898,Bogolyubova,696,France,Male,44,8,161889.79,1,0,0,75562.47,0 -7389,15808023,Remington,836,France,Female,29,9,133681.78,1,1,1,153747.73,0 -7390,15676909,Mishin,667,Spain,Female,34,5,0,2,1,0,163830.64,0 -7391,15764922,Tu,596,Spain,Male,20,3,187294.46,1,1,0,103456.47,0 -7392,15766734,Castiglione,430,France,Male,31,5,0,1,1,0,95655.16,0 -7393,15795079,Nnaife,596,Spain,Male,67,6,0,2,1,1,138350.74,0 -7394,15757434,Yang,599,France,Male,28,7,119706.22,1,0,0,31190.42,0 -7395,15673747,Ayers,519,France,Female,22,8,0,1,0,1,167553.06,0 -7396,15808386,Cocci,721,Germany,Female,45,7,138523.2,1,0,0,59604.45,1 -7397,15603565,Mackenzie,603,Spain,Female,56,5,90778.76,2,1,0,162223.67,1 -7398,15744044,Fiorentini,572,Germany,Male,47,4,99353.42,1,1,0,196549.85,1 -7399,15577771,Akabueze,453,Germany,Female,40,1,111524.49,1,1,1,120373.84,1 -7400,15769548,Hyde,668,France,Female,37,7,128645.67,1,1,0,92149.64,0 -7401,15802071,Levi,762,Germany,Male,35,1,117458.51,1,0,1,178361.48,1 -7402,15677395,Nwabugwu,633,France,Female,39,9,129189.15,2,0,0,170998.83,0 -7403,15632010,Chia,647,Spain,Male,33,7,121260.19,2,1,0,77216.48,0 -7404,15779492,Trevisano,796,Spain,Male,56,6,94231.13,1,0,0,121164.6,1 -7405,15694677,Bennetts,733,France,Male,39,1,0,2,1,1,141841.31,0 -7406,15704315,Teng,556,France,Male,34,8,163757.06,1,1,1,104000.06,0 -7407,15742009,Hsueh,489,Spain,Male,58,4,0,2,1,1,191419.32,0 -7408,15766663,Mahmood,639,France,Male,22,4,0,2,1,0,28188.96,0 -7409,15742297,Sinclair,715,France,Male,35,2,141005.47,1,1,1,60407.93,0 -7410,15688059,Chin,807,Germany,Female,42,9,105356.09,2,1,1,130489.37,0 -7411,15752344,She,714,Spain,Male,34,5,0,2,1,0,193040.32,0 -7412,15698749,He,626,Germany,Female,23,6,85897.95,1,1,0,109742.8,0 -7413,15631693,Hill,697,France,Male,36,7,0,2,1,1,74760.32,0 -7414,15604536,Vachon,850,Germany,Female,31,4,164672.66,1,0,1,61936.1,0 -7415,15802869,Ball,737,Germany,Female,45,2,99169.67,2,1,1,78650.95,0 -7416,15635598,Hsieh,812,France,Male,29,6,0,2,0,0,168023.6,0 -7417,15592326,Baker,583,France,Male,36,8,0,2,0,1,5571.59,0 -7418,15736533,Monaldo,730,Germany,Female,37,5,124053.03,1,1,0,118591.67,0 -7419,15647191,Lucchesi,677,France,Male,36,4,0,2,1,0,7824.31,0 -7420,15622507,Hamilton,748,Germany,Female,40,3,103499.09,2,0,0,38153.19,0 -7421,15765487,Kuo,753,Germany,Female,38,9,151766.71,1,1,1,180829.99,0 -7422,15646521,Fan,634,Spain,Female,36,1,0,1,1,1,143960.72,0 -7423,15746258,Wright,622,France,Male,29,7,101486.96,1,1,1,8788.35,0 -7424,15692430,Milano,699,Germany,Male,36,2,123601.56,2,1,0,103557.85,0 -7425,15625501,Wall,570,Germany,Male,38,1,127201.58,1,1,0,147168.28,1 -7426,15640521,Chidumaga,552,Germany,Male,33,3,144962.74,1,1,0,58844.84,1 -7427,15790630,Olisaemeka,619,France,Female,48,4,0,1,0,0,18094.96,1 -7428,15664720,Kovalyova,714,Spain,Male,33,8,122017.19,1,0,0,162515.17,0 -7429,15750055,Onio,503,Spain,Male,32,9,100262.88,2,1,1,157921.25,0 -7430,15644878,Hill,685,Spain,Female,43,6,117302.62,1,0,0,68701.73,0 -7431,15754578,Okeke,606,France,Female,35,0,135984.15,2,1,0,186778.89,0 -7432,15705379,Upjohn,678,France,Male,38,3,0,2,1,0,66561.6,0 -7433,15761047,H?,724,Germany,Male,31,2,160997.54,2,0,1,64831.36,0 -7434,15671293,Marcus,779,Germany,Female,37,2,128389.63,1,1,1,6589.16,1 -7435,15687527,Yobachukwu,638,Spain,Male,35,1,0,2,1,0,165370.66,0 -7436,15647898,Russell,610,Spain,Female,50,5,130554.51,3,1,0,184758.17,1 -7437,15671534,Hovell,646,Germany,Female,57,6,90212,1,1,0,13911.27,1 -7438,15591248,Chukwumaobim,628,France,Female,29,9,71996.29,1,1,1,34857.46,0 -7439,15676156,Boyle,528,France,Female,32,4,85615.66,2,1,0,156192.43,0 -7440,15812918,Scott,432,France,Female,27,6,62339.81,2,0,0,53874.67,0 -7441,15604130,Johnstone,622,Spain,Female,47,6,142319.03,1,0,0,100183.05,0 -7442,15700549,Alvares,721,France,Male,54,5,0,2,1,1,4493.12,0 -7443,15715519,McDavid,614,Spain,Male,36,5,0,2,1,0,130610.78,0 -7444,15707042,Dellucci,634,France,Female,24,2,87413.19,1,1,0,63340.65,0 -7445,15605276,Brothers,742,France,Female,29,4,0,2,1,1,180066.59,0 -7446,15630592,Sanders,516,France,Female,45,4,0,1,1,0,95273.73,1 -7447,15636626,Morrison,718,France,Male,35,3,97560.16,1,1,1,53511.74,0 -7448,15740411,Molle,636,Germany,Male,30,8,141787.31,2,1,1,109685.61,0 -7449,15593834,Genovese,691,Spain,Male,36,7,129934.64,1,0,0,75664.56,1 -7450,15804235,Zetticci,698,France,Female,37,2,166178.02,2,1,1,71972.95,0 -7451,15679801,Hsueh,712,Spain,Female,39,5,163097.55,2,1,1,23702.42,0 -7452,15673907,Alexander,659,France,Male,20,8,0,2,0,0,112572.02,0 -7453,15636562,Muravyova,573,Spain,Male,44,8,0,2,0,0,62424.46,0 -7454,15702571,Wright,778,Germany,Female,35,1,151958.19,3,1,1,131238.37,1 -7455,15627365,Calabresi,732,France,Male,46,0,0,2,1,1,184350.78,0 -7456,15748499,Johnson,550,Germany,Male,33,4,118400.91,1,0,1,13999.64,1 -7457,15598614,Lucchesi,790,Spain,Male,20,8,0,2,1,0,168152.76,0 -7458,15668889,Galgano,665,Germany,Female,43,2,116322.27,4,1,0,35640.12,1 -7459,15800049,Grigoryeva,728,Spain,Female,43,5,0,1,1,1,120088.17,0 -7460,15583724,Raymond,645,Spain,Female,29,4,0,2,1,1,74346.11,0 -7461,15622083,Paterson,647,Germany,Male,30,6,143138.91,2,1,0,2955.46,0 -7462,15645571,Genovese,596,Spain,Male,32,4,0,2,0,1,146504.35,0 -7463,15598266,Martin,610,France,Male,40,9,0,1,1,1,149602.54,0 -7464,15667934,Moretti,512,France,Male,36,0,129804.17,1,1,0,53020.9,0 -7465,15569682,Leckie,768,Germany,Male,37,9,108308.11,1,1,0,41788.25,1 -7466,15772941,Lane,666,Germany,Male,30,3,110153.27,1,0,1,74849.46,0 -7467,15586174,Brodney,700,Germany,Female,30,4,116377.48,1,1,1,134417.31,0 -7468,15803682,Angelo,651,Germany,Female,37,10,117791.06,2,1,1,75837.58,0 -7469,15627328,Millar,542,Spain,Female,26,2,0,2,1,1,54869.54,0 -7470,15717065,Balashov,686,France,Female,35,8,105419.73,1,1,0,35356.46,0 -7471,15602456,Afanasyev,850,Germany,Female,47,4,99219.47,2,1,1,122141.13,0 -7472,15721569,Chialuka,658,Germany,Female,55,8,119327.93,1,0,1,119439.66,0 -7473,15573798,Yermolayev,448,France,Female,36,6,83947.12,2,1,0,81999.53,0 -7474,15638272,Tien,609,Spain,Male,32,4,99883.16,1,1,1,120594.85,0 -7475,15799859,Lucchesi,704,France,Male,50,4,165438.26,1,1,0,120770.75,1 -7476,15599152,Lai,698,France,Male,31,1,156111.24,1,0,0,134790.74,0 -7477,15737909,Bates,759,France,Male,44,2,111095.58,2,1,0,100137.7,0 -7478,15646190,Saunders,677,France,Female,56,0,119963.45,1,0,0,158325.87,1 -7479,15711249,Chukwuemeka,544,Spain,Male,22,4,0,2,1,0,70007.67,0 -7480,15671987,Meagher,567,Spain,Male,35,8,153137.74,1,1,0,88659.07,0 -7481,15812766,Golubeva,490,Spain,Male,40,6,156111.08,1,0,0,190889.13,0 -7482,15778589,Collier,626,France,Male,34,7,113014.7,2,1,1,56646.28,0 -7483,15750104,Chan,718,Germany,Male,43,5,132615.73,2,1,0,32999.1,0 -7484,15784526,Chen,616,France,Male,44,5,102016.38,1,0,1,178235.37,1 -7485,15646563,Wright,772,France,Female,35,9,0,1,0,1,25448.31,0 -7486,15744423,Cocci,561,France,Male,32,5,0,2,1,0,84871.99,0 -7487,15593694,Williams,814,France,Male,49,8,0,2,0,0,157822.54,0 -7488,15785367,McGuffog,651,France,Female,56,4,0,1,0,0,84383.22,1 -7489,15687765,Chukwujamuike,538,Germany,Female,42,4,80380.24,1,1,0,119216.46,0 -7490,15789014,Scott,600,France,Female,26,6,108909.12,1,1,0,82547.01,0 -7491,15703177,Bell,654,France,Female,35,2,90865.8,1,1,1,86764.46,0 -7492,15660263,Olisaemeka,622,France,Male,40,4,99799.76,2,1,0,197372.13,0 -7493,15776545,Napolitani,682,France,Male,28,10,200724.96,1,0,1,82872.64,1 -7494,15683276,Sargood,610,Spain,Female,37,10,140363.95,2,1,1,129563.86,0 -7495,15599272,Harrington,795,France,Female,36,1,151844.64,1,1,1,135388.89,0 -7496,15589541,Sutherland,557,France,Female,27,2,0,2,0,1,4497.55,0 -7497,15608804,Allan,824,Germany,Male,49,8,133231.48,1,1,1,67885.37,0 -7498,15645820,Folliero,698,France,Male,27,7,0,2,1,0,111471.55,0 -7499,15659031,Mordvinova,630,France,Female,36,8,126598.99,2,1,1,134407.93,0 -7500,15790113,Schofield,609,Germany,Female,71,6,113317.1,1,1,0,108258.22,1 -7501,15652289,Williams,694,France,Male,47,4,0,2,1,0,197528.62,0 -7502,15605341,Baird,681,France,Female,58,8,93173.88,1,1,1,139761.25,0 -7503,15697844,Whitehouse,721,Spain,Female,32,10,0,1,1,0,136119.96,1 -7504,15652048,Thompson,563,Germany,Male,44,7,105007.31,2,1,1,197812.16,0 -7505,15587038,Ogochukwu,654,Spain,Female,32,2,0,1,1,1,51972.92,1 -7506,15660528,Niu,659,Spain,Male,27,4,0,2,1,0,99341.87,0 -7507,15700300,Okoli,674,Germany,Female,44,4,131593.85,1,0,1,171345.02,1 -7508,15642001,Lorenzen,576,Germany,Male,44,9,119530.52,1,1,0,119056.68,1 -7509,15580366,Okechukwu,566,Germany,Male,54,4,118614.6,2,1,1,172601.62,0 -7510,15657228,Anderson,545,Germany,Male,37,9,95829.13,2,0,1,104936.88,0 -7511,15729377,Ku,798,France,Male,36,1,0,2,1,1,159044.1,0 -7512,15686913,Kung,757,France,Male,38,0,0,1,1,0,83263.06,0 -7513,15631267,Lu,641,France,Male,50,6,153590.73,2,1,1,130910.78,0 -7514,15632275,Trevisano,718,France,Male,29,2,0,1,1,0,126336.72,0 -7515,15715907,Onwubiko,699,France,Male,64,9,113109.52,1,1,0,27980.8,1 -7516,15764841,Vidler,623,France,Female,35,0,130557.24,1,1,1,47880.71,0 -7517,15748649,Shen,644,France,Male,40,8,93183.19,1,1,0,73882.49,0 -7518,15771409,McGregor,586,France,Male,58,7,151933.63,1,1,0,162960.05,1 -7519,15779207,Nnamdi,500,Germany,Male,30,2,125495.64,2,1,1,68807.47,0 -7520,15814116,Castiglione,583,France,Female,42,7,0,2,1,0,144039.05,0 -7521,15665087,Bergamaschi,595,Germany,Female,26,8,118547.72,1,1,1,151192.18,0 -7522,15611189,Allingham,670,Spain,Male,43,1,97792.21,1,0,0,120225.62,0 -7523,15729718,Stelzer,610,France,Male,41,6,0,3,0,0,56118.81,1 -7524,15733602,Rubin,814,Spain,Female,72,2,0,2,0,1,130853.03,0 -7525,15620103,Ho,660,France,Female,40,8,167181.01,1,1,1,185156.94,0 -7526,15770406,Watson,580,Germany,Male,35,9,121355.19,1,0,1,35671.45,0 -7527,15800554,Perry,850,France,Female,81,1,0,2,1,1,59568.24,0 -7528,15611409,Sun,676,Spain,Male,35,0,0,2,0,0,139911.58,0 -7529,15646535,Harrell,578,France,Male,46,5,113226.47,1,1,0,56770.76,0 -7530,15575430,Robson,579,France,Female,33,1,118392.75,1,1,1,157564.75,0 -7531,15711299,Wilson,711,Germany,Female,52,8,145262.54,1,0,1,131473.31,0 -7532,15642063,Kelechi,692,France,Male,40,6,163505.16,1,0,0,90424.09,0 -7533,15706602,Bates,760,Spain,Female,33,1,118114.28,2,0,1,156660.21,0 -7534,15592773,Eberegbulam,630,Germany,Female,51,0,108449.23,3,0,0,88372.69,1 -7535,15786539,Olisaemeka,808,France,Male,32,1,0,2,1,1,46200.71,0 -7536,15737542,Davey,611,Germany,Female,36,10,103294.56,1,1,0,160548.12,0 -7537,15590234,De Luca,697,France,Female,42,1,0,1,1,0,1262.83,1 -7538,15773776,Ho,655,France,Female,38,6,0,1,1,1,188639.28,0 -7539,15728082,Vasiliev,601,Spain,Male,28,6,0,2,1,0,14665.28,0 -7540,15609987,Smith,755,France,Male,42,2,119919.12,1,1,0,156868.21,0 -7541,15735330,Sung,553,France,Male,37,1,0,1,1,0,30461.55,0 -7542,15649430,White,723,France,Male,28,4,0,2,1,1,123885.88,0 -7543,15768777,Wang,507,Spain,Female,34,4,0,2,1,1,60688.38,0 -7544,15777893,Davide,777,France,Male,43,1,0,2,1,0,21785.91,0 -7545,15791326,Nnamdi,566,France,Male,34,3,0,1,0,0,188135.69,0 -7546,15615176,Welsh,732,France,Male,26,7,0,2,1,0,154364.66,0 -7547,15735221,Sousa,697,France,Female,42,10,0,2,1,0,61312.15,0 -7548,15617991,Andrews,555,France,Male,29,4,128744.04,1,1,1,47454.93,0 -7549,15658504,Chiawuotu,584,Germany,Female,62,9,137727.34,2,0,1,121102.9,0 -7550,15785705,Thomson,705,Germany,Female,44,10,106731.58,1,1,0,137419.87,1 -7551,15801817,Carpenter,688,France,Female,38,7,123544.21,1,1,1,157664.02,0 -7552,15752578,Yefimova,626,France,Female,37,2,133968.96,2,1,0,148689.65,0 -7553,15781574,Ma,636,Spain,Male,76,9,126534.6,1,1,1,39789.62,0 -7554,15792107,Black,719,Spain,Female,35,8,0,1,1,1,165162.4,0 -7555,15569917,Obijiaku,706,Spain,Male,30,6,87609.68,2,0,0,137674.55,1 -7556,15721504,King,731,Spain,Male,41,3,0,2,1,0,101371.72,0 -7557,15757306,Miller,738,Spain,Male,49,3,0,3,1,1,65066.48,1 -7558,15647295,Chin,426,France,Male,34,9,0,2,1,0,107876.91,0 -7559,15642098,Cox,622,Spain,Female,36,0,108960,2,1,0,111180.3,1 -7560,15696120,Wallace,701,Spain,Female,30,2,0,2,1,0,115650.63,0 -7561,15675176,Price,512,France,Male,51,6,144953.31,1,1,1,165035.17,0 -7562,15700046,Yuan,635,France,Male,41,4,103544.88,2,1,0,193746.55,0 -7563,15782089,Mullen,685,France,Male,33,6,0,1,1,0,58458.26,0 -7564,15706394,Howell,609,France,Male,53,7,0,2,0,1,52332.85,0 -7565,15759387,McIntosh,598,Germany,Male,38,1,101487.18,1,1,1,75959.1,1 -7566,15623369,Clifton,708,France,Male,52,10,105355.81,1,1,0,123.07,1 -7567,15732943,Okwuoma,574,Spain,Male,36,4,77967.5,1,1,0,167066.95,1 -7568,15750545,Chidiebere,629,France,Male,44,5,0,4,0,0,117572.59,1 -7569,15809909,Fan,422,Spain,Female,54,4,0,2,1,1,7166.71,0 -7570,15642448,Onyemauchechukwu,656,Spain,Male,28,8,120047.77,1,1,1,137173.39,0 -7571,15791944,Harker,697,France,Male,32,7,175464.85,3,1,0,116442.42,1 -7572,15768342,Bolton,718,France,Male,52,8,79475.3,3,1,1,32421.32,1 -7573,15567919,Lazarev,586,Germany,Male,37,8,167735.69,2,0,1,104665.79,0 -7574,15674750,Alexeyeva,481,Spain,Female,37,8,0,2,1,0,44215.86,0 -7575,15778345,Stevens,749,France,Female,33,1,74385.98,1,1,0,20164.47,0 -7576,15687634,Glover,561,Germany,Male,49,5,94754,1,1,1,26691.31,0 -7577,15666096,Ibekwe,676,Spain,Male,27,4,0,1,0,1,107955.67,0 -7578,15581700,Paterson,615,Germany,Male,43,3,86920.86,1,1,1,150048.37,0 -7579,15656417,Marsh,582,France,Female,39,1,132077.48,2,1,0,192255.15,0 -7580,15649101,Reeves,601,France,Male,40,10,127847.86,1,0,0,173245.68,0 -7581,15781975,Rees,708,France,Male,34,3,0,1,0,1,121457.88,1 -7582,15700511,Hanson,708,Germany,Male,42,9,176702.36,2,1,1,104804.74,0 -7583,15770255,Onwughara,797,Germany,Female,33,10,83555.58,1,0,0,69767.14,0 -7584,15643574,Odinakachukwu,682,France,Male,26,8,0,2,1,0,178373.43,0 -7585,15595010,Huang,694,Spain,Female,39,9,0,2,0,0,99924.04,0 -7586,15580579,Trevisani,490,France,Female,40,1,0,1,1,1,49594.19,1 -7587,15748532,Dale,828,Spain,Male,42,10,0,1,1,1,186071.14,0 -7588,15773789,Pavlova,594,Spain,Female,38,7,96858.35,1,1,0,77511.45,0 -7589,15600027,Meng,579,Spain,Male,33,1,0,2,1,1,54816.57,0 -7590,15620832,Dean,723,France,Female,35,0,0,2,0,1,61290.99,0 -7591,15568819,Chiganu,619,Germany,Female,42,8,132796.04,3,1,1,191821.35,1 -7592,15748691,Lung,794,Spain,Female,30,1,154970.54,1,0,1,156768.45,0 -7593,15583552,Donaldson,674,Germany,Male,44,3,88902.21,1,1,0,73731.32,0 -7594,15588019,Li Fonti,418,France,Male,28,7,98738.92,1,1,0,122190.22,0 -7595,15713250,Izmailova,502,France,Male,33,8,0,2,1,1,123509.01,0 -7596,15569595,Walker,678,France,Female,50,6,0,1,1,0,8199.5,0 -7597,15794868,Nnonso,599,Germany,Male,40,10,137456.28,2,1,1,14113.11,0 -7598,15576680,Stevenson,736,France,Male,29,4,0,2,0,0,51705.01,0 -7599,15613699,Schnaars,430,France,Female,60,7,73937.02,1,1,0,161937.62,1 -7600,15609758,Geoghegan,537,France,Female,45,7,158621.04,1,1,0,120892.96,1 -7601,15762392,Ilyina,683,Spain,Male,30,1,113257.2,1,1,1,65035.02,0 -7602,15693382,Muir,828,France,Male,31,9,0,1,0,1,164257.37,0 -7603,15791769,Gardener,691,France,Female,29,9,116536.43,1,1,0,51987.99,0 -7604,15712483,Chidi,608,Spain,Female,28,4,0,2,1,0,10899.63,1 -7605,15636454,Fu,691,France,Female,60,6,101070.69,1,1,0,177355.8,1 -7606,15710138,Sun,718,Spain,Male,39,6,0,2,0,1,63889.1,0 -7607,15571571,Ting,680,Germany,Female,31,3,127331.46,3,1,1,176433.6,0 -7608,15638751,Ashton,838,Spain,Female,41,5,0,2,1,0,81313.51,0 -7609,15598574,Uwakwe,695,Spain,Female,31,5,0,2,0,1,13998.88,0 -7610,15796787,Vassiliev,681,France,Male,46,0,105969.42,1,1,0,5771.56,0 -7611,15615670,Kazakova,762,France,Male,36,5,119547.46,1,1,1,42693.65,0 -7612,15705506,Perry,751,Spain,Male,38,7,0,2,0,0,90839.61,0 -7613,15599535,Howell,678,Spain,Male,28,5,138668.18,1,1,1,54144.01,0 -7614,15768449,Ricci,634,France,Female,37,7,51582.5,2,1,1,184312.88,0 -7615,15725002,Smith,749,France,Male,37,7,0,2,1,0,20306.79,0 -7616,15611682,Rossi,590,Spain,Male,37,6,169902.92,1,1,1,128256.18,0 -7617,15749964,Jones,610,France,Female,27,4,87262.4,2,1,0,182720.07,0 -7618,15678779,Quezada,502,France,Male,33,7,0,2,0,1,4082.52,0 -7619,15752601,McCulloch,578,France,Female,40,7,0,2,0,0,102233.73,0 -7620,15758477,Tobeolisa,547,France,Female,32,2,0,2,1,0,132002.83,0 -7621,15629133,Black,579,France,Female,27,9,0,2,1,0,126838.7,0 -7622,15604963,Fraser,661,France,Male,39,5,0,2,0,0,181461.46,0 -7623,15796413,Green,794,France,Male,46,6,0,2,1,0,195325.74,0 -7624,15812470,Allan,719,France,Male,61,5,0,2,0,1,29132.43,0 -7625,15587443,Akudinobi,728,France,Female,69,1,0,2,1,1,131804.86,0 -7626,15689692,Walker,598,Germany,Male,19,3,150348.37,1,1,1,173784.04,0 -7627,15779586,Olisaemeka,822,Germany,Female,46,3,115074.02,2,1,0,26249.86,0 -7628,15667588,Arcuri,670,Spain,Female,40,3,0,1,1,1,182650.15,0 -7629,15624423,Liu,850,France,Male,28,8,99986.98,1,1,0,196582.55,0 -7630,15591107,Flemming,723,Germany,Female,68,3,110357,1,0,0,141977.54,1 -7631,15748986,Bischof,705,Germany,Male,42,8,166685.92,2,1,1,55313.51,0 -7632,15793896,John,677,Spain,Male,40,7,95312.8,1,1,1,62944.75,0 -7633,15620570,Sinnett,736,France,Male,43,4,202443.47,1,1,0,72375.03,0 -7634,15727811,Ts'ui,661,Germany,Female,47,0,109493.62,1,0,0,188324.01,1 -7635,15707681,Pokrovsky,501,Germany,Male,38,9,88977.39,2,0,1,133403.07,0 -7636,15702030,Azarov,516,France,Female,29,2,104982.57,1,1,0,157378.5,0 -7637,15673238,McCarthy,517,Germany,Female,59,8,154110.99,2,1,0,101240.08,1 -7638,15604196,Simpson,766,France,Male,32,6,185714.28,1,1,1,102502.5,0 -7639,15769356,Stevenson,520,Germany,Female,23,3,116022.53,2,1,1,37577.66,0 -7640,15665590,Moore,541,France,Male,46,6,0,2,1,1,83456.67,0 -7641,15572361,Chill,790,Germany,Female,34,2,164011.48,1,1,0,199420.41,0 -7642,15667460,Moore,797,France,Male,31,9,0,2,1,1,24748.89,0 -7643,15654760,Su,811,France,Male,40,1,101514.89,1,1,1,121765,0 -7644,15632669,Rees,722,Spain,Female,32,4,0,2,1,1,113666.48,0 -7645,15613673,Lung,675,France,Male,28,9,0,1,1,0,134110.93,0 -7646,15698522,Thomas,660,Germany,Male,39,9,134599.33,2,1,0,183095.87,0 -7647,15741633,Fuller,566,Spain,Male,32,10,147511.26,1,1,1,159891.03,0 -7648,15674583,Trevisani,768,France,Male,25,0,78396.08,1,1,1,8316.19,0 -7649,15665374,Dumolo,610,Spain,Female,31,5,0,2,0,0,63736.36,0 -7650,15588854,Wu,715,France,Female,31,3,110581.29,1,1,1,94715.24,0 -7651,15810716,Kerr,750,Germany,Male,42,8,151836.36,2,1,0,68695.38,0 -7652,15776921,Geoghegan,431,Germany,Male,45,5,83624.55,2,0,0,36899.62,0 -7653,15569394,Bailey,704,France,Male,24,2,148197.15,2,1,0,182775.08,0 -7654,15788215,Hsia,535,Spain,Female,30,5,122924.75,1,0,0,62390.59,1 -7655,15641007,Holden,614,France,Female,38,4,72594,1,1,1,76042.48,0 -7656,15594651,Milani,748,France,Male,38,4,115221.36,1,0,1,70956.75,0 -7657,15575146,Jamieson,492,Germany,Male,51,8,117808.74,2,1,1,67311.12,0 -7658,15608916,Ndubueze,573,France,Male,40,7,147754.68,1,1,1,110454.46,0 -7659,15666297,Abramova,706,Spain,Female,53,3,0,3,0,0,88479.02,1 -7660,15598586,Wetherspoon,680,France,Male,31,10,113292.17,1,1,1,122639.73,0 -7661,15665014,Middleton,458,Spain,Male,36,5,0,2,1,0,79723.78,0 -7662,15701738,Arcuri,612,Germany,Male,44,2,115163.38,1,1,1,97677.52,1 -7663,15650591,Calabrese,809,Germany,Male,50,10,118098.62,1,1,1,100720.02,1 -7664,15652667,Hampton,590,France,Male,39,9,0,2,1,1,104730.52,0 -7665,15679622,Clayton,602,France,Male,35,8,0,1,1,1,22499.29,0 -7666,15730150,Otutodilichukwu,540,Spain,Male,37,0,120825.7,1,1,0,28257.89,0 -7667,15813192,Chukwuemeka,494,France,Male,25,6,0,2,0,1,109988.09,0 -7668,15606554,Douglas,797,France,Male,29,1,0,1,0,1,149991.32,0 -7669,15611794,Galloway,526,Germany,Male,61,6,133845.28,2,1,1,45180.8,0 -7670,15672357,Sochima,631,Spain,Male,38,7,0,2,1,0,181605.85,0 -7671,15711759,Wilkins,576,France,Female,29,5,108541.04,1,1,1,126469.09,0 -7672,15615296,Rice,405,France,Male,39,10,0,1,1,0,160810.85,1 -7673,15699294,Pope,555,France,Male,30,1,0,2,0,0,88146.86,0 -7674,15788634,Romani,750,Spain,Female,37,2,113817.06,1,0,0,88333.74,0 -7675,15660871,Ch'ang,665,France,Male,28,8,137300.23,1,1,0,90174.83,0 -7676,15618258,Chizuoke,640,Spain,Male,37,5,158024.38,1,1,0,81298.09,0 -7677,15722535,Ireland,457,France,Female,33,7,127837.54,1,0,1,60013.17,0 -7678,15711977,Finch,695,France,Male,36,4,161533,1,1,0,100940.91,0 -7679,15690169,Meng,645,France,Male,31,7,161171.7,2,1,0,12599.94,1 -7680,15790689,Hibbins,647,Spain,Male,32,9,80958.36,1,1,1,128590.73,0 -7681,15665181,Chung,808,Spain,Male,25,7,0,2,0,1,23180.37,0 -7682,15633608,Black,641,France,Male,33,2,146193.6,2,1,1,55796.83,1 -7683,15805261,Balashov,700,Spain,Male,29,8,0,2,0,1,152097.02,0 -7684,15740356,Palmer,660,Germany,Male,26,4,115021.76,1,0,1,162443.05,0 -7685,15808223,Lea,615,Spain,Male,41,1,126773.43,1,1,1,55551.26,0 -7686,15769980,Singleton,705,Germany,Female,40,3,92889.91,1,1,1,109496.69,0 -7687,15675450,Burt,718,France,Male,48,9,0,2,1,1,72105.63,0 -7688,15776494,Siciliano,754,France,Male,61,5,146622.35,1,1,1,41815.22,1 -7689,15592412,Sun,713,Germany,Male,45,4,131038.14,1,1,0,74005.04,1 -7690,15777452,Sauve,587,France,Female,46,6,88820.29,1,0,0,70224.34,0 -7691,15692258,Thompson,569,Spain,Male,31,1,115406.97,1,0,0,145528.22,0 -7692,15791045,Boni,568,France,Female,38,3,132951.92,1,0,1,124486.28,0 -7693,15807889,Wood,634,Germany,Male,74,5,108891.7,1,1,0,10078.02,0 -7694,15602043,Buccho,770,Germany,Female,46,5,141788.63,2,0,0,164967.21,0 -7695,15807335,Spencer,676,Spain,Female,64,4,116954.32,1,1,1,91149.48,0 -7696,15629985,Eidson,723,Germany,Female,47,10,90450,2,0,0,103379.31,1 -7697,15679453,Hung,614,Germany,Female,39,8,125997.22,1,1,1,128049.34,1 -7698,15637315,Melvin,601,Spain,Female,41,3,0,2,1,0,54342.83,0 -7699,15691513,Dawkins,592,France,Male,60,9,0,4,1,1,13614.01,1 -7700,15622289,Rizzo,605,Spain,Female,36,9,0,2,0,1,35521.63,0 -7701,15715184,Capon,752,Spain,Female,31,4,144637.86,2,1,0,40496.72,0 -7702,15702801,Ts'ao,677,France,Female,29,3,86616.35,1,0,0,91903.9,1 -7703,15719931,Johnstone,850,France,Male,31,8,0,2,1,0,178667.7,0 -7704,15806081,Fleming,608,Germany,Female,48,2,127924.25,2,1,0,32202.61,0 -7705,15796336,Chang,786,Spain,Female,34,9,0,2,1,0,117034.32,0 -7706,15647306,Gibbs,777,France,Female,29,9,131240.61,1,1,1,163746.09,1 -7707,15742369,Rita,667,Spain,Male,31,5,0,2,1,1,20346.69,0 -7708,15655859,Munro,848,Spain,Male,35,5,120046.74,2,1,0,84710.65,0 -7709,15675650,Duncan,486,France,Female,39,8,97819.36,1,0,1,120531.31,0 -7710,15574119,Okwuadigbo,598,Spain,Female,64,1,62979.93,1,1,1,152273.57,0 -7711,15754168,McIntosh,506,France,Female,40,3,0,1,1,1,144345.58,0 -7712,15763029,Ch'iu,612,Germany,Male,46,9,161450.03,1,1,1,96961,1 -7713,15765048,Watt,545,France,Male,30,3,0,2,1,0,170307.43,0 -7714,15786215,Udinese,793,France,Male,56,8,119496.25,2,1,0,29880.99,0 -7715,15707559,Clark,682,France,Female,30,9,0,2,1,1,195104.91,0 -7716,15582129,Hsia,517,France,Male,62,1,43772.66,3,1,0,187756.24,1 -7717,15687540,Obiuto,684,France,Male,32,9,100249.41,2,0,1,67599.69,0 -7718,15787196,T'ien,692,Spain,Male,46,2,0,2,1,1,105983.09,0 -7719,15670898,McKenzie,740,France,Female,60,5,108028.08,2,0,0,25980.42,1 -7720,15775433,Tang,666,Germany,Male,71,1,53013.29,2,1,1,112222.64,0 -7721,15700693,Tu,693,France,Male,68,2,0,2,1,1,59864.96,0 -7722,15677955,Tsui,757,Germany,Male,33,1,122088.67,1,1,0,42581.09,0 -7723,15570086,Lynch,684,Germany,Male,18,9,90544,1,0,1,4777.23,0 -7724,15794875,Hung,691,Spain,Male,35,6,0,2,0,1,178038.17,0 -7725,15673591,Oluchukwu,842,France,Male,44,3,141252.18,4,0,1,128521.16,1 -7726,15631756,Tuan,482,France,Female,35,5,147813.05,2,0,0,109029.72,0 -7727,15757617,Lewis,735,France,Male,55,6,134140.68,1,1,0,2267.88,0 -7728,15612729,Chidiebere,681,France,Female,63,7,0,2,1,1,55054.48,0 -7729,15637857,Woolacott,616,France,Female,31,8,0,1,0,1,76456.17,0 -7730,15681007,Yen,850,France,Female,35,2,128548.49,4,1,0,75478.95,1 -7731,15593622,Service,635,France,Male,43,10,122198.21,2,0,1,179144.54,0 -7732,15629273,Lin,638,Germany,Male,42,8,145177.84,1,1,0,193471.74,1 -7733,15765846,Chuang,820,Spain,Female,31,2,94222.53,1,1,0,103570.8,0 -7734,15596013,Akhtar,694,Germany,Female,58,1,143212.22,1,0,0,102628.56,1 -7735,15722473,Faulkner,713,France,Male,41,3,0,2,1,0,55772.04,0 -7736,15774936,Liang,543,Germany,Male,41,6,143350.41,1,1,1,192070.16,1 -7737,15685640,Dancy,649,France,Female,41,3,130931.83,1,1,1,144808.37,0 -7738,15566563,Duigan,777,France,Female,30,4,137851.31,1,1,0,5008.23,1 -7739,15768746,McLean,561,France,Male,33,6,0,2,0,0,173680.39,0 -7740,15689952,Zuyeva,724,Spain,Male,41,5,0,1,0,1,115753.94,0 -7741,15725906,Hankinson,665,Spain,Female,51,8,0,1,1,1,38928.48,1 -7742,15634501,Wei,441,France,Male,60,1,140614.15,1,0,1,174381.23,0 -7743,15571940,Afamefula,579,Spain,Male,22,3,118680.57,1,1,1,49829.8,0 -7744,15741643,Chiang,777,Germany,Male,35,7,122917.69,1,1,1,76169.68,0 -7745,15806822,Myers,739,France,Female,36,0,0,2,0,0,133465.57,0 -7746,15701166,Chinedum,660,France,Male,40,5,131754.11,2,1,1,38761.61,0 -7747,15718531,Ukaegbunam,554,France,Female,35,8,0,2,1,1,176779.46,0 -7748,15628308,Akubundu,850,France,Female,24,6,0,2,1,1,13159.9,0 -7749,15585287,Sal,842,Germany,Female,35,9,119948.09,1,1,0,48217.97,1 -7750,15781619,Stevenson,785,France,Female,38,1,0,1,1,0,134964.85,1 -7751,15805162,Sutherland,550,France,Male,25,0,0,2,1,1,184221.11,0 -7752,15588535,Ts'ao,750,Spain,Female,39,6,0,2,0,0,19264.33,0 -7753,15775307,Sung,490,Spain,Female,38,3,97266.1,1,1,1,92797.23,0 -7754,15777616,Pisani,605,Germany,Male,28,10,113690.83,1,1,0,33114.24,0 -7755,15692291,Hs?eh,563,Spain,Female,42,6,99056.22,2,1,0,154347.95,1 -7756,15680843,Sherrod,675,France,Male,34,8,0,2,1,1,184842.21,0 -7757,15606232,Holloway,621,Spain,Female,36,7,116338.68,1,1,1,155743.48,0 -7758,15641585,Newton,850,France,Male,40,6,97339.99,1,0,1,88815.25,0 -7759,15684358,Kang,711,France,Male,41,3,0,2,1,1,193747.57,0 -7760,15806389,Walton,549,Germany,Female,55,1,137592.31,2,0,1,116548.02,1 -7761,15641860,Bradley,764,Germany,Male,34,6,108760.27,2,1,0,166324.79,1 -7762,15814237,Watkins,627,Germany,Male,30,3,128770.88,2,1,1,40199.01,0 -7763,15808780,Tien,850,France,Female,34,2,0,2,0,0,51919.04,0 -7764,15767064,Davide,614,Spain,Female,36,1,44054.84,1,1,1,73329.08,0 -7765,15751177,Milne,685,Germany,Female,44,2,119657.53,1,1,0,145387.05,1 -7766,15613427,Barling,683,Germany,Female,49,7,108797.63,2,0,0,140763.18,0 -7767,15647259,Barnett,643,Spain,Male,35,2,0,2,0,0,67979.35,0 -7768,15748660,Ellis,561,Germany,Female,49,1,102025.32,1,1,0,133051.64,1 -7769,15726695,Hsia,601,Spain,Female,20,9,122446.61,2,1,0,86791.9,0 -7770,15757473,Chukwujamuike,766,France,Female,27,7,158786.67,2,0,1,47579.25,0 -7771,15809509,Venables,699,France,Male,29,3,125689.29,1,1,1,151623.71,0 -7772,15715512,Hsia,850,Germany,Male,29,1,154640.41,1,1,1,164039.51,0 -7773,15614168,Alexander,792,Germany,Female,50,4,146710.76,1,1,0,16528.4,1 -7774,15679818,Yuan,636,Germany,Male,67,7,136709.35,1,0,1,66753.1,1 -7775,15609928,Johnston,850,Germany,Male,43,5,129305.09,2,0,1,19244.58,0 -7776,15731246,Hobler,628,Spain,Male,40,10,0,2,1,0,103832.58,0 -7777,15685243,Jamieson,736,France,Female,63,10,0,2,0,1,502.7,0 -7778,15638730,Macleod,711,France,Female,21,0,82844.33,2,0,1,1408.68,0 -7779,15697034,Norris,583,Spain,Female,22,2,0,2,0,1,5985.36,0 -7780,15699225,Pirozzi,757,France,Male,46,0,0,2,1,0,37460.05,0 -7781,15677387,Folliero,749,Germany,Female,33,10,76692.22,1,0,1,30396.43,0 -7782,15759184,Russell,705,France,Male,34,7,117715.84,1,1,0,2498.67,0 -7783,15595991,Hsiung,585,France,Male,54,8,87105.32,1,1,1,55346.14,0 -7784,15681332,Tate,437,France,Female,43,6,0,1,1,0,148330.97,1 -7785,15756299,Davis,741,France,Female,64,2,69311.16,1,1,1,59237.72,0 -7786,15750547,Bair,738,France,Male,26,9,0,2,1,1,48644.94,0 -7787,15566380,Drury,586,Spain,Female,33,10,66948.67,2,1,1,140759.03,0 -7788,15675963,Padovano,627,France,Female,57,9,0,2,1,1,107712.42,0 -7789,15674671,Conway,551,Spain,Male,76,2,128410.71,2,1,1,181718.73,0 -7790,15621466,Waters,606,Germany,Male,38,3,99897.53,1,0,0,37054.65,0 -7791,15607176,Kang,674,France,Male,22,3,0,1,1,1,173940.59,0 -7792,15570299,Martin,584,Germany,Female,31,6,152622.34,1,1,0,99298.8,0 -7793,15613197,Ugochukwutubelum,590,France,Male,40,8,0,2,1,0,62933.03,0 -7794,15798885,Burns,585,France,Male,56,4,138227.19,2,1,1,55287.84,0 -7795,15714883,Genovese,508,France,Female,25,2,111395.53,1,0,1,48197.06,0 -7796,15604497,Beale,458,Germany,Male,44,7,84386.57,1,1,0,178642.73,0 -7797,15773949,Cherkasova,692,France,Female,36,3,0,2,1,1,8282.22,0 -7798,15774164,Coles,502,Germany,Male,33,5,174673.65,2,1,0,33300.56,0 -7799,15774127,Potter,518,France,Male,46,3,0,2,1,0,76515.79,0 -7800,15619016,McMinn,660,Germany,Male,46,5,109019.65,2,1,1,33680.56,0 -7801,15795759,Bergamaschi,698,Germany,Female,52,1,107906.75,1,1,0,168886.39,1 -7802,15798844,Chijindum,678,France,Male,54,7,128914.97,1,0,0,191746.23,1 -7803,15717962,Ch'iu,773,Spain,Male,63,9,111179.83,1,1,1,93091.02,0 -7804,15691504,Yusupova,619,Germany,Female,52,8,124099.13,1,0,0,23904.52,0 -7805,15693893,Davis,684,Germany,Male,59,9,122471.09,1,0,1,15807.07,0 -7806,15672499,Iadanza,635,France,Male,34,3,134692.4,2,1,1,83773.02,0 -7807,15750410,Jordan,680,France,Female,25,4,123816.5,1,1,1,90162.35,0 -7808,15568904,Kruglova,608,Germany,Male,34,3,106288.54,1,1,1,36639.25,0 -7809,15649033,Echezonachukwu,603,Germany,Female,55,7,127723.25,2,1,0,139469.11,1 -7810,15780989,Hajek,579,Spain,Male,43,2,145843.82,1,1,1,198402.37,1 -7811,15771059,Welch,756,Germany,Female,34,2,148200.72,1,0,0,194584.48,0 -7812,15687852,Vinogradoff,611,France,Male,30,2,104145.65,1,0,0,159629.64,0 -7813,15695280,Hung,532,Germany,Male,24,8,142755.25,1,0,0,34231.48,0 -7814,15592751,Okwudiliolisa,684,Germany,Female,63,3,81245.79,1,1,0,69643.31,1 -7815,15598338,Mays,647,Germany,Female,33,3,168560.46,2,0,0,90270.16,0 -7816,15735784,Gardner,583,France,Male,38,8,0,1,1,0,47848.56,0 -7817,15629128,Mamelu,774,Germany,Male,42,2,132193.94,2,1,1,162865.52,0 -7818,15642870,Ross,677,France,Male,58,9,0,1,0,1,168650.4,0 -7819,15637977,Barese,542,Germany,Male,25,8,139330.1,1,0,0,54372.37,0 -7820,15600792,Swayne,613,Spain,Male,29,0,0,2,0,1,133897.32,0 -7821,15576131,Phillips,666,France,Male,40,5,0,2,1,0,147878.05,0 -7822,15686588,Manfrin,777,France,Female,28,2,134571.5,1,0,1,118313.38,0 -7823,15761018,Tan,581,Germany,Male,50,2,143829.2,2,1,0,181224.24,1 -7824,15616029,Adams,705,France,Male,32,7,0,2,1,0,7921.57,0 -7825,15761149,Teng,673,France,Female,44,8,133444.97,1,0,1,5708.19,0 -7826,15802758,Chinwendu,594,Germany,Female,23,4,104753.84,2,1,0,56756.52,1 -7827,15647838,Davison,648,Germany,Female,51,2,116574.84,1,1,0,4121.04,1 -7828,15735968,Hsing,605,France,Male,41,10,0,2,0,1,97213.09,0 -7829,15581286,Castro,734,France,Female,40,9,176914.8,1,1,1,12799.23,0 -7830,15625445,Parkin,572,France,Female,36,8,68348.18,2,0,1,50400.32,0 -7831,15600173,Manna,595,France,Female,33,9,0,2,1,1,41447.86,0 -7832,15635143,Fennescey,749,France,Male,42,2,56726.83,2,0,1,185543.35,0 -7833,15664849,Colon,573,Spain,Male,46,3,65269.23,1,0,1,189988.65,1 -7834,15762455,Yeh,624,Spain,Male,33,6,66220.17,1,0,1,170819.01,0 -7835,15797165,Bergamaschi,703,France,Male,56,9,0,1,0,0,85547.33,1 -7836,15788189,Matveyeva,665,France,Female,41,8,96147.55,1,1,0,137037.97,0 -7837,15780492,Ignatyeva,648,France,Male,42,4,0,2,1,0,19283.14,0 -7838,15678497,Lederer,850,Spain,Male,48,2,0,1,1,0,169425.3,1 -7839,15588560,Nwabugwu,569,Germany,Female,32,8,145330.43,1,1,1,132038.65,0 -7840,15606003,Abramowitz,566,France,Female,21,3,0,2,1,1,3626.47,0 -7841,15611756,Chapman,537,Germany,Female,47,4,124192.28,2,1,1,50881.51,0 -7842,15789563,Fiorentino,706,Germany,Female,46,7,111288.18,1,1,1,149170.25,1 -7843,15702416,Cecil,734,France,Male,43,7,107805.67,1,0,0,182505.68,0 -7844,15766288,Ikechukwu,586,Germany,Female,36,5,103700.69,1,1,0,194072.56,1 -7845,15667633,Allen,612,France,Female,38,1,0,2,1,1,9209.21,0 -7846,15622774,Kao,648,France,Male,34,0,0,1,1,1,167931.81,0 -7847,15755416,Hart,557,France,Female,27,3,87739.08,1,1,1,123096.56,0 -7848,15769915,Charlton,643,Spain,Female,20,0,133313.34,1,1,1,3965.69,0 -7849,15643908,Turnbull,433,France,Female,49,10,0,1,1,1,87711.61,0 -7850,15627395,Manners,643,Germany,Male,41,7,154902.66,1,1,1,49667.28,0 -7851,15679663,Chiazagomekpere,488,France,Female,36,0,0,2,1,0,136675.22,0 -7852,15651581,Lavrentyev,758,Germany,Male,68,6,112595.85,1,1,0,35865.44,1 -7853,15596379,Wallace,743,Germany,Male,39,3,119695.75,1,0,1,26136.13,0 -7854,15746674,Miller,730,France,Female,47,7,0,1,1,0,33373.26,1 -7855,15801256,Bazhenov,746,Spain,Male,49,7,0,2,0,1,10096.25,0 -7856,15663808,Ifesinachi,666,Germany,Female,59,8,152614.51,2,1,1,188782.3,0 -7857,15598521,Ma,580,Germany,Female,33,7,131647.01,2,0,0,79775.19,0 -7858,15621457,Chu,850,France,Male,27,6,96654.72,2,0,0,152740.16,0 -7859,15764726,Kerr,563,France,Male,22,3,137583.04,1,0,1,5791.85,0 -7860,15646374,Wynne,766,Germany,Female,28,3,62717.84,2,1,1,13182.43,0 -7861,15716501,Moon,659,France,Male,32,9,95377.13,1,0,1,187551.24,0 -7862,15589948,Disher,607,Spain,Male,28,1,135936.1,2,1,1,110560.14,0 -7863,15811343,Cattaneo,644,Germany,Male,35,5,161591.11,3,1,1,63795.62,0 -7864,15659677,Beluchi,746,France,Male,47,8,142382.03,1,1,1,62086.62,0 -7865,15594436,Mazzi,588,Spain,Male,33,2,0,2,1,1,12483.56,0 -7866,15748995,Ifeajuna,691,Spain,Male,30,9,0,2,0,1,10963.04,0 -7867,15677062,Howe,666,France,Female,38,6,127043.09,1,1,1,8247,0 -7868,15697201,Yocum,640,Spain,Female,46,3,0,1,1,1,156260.08,0 -7869,15666453,Moore,611,Germany,Female,29,4,78885.88,2,1,1,26927.69,0 -7870,15693771,Y?an,651,Spain,Female,45,8,95922.9,1,1,0,84782.42,1 -7871,15569867,Chinweuba,529,France,Female,29,8,0,2,1,0,19842.11,0 -7872,15711602,Lowrie,676,France,Female,36,3,91711.59,1,1,1,95393.43,0 -7873,15717736,Shen,639,Germany,Female,46,10,110031.09,2,1,1,133995.59,0 -7874,15750441,Lavarack,782,France,Male,36,5,81210.72,2,0,1,108003.38,0 -7875,15732791,Davide,641,Germany,Male,32,5,122947.92,1,1,1,99154.86,0 -7876,15775104,Gomes,697,France,Female,38,1,182065.85,1,1,0,49503.5,0 -7877,15757607,Matveyeva,623,France,Male,45,0,0,1,1,0,196533.72,1 -7878,15793070,Fiorentino,494,Spain,Female,41,2,69974.66,2,1,0,188426.13,1 -7879,15760456,Eberechukwu,731,France,Female,38,10,123711.73,2,1,0,171340.68,1 -7880,15665385,Gibney,657,France,Male,44,6,76495.04,1,1,0,79071.89,0 -7881,15612418,Virgo,744,France,Female,38,9,0,2,0,0,20940.76,0 -7882,15727138,Kulikova,774,Spain,Male,46,9,0,2,1,1,34774.26,0 -7883,15732061,Liu,850,Germany,Female,45,1,121874.89,1,0,0,6865.41,1 -7884,15776051,Kao,551,France,Female,45,6,0,2,1,1,51143.43,0 -7885,15616530,Foran,638,France,Male,36,6,188455.19,1,0,0,47031.4,1 -7886,15632344,Jones,792,France,Female,42,0,99045.93,2,1,0,47160.01,0 -7887,15744979,Fowler,666,France,Female,36,8,0,1,0,1,158666.99,0 -7888,15745433,Conti,716,Germany,Female,30,2,205770.78,2,0,0,65464.66,0 -7889,15683657,Stephenson,594,France,Female,31,0,79340.95,1,1,0,78255.86,0 -7890,15718572,Willis,600,Germany,Male,57,9,138456.03,2,1,1,103548.25,0 -7891,15665783,Ts'ui,565,France,Male,49,7,0,2,1,1,89609.26,0 -7892,15652782,Chibuzo,678,Germany,Male,48,2,101099.9,2,0,1,193476.04,0 -7893,15707025,Fang,648,Spain,Female,31,5,0,2,1,1,5199.02,0 -7894,15647807,Wyckoff,642,France,Male,40,8,109219.83,1,1,0,52827.51,0 -7895,15718281,Muir,706,Germany,Male,67,1,123276.69,2,1,1,86507.88,1 -7896,15660571,Halpern,668,Spain,Male,43,10,113034.31,1,1,1,100423.88,0 -7897,15727857,Flynn,635,Spain,Male,41,1,0,2,1,0,175611.5,0 -7898,15639252,Shao,603,Spain,Male,30,6,129548.5,2,1,1,19282.85,0 -7899,15628144,Soares,635,France,Female,72,4,74812.84,1,0,1,27448.33,0 -7900,15683560,Gallo,642,France,Female,40,7,0,2,1,0,183963.34,0 -7901,15653275,Lei,785,Spain,Female,54,1,0,2,1,0,45113.92,1 -7902,15622182,Daniels,628,Germany,Female,28,3,153538.13,2,1,0,110776.01,0 -7903,15613962,Kenechi,499,France,Female,38,9,0,2,0,1,183042.2,0 -7904,15618437,Singleton,567,Spain,Male,34,10,0,2,0,1,161571.79,0 -7905,15783338,Williams,449,Spain,Male,32,0,155619.36,1,1,1,166692.03,0 -7906,15764491,Greece,701,Spain,Male,35,10,159693.9,2,1,1,71173.64,0 -7907,15712960,Olisanugo,613,Spain,Male,37,3,171653.17,1,0,1,5353.12,0 -7908,15688157,Padovano,683,Germany,Female,39,2,47685.47,2,1,1,86019.48,0 -7909,15579287,Rossi,581,France,Male,35,4,0,2,0,1,86383.82,0 -7910,15570931,Grant,620,France,Male,61,5,0,1,0,0,31641.52,1 -7911,15615177,Ebelegbulam,561,Spain,Male,28,6,123692,1,1,1,70548.96,0 -7912,15809906,Mitchell,558,Germany,Male,26,1,148853.29,2,1,1,24411.02,0 -7913,15652169,Buckley,642,France,Male,35,2,133161.95,1,0,1,122254.86,0 -7914,15649450,Repina,805,Germany,Male,24,6,143221.35,2,1,0,186035.72,0 -7915,15777179,Ellis,687,France,Male,35,9,0,2,0,1,73133.82,0 -7916,15803538,Douglas,695,Spain,Male,56,1,0,3,1,0,187734.49,1 -7917,15610936,Becher,562,France,Male,33,6,0,2,1,0,111590.35,0 -7918,15590094,Nwachukwu,613,Germany,Male,38,9,126265.88,2,0,0,15859.95,0 -7919,15572706,Smith,589,France,Male,37,5,0,1,1,0,61324.87,0 -7920,15634564,Aksyonov,593,Spain,Male,31,8,112713.34,1,1,1,176868.89,0 -7921,15684296,Artyomova,714,France,Male,34,5,141173.03,1,0,1,98896.06,0 -7922,15702293,Medvedeva,588,Spain,Female,35,7,0,2,1,1,108739.15,0 -7923,15642099,Tsui,679,Spain,Male,39,6,0,2,1,0,12266.06,0 -7924,15773273,Runyon,730,Spain,Male,38,5,118866.36,1,1,1,163317.5,0 -7925,15613337,Gallo,833,France,Male,47,2,0,2,1,1,182247.77,0 -7926,15800482,Bradshaw,586,Spain,Female,33,7,0,2,1,1,168261.4,0 -7927,15732644,Evans,567,Spain,Female,54,5,92316.31,2,1,0,158590.66,1 -7928,15713426,Hancock,637,Germany,Male,30,1,122185.53,1,1,0,102566.46,1 -7929,15640789,Butler,711,France,Male,38,4,123345.85,1,1,0,141827.83,0 -7930,15598892,Bradshaw,828,France,Male,30,4,73070.18,2,0,0,161671.15,0 -7931,15606436,Bergamaschi,500,Spain,Male,38,7,0,2,0,0,192013.23,0 -7932,15751227,Ebelegbulam,807,France,Male,47,1,95120.59,1,0,0,127875.1,0 -7933,15812365,Greco,850,France,Male,40,8,102800.65,1,1,0,60811.56,0 -7934,15616088,Lucas,782,France,Female,70,7,97072.42,1,0,1,131177.22,0 -7935,15803886,Barber,629,Spain,Male,31,6,132876.55,1,1,1,130862.11,0 -7936,15587311,Dobbs,582,Spain,Male,33,6,0,2,0,1,72970.93,0 -7937,15617401,Thomson,468,France,Male,22,2,0,2,1,0,28123.99,0 -7938,15775886,Su,670,France,Male,36,3,0,1,1,0,140754.19,1 -7939,15807305,Watkins,805,France,Male,39,2,0,1,0,0,166650.32,0 -7940,15761717,Ch'ien,720,France,Male,26,10,51962.91,2,1,0,45507.24,0 -7941,15628008,Monds,781,Spain,Female,29,6,98759.89,1,0,0,112202.64,0 -7942,15583755,McClemans,592,Germany,Male,33,2,156570.86,1,1,1,37140.2,0 -7943,15661409,Shen,542,France,Female,42,1,0,1,1,1,178256.58,1 -7944,15774250,Gallo,532,France,Male,42,1,159024.71,1,1,0,100982.93,1 -7945,15681476,Foveaux,520,France,Female,39,1,73493.17,1,0,1,109626.13,1 -7946,15654870,Longo,759,France,Female,45,8,0,2,1,1,99251.24,0 -7947,15790448,Calabresi,473,France,Female,35,6,69617.36,1,1,0,143345.69,0 -7948,15785326,Randall,639,Spain,Female,35,5,136526.26,2,1,0,59653.03,0 -7949,15592854,Garcia,705,France,Male,25,3,113736.27,1,0,1,196864.61,0 -7950,15617486,Sullivan,530,France,Male,52,1,106723.28,1,0,0,109960.4,1 -7951,15806796,Higgins,516,Germany,Female,33,10,138847.9,1,1,1,127256.7,0 -7952,15644699,Crawford,850,France,Female,40,0,0,2,1,0,1099.95,0 -7953,15622305,Martin,746,Germany,Female,33,2,107868.14,2,1,1,146192.4,0 -7954,15608209,Currey,622,Germany,Male,33,3,96926.12,2,1,0,48553.77,0 -7955,15626898,Teng,743,France,Male,30,7,77599.23,1,0,0,144407.1,0 -7956,15644297,Austin,732,Germany,Male,38,5,178787.54,1,1,1,195760.53,0 -7957,15731569,Hudson,850,France,Male,81,5,0,2,1,1,44827.47,0 -7958,15582149,Ts'ui,850,Germany,Female,34,3,129668.43,2,1,1,88743.99,0 -7959,15802483,Hancock,686,France,Male,34,6,146178.13,2,1,1,88837.11,0 -7960,15686999,Nicholas,556,France,Female,40,8,0,2,1,0,62112.7,0 -7961,15772479,Napolitano,673,France,Male,37,4,0,2,0,0,163563.07,0 -7962,15778884,Jamieson,809,France,Female,38,2,154763.21,2,1,1,174800.31,0 -7963,15623630,Foster,634,Germany,Female,56,3,116251.24,1,0,1,42429.88,1 -7964,15774316,Moretti,630,France,Male,37,6,0,2,1,1,82647.65,0 -7965,15695097,Chiedozie,564,Germany,Female,30,0,100954.88,2,0,0,134175.15,0 -7966,15645404,Okwukwe,625,France,Female,51,4,124620.01,2,1,0,92243.94,1 -7967,15750574,Lumholtz,677,Spain,Female,34,4,0,2,1,1,6175.53,0 -7968,15636812,Rose,583,France,Male,40,9,112701.04,1,0,0,29213.63,0 -7969,15712068,Wan,592,Spain,Male,45,8,84692.5,1,0,1,67214.02,0 -7970,15652030,De Bernales,637,Germany,Male,49,2,108204.52,1,1,0,169037.84,1 -7971,15577398,Ch'eng,850,France,Male,30,6,86449.39,1,1,1,188809.23,0 -7972,15756848,Edmondson,633,Spain,Male,42,10,0,1,0,1,79408.17,0 -7973,15806929,Ch'ien,751,Germany,Male,36,5,73194.99,1,1,1,89222.66,0 -7974,15656005,Millar,592,Germany,Male,31,7,124593.23,1,1,0,86079.67,0 -7975,15722632,Dickson,716,Germany,Male,50,2,119655.77,1,1,1,12944.17,1 -7976,15794356,Toscani,641,Germany,Male,42,3,121765.37,2,1,1,166516.84,0 -7977,15659656,Pan,849,France,Male,35,4,110837.73,1,0,0,126419.8,0 -7978,15588341,Chigozie,647,Spain,Male,47,10,99835.17,1,0,1,89103.05,0 -7979,15709142,Sagese,608,Germany,Female,30,2,91057.37,2,1,0,132973.17,0 -7980,15627042,Reilly,555,France,Female,26,7,0,2,1,0,93122.41,0 -7981,15627517,Taylor,497,Spain,Male,27,7,149400.27,1,0,0,167522.19,0 -7982,15803032,Yen,599,Germany,Male,38,9,89111.63,1,0,0,157239.6,0 -7983,15665129,Kapustin,545,Germany,Male,33,1,132527.9,2,0,1,107429.71,0 -7984,15628272,Singh,774,France,Female,36,9,114997.42,1,1,0,75304.09,0 -7985,15678206,Yeh,464,France,Male,46,6,161798.53,1,1,0,182944.47,0 -7986,15678427,Genovese,696,Germany,Female,27,2,96129.32,2,1,1,5983.7,0 -7987,15678067,Boyle,667,Spain,Male,45,3,0,2,0,0,163655.01,0 -7988,15793331,Blair,812,France,Male,32,5,133050.97,2,1,0,89385.92,0 -7989,15699532,Okagbue,516,France,Male,51,8,120124.35,2,0,1,168773.54,0 -7990,15605827,Khan,645,France,Male,39,8,0,2,0,0,96864.36,0 -7991,15643635,Robertson,664,Spain,Male,32,5,133705.74,1,0,0,134455.84,0 -7992,15787710,Tikhonov,427,Spain,Female,39,9,0,2,1,0,28368.37,0 -7993,15614137,MacDonald,685,France,Female,40,7,0,2,1,0,103898.59,0 -7994,15754494,Ah Mouy,585,France,Female,33,4,152805.05,1,1,0,63239.65,0 -7995,15713440,Barese,519,Germany,Female,21,1,151701.45,3,1,1,170138.68,1 -7996,15803479,Winter-Irving,708,France,Female,67,1,0,2,0,1,3837.08,0 -7997,15709639,Wilson,717,France,Female,22,5,112465.06,1,1,1,92977.75,0 -7998,15601719,Fiorentino,465,Germany,Male,24,6,156007.09,1,1,0,191368.37,0 -7999,15772482,Iloerika,829,Germany,Male,28,3,132405.52,3,1,0,104889.2,1 -8000,15591489,Davison,826,France,Male,26,5,142662.68,1,0,0,60285.3,0 -8001,15629002,Hamilton,747,Germany,Male,36,8,102603.3,2,1,1,180693.61,0 -8002,15798053,Nnachetam,707,Spain,Male,32,9,0,2,1,0,126475.79,0 -8003,15753895,Blue,590,Spain,Male,37,1,0,2,0,0,133535.99,0 -8004,15595426,Madukwe,603,Spain,Male,57,6,105000.85,2,1,1,87412.24,1 -8005,15645815,Mills,615,France,Male,45,5,0,2,1,1,164886.64,0 -8006,15632848,Ferrari,634,France,Female,36,1,69518.95,1,1,0,116238.39,0 -8007,15703068,Nixon,716,Germany,Male,41,8,126145.54,2,1,1,138051.19,0 -8008,15791513,Manfrin,647,France,Male,41,4,138937.35,1,1,1,101617.64,1 -8009,15587210,McCartney,591,Germany,Female,44,10,113581.98,1,1,0,1985.41,0 -8010,15793803,Robinson,574,France,Male,34,1,112572.39,1,0,0,165626.6,0 -8011,15787756,Nkemdirim,467,Germany,Male,51,10,114514.71,2,1,0,177784.68,1 -8012,15723437,Sal,701,France,Female,35,2,0,2,1,1,65765.22,0 -8013,15702715,Kao,747,France,Female,34,10,0,2,1,1,50759.8,0 -8014,15809872,Ikechukwu,650,France,Male,32,2,84906.45,1,1,0,163216.48,0 -8015,15644295,Hargreaves,731,Spain,Female,39,2,126816.18,1,1,1,74850.93,0 -8016,15778694,Sievier,638,Germany,Female,26,1,105249.76,2,1,1,23491.09,0 -8017,15759555,Murphy,569,Spain,Male,41,2,0,2,1,0,134272.57,0 -8018,15631406,Munro,459,Germany,Male,50,5,109387.9,1,1,0,155721.15,0 -8019,15616676,Donnelly,632,Germany,Male,23,3,122478.51,1,1,0,147230.77,1 -8020,15771154,North,683,France,Female,73,8,137732.23,2,1,1,133210.44,0 -8021,15669491,Cruz,850,France,Female,46,2,157866.77,1,1,1,18986.12,0 -8022,15697691,Sinclair,512,France,Female,41,6,0,1,1,1,100507.81,0 -8023,15665180,Vasiliev,616,France,Female,31,3,136789.14,1,1,0,59346.4,1 -8024,15752588,Vasilyeva,664,France,Male,36,1,0,2,1,1,95372.64,0 -8025,15743051,Hamilton,694,France,Male,30,10,144684.03,1,1,1,31805.49,0 -8026,15571873,Sung,655,France,Male,24,9,107065.31,1,1,1,51959.82,0 -8027,15679743,Genovesi,607,France,Female,33,8,91301.72,1,0,1,130824.57,0 -8028,15769412,Atkinson,684,Spain,Male,39,4,207034.96,2,0,0,157694.76,1 -8029,15775124,Watterston,763,Spain,Male,37,8,0,2,1,1,933.38,0 -8030,15732113,Butters,671,Spain,Male,50,8,0,1,0,1,2560.11,0 -8031,15578141,Chien,592,Spain,Male,38,3,0,1,1,1,12905.89,1 -8032,15595874,Gorbunova,666,Spain,Female,36,6,0,2,1,0,176692.87,0 -8033,15755642,Bulgakov,667,France,Male,34,5,0,2,1,1,102908.63,0 -8034,15576526,Steele,850,Spain,Male,36,6,0,2,0,1,41291.05,0 -8035,15792489,Polyakova,622,Spain,Male,42,9,0,2,1,0,119127.06,0 -8036,15733705,Bull,577,France,Female,30,8,92472.1,2,0,1,126434.61,0 -8037,15807221,Weaver,555,Spain,Male,21,1,0,2,0,0,103901.35,0 -8038,15573045,Earl,547,France,Male,62,10,127738.75,2,1,1,85153,0 -8039,15756824,Giordano,613,Germany,Female,50,5,101242.98,2,1,0,12493.61,0 -8040,15773520,Begg,672,France,Female,43,4,92599.55,2,1,1,167336.78,0 -8041,15627439,Pickering,624,Spain,Female,36,10,0,2,0,1,186180.42,0 -8042,15701439,Fanucci,698,Spain,Female,50,1,0,4,1,0,88566.9,1 -8043,15785352,Chang,606,France,Male,37,6,82373.94,1,0,0,172526.9,1 -8044,15616525,Sopuluchi,720,Spain,Male,31,4,141356.47,1,0,0,137985.69,0 -8045,15717489,Martin,835,France,Male,23,9,0,1,1,0,19793.73,1 -8046,15795737,McNaughtan,771,Spain,Female,47,3,72664,2,1,1,107874.39,0 -8047,15693877,Stewart,811,France,Female,47,3,123365.34,2,0,0,171995.34,0 -8048,15576111,Reagan,734,Germany,Male,33,5,121898.58,1,1,0,61829.89,0 -8049,15595713,Heller,548,Spain,Male,33,6,0,1,1,1,31728.35,0 -8050,15808868,Nwokeocha,652,France,Female,31,3,103696.97,3,0,0,155221.05,1 -8051,15708193,Liu,707,France,Male,33,2,0,2,0,0,130866.95,0 -8052,15697801,Sokolova,605,Germany,Female,56,1,74129.18,2,1,1,62199.78,1 -8053,15770121,Bancroft,623,France,Female,34,9,0,1,1,0,24255.21,0 -8054,15800524,Nnanna,686,Germany,Male,29,3,185379.02,1,1,0,64679.07,0 -8055,15686236,Trevisani,525,Germany,Female,47,1,118087.68,1,1,0,88120.78,1 -8056,15659807,Nwachinemelu,657,Spain,Male,41,8,109402.13,1,1,1,66463.62,0 -8057,15736078,Ting,730,Germany,Female,33,7,130367.87,1,1,0,15142.1,1 -8058,15620836,Lo Duca,816,Germany,Female,34,2,108410.87,2,1,0,102908.91,0 -8059,15698184,Marshall,484,France,Female,50,2,90408.16,2,0,0,48170.57,0 -8060,15717643,Band,728,France,Female,34,6,90425.15,2,1,1,11597.69,0 -8061,15776596,Ferri,730,Spain,Female,39,6,140094.59,1,1,0,172450.04,1 -8062,15814757,Carter,477,Spain,Male,31,9,0,2,0,1,184061.17,0 -8063,15812607,Wilson,663,Germany,Female,46,6,95439.4,1,1,1,21038.58,1 -8064,15663888,Connor,549,Germany,Male,34,6,204017.4,2,1,0,109538.35,0 -8065,15748882,Reid,714,Spain,Male,29,9,0,2,1,0,129192.55,0 -8066,15690829,Sandefur,430,Germany,Male,49,3,137115.16,1,1,0,146516.86,1 -8067,15695819,Bidwill,504,Germany,Male,43,5,134740.19,2,1,0,181430.91,0 -8068,15696834,Cone,530,France,Female,29,5,0,2,0,0,121451.21,0 -8069,15797710,Saunders,619,Germany,Male,29,4,98955.87,1,0,1,131712.51,0 -8070,15700654,Liardet,617,Germany,Male,44,9,49157.09,2,1,0,53294.17,0 -8071,15583764,Wilkes,791,Germany,Male,31,1,130240.33,1,0,0,96546.55,0 -8072,15688849,Martin,609,France,Male,48,1,108019.27,3,1,1,184524.65,1 -8073,15661473,Boni,780,Germany,Male,51,4,126725.25,1,1,0,195259.31,1 -8074,15601030,Patel,777,Germany,Female,34,5,96693.66,1,1,1,172618.52,0 -8075,15789557,Howell-Price,817,Germany,Female,27,7,129810.6,1,1,1,59259.44,0 -8076,15745250,Simpson,850,France,Male,58,8,156652.13,1,0,0,25899.21,1 -8077,15590349,Rowland,732,France,Female,36,9,0,1,0,0,3749,1 -8078,15741693,Barnard,693,France,Male,40,4,130661.96,1,1,1,101918.96,0 -8079,15618446,Nnonso,576,France,Female,50,8,0,2,1,1,57802.62,0 -8080,15766552,Rossi,643,France,Male,37,6,0,2,0,0,142454.77,0 -8081,15668775,Pendred,757,France,Male,47,3,130747.1,1,1,0,143829.54,0 -8082,15757895,Martin,569,Germany,Male,30,6,106629.49,1,0,1,44114.88,0 -8083,15774551,K?,772,Spain,Male,36,3,112029.83,1,1,1,186948.35,0 -8084,15684011,Miller,576,Germany,Male,29,7,130575.26,1,0,1,173629.78,0 -8085,15736146,Afamefula,608,Germany,Male,28,4,96679.71,1,1,1,49133.45,0 -8086,15656286,Sims,794,France,Male,33,0,0,2,0,0,178122.71,0 -8087,15774847,Knight,593,France,Male,50,6,171740.69,1,0,0,20893.61,0 -8088,15619340,Obijiaku,597,Spain,Male,38,1,0,2,1,0,41303.29,0 -8089,15815656,Hopkins,541,Germany,Female,39,9,100116.67,1,1,1,199808.1,1 -8090,15623357,Onio,692,Germany,Male,24,2,120596.93,1,0,1,180490.53,0 -8091,15601324,Black,697,France,Female,48,1,0,2,1,1,87400.53,0 -8092,15715510,Eluemuno,768,France,Male,29,2,95984.69,2,1,1,73686.75,0 -8093,15663770,Doyle,802,France,Male,38,1,142557.11,1,1,1,172497.73,0 -8094,15779267,Onyemere,584,France,Male,47,5,0,2,1,0,89286.29,0 -8095,15597957,Rahman,614,Spain,Male,66,2,0,2,0,1,180082.7,0 -8096,15584620,Su,850,Germany,Female,36,6,143644.16,1,1,0,22102.25,1 -8097,15750772,Walker,671,France,Female,38,6,132129.72,1,0,1,76068.95,0 -8098,15706557,Ferguson,626,France,Female,52,0,0,2,1,0,32159.46,1 -8099,15594391,Samaniego,770,France,Female,68,2,183555.24,1,0,0,159557.28,1 -8100,15661656,Onwumelu,633,France,Male,38,2,91902.56,2,1,1,107673.35,0 -8101,15631217,Young,663,France,Male,40,6,156218.19,1,0,1,33607.72,0 -8102,15588955,Mazzi,581,Germany,Female,43,5,93259.57,3,1,0,141035.65,1 -8103,15758252,Toscano,561,Germany,Female,45,2,168085.38,2,0,1,115719.08,0 -8104,15740223,Walton,479,Germany,Male,51,1,107714.74,3,1,0,86128.21,1 -8105,15805413,Chiang,769,France,Female,31,6,117852.26,2,1,0,147668.64,0 -8106,15635116,Burgos,659,Spain,Male,60,2,0,1,1,0,177480.45,1 -8107,15764892,Spinelli,590,Spain,Female,51,10,84474.62,2,1,1,190937.09,0 -8108,15795936,Lung,560,France,Male,50,3,0,2,1,0,84531.79,0 -8109,15655232,Noble,437,Germany,Male,35,6,126803.34,2,1,1,161133.4,0 -8110,15640133,Pai,661,France,Female,34,0,0,2,1,0,185555.63,0 -8111,15751524,Chigozie,677,Germany,Female,36,10,68806.84,1,1,0,33075.24,0 -8112,15670552,Peavy,560,France,Female,31,3,115141.18,1,1,0,39806.75,0 -8113,15623966,Yermakov,578,France,Female,35,2,0,2,0,1,26389.92,0 -8114,15752193,Burton,421,Spain,Male,34,6,90723.36,1,1,1,12162.76,0 -8115,15607269,Costa,492,Germany,Female,49,2,151249.45,2,1,1,167237.94,0 -8116,15700752,Pugliesi,545,France,Female,32,6,0,2,1,1,52067.37,0 -8117,15777901,Lindell,640,Germany,Female,43,9,94752.49,1,1,0,184006.36,1 -8118,15639117,Sorenson,624,Spain,Female,34,6,0,1,1,0,582.59,1 -8119,15720203,Arcuri,577,Spain,Male,28,7,0,1,1,0,143274.41,0 -8120,15586236,Banks,704,France,Male,31,5,132084.66,3,1,1,54474.48,1 -8121,15676645,Parry,523,France,Male,45,5,0,2,1,1,121428.2,0 -8122,15715988,Cockett,793,France,Male,35,2,0,2,1,1,79704.12,0 -8123,15603749,Galkina,564,France,Female,53,2,45472.28,1,1,1,41055.71,1 -8124,15608956,Su,711,France,Male,33,1,0,1,0,0,41590.4,0 -8125,15733872,Marino,791,Germany,Female,33,10,130229.71,2,0,0,54019.93,1 -8126,15666982,Spears,629,Germany,Female,38,9,123948.85,1,1,0,76053.07,0 -8127,15602647,Cunningham,729,Germany,Male,39,6,127415.85,1,1,1,184977.2,1 -8128,15623063,Taylor,651,Germany,Male,35,8,110067.71,1,1,0,127678.95,1 -8129,15682928,Chiazagomekpere,695,Spain,Male,39,4,65521.2,1,1,1,1243.97,0 -8130,15729246,Hardacre,847,Spain,Male,31,5,0,2,1,1,76326.67,0 -8131,15588928,Maslow,704,France,Male,47,5,0,2,1,1,145338.61,0 -8132,15803352,Scott,613,Germany,Male,33,3,155736.42,2,1,1,57751.21,0 -8133,15607485,Wakelin,692,Spain,Female,29,4,0,2,0,0,138880.24,0 -8134,15656249,Esposito,720,France,Female,34,3,118307.57,2,1,1,136120.29,0 -8135,15761783,Shah,577,France,Male,41,6,0,1,1,1,167621.18,0 -8136,15716605,Chukwufumnanya,710,Germany,Female,24,7,103099.17,2,1,0,173276.62,0 -8137,15757425,Fleming,716,France,Female,38,1,0,2,1,1,99661.46,0 -8138,15603096,Lori,410,France,Male,33,6,125789.69,1,0,0,66333.56,1 -8139,15588580,Kennedy,584,Germany,Female,36,4,109646.83,1,1,1,70240.79,0 -8140,15770539,Walters,792,France,Male,30,1,127187.86,1,1,1,113553.42,0 -8141,15572022,Han,605,France,Female,36,6,0,1,0,1,690.84,0 -8142,15571843,Lawrence,486,Spain,Male,24,1,0,1,1,0,98802.76,0 -8143,15752502,Cooke,615,France,Male,41,4,130385.82,1,0,1,130661.95,0 -8144,15609058,Wan,676,France,Male,23,1,107787.47,1,0,1,116378.82,0 -8145,15775108,Lo Duca,571,France,Male,34,1,99325.04,2,0,1,186052.15,0 -8146,15708904,Yermakova,850,France,Female,37,9,0,1,0,0,100101.06,0 -8147,15600086,Combs,717,France,Male,48,7,123764.95,1,1,1,169952.82,0 -8148,15814675,Chien,642,Germany,Female,39,8,128264.03,1,1,0,61792.76,1 -8149,15572777,Meng,780,Spain,Male,47,7,86006.21,1,1,1,37973.13,0 -8150,15585106,Calabresi,492,Germany,Female,38,8,57068.43,2,1,0,188974.81,0 -8151,15738936,Stevenson,760,Germany,Male,29,5,103607.24,2,0,1,86334.64,0 -8152,15750970,Davidson,500,Spain,Male,40,1,99004.24,1,1,1,152845.99,0 -8153,15725772,Ch'in,654,Spain,Female,36,2,0,2,1,1,146652.11,0 -8154,15692106,Rose,606,Spain,Female,25,3,147386.72,3,1,0,45482.04,1 -8155,15791533,Ch'ien,367,Spain,Male,42,6,93608.28,1,1,0,168816.73,1 -8156,15715715,Artyomova,799,Spain,Male,38,2,0,2,1,1,59297.34,0 -8157,15785576,Mayrhofer,434,Germany,Male,71,9,119496.87,1,1,0,125848.88,0 -8158,15798834,Yefremov,719,Spain,Female,32,7,0,1,0,0,76264.27,0 -8159,15744127,Kosovich,641,France,Female,37,2,0,2,1,0,3939.87,0 -8160,15637427,Lu,461,Spain,Female,25,6,0,2,1,1,15306.29,0 -8161,15576990,Taplin,790,Germany,Female,25,5,152885.77,1,1,0,58214.79,0 -8162,15615352,Ebelechukwu,588,France,Male,31,4,99607.37,2,0,1,35877.03,0 -8163,15647333,Fleming,621,France,Male,27,4,137003.68,1,1,0,21254.06,0 -8164,15572050,Yefimov,768,Germany,Male,48,3,122831.58,1,1,1,24533.89,1 -8165,15581370,Andreyeva,681,Spain,Male,38,2,99811.44,2,1,0,23531.5,0 -8166,15813503,Pickering,606,Spain,Male,37,8,154712.58,2,1,0,89099.18,0 -8167,15769783,Allan,542,Spain,Male,37,8,0,1,1,1,807.06,0 -8168,15793135,Wang,713,Germany,Female,24,7,147687.24,1,1,1,121592.5,0 -8169,15599182,Reynolds,597,Spain,Female,33,2,0,2,1,1,4700.66,0 -8170,15689517,Hales,635,France,Male,27,3,127009.83,1,1,0,161909.95,0 -8171,15641366,Y?an,599,Germany,Male,61,1,124737.96,1,0,1,90389.61,1 -8172,15588859,Rowley,496,Spain,Female,44,0,179356.28,2,1,0,2919.21,1 -8173,15732293,Chia,759,Spain,Male,31,8,0,2,1,1,99086.74,0 -8174,15568032,Moore,757,Germany,Male,31,1,127320.36,3,1,0,163170.32,0 -8175,15623525,Copeland,564,Spain,Male,31,0,125175.58,1,1,1,72757.33,0 -8176,15606601,Rishel,561,France,Female,22,6,186788.96,2,1,0,73286.8,0 -8177,15800811,Wan,702,France,Male,40,3,148556.74,1,0,1,146056.29,0 -8178,15610711,Eluemuno,678,Germany,Female,40,8,128644.46,1,0,0,167673.37,0 -8179,15809654,Hsia,707,France,Female,46,7,127476.73,2,1,1,146011.55,0 -8180,15576077,Kelly,610,France,Female,27,9,159561.93,1,0,1,103381.47,0 -8181,15643378,Muir,744,France,Male,42,1,112419.92,1,1,1,83022.92,0 -8182,15566790,McIntyre,598,France,Male,28,8,129991.76,2,0,1,46041.08,0 -8183,15774402,Donaldson,562,Spain,Male,36,5,0,1,0,1,182843.24,0 -8184,15694641,Wright,621,Spain,Female,59,2,0,2,1,1,171364.18,0 -8185,15605916,Uvarova,659,France,Female,50,3,0,1,1,0,183399.12,1 -8186,15812356,Doherty,722,Germany,Female,40,6,89175.06,2,0,1,152883.95,0 -8187,15644179,Allen,606,France,Female,39,3,0,2,1,0,50560.45,1 -8188,15771674,Ma,603,Spain,Female,39,5,162390.52,2,1,0,54702.66,0 -8189,15623314,Tucker,506,Germany,Female,59,3,190353.08,1,1,0,78365.75,0 -8190,15613292,Ch'eng,715,France,Male,21,8,0,2,1,0,68666.63,0 -8191,15813871,Hs?,690,France,Male,47,2,0,2,1,0,151375.73,0 -8192,15759480,H?,644,France,Female,40,10,139180.97,1,1,1,19959.67,0 -8193,15587712,Chimaijem,589,France,Male,36,8,114435.47,1,1,0,26955.72,0 -8194,15671165,Esomchi,592,France,Female,66,5,149950.19,1,1,1,76267.59,0 -8195,15620746,Lorenzo,632,France,Male,42,4,126115.6,1,1,0,100998.5,0 -8196,15706537,Pirogov,577,Germany,Female,59,7,111396.97,1,0,1,191070.01,0 -8197,15589312,Larkin,588,France,Male,30,3,115007.08,1,0,0,176858.5,0 -8198,15741180,Eddy,617,France,Male,54,6,102141.9,1,1,1,45325.26,0 -8199,15733888,Sells,668,Spain,Female,36,3,133686.52,1,1,0,190958.48,1 -8200,15798532,Crawford,810,France,Male,32,9,120879.73,2,0,1,78896.59,0 -8201,15577359,Bezrukov,767,Spain,Male,47,5,0,1,1,0,121964.46,1 -8202,15614936,Mancini,718,Spain,Female,49,10,82321.88,1,0,1,11144.4,0 -8203,15747647,Iadanza,589,Spain,Female,27,4,0,2,1,0,144181.48,0 -8204,15588566,Wilkinson,778,Spain,Male,33,5,116474.28,2,1,1,32757.55,0 -8205,15570141,P'eng,724,France,Female,34,3,132352.69,1,1,0,80320.3,0 -8206,15800793,St Clair,477,Germany,Female,39,4,182491.57,1,1,0,185830.72,0 -8207,15572415,Preston,580,France,Male,34,6,0,2,1,1,160095.31,0 -8208,15635125,Findlay,566,Spain,Male,63,2,120787.18,2,1,1,52198.84,0 -8209,15636551,Nixon,711,France,Female,29,3,130181.47,2,1,0,31811.44,0 -8210,15600912,Gorshkov,706,Germany,Male,32,5,88348.43,2,1,1,104181.78,0 -8211,15768476,Chukwubuikem,703,Spain,Male,31,6,0,2,1,1,67667.19,0 -8212,15650266,Medvedeva,679,Germany,Male,39,2,146186.28,2,1,1,193974.47,0 -8213,15621004,Chukwuhaenye,603,France,Male,32,7,0,1,1,0,198055.94,1 -8214,15748352,Endrizzi,598,Spain,Male,34,0,104488.17,1,0,1,43249.67,0 -8215,15788920,Ch'ang,836,Germany,Female,32,4,109196.67,2,1,0,55218.02,0 -8216,15743236,Piccio,687,France,Female,61,7,80538.56,1,1,0,131305.37,1 -8217,15637717,Lockington,704,Germany,Male,41,4,109026.8,2,1,1,43117.1,0 -8218,15635500,Seleznyov,605,Germany,Male,75,2,61319.63,1,0,1,186655.11,0 -8219,15634792,Weston,516,France,Female,40,9,0,2,0,1,33266.29,0 -8220,15607560,Groom,572,France,Female,39,2,0,2,1,1,555.28,0 -8221,15727177,Manfrin,557,France,Male,42,6,177822.03,1,1,0,150944.31,1 -8222,15774358,Robertson,443,Germany,Male,59,4,110939.3,1,1,0,72846.58,1 -8223,15791304,Ch'ang,604,Germany,Male,25,7,165413.43,1,1,1,35279.74,0 -8224,15603328,Lucchesi,483,France,Male,27,1,77805.66,1,1,1,2101.89,0 -8225,15804937,Cambage,702,France,Male,50,3,0,2,0,0,94949.84,0 -8226,15804142,Tan,670,Spain,Female,57,3,175575.95,2,1,0,99061.75,1 -8227,15608845,Tao,804,Spain,Female,38,3,124197.22,1,1,0,74692.06,0 -8228,15702434,Hsieh,850,France,Female,30,3,0,2,1,0,116692.8,0 -8229,15632609,Burdekin,554,France,Female,39,10,160132.75,1,1,0,32824.15,0 -8230,15603550,Longo,588,Germany,Female,37,7,70258.88,2,1,0,139607.61,0 -8231,15755239,Maughan,758,Germany,Male,32,4,162657.64,2,1,1,115525.13,0 -8232,15670528,Franz,787,Germany,Male,43,0,132217.45,1,1,0,20955.03,1 -8233,15732704,Piazza,582,Spain,Male,25,9,148042.97,2,1,0,52341.15,0 -8234,15589019,Morant,633,Spain,Female,33,4,92855.02,1,1,1,159813.18,0 -8235,15677796,Becher,766,Germany,Male,47,9,129289.98,1,1,0,169935.46,1 -8236,15760177,Lombardi,564,Spain,Male,37,9,100252.18,1,1,1,146033.52,0 -8237,15636595,Loton,602,Spain,Male,37,3,107592.89,2,0,1,153122.73,0 -8238,15737275,Conti,649,France,Male,39,3,113096.41,1,1,1,60335.24,0 -8239,15672905,Sani,679,Spain,Female,40,7,0,2,1,1,163757.29,0 -8240,15753955,Lori,639,Spain,Male,34,7,149940.04,2,0,0,156648.81,0 -8241,15708504,Wong,790,Germany,Male,50,8,121438.58,1,1,1,176471.78,1 -8242,15592451,Lombardi,565,France,Male,32,9,0,2,1,0,5388.3,0 -8243,15790455,Obialo,478,France,Female,50,2,0,1,0,1,93332.64,1 -8244,15572174,Mazzi,825,France,Male,29,3,148874.01,2,0,1,71192.82,0 -8245,15656330,Von Doussa,528,Spain,Female,32,0,68138.37,1,1,1,170309.19,0 -8246,15569626,Miller,577,Spain,Male,35,5,110080.3,1,1,1,109794.31,0 -8247,15608726,Miracle,663,France,Male,24,7,0,2,1,1,166310.82,0 -8248,15637366,Su,505,Germany,Female,25,5,114268.85,2,1,1,126728.27,0 -8249,15778049,Wyatt,633,Germany,Male,29,6,117412.35,1,0,0,30338.94,0 -8250,15727421,Anayolisa,586,France,Female,38,6,0,2,1,1,37935.83,0 -8251,15688865,Wade,850,France,Female,35,9,0,2,0,0,25329.48,0 -8252,15751032,Enemuo,629,Germany,Female,37,1,35549.81,2,0,0,49676.33,0 -8253,15734737,Bruno,744,France,Male,56,9,0,2,1,1,169498.61,0 -8254,15746515,Greece,750,France,Male,36,7,136492.92,3,1,1,26500.29,1 -8255,15664311,Yang,637,Germany,Male,28,3,123675.69,1,1,1,166458.41,0 -8256,15708139,Brown,575,France,Female,40,1,139532.34,1,1,0,181294.39,0 -8257,15768574,Anderson,671,Spain,Male,58,1,178713.98,1,1,1,21768.21,0 -8258,15738018,Johnston,571,France,Male,40,5,0,2,0,0,72849.29,0 -8259,15699753,Zakharov,590,France,Male,41,1,89086.31,1,1,0,24499.97,0 -8260,15703199,Golibe,619,Spain,Male,38,3,96143.47,1,0,0,98994.92,0 -8261,15627830,Nikitina,640,Germany,Female,30,5,32197.64,1,0,1,141446.01,0 -8262,15570855,Leonard,670,France,Male,38,7,0,2,1,1,77864.41,0 -8263,15772503,Burns,737,France,Female,33,4,0,2,1,0,115115.32,0 -8264,15584453,Burtch,555,Spain,Male,32,10,0,2,0,1,168605.96,0 -8265,15710111,Clark,742,France,Male,33,6,0,2,0,0,38550.4,0 -8266,15618562,Woodward,618,Germany,Female,40,0,140306.38,1,1,0,160618.61,1 -8267,15706764,Spencer,560,France,Female,35,1,0,2,1,0,3701.63,0 -8268,15798737,Chao,654,France,Male,38,8,0,2,1,0,88659.44,0 -8269,15712608,Costa,787,Germany,Female,42,2,74483.97,2,0,1,44273.91,0 -8270,15636736,McLachlan,611,France,Female,53,7,0,2,0,1,156495.39,1 -8271,15703544,Hung,559,Spain,Male,34,0,0,1,1,0,182988.94,0 -8272,15815645,Akhtar,481,France,Male,37,8,152303.66,2,1,1,175082.2,0 -8273,15705739,Toscani,753,Germany,Male,32,5,159904.79,1,1,0,148811.14,0 -8274,15709643,Gray,675,France,Male,32,1,0,3,1,0,85901.09,0 -8275,15669805,Warren,748,Germany,Female,31,1,99557.94,1,1,0,199255.32,0 -8276,15737489,Ramsden,610,Spain,Female,46,5,116886.59,1,0,0,107973.44,0 -8277,15775131,Bartlett,580,Spain,Male,32,9,142188.2,2,0,1,128028.6,0 -8278,15765283,Wenz,624,Germany,Female,40,3,149961.99,2,1,0,104610.86,0 -8279,15628715,Kisch,709,France,Female,36,8,0,2,1,1,69676.55,0 -8280,15813283,Mai,605,France,Female,34,2,0,1,0,0,35982.42,0 -8281,15745716,McGregor,706,Spain,Male,53,7,0,2,0,1,117939.17,0 -8282,15598485,Pinto,567,Spain,Male,40,8,28649.64,1,1,1,95140.62,0 -8283,15696552,Newman,747,France,Female,21,4,81025.6,2,1,0,167682.57,0 -8284,15754569,Pagnotto,664,France,Male,57,1,0,2,1,1,56562.57,0 -8285,15701741,Williams,711,France,Female,39,3,152462.79,1,1,0,90305.97,0 -8286,15572631,Ndubuisi,609,France,Male,25,10,0,1,0,1,109895.16,0 -8287,15636069,Plummer,632,Spain,Male,28,7,155519.59,1,1,0,1843.24,0 -8288,15682467,Chimezie,725,France,Female,36,1,118851.05,1,1,1,102747.02,0 -8289,15790744,Nash,850,France,Female,34,9,92899.27,2,1,0,97465.89,0 -8290,15625023,Onochie,682,France,Male,40,4,0,1,0,1,105352.55,0 -8291,15731267,Rizzo,797,France,Male,37,4,75263.7,1,1,0,85801.77,0 -8292,15742879,Boni,668,Spain,Male,38,1,147904.31,1,1,1,69370.05,0 -8293,15757015,Davies,783,Germany,Female,41,5,106640.5,1,1,0,176945.96,0 -8294,15770711,Lu,766,Germany,Female,28,4,90696.78,1,0,1,21597.2,0 -8295,15569430,Burrows,704,Spain,Female,36,2,175509.8,2,1,0,152039.67,0 -8296,15617304,Ershova,722,France,Male,40,6,0,2,1,1,111893.09,0 -8297,15704466,Udokamma,692,France,Female,34,7,0,2,1,0,195074.62,0 -8298,15664681,Aitken,584,France,Female,35,2,114321.28,2,0,0,15959.01,0 -8299,15605534,Turnbull,644,Germany,Female,51,4,95560.04,1,0,0,72628.84,1 -8300,15792473,Reilly,598,Germany,Female,50,5,88379.81,3,0,1,64157.24,1 -8301,15802625,Hardy,733,Germany,Male,48,7,85915.52,1,1,1,23860.5,0 -8302,15766017,Brookman,615,Germany,Male,58,3,72309.3,1,1,1,85687.09,1 -8303,15762172,Kerr,850,France,Female,39,2,0,2,1,0,179451.42,0 -8304,15728333,McBurney,521,France,Male,43,8,0,1,1,1,93180.09,0 -8305,15792868,Mickey,675,France,Male,69,1,0,2,1,0,157097.09,0 -8306,15605698,Harrison,746,France,Male,58,3,0,3,1,1,80344.96,1 -8307,15777060,Olszewski,770,France,Female,33,4,0,1,1,0,26080.54,1 -8308,15626243,Chijioke,618,France,Male,30,3,133844.22,1,1,1,31406.93,0 -8309,15719898,Young,556,France,Male,36,7,154872.08,2,1,1,32044.64,0 -8310,15599976,Bellasis,749,France,Female,27,9,0,2,1,0,132734.87,0 -8311,15752809,De Mestre,702,Spain,Male,43,6,116121.67,1,1,0,61602.42,0 -8312,15589698,De Luca,555,Germany,Male,42,6,107104.5,1,1,1,41304.44,1 -8313,15609977,Mundy,587,France,Male,47,6,71026.77,1,1,0,57962.41,0 -8314,15750121,Tung,639,France,Male,38,3,0,1,1,0,42862.82,0 -8315,15734177,Donahue,643,France,Male,33,4,0,2,1,1,152992.04,0 -8316,15781347,Okagbue,600,France,Female,41,1,0,2,1,1,91193.65,0 -8317,15592025,Nnaemeka,651,France,Male,53,7,0,2,1,1,130132.41,0 -8318,15670163,Verjus,666,France,Female,27,4,0,2,0,0,88751.45,0 -8319,15765402,H?,520,France,Female,39,6,145644.05,1,0,0,104118.93,0 -8320,15624343,Napolitani,650,Spain,Female,50,7,129667.77,1,0,0,42028.16,0 -8321,15602354,Ginikanwa,564,Germany,Male,33,3,109341.87,1,1,0,75632.78,0 -8322,15579183,Spaull,586,France,Male,64,1,0,2,1,1,53710.23,0 -8323,15584899,Siciliani,617,France,Female,35,5,0,2,0,1,13066.3,0 -8324,15723658,Voronina,712,Spain,Female,30,6,0,2,1,0,152417.97,0 -8325,15803965,Tang,654,France,Male,55,3,87485.67,1,1,1,3299.01,0 -8326,15682489,Crumbley,605,France,Male,27,9,0,2,1,0,198091.81,0 -8327,15813645,Hamilton,491,France,Female,36,0,53369.13,1,1,1,103934.12,0 -8328,15766787,Piazza,707,France,Female,35,9,0,2,1,1,70403.65,0 -8329,15687171,Birch,638,Spain,Male,34,5,146679.77,1,1,0,102179.86,0 -8330,15690744,Custance,683,France,Male,43,2,112499.42,2,1,0,30375.18,0 -8331,15707974,Anayochukwu,815,Spain,Female,38,2,48387,1,1,0,184796.84,0 -8332,15673084,Galkin,645,Spain,Male,38,1,68079.8,1,0,1,166264.89,0 -8333,15814772,Adams,645,Germany,Male,49,4,160133.88,1,0,1,88391.97,0 -8334,15743709,Toomey,683,France,Male,30,4,66190.33,1,1,1,115186.97,0 -8335,15610343,Marshall-Hall,705,France,Female,37,10,0,2,1,1,13935.53,1 -8336,15737414,Shen,647,France,Male,35,4,123761.68,1,1,0,83910.4,0 -8337,15788480,Pagnotto,786,Germany,Female,33,0,122325.58,1,0,0,34712.34,1 -8338,15568519,Wood,534,France,Male,41,9,0,2,1,0,13871.34,0 -8339,15792453,More,602,Spain,Female,42,1,138912.17,1,1,1,139494.75,0 -8340,15658100,Piccio,695,France,Female,42,0,0,2,0,1,140724.64,0 -8341,15695197,Tochukwu,553,Germany,Female,25,7,128524.19,2,1,0,20682.46,0 -8342,15749807,Graham,516,Spain,Female,31,3,0,2,1,0,124202.26,0 -8343,15773876,Tung,655,France,Female,34,3,0,2,1,0,159638.77,0 -8344,15591698,P'eng,849,Germany,Female,49,9,132934.89,1,1,0,171056.65,1 -8345,15712813,Nevzorova,520,Germany,Male,43,3,150805.17,3,0,1,25333.03,1 -8346,15763898,Toscani,568,Spain,Female,46,3,0,2,1,1,29372.62,0 -8347,15793324,McKenzie,695,Spain,Male,32,9,0,3,0,1,38533.79,0 -8348,15757759,Okwuoma,807,Spain,Female,28,7,165969.26,3,1,0,156122.13,1 -8349,15796230,Morley,642,Germany,Female,36,2,124495.98,3,1,1,57904.22,1 -8350,15611729,Kerr,703,Germany,Male,39,1,141559.5,1,1,1,31257.1,1 -8351,15709531,Harding,556,France,Male,38,2,114756.14,1,1,0,193214.05,0 -8352,15650751,Butler,585,France,Female,30,6,0,2,1,1,137757.69,0 -8353,15641413,Crawford,587,Germany,Female,49,7,155393.98,2,1,0,13308.2,1 -8354,15753840,Brown,524,Spain,Female,32,6,0,1,1,1,132861.9,1 -8355,15669994,Greece,556,Germany,Female,31,1,128663.81,2,1,0,125083.29,0 -8356,15695301,Matthews,504,Spain,Male,44,4,113522.64,1,1,1,12405.2,0 -8357,15792004,Heath,731,Spain,Female,26,3,0,2,1,0,37697.29,0 -8358,15603035,Vincent,651,France,Male,34,3,0,2,1,1,105599.65,0 -8359,15717286,Sal,675,Spain,Female,40,8,79035.95,1,1,0,142783.98,1 -8360,15577107,Milne,657,Spain,Female,22,6,0,3,0,1,168412.07,1 -8361,15754747,Bazile,686,Germany,Male,33,9,141918.09,2,0,1,184036.47,0 -8362,15705676,Wardle,690,France,Female,35,9,107944.33,2,0,0,48478.47,0 -8363,15751912,Lilly,567,France,Male,36,7,0,2,0,1,3896.08,0 -8364,15677336,Aitken,557,Germany,Male,57,1,120043.13,1,1,0,132370.75,1 -8365,15684395,Enderby,446,Spain,Female,45,10,125191.69,1,1,1,128260.86,1 -8366,15659949,Chiu,850,France,Male,31,1,96399.31,2,1,0,106534.15,0 -8367,15812422,Ugorji,637,France,Male,41,2,0,2,0,1,102515.42,0 -8368,15806941,Sharpe,499,France,Male,60,7,76961.6,2,1,1,83643.87,0 -8369,15637690,Houghton,622,Germany,Female,34,7,98675.74,1,1,0,138906.85,1 -8370,15632882,Konovalova,684,Germany,Male,37,1,126817.13,2,1,1,29995.83,1 -8371,15807107,Patel,612,France,Male,32,3,121394.42,1,1,0,164081.42,0 -8372,15661034,Ngozichukwuka,813,Germany,Female,29,5,106059.4,1,0,0,187976.88,1 -8373,15811958,Medland,850,Germany,Male,44,2,112755.34,2,0,0,158171.36,0 -8374,15785167,Padovano,795,Spain,Male,29,4,0,2,0,0,155711.64,0 -8375,15646720,Tsui,628,Spain,Female,55,7,0,3,1,0,85890.75,1 -8376,15658614,H?,565,Germany,Female,38,7,145400.69,2,1,1,83844.79,0 -8377,15704657,Denman,601,France,Male,39,3,72647.64,1,1,0,41777.9,1 -8378,15567147,Ratten,802,Spain,Male,40,4,0,2,1,1,81908.09,0 -8379,15701319,Baxter,614,Germany,Female,37,6,96340.81,2,1,1,139377.24,1 -8380,15745266,Norman,434,Spain,Male,55,6,0,1,0,1,73562.05,1 -8381,15650437,Shen,522,Germany,Male,32,8,124450.36,2,1,1,165786.1,0 -8382,15764314,Reilly,550,Germany,Male,36,2,113877.23,2,1,0,174921.91,0 -8383,15612594,Ifeanacho,599,Spain,Male,25,3,0,2,1,1,120790.02,0 -8384,15593501,Graham,493,France,Female,36,5,148667.81,2,1,0,56092.51,0 -8385,15804150,Lysaght,755,France,Male,34,3,0,2,1,1,158816.03,0 -8386,15649297,T'ang,605,France,Female,62,4,111065.93,2,0,1,125660.99,0 -8387,15641110,Abron,708,France,Male,41,0,0,1,1,0,128400.62,0 -8388,15660608,Chimaraoke,699,France,Male,44,8,158697.61,1,1,0,107181.22,0 -8389,15806570,Y?an,763,France,Female,53,4,0,1,1,0,77203.72,1 -8390,15715345,Sergeyeva,743,Spain,Male,25,6,0,2,1,0,129740.11,0 -8391,15755521,Ma,660,France,Female,48,0,90044.32,2,0,1,187604.97,1 -8392,15579074,Obiajulu,619,Germany,Male,38,10,84651.79,1,1,1,184754.26,0 -8393,15641158,Belcher,739,Germany,Male,32,3,102128.27,1,1,0,63981.37,1 -8394,15752507,K?,769,Germany,Male,60,9,148846.39,1,1,0,192831.67,1 -8395,15597983,Brown,692,France,Male,69,10,154953.94,1,1,1,70849.47,0 -8396,15586069,Abernathy,560,France,Female,30,0,108883.29,1,1,0,27914.95,0 -8397,15655082,Pape,607,France,Female,48,4,112070.86,3,1,0,173568.3,1 -8398,15720155,Tao,630,Germany,Male,29,6,131354.39,1,0,1,9324.31,1 -8399,15582116,Ma,767,Germany,Female,45,7,132746.2,2,1,0,26628.88,1 -8400,15749365,Earle,543,France,Female,34,8,0,2,0,1,145601.8,0 -8401,15632069,Kazantsev,776,France,Male,39,8,125211.55,2,1,0,144496.07,0 -8402,15663134,Uspenskaya,535,Spain,Male,58,1,0,2,1,1,11779.98,1 -8403,15766683,Coombes,549,Germany,Male,36,6,139422.37,1,0,0,83983.39,1 -8404,15707219,Hopman,844,France,Female,28,4,0,2,0,1,123318.37,0 -8405,15709232,McKay,586,Germany,Female,47,5,157099.47,2,1,1,65481.86,0 -8406,15801351,Milanesi,583,France,Male,40,3,0,2,1,0,47728,0 -8407,15578747,Chineze,701,Spain,Male,26,5,83600.24,1,0,1,59195.05,0 -8408,15675626,Dawson,726,France,Male,28,2,0,1,0,0,98060.51,0 -8409,15583736,Shih,829,Germany,Male,36,4,81795.74,2,1,0,90106.94,0 -8410,15590011,Hughes,749,Spain,Male,38,9,129378.32,1,1,1,13549.34,0 -8411,15609913,Clark,743,France,Female,46,9,0,1,1,0,113436.08,0 -8412,15719479,Chukwuhaenye,619,Spain,Female,56,7,0,2,1,1,42442.21,0 -8413,15575147,Wall,699,France,Male,22,9,99339,1,1,0,68297.61,1 -8414,15597309,Howell,749,Spain,Male,36,7,0,2,0,0,80134.65,0 -8415,15648367,Lo,600,Germany,Female,29,6,74430.1,2,1,1,96051.1,0 -8416,15758031,Lazarev,760,Spain,Male,38,3,91241.85,1,0,1,80682.35,0 -8417,15751771,Lowe,528,Germany,Male,32,2,99092.45,1,0,1,111149.98,0 -8418,15689288,Folliero,630,France,Female,26,5,0,2,1,0,182612.38,0 -8419,15731026,Han,683,Germany,Female,39,2,100062.16,2,1,0,109201.43,0 -8420,15775809,Holloway,677,Germany,Female,26,6,98723.67,1,0,1,151146.67,0 -8421,15743076,Pai,669,Spain,Male,29,9,0,1,1,1,93901.61,0 -8422,15658258,Trejo,693,France,Male,43,6,128760.32,1,1,0,36342.79,0 -8423,15756321,Johnston,612,Spain,Female,52,5,144772.69,1,0,0,98302.57,1 -8424,15706799,Macknight,719,Spain,Male,44,4,0,1,0,0,84972.9,1 -8425,15775703,Lo,702,France,Male,26,2,71281.29,1,1,1,108747.12,1 -8426,15642636,Glossop,755,France,Male,29,9,117035.89,1,1,1,21862.19,0 -8427,15704651,Bishop,514,France,Male,26,1,0,2,0,0,121551.93,0 -8428,15806771,Yefremova,753,France,Female,40,0,3768.69,2,1,0,177065.24,1 -8429,15566735,Obialo,548,Germany,Female,36,2,108913.84,2,1,1,140460.01,0 -8430,15681671,Nkemjika,850,Germany,Male,28,2,101100.22,2,1,1,35337.31,0 -8431,15775949,Trevisani,612,France,Female,38,7,110615.47,1,1,1,193502.93,0 -8432,15586752,Parkes,628,Germany,Male,33,8,152143.89,1,1,1,32174.03,0 -8433,15582519,Seleznyov,479,France,Male,47,6,121797.09,1,0,1,5811.9,1 -8434,15658233,Naylor,724,France,Female,41,5,109798.25,1,0,1,149593.61,0 -8435,15755330,Forbes,512,Germany,Male,41,7,122403.24,1,0,1,37439.9,1 -8436,15605072,Douglas,638,France,Female,43,3,145860.98,1,1,1,142763.51,1 -8437,15617538,Nwankwo,834,Spain,Male,40,7,0,2,0,0,45038.74,0 -8438,15591428,Myers,781,France,Male,29,9,0,2,0,0,172097.4,0 -8439,15692142,Rogova,707,Germany,Female,48,7,105086.74,1,1,1,180344.69,1 -8440,15692931,Hsing,670,France,Male,22,2,114991.45,1,1,1,37392.56,0 -8441,15781127,Giordano,663,Spain,Female,33,8,96769.04,1,1,1,36864.05,0 -8442,15677136,Okwukwe,624,France,Female,23,5,0,2,0,0,132418.59,0 -8443,15677828,Chalmers,598,France,Female,34,4,0,2,0,0,60894.26,0 -8444,15567897,Chiazagomekpere,619,Germany,Male,23,5,132725.1,1,1,1,143913.33,0 -8445,15793641,Evseyev,792,France,Female,70,3,0,2,1,1,172240.27,0 -8446,15678333,Parry-Okeden,683,France,Female,26,7,0,2,1,0,86619.77,0 -8447,15630511,Picot,691,France,Female,33,6,0,2,1,0,164074.89,0 -8448,15792627,Reid,765,Spain,Female,33,5,84557.82,1,1,1,69039.43,0 -8449,15717191,Ferri,508,France,Male,49,1,93817.41,2,1,1,132468.76,1 -8450,15625716,Genovesi,637,France,Female,33,9,113913.53,1,0,1,65316.5,0 -8451,15710053,Neumayer,667,Germany,Female,44,5,140406.68,2,0,1,57164.19,0 -8452,15580043,Murray,575,Spain,Female,22,8,105229.34,1,1,1,34397.08,0 -8453,15601410,Tien,744,Spain,Female,46,1,0,3,1,1,177431.59,1 -8454,15684669,Parkes,567,France,Female,41,9,137891.35,1,1,0,142009.46,1 -8455,15619083,Yip,502,France,Female,35,6,0,2,1,1,80618.47,0 -8456,15692207,Ingle,609,France,Female,53,6,0,2,1,1,124218.27,0 -8457,15730705,Chidubem,715,France,Male,37,9,165252.52,1,1,0,85286.3,0 -8458,15749688,Lu,541,France,Male,32,8,0,2,0,0,40889.14,0 -8459,15728542,Vorobyova,850,France,Female,71,4,0,2,1,1,107236.87,0 -8460,15760063,Chiedozie,595,Spain,Male,23,7,0,2,1,1,168085.97,0 -8461,15658982,Napolitani,650,Germany,Female,28,5,122034.4,3,0,1,146663.43,1 -8462,15758769,Coffey,625,France,Female,44,7,0,1,1,0,4791.8,0 -8463,15778481,Chigbogu,817,France,Male,59,1,118962.58,1,1,1,120819.58,0 -8464,15661162,Akabueze,526,Spain,Male,49,2,0,1,1,0,114539.67,1 -8465,15568164,Istomin,850,France,Female,34,4,71379.53,2,1,1,154000.99,0 -8466,15601569,Ndubueze,598,France,Female,40,2,171178.25,1,1,0,137980.58,1 -8467,15772383,Toscani,613,France,Male,36,9,131307.11,1,0,0,83343.73,0 -8468,15667456,Ross,709,Spain,Male,62,3,0,2,1,1,82195.15,0 -8469,15672983,Fernando,678,Spain,Female,27,5,87099.85,2,1,0,149550.95,0 -8470,15799534,McClaran,720,France,Male,71,5,183135.39,2,1,1,197688.5,0 -8471,15582847,Yermakova,662,France,Male,26,0,0,2,0,1,72929.96,0 -8472,15612478,Somadina,525,France,Male,51,10,0,3,1,0,171045.35,1 -8473,15709621,Wan,662,France,Male,31,3,0,2,0,1,27731.05,0 -8474,15802009,Mazzi,770,France,Female,33,6,0,2,1,1,126131.9,0 -8475,15698816,Tuan,721,Spain,Female,33,4,72535.45,1,1,1,103931.49,0 -8476,15574830,Townsley,633,Germany,Male,58,2,128137.42,2,1,0,147635.33,1 -8477,15603082,Yashina,701,France,Male,51,9,0,2,0,0,61961.57,0 -8478,15685947,Henderson,556,Germany,Male,42,0,115915.53,2,0,1,125435.47,1 -8479,15643048,Mueller,639,France,Male,66,0,0,2,0,1,42240.54,0 -8480,15807568,Wright,632,France,Male,50,2,0,2,0,0,57942.88,0 -8481,15597591,Lung,456,France,Male,29,5,107000.49,1,1,1,153419.62,0 -8482,15747558,Bryant,729,Spain,Female,38,10,0,2,1,0,189727.12,0 -8483,15756655,Madukaife,632,France,Female,34,2,0,2,0,0,165385.55,0 -8484,15589949,Maclean,433,Spain,Male,34,9,152806.74,1,1,0,19687.99,0 -8485,15601012,Abdullah,802,France,Female,60,3,92887.06,1,1,0,39473.63,1 -8486,15724269,Yao,670,France,Male,25,7,0,2,1,1,144723.38,0 -8487,15567506,Cheatham,738,Germany,Female,40,6,114940.67,2,1,1,194895.57,1 -8488,15791877,Gallagher,706,Germany,Male,34,0,140641.26,2,1,1,77271.91,0 -8489,15794360,Hao,592,Germany,Female,70,5,71816.74,2,1,0,105096.82,1 -8490,15686538,Nixon,522,France,Female,41,7,0,2,0,1,176780.39,0 -8491,15585985,Wang,746,France,Male,48,5,165282.42,1,1,0,153786.46,1 -8492,15699257,Kerr,651,Spain,Male,42,2,143145.87,2,1,0,43612.06,0 -8493,15804104,Romani,494,France,Male,28,9,114731.76,2,0,1,79479.74,0 -8494,15727619,Lock,753,Germany,Female,46,9,113909.69,3,1,0,92320.37,1 -8495,15740237,Millar,671,Germany,Male,36,2,116695.27,1,0,0,193201.86,0 -8496,15801436,K'ung,696,France,Male,42,4,0,1,0,0,126353.13,1 -8497,15705735,Onyekachi,577,Spain,Male,43,3,0,2,1,1,135008.92,0 -8498,15649359,Somayina,587,France,Male,36,1,0,2,0,1,17135.6,0 -8499,15624892,Dennis,712,Germany,Male,37,7,93978.96,2,1,0,60651.77,0 -8500,15784918,Brown,498,Germany,Male,35,2,121968.11,2,0,1,188343.05,0 -8501,15584785,Ogochukwu,660,France,Male,37,2,97324.91,1,1,0,23291.83,0 -8502,15797197,Macleod,678,Spain,Male,29,6,0,2,1,0,64443.75,0 -8503,15574858,Page,530,France,Male,37,8,0,2,1,1,287.99,0 -8504,15794101,Barese,559,France,Female,48,2,0,2,0,1,137961.41,0 -8505,15743245,Agafonova,624,France,Male,42,3,145155.37,1,1,0,72169.95,1 -8506,15791535,Caraway,592,France,Male,28,5,137222.77,1,0,0,39608.58,0 -8507,15605215,Stevenson,767,France,Male,48,9,0,2,0,1,175458.21,0 -8508,15771749,Duncan,653,Germany,Female,38,5,114268.22,2,1,1,89524.83,0 -8509,15616833,Wang,678,Spain,Male,27,2,0,2,1,1,13221.25,0 -8510,15750728,Kaur,586,Spain,Female,42,2,0,1,1,0,102889.34,0 -8511,15769353,Jenkins,550,France,Female,40,8,150490.32,1,0,0,166468.21,1 -8512,15770091,Edwards,643,Germany,Male,28,9,160858.13,2,1,0,27149.27,0 -8513,15716420,Kelly,612,Spain,Male,39,5,170288.38,1,1,1,59601.15,0 -8514,15740602,Boyle,674,Germany,Female,27,4,111568.01,1,0,1,22026.18,0 -8515,15796071,Loane,657,Spain,Male,29,7,83889.03,1,1,0,153059.62,0 -8516,15811389,Padovano,724,Germany,Female,35,0,171982.95,2,0,1,167313.07,0 -8517,15783875,Li Fonti,500,France,Female,34,4,0,2,1,0,12833.96,0 -8518,15671800,Robinson,688,France,Male,20,8,137624.4,2,1,1,197582.79,0 -8519,15677288,Geach,599,France,Male,50,3,121159.65,1,0,0,4033.39,1 -8520,15633525,Payne,631,France,Male,29,7,0,2,0,1,125877.22,0 -8521,15634606,Chinonyelum,634,Spain,Male,52,1,0,2,1,1,176913.42,0 -8522,15579207,Watkins,545,France,Male,37,3,91184.01,1,1,0,105476.65,0 -8523,15619892,Page,644,Spain,Male,18,8,0,2,1,0,59172.42,0 -8524,15567778,Genovese,690,Germany,Female,54,1,144027.8,1,1,1,108731.02,1 -8525,15711750,Watson,711,France,Female,34,6,0,2,1,1,175310.38,0 -8526,15751084,Mancini,712,France,Female,29,8,140170.61,1,1,1,38170.04,0 -8527,15768945,Chibueze,627,France,Male,27,1,62092.9,1,1,1,105887.04,0 -8528,15586931,Hunter,694,Spain,Male,39,3,0,1,1,1,95625.03,0 -8529,15636353,Buchi,534,Spain,Male,35,4,0,2,0,0,9541.15,0 -8530,15623858,Charteris,603,France,Male,45,9,0,1,0,0,148516.79,0 -8531,15703354,Aksenov,808,France,Female,33,2,103516.87,1,1,0,113907.8,0 -8532,15663987,Wright,723,Spain,Male,30,1,0,3,1,0,164647.72,1 -8533,15780805,Lu,585,France,Female,35,2,0,2,1,0,98621.04,1 -8534,15768566,K?,706,France,Male,34,8,0,2,1,1,37479.97,0 -8535,15643229,Hou,671,France,Female,31,6,0,2,1,1,15846.42,0 -8536,15754940,Descoteaux,597,Spain,Male,43,2,85162.26,1,0,1,5104.08,1 -8537,15676576,Stephenson,646,France,Female,43,8,143061.88,1,1,0,61937.6,0 -8538,15800068,Cooper,801,Spain,Female,46,6,0,2,1,1,170008.74,0 -8539,15648030,Crump,731,Spain,Female,33,5,137388.01,2,1,0,165000.68,0 -8540,15668594,Diggs,620,Germany,Female,25,1,137712.01,1,1,1,76197.05,0 -8541,15728709,Shih,484,Germany,Male,40,7,106901.42,2,0,0,118045.98,0 -8542,15724181,Hudson,647,Spain,Male,47,5,105603.21,2,1,1,157360.9,0 -8543,15647546,Carvosso,688,Germany,Female,40,8,150679.71,2,0,1,196226.38,0 -8544,15702601,Wyatt,680,Germany,Male,30,4,108300.27,2,0,1,44384.57,1 -8545,15567725,Kodilinyechukwu,689,France,Female,46,7,52016.08,2,1,1,72993.65,0 -8546,15674179,Vorobyova,513,Germany,Male,34,7,60515.13,1,0,0,124571.09,0 -8547,15686957,Piccio,553,Germany,Male,35,2,158584.28,2,1,0,43640.16,0 -8548,15607690,Hsing,689,Germany,Male,47,2,118812.5,2,0,0,31121.42,0 -8549,15806546,Lucas,517,Spain,Male,46,4,0,1,1,0,22372.78,0 -8550,15632850,T'ang,731,France,Male,37,8,0,2,1,1,170338.35,0 -8551,15709016,North,687,Germany,Female,47,1,91219.29,1,0,0,158845.49,1 -8552,15638068,Thompson,507,Spain,Male,32,7,0,2,1,0,67926.18,0 -8553,15749345,Simpson,468,France,Female,22,1,76318.64,1,1,1,194783.12,0 -8554,15791321,Nwora,682,Spain,Female,58,4,0,1,1,0,176036.01,0 -8555,15699095,Chandler,603,France,Female,24,3,0,1,1,1,198826.03,1 -8556,15638329,Uspensky,522,Germany,Male,25,1,111432.13,1,1,1,168683.57,0 -8557,15575445,Ferguson,629,Spain,Male,41,10,150148.51,1,0,0,6936.27,0 -8558,15752622,Kerr,729,France,Female,32,7,38550.06,1,0,1,179230.23,0 -8559,15774507,Furneaux,574,France,Female,39,5,119013.86,1,1,0,103421.91,0 -8560,15570857,Kambinachi,677,Germany,Female,39,0,111213.64,2,1,1,147578.26,0 -8561,15599386,Black,627,Germany,Male,28,5,71097.23,1,1,1,130504.49,0 -8562,15744913,Chizoba,788,Spain,Male,36,10,109632.85,1,1,1,16149.13,0 -8563,15647292,Peng,697,France,Male,63,7,148368.02,1,0,0,118862.08,1 -8564,15728838,Leach,578,France,Male,45,1,148600.91,1,1,0,143397.14,1 -8565,15584704,Chiazagomekpele,519,France,Male,48,10,71083.98,1,1,0,137959,0 -8566,15749068,Nickson,632,France,Female,40,9,139625.34,1,1,0,93702.96,1 -8567,15622985,Lin,679,France,Female,39,4,0,1,0,0,172939.3,1 -8568,15587676,Alexeieva,699,France,Male,30,9,0,1,1,1,108162.13,0 -8569,15779496,Sykes,615,France,Male,64,0,81564.1,2,0,1,35896.09,0 -8570,15733460,Martin,622,Spain,Male,36,9,0,2,1,1,104852.6,0 -8571,15711457,Herz,755,France,Female,28,7,124540.28,1,0,1,188850.89,0 -8572,15795290,Nikitina,767,France,Female,42,2,133616.39,1,1,0,28615.8,0 -8573,15611223,Ko,752,Germany,Female,38,10,101648.5,2,1,0,172001.44,0 -8574,15794159,Highett,633,France,Female,26,8,124281.84,1,1,1,60116.57,0 -8575,15780677,Jackson,717,France,Female,59,4,0,2,1,1,170528.63,0 -8576,15690175,Ball,585,Spain,Male,45,0,0,2,0,0,189683.7,0 -8577,15722599,Nelson,751,France,Female,37,9,183613.66,2,0,0,49734.94,0 -8578,15569976,Woronoff,754,Germany,Male,65,1,136186.44,1,1,1,121529.59,1 -8579,15707011,Morrison,495,France,Male,47,10,137682.68,1,1,0,71071.47,0 -8580,15702277,Smith,650,France,Male,34,4,106005.54,1,0,1,142995.32,0 -8581,15801915,Rendall,529,France,Female,31,6,152310.55,1,1,0,13054.25,0 -8582,15580213,McIntyre,585,France,Female,43,2,0,2,1,0,89402.54,0 -8583,15637947,Wei,668,Spain,Male,32,1,134446.04,1,0,1,111241.37,0 -8584,15715888,Allardyce,591,France,Female,38,2,142289.28,1,0,1,119638.85,0 -8585,15732967,Cremonesi,731,France,Male,19,6,0,2,1,1,151581.79,0 -8586,15737047,Weatherford,754,France,Female,45,6,0,1,1,0,73881.68,1 -8587,15694039,Jen,650,Germany,Female,46,9,149003.76,2,1,0,176902.83,0 -8588,15649457,Macleod,588,Germany,Male,41,2,131341.46,2,0,1,7034.94,0 -8589,15742809,Mironova,712,Spain,Female,29,7,77919.78,1,1,0,122547.58,0 -8590,15637829,Sharpe,691,France,Female,34,7,0,2,0,1,161559.12,0 -8591,15633194,Osborne,771,France,Female,41,10,108309,4,1,1,137510.41,1 -8592,15611635,Chu,678,Spain,Female,39,6,0,1,0,1,185366.56,0 -8593,15638774,Chong,719,Spain,Female,40,9,0,2,1,0,182224.14,0 -8594,15722037,Alvarez,610,Germany,Male,36,7,115462.02,1,0,1,42581.04,0 -8595,15672930,Palerma,722,Spain,Male,37,9,0,2,1,0,31921.95,0 -8596,15668774,Chiemenam,758,Germany,Female,23,5,122739.1,1,1,0,102460.84,1 -8597,15780966,Pritchard,709,France,Female,32,2,0,2,0,0,109681.29,0 -8598,15659694,Wallis,634,Germany,Female,53,3,113781.5,2,1,1,106345.05,1 -8599,15624424,Palerma,678,Spain,Female,49,1,0,2,1,1,102472.9,0 -8600,15708713,Hill,633,France,Male,35,3,0,2,1,1,36249.76,0 -8601,15755405,Hudson,710,France,Male,43,9,128284.45,1,1,0,32996.89,1 -8602,15647570,Chung,640,Germany,Male,45,8,120591.19,1,0,0,195123.94,0 -8603,15684348,Zhdanova,656,France,Male,63,8,0,2,0,1,57014.43,0 -8604,15702541,Fraser,551,France,Female,59,2,166968.28,1,1,0,159483.76,1 -8605,15646942,Meng,786,Spain,Female,39,7,0,2,0,0,100929.59,0 -8606,15748920,Cherkasova,561,France,Female,49,8,0,2,1,1,12513.07,0 -8607,15694581,Rawlings,807,Spain,Male,42,5,0,2,1,1,74900.9,0 -8608,15643215,Jen,602,Germany,Male,38,2,71667.97,2,0,0,137111.89,0 -8609,15649060,Chien,727,Germany,Female,31,3,82729.47,2,1,0,60212.51,0 -8610,15774258,Gorbunov,678,France,Male,40,1,0,2,1,1,187343.4,0 -8611,15731553,Lucas,730,France,Male,23,8,0,2,1,0,183284.53,0 -8612,15617029,Young,596,Spain,Female,30,1,0,2,1,0,8125.39,0 -8613,15780716,Colombo,686,Germany,Male,39,3,129626.19,2,1,1,103220.56,0 -8614,15577018,Tsao,684,Germany,Female,26,2,114035.39,1,0,0,96885.19,0 -8615,15809515,Lewis,797,Germany,Male,32,1,151922.94,1,1,0,8877.06,0 -8616,15789924,Hussain,658,France,Female,39,4,0,1,1,1,147530.06,0 -8617,15725076,Anderson,653,Spain,Female,27,6,107751.68,2,1,1,33389.42,0 -8618,15672481,Ulyanov,641,France,Male,37,6,0,2,1,0,45309.24,0 -8619,15574115,Shaw,656,Spain,Female,41,6,101179.23,2,1,1,35230.61,0 -8620,15661830,Lucciano,750,Spain,Female,36,6,0,2,1,1,59816.41,0 -8621,15665879,Gordon,768,France,Female,40,8,0,2,0,1,69080.46,0 -8622,15673820,Woodward,568,France,Male,33,7,0,2,1,0,143450.61,0 -8623,15747772,Cunningham,706,Germany,Male,36,9,58571.18,2,1,0,40774.01,0 -8624,15666197,Boni,430,Germany,Female,38,8,153058.64,1,1,0,99377.27,0 -8625,15773639,Truscott,745,Germany,Male,35,4,98270.34,1,1,0,133617.43,0 -8626,15581893,Ginikanwa,747,France,Male,43,1,130788.71,1,0,1,101495,1 -8627,15672447,Bailey,657,Germany,Male,40,7,99165.84,1,0,1,119333.95,1 -8628,15777830,Hutchinson,639,France,Female,42,4,0,2,0,0,167682.37,0 -8629,15713890,Maclean,704,France,Male,44,3,0,2,0,1,152884.85,0 -8630,15577598,Chiang,651,Spain,Male,23,4,115636.05,2,1,0,70400.86,0 -8631,15786042,Willmore,706,Germany,Female,44,2,185932.18,2,1,0,65413.41,0 -8632,15753462,Godson,632,Germany,Male,30,2,72549,2,0,1,182728.8,0 -8633,15759690,Smith,751,France,Male,42,4,0,2,1,1,81442.6,0 -8634,15801414,Bitter,767,France,Female,35,2,0,2,0,0,144251.38,0 -8635,15656141,Ts'ao,741,France,Male,39,5,0,1,0,1,40207.06,0 -8636,15608701,Chialuka,651,Germany,Male,29,3,121890.06,1,1,0,54530.51,1 -8637,15582892,Scott,601,France,Male,46,2,99786.07,1,1,1,32683.88,1 -8638,15632967,Feng,520,France,Male,34,3,0,2,1,1,104703.96,0 -8639,15587573,Castiglione,626,Germany,Male,27,4,115084.53,2,0,1,26907.43,0 -8640,15654891,He,811,France,Male,30,6,0,2,1,1,180591.32,0 -8641,15611365,Fanucci,730,France,Female,32,9,127661.69,1,0,0,60905.51,0 -8642,15749103,Ginikanwa,604,Germany,Female,47,4,118907.6,1,0,1,47777.15,1 -8643,15810203,Manning,499,Germany,Female,44,6,77627.33,2,1,0,108222.68,0 -8644,15813660,Forlonge,754,Spain,Male,40,2,160625.17,1,0,1,3554.63,0 -8645,15605673,Liang,716,Spain,Female,29,8,0,2,0,0,78616.92,0 -8646,15669282,Uchechukwu,636,France,Female,20,10,124266.86,1,0,0,100566.81,0 -8647,15792726,Sung,470,France,Female,25,8,127974.06,2,1,1,183259.35,0 -8648,15593241,Tochukwu,444,France,Male,43,3,0,2,1,1,159131.21,0 -8649,15683053,Reyna,809,Spain,Female,48,2,0,1,1,0,160976.85,1 -8650,15632736,Liang,850,Germany,Female,30,3,104911.35,2,1,1,42933.26,0 -8651,15731865,Unwin,637,France,Male,27,1,0,2,1,0,91291.2,0 -8652,15760450,Rutherford,512,France,Male,43,1,0,2,1,1,52471.36,0 -8653,15787204,Howe,774,Spain,Female,43,1,110646.54,1,0,0,108804.28,0 -8654,15650454,Tran,641,France,Male,57,5,0,2,1,1,122449.18,0 -8655,15573730,Thompson,586,Germany,Male,42,6,126704.49,2,1,0,41682.3,0 -8656,15705050,Linger,611,France,Male,30,9,0,2,1,1,148887.69,0 -8657,15791342,Johnston,660,Spain,Male,31,1,84560.04,1,1,1,137784.25,0 -8658,15684316,Udokamma,532,France,Male,43,9,0,2,0,0,190573.91,1 -8659,15700540,Barrera,557,Germany,Female,38,2,129893.56,1,0,0,102076.03,0 -8660,15770631,Sutherland,730,Spain,Male,25,5,167385.81,1,1,1,56307.51,0 -8661,15790594,Bednall,535,France,Female,27,6,0,2,0,1,49775.58,0 -8662,15604020,Otoole,773,Germany,Female,36,4,105858.71,1,0,1,4395.45,0 -8663,15637599,Cremonesi,510,Germany,Female,44,4,123070.89,1,1,0,28461.29,1 -8664,15736578,Hamilton,539,France,Male,39,1,0,1,1,1,28184.7,0 -8665,15666332,Donaldson,690,Spain,Female,48,2,0,2,1,1,3149.1,0 -8666,15727291,McKay,821,France,Female,40,1,0,2,1,0,194273.12,0 -8667,15785920,Black,687,Germany,Male,35,1,125141.24,2,1,1,148537.07,0 -8668,15658987,Kane,557,France,Female,46,4,96173.17,2,1,1,116378.31,0 -8669,15687719,She,532,Spain,Female,37,5,0,2,0,1,6761.84,0 -8670,15799641,Bruno,540,Spain,Male,39,2,0,2,1,0,81995.92,0 -8671,15758702,Watson,705,France,Female,55,8,0,2,1,1,14392.68,0 -8672,15689526,Shih,542,Germany,Female,35,9,127543.11,2,1,0,468.94,1 -8673,15586848,Rose,706,France,Male,38,1,0,2,1,0,122379.54,0 -8674,15707637,Zikoranachukwudimma,765,France,Female,56,1,0,1,1,0,13228.93,1 -8675,15719426,Cole,529,France,Male,67,8,103101.56,2,1,1,154002.02,1 -8676,15639265,Isaacs,714,France,Male,54,7,126113.28,1,1,0,112777.38,0 -8677,15576124,Muravyova,582,France,Male,41,1,40488.76,1,1,0,128528.83,0 -8678,15757829,Timperley,609,Germany,Female,40,10,137389.77,2,1,0,170122.22,0 -8679,15633227,Kenechukwu,518,France,Female,28,9,85146.36,1,0,0,2803.89,0 -8680,15753092,He,791,Germany,Male,35,5,129828.58,1,1,1,181918.26,1 -8681,15782939,Storey,747,France,Male,42,4,80214.36,1,1,0,115241.96,1 -8682,15746338,Onyekachukwu,565,France,Female,40,2,0,2,1,1,129956.13,0 -8683,15590676,Kharlamova,735,France,Male,34,1,141796.43,1,1,0,45858.49,0 -8684,15599329,Christopher,697,France,Female,49,7,195238.29,4,0,1,131083.56,1 -8685,15783097,Lombardo,813,Germany,Male,27,6,111348.15,1,1,0,46422.46,0 -8686,15597885,Kerr,772,France,Male,43,6,0,2,1,1,57675.88,0 -8687,15597467,Duncan,606,France,Female,71,8,0,2,1,1,169741.96,0 -8688,15724764,Lawley,667,Germany,Female,42,10,64404.26,2,0,0,26022.37,0 -8689,15778418,Burns,637,Germany,Male,40,9,154309.67,1,1,1,125334.16,1 -8690,15684769,Whitson,542,France,Male,67,10,129431.36,1,0,1,21343.74,0 -8691,15756167,Doyne,762,Spain,Female,43,5,134204.67,1,1,1,139971.01,0 -8692,15632439,Pinto,698,France,Female,39,4,0,2,0,1,47455.82,0 -8693,15755138,Chin,850,France,Female,32,8,0,2,1,1,55593.8,0 -8694,15659092,Davide,621,France,Female,50,5,0,2,1,0,191756.54,1 -8695,15742116,Torres,671,Germany,Female,48,9,116711.06,2,0,0,76373.38,0 -8696,15801994,Buccho,775,France,Male,31,9,0,2,1,0,169278.51,0 -8697,15647572,Greece,504,Spain,Male,34,0,54980.81,1,1,1,136909.88,0 -8698,15644551,Wimble,751,Spain,Female,37,3,99773.85,2,1,0,54865.92,0 -8699,15709135,Pirozzi,691,Germany,Male,30,7,101231.77,2,0,0,156529.44,0 -8700,15684469,Hsiung,841,Germany,Male,32,2,117070.21,1,1,0,113482.2,0 -8701,15627637,Obioma,709,Germany,Male,23,8,73314.04,2,1,0,63446.47,0 -8702,15667093,Onio,673,France,Male,37,2,0,1,1,1,13624.02,0 -8703,15690589,Udinesi,541,France,Male,37,9,212314.03,1,0,1,148814.54,0 -8704,15595350,Fermin,661,France,Female,31,3,136067.82,2,1,0,65567.91,0 -8705,15777586,Moss,784,Spain,Female,42,2,109052.04,2,1,0,6409.55,0 -8706,15804064,Docherty,742,France,Female,35,2,79126.17,1,1,1,126997.53,0 -8707,15717770,Marcelo,850,Spain,Female,55,7,0,1,0,0,171762.87,1 -8708,15754443,Fadden,443,France,Female,35,9,108308,1,1,0,129031.19,1 -8709,15776939,Zox,778,Germany,Female,48,3,102290.56,2,1,0,182691.31,0 -8710,15713517,Otitodilinna,529,France,Male,39,6,102025.08,2,1,0,12351.01,0 -8711,15683522,Kennedy,678,Germany,Female,37,2,113383.07,1,1,1,135123.96,0 -8712,15673995,Tu,516,Spain,Female,65,9,102541.1,1,1,0,181490.42,0 -8713,15771054,Barnes,469,Spain,Male,35,5,0,2,1,0,186490.37,0 -8714,15578788,Bibi,786,Spain,Male,40,6,0,2,0,0,41248.8,0 -8715,15737408,L?,703,France,Female,41,6,109941.51,1,1,0,116267.28,0 -8716,15750837,Landseer,579,Germany,Male,41,0,141749.68,1,0,1,9201.53,0 -8717,15576022,Nwachinemelu,565,France,Male,38,5,0,2,0,1,80630.32,0 -8718,15635502,Ch'iu,443,France,Male,44,2,0,1,1,0,159165.7,0 -8719,15627298,Vinogradova,589,France,Male,37,7,85146.48,2,1,0,86490.09,1 -8720,15811415,Jenks,691,France,Female,44,6,134066.1,2,1,1,197572.41,0 -8721,15645059,Crace,711,France,Female,28,8,0,2,0,0,105159.89,0 -8722,15689671,Packham,775,Spain,Male,27,4,0,1,1,1,40807.26,0 -8723,15718667,T'ien,621,France,Male,35,7,87619.29,1,1,0,143.34,0 -8724,15803202,Onyekachi,350,France,Male,51,10,0,1,1,1,125823.79,1 -8725,15593683,Solomina,668,Spain,Female,30,8,0,2,1,0,138465.7,0 -8726,15703394,Hawes,633,Spain,Male,27,3,0,2,1,0,44008.91,0 -8727,15570289,Benson,697,Germany,Male,43,8,103409.16,1,1,0,66893.28,1 -8728,15567437,Emenike,734,Germany,Female,30,7,123040.38,1,1,1,76503.06,0 -8729,15711687,Nero,434,France,Male,41,4,108128.52,1,0,1,56784.11,0 -8730,15656592,Toscano,646,Germany,Male,48,8,169023.33,2,1,1,175657.55,0 -8731,15634373,Yang,764,France,Male,30,5,0,2,0,1,105155.66,0 -8732,15769125,Palerma,727,Spain,Female,41,10,0,2,0,1,47468.56,0 -8733,15711386,Trentini,724,France,Female,29,6,0,2,0,1,64729.51,0 -8734,15714241,Haddon,749,Spain,Male,42,9,222267.63,1,0,0,101108.85,1 -8735,15642530,Coates,706,Germany,Female,47,10,144090.42,1,1,0,140938.95,1 -8736,15713599,Castiglione,728,France,Male,30,10,114835.43,1,0,1,37662.49,0 -8737,15744770,Stone,636,France,Male,44,2,0,2,0,0,86414.41,0 -8738,15780498,Maynard,634,France,Male,34,3,145030.92,1,1,1,41820.65,0 -8739,15624397,Moore,627,France,Male,43,8,71240.3,1,0,1,127734.16,0 -8740,15615219,Obielumani,518,France,Male,59,5,138772.15,1,0,1,123872,0 -8741,15570908,Harding,687,Spain,Female,29,7,93617.07,1,0,1,113050.92,0 -8742,15762855,Hill,622,Spain,Female,23,8,0,2,1,1,131389.39,0 -8743,15661827,Brown,693,Spain,Female,45,4,0,2,1,1,26589.56,0 -8744,15746035,Pagnotto,450,Spain,Male,25,9,74237.2,2,0,1,195463.35,0 -8745,15691906,Esposito,664,Germany,Female,49,5,127421.78,2,1,0,108876.75,1 -8746,15793424,Tan,663,Spain,Female,28,8,61274.7,2,1,0,136054.45,0 -8747,15577905,Hammond,660,France,Male,34,8,106486.66,2,0,1,182262.66,0 -8748,15667216,Chung,579,France,Female,29,10,73194.52,2,1,1,129209.09,0 -8749,15673971,Houghton,655,Germany,Female,44,6,146498.76,1,1,0,64853.51,1 -8750,15701238,Chia,683,France,Male,47,1,0,2,1,0,148989.15,0 -8751,15644849,Zikoranachidimma,655,France,Female,32,2,0,1,1,1,71047.51,0 -8752,15635531,Boag,575,Spain,Female,30,8,0,2,1,0,185341.63,0 -8753,15632263,Pagnotto,574,Spain,Male,30,5,120355,1,1,0,137793.35,0 -8754,15720110,Oluchukwu,795,France,Male,32,2,117265.21,1,1,1,198317.23,0 -8755,15619045,Baxter,776,France,Female,43,4,0,2,0,1,162137.5,0 -8756,15697510,Tien,707,Spain,Female,52,7,0,1,1,0,109688.82,1 -8757,15784923,Chimezie,705,Germany,Female,37,3,109974.22,1,1,1,36320.87,1 -8758,15567383,Slone,678,Germany,Female,44,2,98009.13,2,0,1,31384.86,0 -8759,15732621,Martin,663,France,Male,34,10,0,1,1,1,114083.73,0 -8760,15757981,Loggia,748,France,Male,66,8,0,1,1,1,163331.65,0 -8761,15727819,Hartley,677,Spain,Female,34,10,171671.9,1,1,1,50777.77,0 -8762,15738088,Parkin,634,Spain,Male,63,10,0,2,1,0,30772.86,1 -8763,15765173,Lin,350,France,Female,60,3,0,1,0,0,113796.15,1 -8764,15665159,Brooks,727,France,Male,61,0,128213.96,2,1,1,188729.08,1 -8765,15618203,Tien,773,Germany,Male,51,8,116197.65,2,1,1,86701.4,0 -8766,15791452,Dann,675,France,Male,39,1,0,2,1,0,153129.22,0 -8767,15638159,Trentino,649,Spain,Female,36,6,86607.39,1,0,0,19825.09,0 -8768,15585466,Russo,552,France,Male,29,10,0,2,1,0,12186.83,0 -8769,15677310,Christie,761,Germany,Male,62,5,98854.34,1,0,0,86920.97,1 -8770,15646262,Ross,622,France,Male,31,7,0,1,1,0,35408.77,0 -8771,15656901,Nnonso,615,France,Male,59,8,0,2,1,1,165576.55,0 -8772,15621093,Teng,681,Germany,Male,31,4,97338.19,2,0,0,48226.76,0 -8773,15592123,Buccho,768,France,Male,30,6,0,2,1,1,199454.37,0 -8774,15589200,Madukaife,617,Spain,Male,34,9,0,2,1,0,118749.58,0 -8775,15602934,Dunn,452,France,Female,33,6,131698.57,2,1,0,151623.91,0 -8776,15812720,Hooker,807,Germany,Male,37,10,130110.45,2,0,1,172097.95,0 -8777,15695383,Griffin,567,Spain,Male,44,9,0,2,1,0,87677.15,0 -8778,15723064,Kistler,603,Spain,Male,24,1,165149.13,2,1,0,21858.28,0 -8779,15761606,Law,617,Spain,Female,37,9,101707.8,1,1,0,123866.28,0 -8780,15650322,Grigoryeva,701,France,Female,34,3,105588.66,1,0,1,74694.41,0 -8781,15669782,Chu,820,Germany,Male,39,9,111336.89,1,1,0,16770.31,1 -8782,15751628,Onyemachukwu,438,France,Male,60,7,78391.17,1,0,1,49424.6,0 -8783,15809057,Lu,600,Spain,Female,27,6,0,2,1,1,172031.22,0 -8784,15617052,Watson,782,France,Male,34,9,0,1,1,0,183021.06,1 -8785,15590810,Fallaci,638,Germany,Female,41,9,144326.09,1,1,0,73979.85,1 -8786,15801293,Ni,850,Germany,Male,27,1,101278.25,2,1,1,26265.18,0 -8787,15770968,Leason,741,Germany,Female,19,8,108711.57,2,1,0,24857.25,0 -8788,15572356,Tsai,689,Spain,Male,73,1,108555.07,1,0,1,167969.15,0 -8789,15603247,Bruner,743,Germany,Female,35,1,146781.24,1,1,0,189307.7,0 -8790,15619116,Wallace,493,France,Female,36,2,0,2,0,1,99770.3,0 -8791,15691792,Young,416,Spain,Male,35,8,0,1,0,0,119712.78,0 -8792,15783276,Forbes,725,France,Female,25,9,0,2,1,1,168607.74,0 -8793,15766137,Muir,497,France,Male,34,2,0,2,1,1,83087.13,0 -8794,15574554,Pugh,537,Germany,Male,66,8,103291.25,2,1,1,130664.79,0 -8795,15578671,Webb,706,Spain,Female,29,1,209490.21,1,1,1,133267.69,1 -8796,15716608,Walker,651,Spain,Male,38,2,0,3,1,0,67029.82,1 -8797,15690670,Cox,720,France,Male,33,2,0,2,0,1,141031.08,0 -8798,15630466,Maclean,797,France,Male,45,8,0,1,0,0,125110.02,0 -8799,15630349,Hollis,543,Spain,Male,23,5,0,2,1,0,117832.39,0 -8800,15803801,Jamieson,454,France,Male,34,4,0,2,1,0,198817.72,0 -8801,15647890,Su,691,France,Male,37,9,149405.18,1,1,1,146411.6,0 -8802,15606115,P'eng,510,France,Female,52,6,191665.21,1,1,1,131312.56,1 -8803,15714642,Hawkins,792,Spain,Female,40,7,0,1,1,0,141652.2,0 -8804,15741181,Ndubuagha,721,France,Male,41,6,135071.12,1,1,1,64477.25,0 -8805,15773973,Hill,765,France,Male,41,2,0,2,0,1,191215.61,0 -8806,15758546,Norton,850,Spain,Male,39,8,0,2,1,1,37090.44,0 -8807,15598940,Achebe,681,Germany,Male,38,6,181804.34,2,1,1,57517.71,0 -8808,15669783,Simpson,586,France,Female,60,3,47020.65,2,0,1,63241.21,1 -8809,15624993,Chiang,753,France,Female,36,7,128518.98,1,1,1,44567.83,1 -8810,15760568,Dalrymple,593,Germany,Female,38,5,142658.04,2,0,1,135337.11,0 -8811,15699047,Chukwuemeka,674,France,Female,21,9,120150.39,2,1,1,33964.03,0 -8812,15616168,Ojiofor,610,France,Female,35,7,81905.95,1,1,1,61623.19,0 -8813,15773146,Rubeo,652,France,Male,26,3,137998.2,2,0,1,168989.77,0 -8814,15770375,Fanucci,850,Germany,Female,26,8,123126.29,1,1,0,74425.41,0 -8815,15589725,Zubarev,740,France,Female,51,4,0,2,1,1,178929.84,0 -8816,15710034,T'ao,637,Germany,Male,43,1,135645.29,2,0,1,101382.86,1 -8817,15800806,Pai,685,Spain,Male,31,7,122449.31,2,1,1,180769.55,0 -8818,15570485,Udegbunam,558,Spain,Male,40,4,161766.87,1,0,0,92378.54,0 -8819,15575391,Claypool,677,France,Female,37,3,0,2,1,1,38252.25,0 -8820,15790750,Manfrin,592,Germany,Male,36,10,123187.51,1,0,1,146111.35,0 -8821,15714832,Baker,652,Germany,Male,36,9,150956.71,1,0,0,72350.17,0 -8822,15619953,Efremov,662,Spain,Female,42,6,105021.28,1,1,0,48242.38,0 -8823,15673929,Chin,543,France,Male,64,4,0,2,1,1,148305.82,0 -8824,15578835,Brookes,675,Spain,Female,50,1,133204.91,1,0,1,8270.06,0 -8825,15752388,Doyle,643,Spain,Female,35,6,0,2,1,1,41549.64,0 -8826,15797081,Ajuluchukwu,611,Germany,Female,49,9,115488.52,2,1,1,138656.81,1 -8827,15570194,Ikemefuna,412,France,Male,29,5,0,2,0,0,12510.53,0 -8828,15580149,Fowler,638,Spain,Male,41,7,0,2,1,0,43889.41,0 -8829,15777708,Liao,824,Spain,Female,38,3,0,2,1,0,192800.25,0 -8830,15769955,Onuora,683,France,Female,40,1,0,2,0,0,75762,0 -8831,15810444,Aksenov,562,Germany,Female,39,6,130565.02,1,1,0,9854.72,1 -8832,15645593,Trevisani,599,France,Female,41,2,91328.71,1,1,0,115724.78,0 -8833,15765345,Wood,753,France,Male,35,4,0,2,1,1,106303.4,0 -8834,15760873,Lombardo,594,France,Male,50,7,81310.34,1,1,1,183868.01,0 -8835,15794178,Walpole,657,France,Male,34,3,107136.6,1,1,0,153895.46,0 -8836,15589361,Chikwendu,716,Spain,Male,34,9,0,1,1,1,66695.71,0 -8837,15662483,Ko,850,France,Male,43,7,0,2,1,1,173851.11,0 -8838,15809736,Steigrad,664,France,Male,46,2,0,1,1,1,177423.02,1 -8839,15731148,Isayeva,558,France,Male,33,0,108477.49,1,1,1,109096.71,1 -8840,15774328,Boni,606,Germany,Male,40,1,144757.97,2,1,1,166656.18,0 -8841,15646969,Anayolisa,776,Spain,Male,33,2,0,2,1,1,176921,0 -8842,15718769,Fallaci,557,Spain,Male,36,1,113110.26,1,1,0,98413.1,0 -8843,15610226,Fenton,614,France,Female,27,9,106414.57,2,0,0,77500.81,0 -8844,15616270,Chao,620,Spain,Male,42,4,106920.91,1,0,1,119747.08,0 -8845,15790717,Osinachi,695,Spain,Male,35,7,0,2,1,0,160387.98,0 -8846,15635703,Chu,729,Germany,Female,39,1,131513.26,1,1,1,193715,0 -8847,15616365,Obiuto,571,France,Female,53,2,0,2,1,0,28045.77,0 -8848,15630244,Chu,457,France,Male,40,10,134320.23,2,1,0,150757.35,0 -8849,15734714,Nash,559,France,Female,29,3,79715.36,1,1,0,82252.28,0 -8850,15721433,Hixson,664,France,Female,38,4,74306.19,2,1,0,154395.56,0 -8851,15590201,Fiorentini,500,Spain,Female,50,5,0,4,1,1,83866.35,1 -8852,15590828,Chidimma,782,Germany,Male,42,7,126428.38,1,1,0,39830.1,0 -8853,15752097,Chiazagomekpere,708,Spain,Male,38,8,99640.89,1,1,0,12429.22,0 -8854,15800031,Laura,681,France,Male,43,3,66338.68,1,1,1,18772.5,1 -8855,15630857,Wu,674,Spain,Female,39,6,0,2,1,1,9574.83,0 -8856,15689953,Toscani,697,Spain,Male,43,10,128226.37,1,0,0,188486.94,0 -8857,15759733,McMillan,774,France,Female,26,5,0,2,1,1,64716.08,0 -8858,15810826,Chiekwugo,624,France,Male,36,6,0,2,0,0,84749.96,0 -8859,15668009,Hendley,747,Spain,Male,37,1,0,2,0,1,180551.76,0 -8860,15743456,Birnie,715,France,Female,32,10,0,2,1,0,60907.49,0 -8861,15725762,Kemp,808,France,Male,24,4,122168.65,1,1,0,174107.04,0 -8862,15761713,Johnstone,678,France,Female,43,7,178074.33,1,0,0,110405.9,0 -8863,15769246,Lo Duca,813,Germany,Male,59,2,135078.41,1,1,0,187636.06,1 -8864,15781129,Montgomery,687,Spain,Male,38,8,69434.4,2,1,1,66580.13,1 -8865,15599124,Miller,832,France,Female,29,5,0,2,1,0,178779.52,0 -8866,15639004,Chiemezie,668,France,Male,72,2,0,2,1,1,70783.61,0 -8867,15810995,Wright,526,Germany,Male,34,3,122726.56,1,1,1,46772.36,0 -8868,15653773,Shaw,457,France,Female,38,7,164496.99,1,1,1,163327.27,0 -8869,15708357,Chapman,649,Spain,Female,38,8,0,1,1,0,103760.53,0 -8870,15733597,Y?an,669,France,Female,41,0,150219.41,2,0,0,107839.03,0 -8871,15789560,Clark,668,France,Male,42,8,187534.79,1,1,1,32900.41,1 -8872,15699524,Howells,466,France,Female,30,3,0,1,1,0,193984.6,0 -8873,15626475,Gamble,685,France,Male,30,2,0,2,1,1,140889.32,0 -8874,15810839,Rogers,610,France,Male,34,0,103108.17,1,0,0,125646.82,0 -8875,15684318,McMillan,582,Germany,Female,50,6,96486.57,2,1,1,20344.02,0 -8876,15768120,Brown,702,Germany,Male,36,9,90560.48,2,1,0,174268.87,0 -8877,15712807,Robertson,556,Spain,Male,46,3,131764.96,1,1,1,108500.66,1 -8878,15696371,Thomas,812,Spain,Female,24,1,92476.88,1,0,0,83247.14,0 -8879,15675794,Hsing,645,Germany,Male,47,9,152076.93,1,1,0,121840.2,1 -8880,15774277,Chiu,809,France,Male,43,2,0,2,1,1,132908.07,0 -8881,15603764,Chang,560,France,Male,49,4,0,1,1,1,100075.1,1 -8882,15618647,Kornilova,744,France,Male,29,1,43504.42,1,1,1,119327.75,0 -8883,15614643,Chifo,731,Spain,Female,39,2,0,2,1,0,136737.13,0 -8884,15707696,Lu,471,Spain,Female,28,5,0,2,1,1,22356.97,0 -8885,15749583,Bellucci,686,Germany,Female,38,2,93569.86,3,0,0,10137.34,1 -8886,15815125,Michael,668,Spain,Male,45,4,102486.21,2,1,1,158379.25,0 -8887,15779620,Sinclair,575,France,Male,36,1,0,1,0,1,94570.56,0 -8888,15768233,Chukwuebuka,435,Germany,Male,37,8,114346.3,1,0,1,980.93,1 -8889,15637788,Schmidt,743,France,Male,23,3,110203.77,1,1,0,95583.45,0 -8890,15777046,Parry,580,France,Female,39,9,128362.59,1,1,0,86044.98,0 -8891,15788723,McIntyre,599,Germany,Female,49,10,143888.22,2,1,1,166236.38,1 -8892,15790489,Lo Duca,534,Spain,Male,34,5,170600.78,1,0,1,5240.53,0 -8893,15739476,Ferrari,680,France,Female,32,5,0,1,1,1,150684.23,0 -8894,15612670,Berry,631,Spain,Female,46,10,0,2,1,1,129508.96,0 -8895,15631222,Cattaneo,485,France,Female,39,2,75339.64,1,1,1,70665.16,0 -8896,15658972,Foster,699,France,Female,40,8,122038.34,1,1,0,102085.35,0 -8897,15724691,Gordon,712,France,Male,34,1,0,2,1,1,195052.12,0 -8898,15740442,May,603,France,Male,51,8,186825.57,1,1,0,93739.71,1 -8899,15760427,Cameron,850,France,Male,40,6,124788.18,1,1,0,65612.12,0 -8900,15677939,Ch'eng,584,France,Female,41,3,0,2,1,1,160095.48,0 -8901,15611599,Curtis,604,France,Female,71,2,0,2,1,1,49506.82,0 -8902,15633474,Whitehead,586,France,Male,51,2,138553.57,1,1,1,92406.22,0 -8903,15671973,Chukwuemeka,467,Spain,Male,39,5,0,2,1,1,7415.96,0 -8904,15790019,Onwughara,520,France,Male,35,9,105387.89,1,1,1,25059.06,0 -8905,15737735,Grant,683,Spain,Male,40,4,95053.1,1,1,1,116816.54,1 -8906,15661745,Browne,557,France,Male,36,3,0,1,0,1,144078.02,0 -8907,15797065,Goloubev,613,Spain,Female,32,0,0,2,0,1,126675.62,0 -8908,15710671,Gordon,786,France,Male,34,3,137361.96,1,0,0,183682.09,0 -8909,15656522,Sutherland,593,Spain,Male,32,10,158537.42,1,1,0,166850.57,0 -8910,15705085,Quesada,670,Spain,Female,29,9,0,2,1,0,27359.19,0 -8911,15744873,Wright,657,Germany,Female,48,5,143595.87,1,0,0,101314.65,1 -8912,15781914,Simmons,718,Germany,Male,32,9,169947.41,2,1,1,27979.16,0 -8913,15637354,Yobachukwu,623,France,Female,24,7,148167.83,2,1,1,109470.34,0 -8914,15717307,Read,496,France,Male,31,5,0,2,1,0,93713.13,0 -8915,15746695,Wunder,429,France,Female,39,6,48023.83,1,1,0,74870.99,0 -8916,15804962,Nnaife,606,France,Male,36,1,155655.46,1,1,1,192387.51,1 -8917,15665378,Shen,499,France,Female,46,6,0,2,1,0,73457.55,0 -8918,15757865,Powell,642,France,Male,62,7,0,2,1,1,61120.75,0 -8919,15578787,Goddard,641,France,Female,52,4,0,1,1,0,90964.54,1 -8920,15794323,Buckley,673,France,Male,32,8,121240.76,1,1,0,116969.73,0 -8921,15697546,McIntyre,570,France,Female,36,3,0,2,1,0,92118.75,0 -8922,15629519,Yen,472,France,Female,37,1,0,2,1,1,48357.9,0 -8923,15624703,Okonkwo,550,Germany,Male,35,9,129847.75,2,1,0,197325.4,0 -8924,15570002,Burlingame,625,Germany,Female,55,8,118772.71,4,0,0,135853.62,1 -8925,15808566,Hs?,516,France,Male,46,2,0,2,1,1,169122.54,0 -8926,15805463,Board,682,Germany,Male,32,2,105163.88,2,1,1,164170.46,0 -8927,15709136,Adams,620,France,Male,28,8,0,2,1,1,199909.32,0 -8928,15801605,Rizzo,626,France,Female,39,0,0,2,1,1,83295.09,0 -8929,15567855,Chukwufumnanya,623,France,Female,29,1,0,2,0,0,39382.06,0 -8930,15675141,Fraser,569,France,Female,35,4,93934.63,1,1,0,184748.23,0 -8931,15665759,Russell,724,France,Female,69,5,117866.92,1,1,1,62280.91,0 -8932,15761487,Yefimova,678,France,Female,55,5,0,1,0,1,196794.11,1 -8933,15700394,Palermo,713,Spain,Female,26,4,122857.46,2,1,0,144682.17,1 -8934,15631162,Bergamaschi,631,France,Male,32,10,0,2,0,1,196342.66,0 -8935,15630641,Shao,846,France,Female,37,6,127103.97,1,1,1,41516.44,0 -8936,15585066,Chimaraoke,660,France,Female,43,1,0,1,0,1,112026.1,1 -8937,15722991,McGregor,567,France,Male,54,9,96402.96,1,0,0,52035.29,1 -8938,15737404,Kesteven,731,France,Male,31,1,132512.26,1,1,1,185466.85,0 -8939,15722409,Ritchie,693,Spain,Male,47,8,107604.66,1,1,1,80149.27,0 -8940,15806420,Jenks,772,France,Male,34,9,0,2,1,0,170980.86,0 -8941,15658148,Udokamma,657,France,Male,38,7,0,2,1,0,185827.74,0 -8942,15810660,Boyle,774,Germany,Male,34,4,120875.23,2,0,1,113407.26,0 -8943,15709780,Azuka,667,France,Female,37,9,71786.9,2,1,1,67734.79,0 -8944,15727350,Pai,516,France,Female,37,8,113143.12,1,0,0,3363.36,0 -8945,15752312,Howells,551,Spain,Male,49,1,150777.72,2,1,1,135757.27,0 -8946,15616745,Hs?,542,Spain,Male,35,2,174894.53,1,1,1,22314.55,0 -8947,15572294,Kelly,623,France,Male,28,7,0,1,0,0,129526.57,0 -8948,15674110,Walton,701,France,Female,43,2,160416.56,1,0,1,37266.43,0 -8949,15662501,Ebelechukwu,583,France,Male,48,3,91246.53,1,1,0,60017.46,1 -8950,15649239,Vasilieva,731,Spain,Male,46,10,0,2,1,0,153015.42,0 -8951,15700424,Hsiao,461,France,Female,35,5,0,1,1,1,54209.02,0 -8952,15636388,Abrego,702,Germany,Female,23,7,98775.23,1,1,0,114603.96,0 -8953,15713975,Gibson,565,Germany,Female,47,10,139756.12,1,1,0,165849.49,1 -8954,15592925,Giordano,711,Spain,Male,42,3,177626.77,3,0,1,16392.72,1 -8955,15581626,Mancini,664,France,Male,54,8,0,1,1,1,162719.69,1 -8956,15641319,Afanasyeva,518,Spain,Male,50,4,0,1,0,0,107112.25,1 -8957,15723481,Wright,728,Spain,Male,42,8,0,2,0,1,41823.22,0 -8958,15787825,Okwudiliolisa,585,Germany,Male,37,6,152496.82,1,1,1,99907.29,0 -8959,15710726,Hughes,573,France,Male,52,8,0,2,0,1,178229.04,0 -8960,15627195,Parrott,568,Germany,Male,26,1,112930.28,2,1,0,22095.73,0 -8961,15657957,Hughes,602,Germany,Female,26,8,113674.2,1,1,0,197861.16,1 -8962,15676117,Zinachukwudi,603,France,Male,44,9,0,1,1,0,138328.24,0 -8963,15607874,Keane,687,France,Male,38,0,144450.58,1,0,1,137276.83,0 -8964,15796993,McCollum,741,France,Male,52,1,171236.3,2,0,0,21834.4,1 -8965,15649858,Simpson,469,Spain,Male,37,9,96776.49,1,1,1,119890.86,0 -8966,15811032,Gambrell,477,Germany,Female,58,8,145984.92,1,1,1,24564.7,0 -8967,15679963,Moretti,737,Germany,Male,43,8,96353.8,1,0,0,10209.8,0 -8968,15579131,Ricci,835,France,Male,25,7,0,2,1,1,83449.65,0 -8969,15572428,Rieke,717,Germany,Female,33,0,115777.23,1,1,1,81508.1,0 -8970,15622461,Ndubuagha,562,France,Female,51,7,122822,2,0,0,32626.21,0 -8971,15636105,Chung,758,Spain,Male,61,2,0,2,1,1,43982.41,0 -8972,15583849,Ts'ai,408,France,Male,40,3,0,2,0,0,124874.23,0 -8973,15718780,Cox,650,Spain,Female,32,4,79450.09,1,1,1,118324.75,0 -8974,15739271,Lei,582,Germany,Male,33,2,122394,1,1,1,22113.93,0 -8975,15697129,Ulyanova,706,Spain,Female,43,1,0,2,1,0,31962.77,0 -8976,15763415,Gray,567,Germany,Male,41,0,134378.89,1,1,1,105746.94,0 -8977,15796617,McGregor,720,France,Male,29,2,0,2,1,0,39925.52,0 -8978,15626628,Tretiakova,631,Spain,Female,31,2,88161.85,2,1,0,127630.88,0 -8979,15765857,Genovesi,623,Spain,Male,41,2,142412.13,1,1,0,28778.98,0 -8980,15742511,Gordon,514,France,Male,35,3,121030.9,1,1,0,10008.68,0 -8981,15786433,Aitken,650,Germany,Female,35,3,165982.43,2,1,1,24482.16,0 -8982,15685805,Ginikanwa,673,Spain,Female,35,6,0,2,1,0,98618.79,0 -8983,15627971,Coates,504,France,Female,32,8,206663.75,1,0,0,16281.94,0 -8984,15783025,Piazza,723,Germany,Male,37,3,94661.53,2,1,0,121239.65,0 -8985,15726289,Cawood,645,France,Male,25,0,174400.36,1,1,0,42669.37,0 -8986,15802118,Ignatieff,664,Spain,Male,41,7,123428.69,1,1,1,164924.11,0 -8987,15607990,Gallo,760,Spain,Male,43,6,175735.5,1,1,1,157337.29,0 -8988,15695932,Yelverton,766,Spain,Male,36,5,78381.13,1,0,1,153831.6,0 -8989,15812279,William,634,France,Male,37,5,115345.86,2,0,0,168781.8,0 -8990,15687558,Mault,640,Germany,Female,31,10,118613.34,1,1,0,168469.65,0 -8991,15729065,Mackay,784,Germany,Male,28,2,109960.06,2,1,1,170829.87,0 -8992,15698902,McIntyre,547,Germany,Female,42,1,142703.4,1,1,0,86207.49,1 -8993,15570192,Henry,608,Germany,Female,40,8,121729.42,1,0,0,61164.45,0 -8994,15809265,Kao,547,France,Female,35,4,0,1,1,1,133287.73,0 -8995,15745201,Frewin,612,France,Female,43,4,139496.35,2,1,1,77128.23,0 -8996,15580623,Yefremova,573,Spain,Male,28,8,0,2,0,0,77660.03,0 -8997,15578156,Anenechukwu,615,Spain,Male,32,5,138521.83,1,1,1,56897.1,0 -8998,15631063,Trentino,710,France,Female,33,2,0,2,1,0,72945.32,0 -8999,15692577,Tomlinson,674,Germany,Female,38,10,83727.68,1,1,0,45418.12,0 -9000,15810910,Royston,702,Spain,Female,38,9,0,2,1,1,158527.45,0 -9001,15723217,Cremonesi,616,France,Male,37,9,0,1,1,0,111312.96,0 -9002,15733111,Yeh,688,Spain,Male,32,6,124179.3,1,1,1,138759.15,0 -9003,15610727,Ch'in,605,France,Male,36,7,128829.25,1,1,0,190588.59,0 -9004,15792720,Martinez,676,France,Male,33,6,171490.78,1,0,0,79099.64,0 -9005,15723153,Wearing,708,Spain,Male,33,3,0,2,1,0,138613.21,0 -9006,15802823,Maclean,745,Spain,Female,38,7,0,2,1,1,194230.82,0 -9007,15756118,T'ao,661,Spain,Male,20,8,0,1,1,0,110252.53,0 -9008,15684934,Rose,726,France,Male,31,9,0,2,1,1,106117.3,0 -9009,15776936,Whitworth,475,France,Male,40,7,160818.08,1,0,1,169642.13,1 -9010,15729087,Suttor,751,Germany,Male,54,9,156367.6,2,0,1,116179.92,0 -9011,15786463,Hsing,645,Germany,Female,59,8,121669.93,2,0,0,91.75,1 -9012,15717498,Boni,775,France,Male,42,6,133970.22,2,0,1,187839.9,0 -9013,15718406,Marshall,540,France,Male,41,3,0,2,1,0,121098.65,0 -9014,15799468,Catchpole,591,France,Female,34,3,96127.27,1,0,0,30972.06,0 -9015,15626383,Tang,596,Spain,Male,60,7,121907.97,1,0,1,30314.04,0 -9016,15597385,Siddons,573,Spain,Male,41,5,0,2,0,1,14479.29,0 -9017,15570271,Wan,577,Spain,Male,31,6,0,1,1,1,196395.25,0 -9018,15690330,Efimov,830,Germany,Female,40,8,77701.64,1,0,1,19512.38,0 -9019,15680611,Rose,663,France,Male,67,9,0,3,1,1,72318.77,0 -9020,15810227,Fanucci,421,France,Male,34,2,0,2,1,1,96615.23,0 -9021,15807194,Iweobiegbulam,718,Spain,Male,34,5,113922.44,2,1,0,30772.22,0 -9022,15712199,Ijendu,655,Germany,Female,61,2,183997.7,2,1,1,161217.18,0 -9023,15694995,O'Sullivan,712,France,Male,23,2,0,2,0,1,66795.78,0 -9024,15723400,Hutchinson,663,France,Male,28,4,0,2,1,1,123969.64,0 -9025,15654772,Kwemto,640,France,Female,47,6,89799.46,2,0,1,13783.77,1 -9026,15574743,Chiu,577,Spain,Male,29,2,0,1,1,1,168924.41,0 -9027,15807593,Berry,546,Spain,Female,36,7,85660.96,1,0,0,134778.01,0 -9028,15686718,Hung,802,Germany,Male,37,9,115569.21,1,0,1,119782.89,0 -9029,15695299,Mordvinova,590,France,Female,45,2,81828.22,1,1,0,52167.97,0 -9030,15722701,Bruno,594,Germany,Male,18,1,132694.73,1,1,0,167689.56,0 -9031,15799635,Arbour,577,Spain,Male,51,2,108867,1,0,0,140800.66,1 -9032,15742323,Barese,541,France,Male,39,7,0,2,1,0,19823.02,0 -9033,15658435,Hingston,781,France,Female,27,5,0,2,0,0,72969.9,0 -9034,15586029,Davis,806,Germany,Male,34,2,96152.68,2,1,0,143711.02,0 -9035,15772337,Lawrence,723,Germany,Female,49,0,153855.52,1,1,1,180862.26,1 -9036,15807555,Chung,535,France,Male,45,2,0,2,1,0,125658.28,0 -9037,15603378,Padovano,768,France,Female,36,3,141334.95,1,0,1,125870.5,0 -9038,15792862,Blinova,653,Germany,Male,41,1,104584.11,1,1,0,15126.32,1 -9039,15657349,Carter,803,Germany,Female,50,8,98173.02,1,0,0,22457.25,1 -9040,15777614,Webb,545,Spain,Female,44,1,0,2,1,1,82614.89,0 -9041,15653952,T'an,581,Germany,Female,38,3,135157.05,1,1,1,32919.42,0 -9042,15724336,Yates,513,Germany,Female,49,5,171601.27,1,1,0,126223.84,0 -9043,15689594,Su,731,France,Male,29,5,179539.2,1,0,0,112010.02,0 -9044,15801920,Christian,727,Germany,Male,39,5,80615.46,2,0,0,180962.32,0 -9045,15653347,Chiu,560,Spain,Male,47,1,0,1,0,0,128882.66,1 -9046,15749951,Sacco,766,Germany,Male,27,5,126285.73,1,1,0,177614.17,1 -9047,15648178,Lettiere,630,Germany,Female,23,4,137964.51,1,0,1,174570.55,0 -9048,15738662,Daluchi,652,Germany,Male,41,9,159434.03,1,1,0,178373.93,0 -9049,15640855,T'ien,729,Germany,Male,40,5,113574.61,2,1,0,103396.08,0 -9050,15584288,Hung,629,France,Female,33,6,0,2,1,1,59129.72,0 -9051,15760988,Liu,667,Germany,Male,33,9,124573.33,2,0,0,683.37,0 -9052,15569624,Feng,671,Germany,Female,31,6,105864.6,2,1,0,145567.34,0 -9053,15597949,Gilbert,768,Germany,Female,47,5,104552.61,1,1,0,48137.08,1 -9054,15604551,Robb,732,France,Female,35,3,0,2,1,0,90876.95,0 -9055,15617476,Manfrin,546,France,Female,30,5,0,2,0,1,198543.09,0 -9056,15645323,Chinwenma,630,France,Male,55,2,0,1,1,1,106202.07,1 -9057,15793311,Smith,765,Germany,Female,46,8,119492.88,2,0,1,166896.01,1 -9058,15764153,Rowe,704,France,Female,33,0,130499.09,2,1,1,74804.36,0 -9059,15802560,Moran,470,Spain,Female,48,6,140576.11,1,1,1,116971.05,0 -9060,15728608,Walker,688,Germany,Female,34,9,91025.58,2,0,1,163783,0 -9061,15770474,Myers,685,France,Female,33,1,0,3,0,1,70221.13,1 -9062,15724444,Wall,567,France,Female,38,1,125877.65,2,1,1,107841.77,0 -9063,15753110,McKay,720,Spain,Male,64,3,45752.78,2,1,0,79623.28,1 -9064,15711521,Egobudike,609,France,Male,39,3,121778.71,1,1,1,138399.67,0 -9065,15632816,Williams,521,Germany,Female,49,2,127948.57,1,1,1,182765.14,0 -9066,15693637,Ochoa,556,France,Female,30,7,0,2,1,1,186648.19,0 -9067,15725509,Otutodilinna,662,Germany,Male,30,5,115286.68,2,1,1,149587.92,0 -9068,15684645,Ajuluchukwu,704,Germany,Male,41,9,62078.21,2,1,0,129050.67,0 -9069,15692235,Bellucci,750,France,Female,38,1,0,2,1,0,47764.99,0 -9070,15777459,Gordon,619,Spain,Female,32,4,175406.13,2,1,1,172792.43,1 -9071,15656937,Johnston,468,Spain,Male,26,1,131643.25,1,1,0,64436.16,0 -9072,15610643,De Luca,435,Germany,Male,44,3,151739.65,1,1,0,167461.5,0 -9073,15777315,Hill,529,France,Male,43,6,93616.35,2,0,0,98348.66,0 -9074,15611058,Eluemuno,702,Germany,Female,60,5,138597.54,2,1,1,41536.59,1 -9075,15630413,Howarth,608,France,Female,41,5,0,2,1,1,72462.25,0 -9076,15635942,Thomson,576,France,Male,40,9,0,2,1,0,112465.19,1 -9077,15648858,King,666,France,Female,27,1,85225.21,1,0,1,64511.44,0 -9078,15810732,Grant,730,France,Female,36,8,148749.29,2,1,0,91830.75,0 -9079,15705448,Gilbert,647,Germany,Male,52,7,130013.12,1,1,1,190806.36,1 -9080,15730488,Richmond,516,Spain,Female,27,1,0,1,0,1,112311.15,0 -9081,15620443,Fiorentino,711,France,Female,81,6,0,2,1,1,72276.24,0 -9082,15741078,Greece,736,France,Male,54,7,111729.47,2,0,1,84920.49,0 -9083,15753161,Dickson,768,France,Female,36,5,180169.44,2,1,0,17348.56,0 -9084,15711396,Henderson,427,Spain,Male,40,8,0,2,1,1,82870.75,0 -9085,15593499,Stevens,686,Spain,Female,47,6,0,1,1,0,32080.69,1 -9086,15579189,Mitchell,690,France,Female,42,5,0,2,0,1,120512.08,0 -9087,15743545,Nworie,647,Spain,Female,29,2,0,2,1,0,179032.68,0 -9088,15791316,Boni,714,France,Male,35,3,0,2,1,1,95623.28,0 -9089,15608246,Wentcher,736,Germany,Female,36,8,103914.17,1,1,1,110035.88,1 -9090,15676526,Bentley,608,France,Female,34,4,88772.87,1,1,1,168822.01,0 -9091,15813911,Hayes-Williams,809,France,Female,39,5,0,1,1,0,77705.75,0 -9092,15630195,Johnstone,745,France,Female,40,6,131184.67,1,1,1,49815.62,0 -9093,15736250,Johnstone,781,France,Male,38,2,117810.79,1,0,1,65632.33,1 -9094,15671334,Nixon,527,France,Male,31,4,0,1,1,0,169361.89,0 -9095,15574169,Trevisano,595,Germany,Female,32,0,92466.21,1,1,0,4721.3,0 -9096,15718839,Tsui,850,Germany,Female,38,2,102741.15,2,0,1,23974.85,0 -9097,15762331,Moss,569,France,Male,37,9,178755.84,1,1,0,199929.17,0 -9098,15606901,Graham,728,France,Male,43,7,0,2,1,0,40023.7,0 -9099,15713559,Onyemauchechukwu,473,Germany,Female,32,5,146602.25,2,1,1,72946.95,0 -9100,15768881,Saunders,738,France,Male,29,2,0,2,1,1,170421.13,0 -9101,15743075,Ko,659,France,Male,35,6,0,2,1,1,58879.11,0 -9102,15660980,Cairns,597,Spain,Male,38,6,115702.67,2,1,1,25059.05,0 -9103,15810942,Chiemela,445,Germany,Female,61,2,137655.31,1,0,1,29909.84,0 -9104,15728362,Robertson,671,France,Female,29,3,0,2,1,0,158043.11,0 -9105,15683339,P'eng,656,Spain,Female,34,6,59877.33,1,1,0,14032.62,1 -9106,15685476,Tseng,658,France,Male,31,5,100082.14,1,0,1,49809.88,0 -9107,15663650,Russell,698,Germany,Male,52,10,107304.39,3,1,0,28806.32,1 -9108,15617434,Yen,655,Spain,Male,38,9,0,1,0,1,90490.33,0 -9109,15622470,Yeh,772,Spain,Male,41,10,96032.22,1,1,1,75825.57,0 -9110,15703682,Kalinina,681,Spain,Male,33,10,0,1,0,0,158336.36,0 -9111,15727391,Collier,688,Germany,Male,29,9,144553.5,2,1,0,143454.95,0 -9112,15711062,Thomas,633,Germany,Male,40,5,86172.81,2,1,1,117279.49,0 -9113,15567339,Shaw,735,France,Male,73,9,0,1,1,1,114283.33,0 -9114,15760662,Francis,521,Germany,Female,29,2,87212.8,1,1,1,994.86,0 -9115,15605737,George,541,France,Male,36,5,0,2,1,0,124795.84,0 -9116,15692977,Ikenna,612,Germany,Female,36,2,130700.92,2,0,0,77592.8,0 -9117,15672082,Schatz,562,France,Male,62,3,0,2,1,0,105986.01,0 -9118,15600280,Tao,703,France,Female,32,6,0,2,0,0,33606.52,0 -9119,15804052,Scott,710,Spain,Male,23,6,0,2,1,1,134188.11,0 -9120,15576065,Sims,731,Spain,Female,40,5,171325.98,1,1,1,159718.27,1 -9121,15796838,Chibugo,703,Spain,Male,58,4,92930.92,1,0,1,85148.78,0 -9122,15693526,Ku,618,France,Female,40,0,0,1,1,0,119059.13,0 -9123,15748595,Stanton,689,France,Female,29,1,77556.79,2,1,1,122998.26,0 -9124,15679029,Kung,718,France,Male,33,7,102874.28,1,0,0,117841.06,0 -9125,15753639,Gibson,608,France,Male,37,5,146093.39,2,0,0,160593.41,0 -9126,15604138,Iheanacho,749,Spain,Male,34,2,0,1,0,0,174189.04,1 -9127,15666095,Costa,753,Spain,Male,51,4,79811.72,2,0,1,68260.27,1 -9128,15643487,Sal,630,Spain,Male,39,10,105473.74,1,0,0,58854.88,1 -9129,15764033,Lin,693,Germany,Female,43,1,121927.92,1,1,0,87994.95,1 -9130,15747288,Ferri,838,Spain,Female,40,6,61671.19,1,0,1,150659.35,1 -9131,15790599,Yin,756,Germany,Female,39,5,149363.12,2,1,1,109098.39,0 -9132,15737705,Avdeyeva,775,France,Female,27,4,152309.37,1,1,0,104112,0 -9133,15737194,Tu,635,France,Female,33,5,0,2,1,0,122949.71,0 -9134,15726776,Donnelly,705,Spain,Male,36,1,111629.29,1,1,1,21807.16,0 -9135,15804357,Loggia,481,France,Male,40,3,0,1,1,1,32319.93,0 -9136,15664432,Chao,727,Spain,Female,49,7,96296.78,1,1,0,190457.87,1 -9137,15688984,Belonwu,595,France,Male,20,4,95830.43,1,1,0,177738.98,0 -9138,15583026,Welch,535,France,Female,38,0,135919.33,1,1,0,80425.65,0 -9139,15771668,Henderson,578,France,Male,59,10,185966.64,1,0,0,9445.42,1 -9140,15779904,Yobanna,597,France,Female,29,5,0,2,1,1,174825.57,0 -9141,15784323,Gallo,449,France,Female,21,7,0,2,0,0,175743.92,0 -9142,15756277,Wilson,850,Germany,Female,43,8,92244.83,2,1,0,54949.73,0 -9143,15663312,Marino,494,France,Female,35,9,112727.06,2,1,0,183752.91,0 -9144,15793197,Bailey,676,France,Female,34,8,100359.54,1,0,0,46038.28,0 -9145,15731463,Gboliwe,818,Germany,Male,43,10,105301.5,1,1,1,78941.59,0 -9146,15621768,Chukwuhaenye,712,Spain,Male,45,6,112994.65,1,0,0,198398.68,0 -9147,15691323,Bianchi,672,Germany,Male,40,4,89025.88,2,1,0,188892.19,0 -9148,15781326,Ford,636,France,Male,35,9,95478.17,1,0,0,169286.74,0 -9149,15595640,Rizzo,698,France,Male,37,8,0,2,0,0,145004.39,0 -9150,15814331,Lung,597,Germany,Female,43,7,119127.46,2,1,0,55809.92,0 -9151,15602030,Ramirez,717,France,Male,28,4,128206.79,1,1,1,54272.12,0 -9152,15747974,Sabbatini,614,France,Male,49,1,0,2,1,0,192440.54,0 -9153,15611315,Ts'ao,708,Germany,Female,23,4,71433.08,1,1,0,103697.57,0 -9154,15636977,Trevisan,507,Germany,Male,36,9,118214.32,3,1,0,119110.03,1 -9155,15690337,Chinwenma,581,France,Female,27,5,102258.11,2,1,0,194681.6,0 -9156,15680666,Berry,579,Spain,Female,39,2,151963.26,2,1,0,158948.63,0 -9157,15679551,Colombo,504,Spain,Female,46,2,163764.84,1,1,1,165122.55,1 -9158,15778915,Harris,737,France,Female,32,7,128551.36,2,0,1,189402.71,0 -9159,15568849,Bryan,540,Spain,Female,31,10,118158.74,1,1,1,158027.57,0 -9160,15747762,Chigozie,609,France,Male,32,7,118520.41,1,0,0,3815.48,0 -9161,15753679,Mullawirraburka,778,France,Male,24,4,0,2,1,1,162809.2,0 -9162,15750049,Steele,621,France,Male,40,10,163823.37,1,0,0,89519.47,0 -9163,15606097,Zakharov,665,Germany,Male,63,7,104469.58,1,1,1,25165.36,1 -9164,15802368,Ch'eng,608,France,Female,47,6,0,1,1,1,126012.57,0 -9165,15767488,Berry,680,Spain,Male,36,7,0,2,1,0,20109.21,0 -9166,15669946,Jen,663,Germany,Female,46,2,141726.88,1,1,1,58257.23,0 -9167,15612103,Wang,627,Germany,Female,35,2,137852.96,1,1,1,172269.21,1 -9168,15645353,Chubb,607,France,Male,26,1,0,1,1,0,29818.2,0 -9169,15650018,Chen,681,France,Female,43,8,154100.3,1,0,0,114659.81,0 -9170,15659002,Mazzanti,766,France,Female,45,6,0,2,0,0,147184.74,0 -9171,15616028,T'ao,694,France,Male,30,2,0,3,0,1,15039.41,0 -9172,15660475,Ndubueze,411,France,Female,54,9,0,1,0,1,76621.49,0 -9173,15652615,Ferri,742,France,Male,39,8,140004.96,1,1,1,92985.78,0 -9174,15653572,Thornton,673,Spain,Male,43,8,127132.96,1,0,1,6009.27,1 -9175,15628059,DeRose,529,France,Male,61,1,0,2,1,1,191370.97,0 -9176,15703413,Montes,519,France,Female,38,7,125328.56,1,1,0,188225.67,0 -9177,15610433,Kwemto,573,France,Male,35,9,0,2,1,0,11743.89,0 -9178,15770548,Lucchese,453,Germany,Female,28,3,139986.65,1,1,0,136846.75,0 -9179,15645637,Huggins,798,Germany,Female,39,6,119787.76,1,1,1,164248.33,0 -9180,15590888,Wade,693,Spain,Female,34,10,107556.06,2,0,0,154631.35,0 -9181,15568326,Kenenna,637,France,Female,44,2,0,2,1,0,149665.65,0 -9182,15655368,Wheeler,672,France,Male,47,1,0,1,0,0,91574.92,0 -9183,15665579,Cartwright,597,France,Female,28,0,142705.95,1,1,0,127233.39,0 -9184,15676091,Iloerika,543,France,Male,42,7,0,1,1,1,56650.47,0 -9185,15716984,Palermo,695,Spain,Female,56,4,0,2,1,0,84644.76,0 -9186,15715078,Nkemakolam,584,France,Male,35,6,161613.94,2,1,1,148238.16,0 -9187,15569452,Butler,652,Germany,Female,58,3,116353.2,2,0,1,193502.9,0 -9188,15628863,Calabresi,601,France,Male,38,4,60013.81,1,1,1,38020.05,0 -9189,15778192,Nkemdilim,628,Spain,Male,28,4,0,2,1,1,176750.81,0 -9190,15793723,Ch'iu,607,Germany,Male,32,9,144272.07,2,1,0,176580.63,0 -9191,15798943,Alexander,646,France,Female,46,8,0,2,1,0,133059.15,0 -9192,15764708,Chiabuotu,572,France,Male,30,6,117696.67,1,1,0,100843.82,0 -9193,15791040,Vasilyeva,801,Spain,Male,58,1,79954.61,2,1,1,30484.19,0 -9194,15631512,Schneider,597,France,Female,26,8,149989.39,1,1,0,42330.58,0 -9195,15640106,Mason,613,France,Male,40,7,124339.9,1,0,0,193309.58,0 -9196,15710315,Chukwukadibia,529,Germany,Male,29,4,135759.4,1,0,0,112813.79,1 -9197,15771535,Tsui,794,Spain,Female,37,9,0,2,1,0,68008.85,0 -9198,15611947,Banks,557,France,Male,34,3,83074,1,1,0,132673.22,0 -9199,15670266,Shih,499,France,Female,28,4,141792.61,1,1,1,22001.91,0 -9200,15609083,Tretiakova,544,France,Female,26,6,0,1,1,0,100200.4,1 -9201,15567923,Barese,739,France,Female,30,6,0,1,0,0,122604.44,0 -9202,15788183,Longo,458,Germany,Female,43,1,106870.12,2,1,0,100564.37,0 -9203,15735782,MacDonald,528,France,Male,31,9,120962.59,1,1,0,5419.31,0 -9204,15774401,Chambers,773,Spain,Male,51,4,0,2,0,0,123587.83,1 -9205,15737971,Cowen,646,France,Female,30,5,0,2,1,0,13935.32,0 -9206,15758750,Iweobiegbunam,564,France,Male,31,0,110527.17,1,1,1,87060.77,0 -9207,15611767,Mai,624,Germany,Female,52,0,133723.43,1,0,0,4859.59,1 -9208,15643770,Yu,682,France,Female,52,5,112670.48,1,1,0,21085.17,1 -9209,15744717,Duffy,726,France,Female,44,2,0,2,1,1,26733.86,0 -9210,15570681,Chiang,560,France,Male,24,1,116084.32,1,1,0,89734.7,0 -9211,15792650,Watts,382,Spain,Male,36,0,0,1,1,1,179540.73,1 -9212,15605531,Daly,457,Spain,Female,38,6,0,2,1,0,173219.09,0 -9213,15605339,Baker,673,France,Female,37,10,0,2,1,1,37411.35,0 -9214,15672216,Uvarov,584,France,Female,40,4,82441.75,1,0,0,80852.11,0 -9215,15812893,Costa,629,France,Female,39,10,0,2,1,1,43174.49,1 -9216,15624180,Genovesi,584,Germany,Female,37,10,134171.8,4,1,1,70927.11,1 -9217,15701364,Doherty,724,France,Male,30,10,0,2,1,1,54265.55,0 -9218,15762588,Kaleski,644,France,Male,31,5,0,2,1,1,41872.17,0 -9219,15806318,Wright,676,Germany,Female,48,2,124442.38,1,1,0,15068.53,1 -9220,15712596,Huang,499,France,Male,31,4,0,1,1,0,25950.49,0 -9221,15600399,Trentino,598,France,Male,60,4,0,1,1,0,197727.14,1 -9222,15576216,Chienezie,655,Germany,Female,37,4,108862.76,1,1,0,79555.08,1 -9223,15620750,Sugden,559,France,Male,28,3,141099.43,1,1,1,15607.27,0 -9224,15623489,Tu,543,France,Female,67,0,128843.67,1,1,1,134612.48,0 -9225,15667944,Onuchukwu,679,France,Male,39,0,86843.61,1,0,1,159830.58,0 -9226,15584928,Ugochukwutubelum,594,Germany,Female,32,4,120074.97,2,1,1,162961.79,0 -9227,15779913,Davidson,586,France,Male,27,5,130231.8,2,1,1,192427.16,0 -9228,15644977,Goddard,776,France,Female,31,5,0,2,1,0,92647.94,0 -9229,15749679,Beck,699,France,Male,39,2,109724.38,1,1,1,180022.39,0 -9230,15629010,Beam,847,Germany,Female,35,5,111743.43,1,1,1,183584.14,0 -9231,15768465,Sheppard,582,Germany,Male,35,8,121309.17,2,1,1,28750.67,0 -9232,15767781,Godfrey,648,France,Male,38,10,82697.28,1,1,0,74846.67,0 -9233,15635364,Gray,618,France,Female,49,9,44301.43,3,1,1,89729.3,1 -9234,15722004,Hsiung,543,France,Female,31,4,138317.94,1,0,0,61843.73,0 -9235,15766044,Cameron,642,Germany,Male,49,4,120688.61,1,1,0,24770.22,1 -9236,15586680,Fleming,462,France,Male,27,4,176913.52,1,1,0,80587.27,0 -9237,15635388,Austin,640,Spain,Male,47,6,89047.14,1,1,0,116286.25,0 -9238,15655175,Wallace,740,Germany,Male,40,4,114318.78,2,1,0,129333.69,1 -9239,15639133,Ku,773,France,Female,50,4,0,2,1,0,129372.94,0 -9240,15799653,Fiorentino,583,Germany,Female,32,7,94753.55,2,1,1,18149.03,0 -9241,15723872,Buccho,589,Spain,Female,46,10,0,2,0,1,168369.37,0 -9242,15775627,Gordon,509,France,Male,35,8,0,2,0,1,67431.28,0 -9243,15630704,Haworth,612,Germany,Male,32,9,106520.73,2,1,0,177092.16,0 -9244,15815534,Guidry,505,Spain,Male,37,0,134006.39,1,1,1,93736.69,0 -9245,15697249,Lettiere,546,Germany,Female,25,3,132837.7,1,1,0,131647.31,0 -9246,15681316,Tai,681,France,Female,41,0,120549.29,2,1,0,175722.31,0 -9247,15682523,Chigozie,762,France,Male,20,1,139432.55,1,1,1,85606.83,0 -9248,15650244,Bezrukov,786,Spain,Male,29,7,80895.44,2,1,0,64945.57,0 -9249,15648638,Chia,629,Spain,Male,34,6,0,2,1,0,190347.72,0 -9250,15795747,Sheppard,787,Spain,Female,39,7,171646.76,1,0,1,100791.36,0 -9251,15607330,Vasilyev,713,Spain,Male,42,0,109121.71,1,0,1,167873.49,0 -9252,15624013,Maxwell,541,France,Female,39,6,109844.81,1,1,0,25289.23,0 -9253,15800805,Maher,451,France,Female,31,7,140931.82,1,0,1,20388.77,0 -9254,15667321,Cocci,644,Spain,Male,49,10,0,2,1,1,145089.64,0 -9255,15601116,P'an,686,France,Male,32,6,0,2,1,1,179093.26,0 -9256,15622033,Rapuluchukwu,847,Germany,Female,41,3,101543.51,4,1,0,16025.17,1 -9257,15758451,Azuka,765,Germany,Male,37,7,102708.77,1,1,0,9087.81,0 -9258,15688689,Esposito,678,Germany,Female,37,8,149000.91,2,1,1,21472.42,0 -9259,15652674,Hou,539,France,Male,20,0,83459.86,1,1,1,146752.67,0 -9260,15806327,Cyril,800,France,Female,40,3,75893.11,2,1,0,132562.23,0 -9261,15649618,Tomlinson,799,Germany,Female,39,7,167395.6,2,0,1,139537.43,0 -9262,15677117,Crawford,629,France,Female,61,6,0,2,1,1,133672.61,0 -9263,15751445,Chikwado,734,Germany,Female,52,6,71283.09,2,0,1,38984.37,0 -9264,15749669,Hargreaves,542,France,Female,31,3,0,2,1,1,115217.59,0 -9265,15656351,Laidley,414,Spain,Male,60,3,0,2,1,1,93844.82,0 -9266,15667438,Ferguson,675,France,Female,38,1,104016.88,1,0,0,22068.83,1 -9267,15682273,Burns,683,France,Female,38,5,127616.56,1,1,0,123846.07,0 -9268,15580912,McNeill,748,France,Male,32,5,154737.88,2,1,1,172638.13,0 -9269,15785183,Chukwuebuka,596,Spain,Male,29,2,0,2,1,1,1591.19,0 -9270,15705383,Shen,642,France,Male,35,4,125476.31,1,1,1,91775.51,0 -9271,15712903,Diaz,499,France,Female,21,3,176511.08,1,1,1,153920.22,0 -9272,15774285,Kentish,649,Spain,Female,47,8,110783.28,1,1,1,71420.16,0 -9273,15583138,Persse,739,France,Male,42,2,141642.92,2,1,0,172149.76,0 -9274,15740160,Okwukwe,616,France,Male,31,1,0,2,1,1,54706.75,0 -9275,15793425,Watt,560,Spain,Female,33,9,0,1,0,1,183358.21,0 -9276,15749265,Carslaw,427,Germany,Male,42,1,75681.52,1,1,1,57098,0 -9277,15623989,Griffin,435,France,Male,54,3,0,1,1,0,156910.46,1 -9278,15604832,Hsia,633,France,Male,29,7,0,1,1,1,130224.73,0 -9279,15584580,Fyodorova,443,France,Male,35,6,161111.45,1,0,0,13946.66,0 -9280,15573854,Chukwujekwu,727,France,Male,62,5,0,2,0,1,38652.96,0 -9281,15614847,Townsend,674,France,Female,45,6,72494.69,1,0,1,140041.78,0 -9282,15679966,Marsh,661,France,Female,31,3,133964.3,1,1,1,166187.1,0 -9283,15799435,Hayes,619,Spain,Male,34,1,0,1,1,0,139919.38,0 -9284,15752186,Padovano,562,France,Female,27,3,0,2,1,0,28137.03,0 -9285,15705544,Ma,633,France,Male,61,3,157201.48,1,0,1,50368.63,0 -9286,15713632,Ham,551,Spain,Female,48,5,95679.29,1,0,0,94978.1,0 -9287,15586523,Paten,720,Germany,Female,29,7,106230.92,1,1,1,69903.93,1 -9288,15609176,Cawthorne,688,France,Female,32,5,0,2,0,1,177607.77,0 -9289,15769308,Herbert,635,Germany,Female,36,9,81231.85,2,1,0,196731.08,0 -9290,15676810,Jen,561,France,Female,31,1,81480.27,2,1,1,65234.6,0 -9291,15634591,Saunders,850,France,Male,33,8,73059.38,1,1,1,186281,0 -9292,15679804,Esquivel,636,France,Male,36,5,117559.05,2,1,1,111573.3,0 -9293,15677764,Chao,461,Germany,Female,74,1,186445.31,2,1,1,196767.83,0 -9294,15571917,Eluemuno,771,Germany,Female,38,5,137657.71,2,1,0,72985.61,0 -9295,15574608,Sidorova,713,France,Male,36,8,133889.35,1,1,1,143265.65,0 -9296,15740868,Pirogova,658,Germany,Female,45,9,134562.8,1,1,1,159268.67,0 -9297,15702442,Benson,586,Germany,Female,56,9,100781.75,2,1,1,54448.41,0 -9298,15699797,Santana,737,France,Male,30,8,174356.13,1,0,0,31928.5,0 -9299,15648047,Williamson,742,Germany,Male,27,5,190125.43,2,0,0,21793.59,0 -9300,15766826,North,824,France,Male,26,7,146266,1,1,0,21903.62,1 -9301,15591628,Davies,701,Germany,Male,41,9,164046.1,1,1,0,49405.93,0 -9302,15583857,Siciliano,623,Spain,Female,43,4,123536.52,2,0,0,154908.52,0 -9303,15752534,Mironov,744,France,Male,36,10,0,2,1,1,182867.84,0 -9304,15741403,Amechi,698,Spain,Female,38,1,171848.38,1,0,0,16957.45,0 -9305,15783589,Toscano,616,France,Male,40,9,0,2,0,0,93717.55,0 -9306,15598046,Su,662,France,Female,39,5,139562.05,2,1,0,61636.22,0 -9307,15643330,Chukwuemeka,594,France,Male,37,2,0,2,0,1,95864.5,0 -9308,15680405,P'eng,685,France,Male,40,2,168001.34,2,1,1,167400.29,0 -9309,15728683,Lombardo,742,France,Male,27,0,0,2,0,1,131534.96,0 -9310,15621644,Lombardi,678,Germany,Male,83,6,123356.63,1,0,1,92934.41,0 -9311,15733032,Butler,651,Spain,Male,47,2,0,2,1,1,119808.64,0 -9312,15608381,Dean,585,Germany,Male,50,2,125845.66,1,1,0,9439.31,1 -9313,15658946,Piccio,579,Germany,Male,40,10,45408.85,2,1,0,18732.91,0 -9314,15757912,Bradley,722,Germany,Female,37,0,125977.81,1,0,0,160162.42,0 -9315,15645371,Cameron,613,Germany,Female,51,7,147262.11,1,1,1,53630.9,1 -9316,15653110,Chan,694,France,Male,42,8,133767.19,1,1,0,36405.21,0 -9317,15766355,Lettiere,550,Germany,Male,49,0,108806.96,3,1,0,61446.92,1 -9318,15585249,Mironova,741,France,Male,42,6,106036.52,1,1,0,194686.78,1 -9319,15611786,Tsui,668,Spain,Female,69,9,0,1,0,1,134483.07,0 -9320,15575486,Okoli,529,France,Female,27,1,0,2,1,1,37769.98,0 -9321,15780215,Berry,636,France,Male,31,6,0,2,1,1,2382.61,0 -9322,15686099,Ruse,563,Spain,Male,61,1,82182.1,1,1,0,106826.92,1 -9323,15739042,Bogolyubov,767,France,Female,35,9,0,2,1,0,39511.61,0 -9324,15815316,Kennedy,644,France,Male,50,9,76817,4,1,0,196371.13,1 -9325,15778489,Bolton,780,Germany,Male,71,9,142550.25,2,1,1,122506.78,0 -9326,15786389,Chuang,635,Spain,Female,41,10,0,2,1,1,61994.2,0 -9327,15601787,Greco,641,Germany,Male,35,2,103711.56,1,0,1,192464.21,1 -9328,15624715,Ma,593,Spain,Female,40,2,0,1,1,1,5194.95,0 -9329,15763093,Nucci,540,Germany,Female,35,7,128369.75,2,1,0,198256.15,0 -9330,15572073,Yao,663,Spain,Male,35,5,0,2,1,1,62634.94,0 -9331,15780256,Palfreyman,630,France,Male,34,9,0,2,1,1,114006.35,0 -9332,15659305,Webster,605,Germany,Male,19,8,166133.28,1,1,1,107994.99,0 -9333,15638882,Cardell,710,Germany,Female,62,9,148214.36,1,1,0,48571.14,1 -9334,15714680,Bianchi,755,France,Female,78,5,121206.96,1,1,1,76016.49,0 -9335,15777217,Somadina,641,Spain,Male,25,10,0,2,1,1,180808.39,0 -9336,15739123,Mellor,737,Germany,Male,50,4,127552.85,2,1,0,4225.11,0 -9337,15594450,Tomlinson,695,France,Male,49,9,159458.53,1,1,0,135841.35,0 -9338,15797751,Pai,466,Germany,Female,47,5,102085.72,1,1,1,183536.24,1 -9339,15691543,Lennox,558,Germany,Male,58,2,142537.18,1,1,1,88791.83,0 -9340,15722845,Meldrum,665,Spain,Male,29,1,182781.74,2,1,1,63732.9,0 -9341,15605804,Watson,737,France,Male,45,10,0,2,1,0,1364.54,0 -9342,15702061,Findlay,654,France,Male,29,7,0,2,1,1,149184.15,0 -9343,15694321,Su,619,France,Female,28,3,0,2,1,0,53394.12,0 -9344,15798749,Davidson,845,Germany,Female,43,3,152063.59,2,1,0,97910.06,0 -9345,15720050,Barrett,727,France,Female,28,2,110997.76,1,1,0,101433.76,0 -9346,15758048,Miah,582,France,Male,50,2,148942,1,1,1,116944.3,0 -9347,15805681,Chamberlain,716,France,Male,41,9,0,1,1,1,113267.48,0 -9348,15802809,Vidal,660,Spain,Female,36,0,84438.57,1,1,1,181449.51,0 -9349,15807239,Lung,664,France,Female,34,7,93920.47,1,0,0,179913.98,0 -9350,15749093,Tretyakova,801,France,Male,43,4,158713.08,2,0,0,98586.14,0 -9351,15689344,Montgomery,615,Spain,Male,42,4,0,3,0,1,120321.09,0 -9352,15606076,Golubev,718,Germany,Male,63,7,123204.88,1,1,1,100538.8,0 -9353,15610090,Han,667,France,Male,40,8,72945.29,2,1,0,98931.5,0 -9354,15693926,Pan,670,Spain,Male,37,0,178742.71,1,1,1,194493.57,0 -9355,15791501,Carroll,590,France,Male,43,8,0,2,1,1,143628.31,0 -9356,15621870,Hawkins,739,Spain,Female,40,8,0,1,1,0,167030.51,0 -9357,15734711,Loggia,373,France,Male,42,7,0,1,1,0,77786.37,1 -9358,15814405,Chesnokova,418,France,Female,46,9,0,1,1,1,81014.5,1 -9359,15729359,Chambers,837,France,Female,29,9,0,2,1,1,41866.26,0 -9360,15606944,Fleming,645,Germany,Male,43,9,140121.17,1,1,0,11302.7,1 -9361,15671934,Veale,552,Germany,Male,39,2,132906.88,1,0,1,149384.43,0 -9362,15641773,Browne,580,Germany,Male,45,2,179334.83,2,1,1,169303.65,0 -9363,15701972,Parsons,684,France,Male,35,3,137179.39,1,1,1,37264.11,0 -9364,15749114,Bailey,634,Spain,Male,35,3,0,2,1,1,19515.48,0 -9365,15780362,Ferrari,607,France,Female,49,9,119960.29,2,1,0,103068.22,0 -9366,15753229,Genovese,802,France,Male,29,9,127414.55,1,1,1,134459.12,0 -9367,15656009,McIntyre,736,France,Female,36,6,0,1,1,0,70496.66,0 -9368,15785024,Warner,629,France,Female,40,9,137409.19,1,1,0,175877.7,1 -9369,15670492,Gordon,737,France,Male,28,8,0,2,1,0,106390.01,0 -9370,15795458,McMillan,718,Spain,Female,39,2,0,1,1,1,52138.49,0 -9371,15732438,Cheng,561,France,Male,43,4,0,4,0,0,18522.91,1 -9372,15781987,Akhtar,641,France,Male,31,9,112494.99,1,1,1,32231.6,0 -9373,15775826,Iadanza,677,France,Male,30,1,78133.15,1,0,1,174225.88,0 -9374,15807457,Abernathy,641,Spain,Female,36,1,0,2,1,0,102021.39,0 -9375,15632538,Watson,658,Spain,Female,32,5,145553.07,1,1,1,31484.76,0 -9376,15641389,Shen,659,Germany,Male,48,4,123593.22,2,1,0,82469.06,1 -9377,15657306,Kershaw,567,France,Female,47,2,0,1,0,0,110900.43,1 -9378,15709447,Reed,584,France,Female,26,0,146286.22,1,1,0,105105.35,0 -9379,15762682,Mitchell,709,Spain,Female,35,1,111827.27,2,1,0,12674.68,0 -9380,15626042,Webb,690,Spain,Female,26,2,0,2,1,1,93255.85,0 -9381,15597109,Vanzetti,627,France,Male,70,1,94416.78,1,0,1,145299.5,0 -9382,15756148,Nnanna,765,Spain,Male,45,2,91549.78,1,1,1,47139.44,0 -9383,15665634,Campbell,645,France,Female,38,7,59568.57,1,1,1,167723.25,0 -9384,15739997,Capon,716,France,Female,23,2,94464.81,2,0,1,185900.88,0 -9385,15686242,Otutodilichukwu,771,France,Female,57,4,0,1,0,0,85876.67,1 -9386,15759244,Boone,687,Germany,Male,44,8,95368.14,2,1,1,1787.85,0 -9387,15672027,McIntyre,717,Germany,Female,33,10,102185.42,2,1,0,23231.93,0 -9388,15594576,Zhdanov,524,France,Male,32,1,144875.71,1,0,0,187740.04,0 -9389,15707138,Nagy,679,Spain,Male,39,5,0,2,1,1,100060.54,0 -9390,15756954,Lombardo,538,France,Female,32,2,0,1,1,1,80130.54,0 -9391,15619130,Simpson,752,Germany,Female,37,5,113291.05,2,1,1,132467.54,0 -9392,15639665,Herbert,846,Spain,Male,61,0,0,2,1,1,96202.44,0 -9393,15571065,Lehr,532,Spain,Female,39,0,0,2,1,0,94977.3,0 -9394,15686060,Chou,670,Germany,Male,43,9,111677.88,1,1,0,178827.3,1 -9395,15615753,Upchurch,597,Germany,Female,35,8,131101.04,1,1,1,192852.67,0 -9396,15800961,Ugorji,627,Germany,Male,52,1,76101.81,2,0,1,177238.35,0 -9397,15763065,Palerma,700,Spain,Female,40,2,0,2,1,0,199753.97,0 -9398,15672467,Coles,766,France,Female,52,7,92510.9,2,0,1,66193.61,0 -9399,15752915,Hsueh,488,France,Female,34,2,0,2,1,1,181270.84,0 -9400,15744695,Tu,694,France,Male,39,5,77652.4,1,1,1,25407.59,0 -9401,15584897,Kuo,639,France,Female,31,3,98360.03,1,0,0,20973.8,0 -9402,15601857,Woodhouse,705,Germany,Female,46,4,115518.07,1,0,0,76544.9,1 -9403,15674156,Tretiakova,810,Germany,Male,69,3,27288.43,1,1,1,110509.9,0 -9404,15695465,Gibson,638,France,Female,36,6,0,1,1,0,164247.51,0 -9405,15792232,Moss,595,Spain,Female,43,5,0,2,0,0,105149.8,0 -9406,15807900,Chineze,575,France,Male,36,7,0,1,1,1,55868.97,1 -9407,15743760,Davidson,850,France,Male,31,6,131996.66,2,1,1,178747.43,0 -9408,15652835,Liang,419,Spain,Female,27,2,121580.42,1,0,1,134720.51,0 -9409,15767818,Graham,640,France,Male,55,10,132436.34,1,1,0,978.66,0 -9410,15591150,Nwebube,570,Spain,Male,34,10,0,2,0,1,183387.12,0 -9411,15734659,Sozonov,640,Germany,Female,46,5,107978.4,2,1,0,155876.06,0 -9412,15796115,Forbes,689,Germany,Female,40,4,78119.59,4,1,0,119259.34,1 -9413,15724648,Chikezie,725,France,Male,26,6,98684.15,1,0,0,133720.57,0 -9414,15737732,Onwuemelie,751,France,Female,44,10,0,2,1,0,170634.49,0 -9415,15632280,Toth,544,Spain,Female,53,9,0,1,1,0,125692.07,1 -9416,15750407,Hunt,768,Germany,Female,43,2,129264.05,2,0,0,19150.14,0 -9417,15795370,Mazure,648,Germany,Male,37,6,131753.41,1,1,0,86894.67,0 -9418,15656829,Hughes,577,Spain,Female,33,6,0,2,1,0,57975.8,0 -9419,15643794,Bennett,639,Spain,Female,27,2,0,1,1,1,82938.99,0 -9420,15798605,Tien,686,Germany,Male,26,1,57422.62,1,1,1,79189.4,0 -9421,15637324,Kay,657,France,Female,28,7,0,2,0,1,5177.62,0 -9422,15589589,Bryan,613,France,Male,34,5,144094.2,1,1,0,44510.26,0 -9423,15778936,Ingamells,701,France,Male,33,9,147510.34,1,1,0,190611.92,0 -9424,15757385,Milne,578,Spain,Female,28,8,161592.76,1,1,0,177834.79,0 -9425,15666200,Lombardo,689,France,Female,40,1,0,2,1,1,119446.64,0 -9426,15683977,Owens,687,Spain,Female,72,4,0,2,1,1,50267.69,0 -9427,15675518,Charlton,499,Spain,Female,53,1,75225.53,2,0,0,144849.1,1 -9428,15584812,Overby,693,Spain,Female,39,0,0,2,0,0,81901.6,0 -9429,15752984,Chifley,737,France,Female,70,9,87542.89,2,1,1,42576.86,0 -9430,15577913,Oliver,651,France,Female,32,8,144581.96,1,1,1,87609.5,0 -9431,15591980,Hill,753,France,Male,33,5,122568.05,2,1,1,82820.85,0 -9432,15598948,DeRose,523,Spain,Female,24,5,172231.93,1,0,1,155144.12,0 -9433,15574142,Chuang,458,Germany,Female,28,2,171932.26,2,1,1,9578.24,0 -9434,15582903,Edwards,643,France,Male,39,7,0,2,1,1,170392.59,0 -9435,15733229,Rodriguez,638,Spain,Female,34,7,0,2,0,0,3946.29,0 -9436,15635752,Lo,685,Germany,Male,38,4,111798.06,2,1,1,102184.66,0 -9437,15771000,Powell,684,France,Male,38,4,0,3,1,0,75609.84,0 -9438,15804864,Chu,670,France,Female,27,5,79336.61,1,1,1,26170.08,0 -9439,15641175,Munro,701,Germany,Male,63,3,120916.52,3,0,0,144727.45,1 -9440,15692226,Onwumelu,705,France,Female,31,3,142905.51,1,1,1,58134.97,0 -9441,15584156,Siciliani,593,Spain,Male,27,10,0,3,0,0,94620,1 -9442,15702656,Yobachi,651,France,Female,33,1,96834.78,1,1,0,108764.69,0 -9443,15606552,Akabueze,741,France,Male,37,9,105261.76,2,1,1,149503.54,0 -9444,15687001,Chiemenam,596,Germany,Male,54,1,123544,1,1,1,120314.75,1 -9445,15781903,Odinakachukwu,581,Germany,Male,41,2,127913.71,2,1,1,44205.95,0 -9446,15731951,Reilly,689,Spain,Female,28,5,95328.6,1,1,0,6129.61,1 -9447,15580953,Forbes,544,France,Male,30,4,73218.89,1,0,1,126796.69,0 -9448,15810390,Amadi,718,France,Female,41,1,0,2,0,1,27509.52,1 -9449,15628274,Ferri,583,Germany,Male,35,8,149995.72,2,1,0,42143.55,0 -9450,15615444,Y?an,663,Germany,Male,28,8,123674.28,2,1,1,87985.2,0 -9451,15784010,Williamson,666,Germany,Male,33,2,124125.26,1,1,0,81884.8,0 -9452,15571586,Briggs,524,Spain,Male,29,3,159035.45,1,1,0,2705.31,1 -9453,15748616,Napolitani,599,France,Male,27,5,0,2,1,0,30546.4,0 -9454,15769402,Carpenter,667,France,Male,27,7,156811.74,1,1,1,149402.59,0 -9455,15739248,Lin,727,France,Male,52,4,0,2,1,1,118429.02,0 -9456,15603481,Robinson,689,Spain,Female,55,4,0,2,1,1,58442.25,0 -9457,15723604,Collins,639,France,Male,39,6,150555.83,1,1,0,30414.17,0 -9458,15797822,Kingsley,678,France,Male,28,2,109137.12,1,1,1,58814.41,0 -9459,15665064,Harvey,523,France,Male,36,8,158351.02,2,1,0,155304.53,0 -9460,15640580,Obiora,650,France,Female,47,9,0,1,1,0,187943.6,0 -9461,15581089,Knight,744,Spain,Male,35,7,0,2,1,1,43036.6,0 -9462,15728605,Hung,697,France,Male,40,4,0,2,0,1,26543.28,0 -9463,15737385,Curtis,800,Spain,Female,46,6,0,2,1,0,171928.04,0 -9464,15714789,Perez,664,France,Male,24,7,0,1,0,1,35611.35,0 -9465,15786035,Gosnell,740,France,Male,39,9,0,2,1,0,19047.23,0 -9466,15815259,Fang,835,France,Female,56,2,0,2,1,1,39820.13,0 -9467,15592716,Clarke,559,France,Male,52,2,0,1,1,0,129013.59,1 -9468,15734850,Milanesi,676,Spain,Male,36,1,82729.49,1,1,0,113810.12,0 -9469,15638047,Chia,613,Germany,Female,45,9,142765.24,2,1,0,34749.65,0 -9470,15674573,Gearhart,713,France,Female,25,4,121172.97,1,1,1,56268.98,0 -9471,15694859,McLean,751,Germany,Female,28,10,132932.14,2,1,1,46630.47,0 -9472,15776404,Williamson,523,France,Male,22,8,123374.46,1,1,1,124906.59,0 -9473,15579345,Murphy,775,Germany,Female,74,0,161371.5,1,1,1,134869.93,0 -9474,15690733,Angelo,608,Spain,Male,45,4,0,2,0,0,36697.48,1 -9475,15631481,Thomson,673,France,Male,51,8,79563.36,2,1,1,172200.91,0 -9476,15620988,Murray,616,France,Male,46,2,0,2,1,0,137136.46,0 -9477,15571529,Kirby,650,Germany,Female,48,7,138232.24,1,1,0,57594.78,0 -9478,15592104,Lane,655,France,Female,41,5,0,1,0,0,36548,1 -9479,15651900,Bergamaschi,782,Germany,Female,53,1,81571.05,1,1,0,182960.46,1 -9480,15596212,Yang,781,Spain,Male,35,1,0,2,0,0,42117.9,0 -9481,15710687,Mills,593,France,Female,33,0,95927.04,1,1,0,199478.05,0 -9482,15613787,Chidubem,505,Spain,Male,35,8,116932.59,1,1,0,91092.84,0 -9483,15599211,Findlay,707,France,Male,40,1,0,2,1,0,14090.4,1 -9484,15675983,Wood,692,France,Female,36,3,79551.12,1,0,1,178267.07,0 -9485,15622370,Boyle,813,Germany,Male,30,1,116416.94,1,0,1,85808.22,0 -9486,15656319,Toscano,850,Spain,Male,37,4,88141.1,1,1,0,109659.12,0 -9487,15605130,Seccombe,753,France,Male,32,6,177729.13,1,1,1,161642.08,0 -9488,15672574,Uspenskaya,850,Spain,Female,32,5,0,1,1,1,3830.59,0 -9489,15659355,McKenzie,671,Spain,Male,32,6,123912.78,2,1,1,146636.44,0 -9490,15777907,Liang,791,France,Female,33,3,0,1,1,1,144413.92,1 -9491,15655171,Yermakova,624,France,Male,80,3,0,1,1,1,65801.44,0 -9492,15619674,White,649,France,Female,35,4,108306.44,1,1,1,192486.24,0 -9493,15775192,Rounsevell,732,Germany,Female,48,4,102962.62,1,1,0,120852.85,1 -9494,15617657,Ts'ai,664,France,Female,36,0,103502.22,1,1,1,146191.82,0 -9495,15688951,Stoneman,789,Germany,Male,43,8,119654.44,2,0,1,148412.24,1 -9496,15763460,Yao,680,France,Male,33,10,183768.47,1,1,0,164119.35,0 -9497,15756992,Chukwukere,701,France,Male,37,1,0,2,1,0,163457.55,0 -9498,15617454,Ifeatu,684,France,Female,25,1,0,2,0,1,144978.47,0 -9499,15701932,Millar,586,France,Female,52,6,140900.97,1,1,1,67288.89,0 -9500,15700813,Igwebuike,522,Germany,Female,25,5,94049.92,2,1,0,103269,0 -9501,15645600,Obidimkpa,739,Spain,Female,27,8,98926.4,1,1,1,106969.98,0 -9502,15634146,Hou,835,Germany,Male,18,2,142872.36,1,1,1,117632.63,0 -9503,15686743,Moody,790,Spain,Male,29,3,46057.96,2,1,1,189777.66,0 -9504,15698792,Keldie,671,France,Female,48,6,119769.77,1,0,1,66032.65,0 -9505,15591724,Liu,560,France,Female,44,5,143244.97,1,1,0,98661.27,0 -9506,15571281,Ts'ao,651,France,Male,28,10,79562.98,1,1,1,74687.37,0 -9507,15661380,Walker,682,France,Male,69,6,0,2,0,1,149604.18,0 -9508,15728885,Defalco,808,France,Male,41,0,0,1,1,1,79888.78,0 -9509,15618950,Lo Duca,644,Spain,Male,26,8,96659.64,2,1,1,138775.69,0 -9510,15609804,Hyde,688,France,Male,29,1,0,2,1,0,154695.57,0 -9511,15735849,Kanayochukwu,617,France,Female,26,2,165947.99,2,0,1,168834.38,0 -9512,15652948,Yen,738,France,Male,33,4,92676.3,1,1,0,105817.63,0 -9513,15618155,Ts'ui,663,France,Male,45,5,83195.12,1,1,1,48682.1,0 -9514,15566378,Tillman,515,France,Male,48,5,129387.94,1,0,1,147955.91,1 -9515,15565879,Riley,845,France,Female,28,9,0,2,1,1,56185.98,0 -9516,15792922,Tu,639,Spain,Male,38,9,130233.14,1,1,1,81861.1,0 -9517,15770567,Ruiz,557,France,Female,32,3,123502.53,1,1,1,69826.8,0 -9518,15738042,Goliwe,543,Germany,Male,37,8,140894.06,2,1,1,118059.19,0 -9519,15714920,Balashov,585,Germany,Male,44,7,163867.86,1,1,1,112333.22,0 -9520,15782121,Leonard,610,France,Female,27,2,0,2,1,0,14546.76,0 -9521,15673180,Onyekaozulu,727,Germany,Female,18,2,93816.7,2,1,0,126172.11,0 -9522,15660636,Carpenter,540,Spain,Female,40,8,0,2,1,0,3560,0 -9523,15664504,Beede,418,France,Male,35,7,0,2,1,1,88878.15,0 -9524,15790322,Beneventi,660,France,Female,32,0,114668.89,1,1,0,84605,0 -9525,15739847,Sadlier,850,Germany,Male,38,5,146756.68,1,1,0,78268.61,0 -9526,15699415,Lewis,618,France,Female,46,6,150213.71,1,1,0,120668.46,1 -9527,15665521,Chiazagomekpele,642,Germany,Male,18,5,111183.53,2,0,1,10063.75,0 -9528,15682868,Elliott,850,France,Female,40,9,99816.46,1,1,1,163989.66,1 -9529,15584462,Liang,739,France,Male,34,9,0,1,1,0,60584.33,0 -9530,15661708,She,508,France,Female,41,5,0,2,1,1,94170.84,0 -9531,15584452,Bozeman,667,France,Male,41,6,0,2,0,0,167181.77,0 -9532,15717010,Yu,741,France,Female,60,5,0,1,1,1,38914.51,0 -9533,15643828,Teng,592,France,Male,29,7,0,2,1,1,91196.67,0 -9534,15733361,Davide,651,Germany,Female,45,6,86714.06,1,1,0,85869.89,1 -9535,15795488,Beneventi,773,Spain,Male,52,2,0,2,1,0,57337.79,0 -9536,15581551,Yobachukwu,850,Spain,Male,41,8,132838.07,1,1,1,175347.28,0 -9537,15632051,Douglas,550,Germany,Female,42,10,128707.31,1,1,0,63092.65,1 -9538,15780409,Egobudike,783,France,Male,40,6,0,2,1,0,109742.55,0 -9539,15572767,Shelby,777,France,Male,29,2,0,2,1,0,124489.88,0 -9540,15590337,Golubov,659,France,Male,29,6,123192.12,1,1,1,56971.41,1 -9541,15634551,Williamson,727,Germany,Male,46,3,115248.11,4,1,0,130752.01,1 -9542,15669290,Fan,603,France,Male,38,8,59360.77,1,1,1,191457.06,0 -9543,15621140,Nwebube,644,Spain,Male,37,9,0,2,1,1,96442.86,0 -9544,15613518,Bellucci,647,France,Female,35,6,112668.7,1,0,1,122584.29,0 -9545,15728043,Udinese,648,Germany,Female,37,7,138503.51,2,1,0,57215.85,0 -9546,15570073,Marian,721,Spain,Male,57,1,0,1,1,1,195940.96,0 -9547,15777033,Chizoba,524,France,Male,29,7,0,2,1,1,105448.74,0 -9548,15682454,McFarland,626,France,Female,34,3,0,2,1,1,37870.29,0 -9549,15758513,McDonald,569,France,Male,43,7,0,2,1,0,52534.81,0 -9550,15772604,Chiemezie,578,Spain,Male,36,1,157267.95,2,1,0,141533.19,0 -9551,15721715,Fane,769,France,Female,40,9,133871.05,1,1,1,50568.02,0 -9552,15688563,Marchesi,694,Germany,Male,31,4,141989.27,2,1,0,26116.82,0 -9553,15772009,Scott,664,France,Female,41,5,0,1,1,1,152054.33,0 -9554,15809585,H?,646,France,Male,38,7,0,2,1,0,1528.4,0 -9555,15593778,Craig,779,France,Female,29,3,46388.16,3,1,0,127939.26,1 -9556,15655360,Chikelu,782,Germany,Female,72,5,148666.99,1,1,0,2605.65,1 -9557,15780909,Caffyn,769,Germany,Male,34,7,115101.5,1,0,0,57841.89,1 -9558,15757310,Otitodilichukwu,655,Germany,Male,67,6,148363.38,1,1,1,186995.17,0 -9559,15801411,Green,623,Spain,Male,46,4,0,1,1,0,5549.11,1 -9560,15761706,Y?an,705,Spain,Female,39,8,144102.32,1,1,1,11682.36,0 -9561,15658409,Mao,686,France,Male,41,5,128876.71,3,1,1,106939.34,1 -9562,15810010,Dahlenburg,678,Germany,Male,36,6,118448.15,2,1,0,53172.02,0 -9563,15627027,Shih,738,France,Male,39,5,0,2,1,1,114388.98,0 -9564,15624374,Maclean,703,France,Male,28,9,0,2,0,1,2151.17,0 -9565,15720083,Fiorentino,554,Spain,Male,42,1,0,2,0,1,183492.9,0 -9566,15752294,Long,582,France,Female,38,9,135979.01,4,1,1,76582.95,1 -9567,15743193,Olson,644,France,Male,37,6,117271.8,2,1,0,104217.96,1 -9568,15696733,McKenzie,724,France,Male,29,4,0,1,1,0,8982.75,0 -9569,15677522,Rossi,593,France,Male,33,1,0,2,0,0,9984.4,0 -9570,15643523,Power,710,Spain,Female,30,10,0,2,1,0,19500.1,0 -9571,15624936,Yen,631,France,Male,35,8,129205.49,1,1,1,79146.36,0 -9572,15716085,Norris,739,Spain,Female,41,8,0,1,1,0,191694.77,1 -9573,15641688,Collier,644,Spain,Male,18,7,0,1,0,1,59645.24,1 -9574,15796834,Rivers,652,Germany,Male,35,7,104015.54,2,1,1,55207.88,0 -9575,15720123,Hudson,554,Spain,Male,37,3,0,2,1,0,166177.3,0 -9576,15604732,Milani,483,France,Female,30,9,0,2,0,0,136356.97,0 -9577,15723484,Hunt,669,Germany,Female,42,1,103873.39,1,1,0,148611.52,0 -9578,15807120,Oluchukwu,841,Germany,Female,52,3,112383.03,1,1,0,85516.37,1 -9579,15810891,Lorenzo,662,France,Male,34,2,117731.79,2,0,1,55120.79,0 -9580,15640407,Chidiegwu,821,Germany,Male,45,0,135827.33,2,1,1,131778.58,0 -9581,15778838,Warren,783,France,Male,38,9,114135.17,1,1,0,153269.98,0 -9582,15709256,Glover,850,France,Female,28,9,0,2,1,1,164864.67,0 -9583,15742285,Andersen,559,France,Male,62,6,118756.62,1,1,1,20367.68,0 -9584,15729019,Arcuri,602,Spain,Male,34,8,98382.72,1,1,0,39542,0 -9585,15608588,Mackinlay,563,Germany,Male,41,2,100520.92,1,1,1,19412.8,1 -9586,15610557,McCarthy,695,Spain,Female,35,7,79858.13,2,1,1,127977.66,0 -9587,15786418,Chiu,546,France,Female,20,6,0,1,0,1,20508.85,0 -9588,15653050,Norriss,719,Germany,Female,76,10,95052.29,1,1,0,176244.87,0 -9589,15744914,Moore,539,Germany,Male,42,1,177728.55,1,1,0,105013.63,0 -9590,15669611,Mott,632,France,Male,71,3,83116.68,1,1,1,27597.76,0 -9591,15594786,Ts'ai,772,Germany,Male,34,7,111565.91,1,1,1,121073.23,0 -9592,15649211,Fokina,708,Spain,Male,40,8,83015.71,1,1,0,101089.76,0 -9593,15766066,Nikitina,668,Germany,Female,28,1,124511.01,1,0,0,114258.18,0 -9594,15772216,Henry,738,France,Female,67,1,130652.52,1,0,1,22762.23,0 -9595,15619898,Chiefo,785,France,Male,55,5,0,2,1,1,7008.65,0 -9596,15724543,Mao,597,France,Male,61,5,0,2,1,1,81299.17,0 -9597,15755084,Bezrukova,531,France,Male,37,7,121854.45,1,1,0,147521.35,0 -9598,15730441,Dodd,509,France,Male,26,10,0,2,1,1,6177.83,0 -9599,15666767,Lori,508,France,Male,35,1,86893.28,1,0,0,59374.82,0 -9600,15690456,Yudina,749,Germany,Female,32,7,79523.13,1,0,1,157648.12,0 -9601,15570533,Conti,621,Germany,Female,55,7,131033.76,1,0,1,75685.59,1 -9602,15797692,Volkova,659,France,Female,33,7,89939.62,1,1,0,136540.09,0 -9603,15603135,Boni,634,Germany,Female,59,3,95727.05,1,0,0,97939.4,1 -9604,15698927,Ritchie,675,France,Male,39,7,0,2,0,1,36267.21,0 -9605,15687363,McMillan,770,France,Male,31,3,155047.56,2,1,1,186064.34,0 -9606,15733444,Phillips,736,France,Female,29,9,0,2,0,0,176152.7,0 -9607,15678057,Lombardi,524,France,Male,44,10,118569.03,2,0,0,82117.2,0 -9608,15806918,Ireland,674,France,Male,28,5,0,1,1,1,151925.25,0 -9609,15638247,Boan,700,Spain,Male,44,9,0,2,1,0,142287.65,0 -9610,15674833,Shao,741,France,Female,35,1,0,2,1,0,36557.55,0 -9611,15812534,Chiemenam,455,France,Male,40,1,0,3,0,1,129975.34,0 -9612,15586522,Hunter,608,Spain,Male,37,2,130461.02,1,1,0,21967.15,0 -9613,15794297,McKay,776,France,Male,36,1,0,2,1,0,53477.76,0 -9614,15737025,Roberts,635,France,Male,33,1,0,3,0,0,178067.33,1 -9615,15615931,Aitken,746,France,Female,37,4,0,2,0,1,171039.56,0 -9616,15664860,Chao,692,Spain,Female,47,3,0,2,1,0,150802.41,1 -9617,15664539,Bruce,683,Spain,Male,35,9,61172.04,1,0,0,82951.12,0 -9618,15583692,Chan,591,Germany,Female,35,2,90194.34,2,1,0,57064.57,0 -9619,15693131,Watts,581,France,Female,24,3,95508.2,1,1,1,45755,0 -9620,15779973,Gibbons,684,Germany,Male,35,3,99967.76,1,1,1,176882.08,0 -9621,15620557,Ni,561,Spain,Male,37,4,101470.29,1,0,1,88838.14,0 -9622,15639549,Jen,718,Germany,Female,33,4,70541.06,1,0,0,88592.8,0 -9623,15618750,Phillips,590,France,Male,31,8,112211.61,1,1,0,26261.42,0 -9624,15796790,Amaechi,573,France,Female,47,8,154543.98,1,1,0,29586.73,0 -9625,15668309,Maslow,350,France,Female,40,0,111098.85,1,1,1,172321.21,1 -9626,15732437,Rowley,504,Germany,Female,44,0,131873.07,2,1,1,158036.72,1 -9627,15665158,Chukwuemeka,813,Spain,Male,27,1,137275.36,1,0,1,115733.16,0 -9628,15689322,Bevan,641,Spain,Male,31,3,153316.14,1,1,0,59927.99,0 -9629,15596624,Topp,662,France,Female,22,9,0,2,1,1,44377.65,0 -9630,15601977,Burgoyne,497,Spain,Male,44,2,121250.04,1,0,1,79691.4,0 -9631,15801462,Yermakov,716,France,Male,31,8,109578.04,2,1,1,51503.51,0 -9632,15566139,Ts'ui,526,France,Female,37,5,53573.18,1,1,0,62830.97,0 -9633,15791006,Kodilinyechukwu,760,Germany,Female,34,6,58003.41,1,1,0,90346.1,0 -9634,15668057,K?,669,France,Female,31,6,113000.66,1,1,0,40467.82,0 -9635,15580805,Marino,655,France,Male,27,10,0,2,1,0,51620.94,0 -9636,15658768,Lucas,547,France,Female,49,2,0,1,0,0,65466.93,1 -9637,15613048,Anderson,648,Germany,Female,40,5,139973.65,1,1,1,667.66,1 -9638,15803654,Wei,790,France,Female,31,2,151290.16,1,1,1,172437.12,0 -9639,15662337,Baldwin,744,Germany,Female,50,1,121498.11,2,0,1,106061.47,1 -9640,15650924,Foster,761,Spain,Female,32,4,103515.39,2,1,1,177622.38,0 -9641,15647203,Gebhart,750,France,Female,35,3,0,1,1,0,191520.5,0 -9642,15682778,Fedorov,680,France,Male,34,9,0,2,1,1,95686.6,0 -9643,15579820,Robertson,704,Spain,Male,38,6,106687.76,1,1,0,173776.5,0 -9644,15709354,Tudawali,521,France,Female,41,2,0,2,1,1,113089.43,0 -9645,15728480,Iloerika,452,France,Female,35,8,0,2,1,1,149614.81,0 -9646,15641091,Onyemauchechukwu,695,France,Female,31,5,106089.2,1,0,0,99537.68,0 -9647,15603111,Muir,850,Spain,Male,71,10,69608.14,1,1,0,97893.4,1 -9648,15679693,Walker,625,France,Male,31,5,0,2,0,1,90.07,0 -9649,15797190,Charlton,608,Germany,Female,40,7,96202.32,1,0,0,161154.85,0 -9650,15788025,Tseng,715,France,Female,38,0,0,2,1,1,332.81,0 -9651,15646168,Ifeatu,834,Spain,Male,33,5,0,2,1,0,66285.18,0 -9652,15580493,Chin,469,France,Male,33,1,127818.52,1,1,0,163477.22,0 -9653,15726720,Blinova,480,France,Female,40,7,0,1,1,0,170332.67,1 -9654,15735799,Maconochie,527,Germany,Male,58,3,137318.42,1,1,1,126144.96,0 -9655,15773098,Ch'in,834,Spain,Male,34,5,0,2,0,0,53437.1,0 -9656,15668971,Nicholson,583,France,Female,40,4,55776.39,2,1,0,26920.43,0 -9657,15603221,Burgess,696,Germany,Male,32,4,84421.62,1,0,1,52314.71,0 -9658,15740043,Young,606,France,Male,32,5,83161.65,1,1,1,116885.59,0 -9659,15712264,Plumb,713,France,Female,39,10,0,2,1,1,126263.97,0 -9660,15751926,Trentino,821,Germany,Male,42,3,87807.29,2,1,1,64613.81,0 -9661,15589401,Allen,550,France,Female,30,4,0,2,1,0,89216.29,0 -9662,15742019,Benford,675,France,Female,39,6,0,2,0,0,83419.15,0 -9663,15660611,Gallo,748,Spain,Male,39,3,0,2,1,1,123998.52,0 -9664,15607634,Cobb,606,Germany,Male,40,9,95293.86,2,0,1,96985.58,0 -9665,15595036,Doherty,726,Germany,Male,30,7,92847.59,1,1,0,146154.06,0 -9666,15745794,Cocci,547,France,Male,30,6,0,2,1,1,18471.86,0 -9667,15781689,Macadam,758,Spain,Male,35,5,0,2,1,0,95009.6,0 -9668,15696054,Tychonoff,596,France,Male,37,2,0,1,0,1,121175.86,0 -9669,15752467,Johnson,720,Spain,Male,34,3,0,2,1,1,77047.78,0 -9670,15597739,Tu,674,France,Male,37,3,0,1,1,0,158049.9,0 -9671,15651336,Chidiebere,756,France,Female,32,4,0,2,1,0,147040.25,0 -9672,15636061,Pope,649,Germany,Male,78,4,68345.86,2,1,1,142566.75,0 -9673,15723013,Sutherland,613,Germany,Male,28,7,76656.4,2,1,1,185483.24,0 -9674,15784148,Beneventi,643,France,Male,62,9,0,2,0,0,155870.82,0 -9675,15578098,Jamieson,600,France,Male,31,8,0,2,1,1,121555.51,0 -9676,15638621,Simmons,735,Spain,Male,39,1,60374.98,1,1,0,40223.74,0 -9677,15720924,Chijioke,585,France,Female,34,1,0,1,1,1,75503.6,0 -9678,15566531,Iloerika,724,Germany,Male,33,4,88046.88,1,0,1,186942.49,1 -9679,15718064,Chia,635,Spain,Male,29,2,0,2,0,0,117173.8,0 -9680,15605067,Nwachinemelu,472,France,Male,19,9,0,2,1,0,3453.4,0 -9681,15655335,Becher,590,France,Male,36,1,0,2,1,0,48876.84,0 -9682,15607301,Romano,651,Spain,Female,63,8,129968.67,1,1,1,11830.53,0 -9683,15694628,Walker,686,Germany,Female,39,4,157731.6,2,1,0,162820.6,0 -9684,15607112,Chiawuotu,606,France,Male,32,6,0,2,0,1,36540.63,0 -9685,15635775,Watt,781,France,Male,33,3,89276.48,1,1,0,6959,0 -9686,15644280,Udegbunam,593,France,Male,45,4,138825.19,1,0,0,10828.78,0 -9687,15708362,Watson,793,France,Male,63,4,103729.79,2,1,1,80272.06,0 -9688,15771997,Bryant,791,France,Female,31,10,75499.24,1,1,0,22184.14,0 -9689,15730579,Ward,850,France,Male,68,5,169445.4,1,1,1,186335.07,0 -9690,15728005,Urban,698,France,Female,57,9,111359.55,2,1,0,105715.01,0 -9691,15791674,Sutherland,846,France,Female,34,10,142388.61,2,0,1,68393.64,1 -9692,15754599,K'ung,765,France,Male,42,4,123311.39,2,1,1,82868.34,0 -9693,15693690,Iweobiegbunam,574,Spain,Male,52,7,115532.52,1,1,0,196257.67,0 -9694,15728963,Wei,617,Germany,Female,51,10,167273.71,1,0,0,93439.75,1 -9695,15659710,Lascelles,581,France,Male,25,5,77886.53,2,1,0,150319.49,0 -9696,15658675,Ts'ao,710,Germany,Male,37,6,135795.63,1,0,1,46523.6,0 -9697,15638788,Mack,550,France,Male,32,8,97514.07,1,1,1,199138.84,0 -9698,15609735,Campbell,533,Germany,Male,51,6,127545.56,2,0,0,79559.02,1 -9699,15771477,Fiorentini,779,France,Male,49,9,106160.37,1,0,0,116893.87,0 -9700,15570145,Long,763,France,Female,23,2,0,2,1,0,153983.99,0 -9701,15797149,Lloyd,563,Spain,Female,36,4,143680.47,2,1,1,63531.19,0 -9702,15636912,Sneddon,678,Spain,Male,38,3,124483.53,1,1,0,126253.31,0 -9703,15687828,Gorshkov,644,Spain,Female,31,5,86006.3,1,1,1,73922.95,0 -9704,15667424,Forbes,682,Germany,Female,43,7,111094.05,2,1,1,64679.3,0 -9705,15759872,L?,625,France,Male,22,9,0,2,1,0,157072.91,0 -9706,15572374,Hopetoun,733,Spain,Male,36,1,0,2,0,1,108377.82,0 -9707,15754926,Lucchesi,512,France,Female,30,6,0,2,1,0,88827.31,0 -9708,15687431,Faria,642,France,Female,41,7,115171.71,1,1,1,37674.47,0 -9709,15604515,Yefremov,737,Germany,Female,22,10,111543.26,2,0,0,106327.85,0 -9710,15682839,Genovesi,575,France,Female,57,8,137936.94,1,1,1,84475.13,0 -9711,15624677,Marquez,543,Germany,Female,37,3,122304.65,2,0,0,33998.7,0 -9712,15646366,Trevisani,521,Germany,Male,41,8,120586.54,1,0,1,20491.15,0 -9713,15701768,Tung,637,France,Male,32,3,0,2,1,1,197827.06,0 -9714,15623566,Barnhill,714,France,Male,40,9,46520.69,1,1,1,96687.25,0 -9715,15681274,Marshall,726,Spain,Female,56,2,105473.74,1,1,1,46044.7,0 -9716,15762573,Bednall,680,Spain,Female,34,7,0,2,1,0,98949.85,0 -9717,15706458,Pan,812,Germany,Male,39,5,115730.71,3,1,1,185599.34,1 -9718,15654222,Ogg,757,Spain,Male,30,3,145396.49,1,0,1,198341.15,0 -9719,15704053,T'ang,710,Spain,Male,62,3,131078.42,2,1,0,119348.76,1 -9720,15724321,Baresi,516,Germany,Female,47,9,128298.74,1,0,0,149614.17,1 -9721,15621815,Obiajulu,803,France,Female,40,6,165526.71,1,1,0,12328.08,0 -9722,15724876,McGregor,560,France,Female,38,5,83714.41,1,1,1,33245.97,0 -9723,15696588,Lung,679,France,Female,36,3,0,2,1,1,2243.41,0 -9724,15612832,Jamieson,526,France,Male,32,7,125540.05,1,0,0,86786.41,0 -9725,15804295,Pinto,485,France,Male,41,2,100254.76,2,1,1,12706.67,0 -9726,15712536,Fallaci,625,France,Female,36,3,0,2,1,0,41295.1,1 -9727,15662494,Goliwe,773,Spain,Male,43,7,138150.57,1,1,1,177357.16,0 -9728,15807728,Ferri,530,France,Female,45,1,0,1,0,1,190663.89,1 -9729,15764916,Rowley,616,Germany,Female,43,7,95984.21,1,0,1,115262.54,1 -9730,15615330,Tretiakova,651,France,Male,23,10,0,2,1,1,170099.23,0 -9731,15638487,She,586,Germany,Male,38,2,136858.42,1,0,1,189143.94,0 -9732,15627859,Nebeolisa,607,Germany,Male,29,7,102609,1,1,0,163257.44,0 -9733,15622192,Young,724,Spain,Male,39,3,0,2,0,1,95562.81,0 -9734,15789413,Fitzgerald,733,France,Male,64,3,0,2,1,1,75272.63,0 -9735,15583221,Arnold,667,Germany,Male,70,3,77356.92,2,1,1,20881.96,0 -9736,15768495,Chidimma,700,France,Female,32,8,110923.15,2,1,1,161845.81,1 -9737,15644103,Wells,659,Spain,Male,78,2,151675.65,1,0,1,49978.67,0 -9738,15741197,Calzada,710,Spain,Male,22,8,0,3,1,0,107292.91,0 -9739,15664547,Black,760,France,Male,37,7,0,1,0,0,32863.24,1 -9740,15797293,Sopuluchukwu,677,France,Female,25,3,0,2,1,0,179608.96,0 -9741,15572021,Ts'ao,798,Germany,Female,29,8,80204.11,2,1,0,70223.22,0 -9742,15637461,Ukaegbunam,758,France,Male,35,7,0,2,1,0,77951.84,0 -9743,15620577,Wood,715,France,Male,45,4,0,2,1,1,55043.93,0 -9744,15609643,Furneaux,752,Germany,Male,32,9,115587.49,2,0,1,101677.46,0 -9745,15785358,Gresswell,586,Germany,Male,46,8,106968.96,1,1,1,79366.98,1 -9746,15603883,Ch'in,818,France,Male,36,4,0,2,1,1,8037.03,0 -9747,15782550,Ma,490,Germany,Female,41,0,139659.04,1,1,1,176254.12,0 -9748,15775761,Iweobiegbunam,610,Germany,Female,69,5,86038.21,3,0,0,192743.06,1 -9749,15680201,Marcelo,627,Germany,Male,24,5,102773.2,2,1,0,56793.02,1 -9750,15767594,Azubuike,533,France,Female,35,8,0,2,1,1,187900.12,0 -9751,15591985,Stewart,708,France,Female,51,8,70754.18,1,1,1,92920.04,1 -9752,15789339,Yen,681,France,Male,59,4,122781.51,1,0,1,140166.95,0 -9753,15781530,Hsieh,690,France,Male,21,8,0,2,1,1,155782.89,0 -9754,15705174,Chiedozie,656,Germany,Male,68,7,153545.11,1,1,1,186574.68,0 -9755,15572114,Shih,673,Spain,Male,40,1,121629.22,1,1,1,3258.6,0 -9756,15804009,Amechi,806,Germany,Male,36,8,167983.17,2,1,1,106714.28,0 -9757,15662698,Ko,648,Spain,Female,43,7,81153.82,1,1,1,144532.85,1 -9758,15696047,Chimezie,501,France,Male,35,6,99760.84,1,1,1,13591.52,0 -9759,15701160,Azubuike,556,Germany,Female,43,4,125890.72,1,1,1,74854.97,0 -9760,15790093,Aguirre,627,France,Female,27,2,0,2,1,0,125451.01,0 -9761,15632143,Lung,652,France,Male,31,2,119148.55,1,0,0,149740.22,0 -9762,15736778,Adams,807,Germany,Female,60,1,72948.58,2,1,1,17355.36,0 -9763,15734917,Castiglione,708,Germany,Male,21,8,133974.36,2,1,0,50294.09,0 -9764,15643903,Yao,619,France,Male,27,1,154483.98,1,1,0,156394.74,0 -9765,15569526,Morales,601,France,Male,40,10,98627.13,2,0,0,77977.69,0 -9766,15777067,Thomas,445,France,Male,64,2,136770.67,1,0,1,43678.06,0 -9767,15795511,Vasiliev,800,Germany,Male,39,4,95252.72,1,1,0,13906.34,0 -9768,15610419,Chukwueloka,554,France,Male,33,3,117413.95,1,1,1,12766.74,0 -9769,15644994,Ko,714,Germany,Male,54,4,137986.58,2,0,1,51308.54,1 -9770,15703707,Atkins,656,France,Male,44,10,143571.52,1,0,0,127444.14,0 -9771,15659327,Moffitt,520,France,Male,49,5,121197.64,1,1,0,72577.33,1 -9772,15771323,Panicucci,480,Spain,Male,39,5,121626.9,1,1,1,82438.13,0 -9773,15750549,Akobundu,660,Germany,Male,30,1,84440.1,2,1,1,60485.98,0 -9774,15698462,Chiu,532,France,Male,36,4,0,2,1,1,132798.78,0 -9775,15739692,Tsui,679,France,Male,42,1,0,2,0,0,71823.15,0 -9776,15744041,Yobanna,780,France,Female,26,3,140356.7,1,1,0,117144.15,0 -9777,15700714,Hollis,747,France,Male,29,7,0,2,1,1,141706.43,0 -9778,15777743,Cattaneo,705,France,Female,39,3,92224.56,1,1,1,54517.25,0 -9779,15623143,Lung,732,France,Female,43,9,0,2,1,0,183147.17,0 -9780,15712568,Angelo,515,Spain,Male,40,10,121355.99,1,1,0,138360.29,0 -9781,15617432,Folliero,816,Germany,Female,40,9,109003.26,1,1,1,79580.56,0 -9782,15650424,Bryant,641,France,Female,48,3,147341.43,1,1,1,157458.61,1 -9783,15728829,Weigel,509,France,Male,18,7,102983.91,1,1,0,171770.58,0 -9784,15680430,Ajuluchukwu,601,Germany,Female,49,4,96252.98,2,1,0,104263.82,0 -9785,15687626,Zhirov,527,France,Male,39,4,0,2,1,0,167183.07,1 -9786,15609187,Cox,455,France,Female,27,5,155879.09,2,0,0,70774.97,0 -9787,15609521,Chimaraoke,803,Germany,Male,34,4,142929.16,2,1,1,114869.56,0 -9788,15752626,Genovese,553,France,Male,32,7,64082.09,1,0,1,109159.58,0 -9789,15571756,Ohearn,724,France,Female,28,5,0,1,1,0,59351.68,0 -9790,15814040,Munroe,610,France,Female,45,1,0,2,1,1,199657.46,0 -9791,15658211,Morrison,559,Spain,Female,39,2,0,2,1,1,121151.1,0 -9792,15742091,Parkhill,825,Germany,Female,35,6,118336.95,1,1,0,26342.33,1 -9793,15787168,Y?,819,Spain,Female,28,8,168253.21,1,1,1,102799.14,0 -9794,15772363,Hilton,772,Germany,Female,42,0,101979.16,1,1,0,90928.48,0 -9795,15659364,Thompson,685,Spain,Male,23,5,164902.43,1,0,0,141152.28,0 -9796,15738980,Yobanna,506,France,Male,43,2,0,2,1,0,105568.6,0 -9797,15794236,Thorpe,642,Germany,Male,22,10,111812.52,2,1,1,183045.46,0 -9798,15721383,Harvey,627,Spain,Male,40,10,0,2,1,1,194792.42,0 -9799,15652981,Robinson,600,Germany,Male,30,2,119755,1,1,1,21852.91,0 -9800,15722731,Manna,653,France,Male,46,0,119556.1,1,1,0,78250.13,1 -9801,15640507,Li,762,Spain,Female,35,3,119349.69,3,1,1,47114.18,1 -9802,15578878,Hancock,569,Spain,Female,30,3,139528.23,1,1,1,33230.37,0 -9803,15744295,Hao,756,France,Male,40,1,94773.11,1,1,0,114279.63,0 -9804,15776558,Nicholls,673,France,Male,31,1,108345.22,1,0,1,38802.03,0 -9805,15596136,Folliero,637,France,Female,36,9,166939.88,1,1,1,72504.76,0 -9806,15704597,Trumbull,644,France,Male,33,7,174571.36,1,0,1,43943.09,0 -9807,15648272,Medvedeva,658,Spain,Male,35,9,71829.34,1,1,1,68141.92,0 -9808,15594915,Crist,649,France,Female,36,8,0,2,0,1,109179.89,0 -9809,15581115,Middleton,603,France,Female,39,9,76769.68,1,0,0,48224.72,0 -9810,15763907,Watts,820,France,Female,39,1,104614.29,1,1,0,61538.43,1 -9811,15705994,Udinese,712,Spain,Male,27,10,0,1,1,0,94544.88,0 -9812,15772421,Tretiakov,645,Germany,Female,31,1,128927.93,1,1,1,2850.01,0 -9813,15711572,O'Kane,705,Germany,Female,31,9,110941.93,2,1,0,163484.8,0 -9814,15691170,Vasilyeva,590,Spain,Female,29,10,99250.08,1,1,1,129629.41,0 -9815,15600106,Wei,631,France,Male,36,1,0,2,0,0,133141.34,0 -9816,15745431,Chinonyelum,604,France,Male,34,7,0,2,1,1,188078.55,0 -9817,15649508,Chin,643,Spain,Male,48,8,0,2,1,0,174729.3,0 -9818,15812611,Lorimer,690,Spain,Female,30,5,0,2,0,1,78700.03,0 -9819,15619699,Yeh,558,France,Male,31,7,0,1,1,0,198269.08,0 -9820,15813946,Duffy,637,Germany,Male,51,1,104682.83,1,1,0,55266.96,1 -9821,15762762,Onyekachukwu,648,Germany,Female,45,5,118886.55,1,0,0,51636.7,0 -9822,15629793,Banks,652,Spain,Male,28,8,156823.7,2,1,0,198251.52,0 -9823,15781298,Hughes,808,Germany,Male,39,3,124216.93,1,0,1,171442.36,0 -9824,15622658,Lai,551,France,Female,26,2,144258.52,1,1,0,49778.79,0 -9825,15658980,Matthews,711,Germany,Male,26,9,128793.63,1,1,0,19262.05,0 -9826,15701936,Bell,467,Germany,Male,28,10,126315.26,1,1,0,32349.29,1 -9827,15686917,Tu,789,Spain,Female,40,4,0,2,1,0,137402.27,0 -9828,15807312,Hsia,602,Spain,Male,33,5,0,2,0,1,64038.34,0 -9829,15574523,Cheng,576,France,Male,39,1,0,2,1,1,68814.23,0 -9830,15724200,Cheng,584,France,Male,38,1,115341.55,1,0,1,173632.92,0 -9831,15738224,Lin,593,France,Male,32,6,99162.29,1,1,0,128384.11,0 -9832,15593283,Higgins,705,Germany,Female,48,1,156848.13,2,1,1,99475.95,1 -9833,15814690,Chukwujekwu,595,Germany,Female,64,2,105736.32,1,1,1,89935.73,1 -9834,15807245,McKay,699,Germany,Female,41,1,200117.76,2,1,0,94142.35,0 -9835,15799358,Vincent,516,France,Female,46,6,62212.29,1,0,1,171681.86,1 -9836,15616172,Ubanwa,838,France,Male,31,2,0,2,1,0,8222.96,0 -9837,15777958,Ch'ien,587,France,Male,39,10,0,2,1,1,170409.45,0 -9838,15809124,T'ien,750,France,Male,38,5,151532.4,1,1,1,46555.15,0 -9839,15616367,Ricci,581,Germany,Male,39,1,121523.51,1,0,0,161655.55,1 -9840,15687385,McDowell,484,France,Male,41,5,0,1,1,1,74267.35,0 -9841,15607877,Maclean,576,Spain,Male,26,8,0,2,0,1,34101.06,0 -9842,15736327,Manna,567,Germany,Female,46,1,68238.51,2,1,1,109572.58,0 -9843,15746704,Jibunoh,638,Spain,Male,30,9,136808.53,2,1,1,106642.97,0 -9844,15778304,Fan,646,Germany,Male,24,0,92398.08,1,1,1,18897.29,0 -9845,15588456,Hsieh,658,France,Female,40,5,143566.12,1,1,1,189607.71,0 -9846,15664035,Parsons,590,Spain,Female,38,9,0,2,1,1,148750.16,0 -9847,15596405,Udinese,546,Spain,Male,25,7,127728.24,2,1,1,105279.74,0 -9848,15815097,Root,603,France,Female,34,9,0,2,1,0,167916.35,0 -9849,15762708,Chiemezie,619,Spain,Female,38,10,119658.49,1,1,1,8646.58,0 -9850,15776211,Toscani,678,France,Female,34,6,0,2,1,1,124592.84,0 -9851,15626012,Obidimkpa,459,France,Male,26,4,149879.66,1,0,0,50016.17,0 -9852,15792077,Degtyaryov,671,Germany,Male,28,8,119859.52,2,1,0,125422.66,0 -9853,15718765,Maclean,501,Spain,Male,43,6,104533.24,1,0,0,81123.59,1 -9854,15576615,Giordano,719,Spain,Male,37,10,145382.61,1,1,0,80408.59,0 -9855,15752650,Saad,681,Spain,Female,37,6,121231.39,1,1,1,146366.08,0 -9856,15797502,Lord,706,Spain,Male,24,2,141078.57,1,1,1,24402.87,0 -9857,15687329,Hope,763,Germany,Female,32,1,108465.65,2,1,0,60552.44,1 -9858,15779423,K?,716,France,Male,39,1,70657.61,2,1,1,76476.05,0 -9859,15619514,Bull,507,Germany,Male,40,3,120105.43,1,1,0,92075.01,1 -9860,15615430,Adams,678,Germany,Male,55,4,129646.91,1,1,1,184125.1,1 -9861,15716431,Brookes,775,France,Female,30,10,191091.74,2,1,1,96170.38,0 -9862,15798341,Victor,544,France,Male,38,8,0,1,1,1,98208.62,0 -9863,15651958,Giles,756,France,Male,27,8,0,2,1,1,157932.75,0 -9864,15726179,Ferrari,757,Germany,Female,43,5,131433.33,2,1,1,3497.43,1 -9865,15652999,Milne,742,Germany,Male,33,1,137937.95,1,1,1,51387.1,0 -9866,15691950,Parry,591,France,Male,49,3,0,2,1,0,50123.44,0 -9867,15632446,Allan,667,France,Male,24,4,0,2,0,0,180329.83,0 -9868,15620936,Warren,787,France,Male,32,4,0,2,1,1,13238.93,0 -9869,15587640,Rowntree,718,France,Female,43,0,93143.39,1,1,0,167554.86,0 -9870,15782231,Andrejew,521,France,Male,38,6,0,2,1,0,51454.06,0 -9871,15580462,Corby,607,Spain,Male,40,1,112544.45,1,1,1,19842.22,0 -9872,15736371,Kennedy,633,France,Female,34,3,123034.43,2,1,1,38315.04,0 -9873,15648032,Young,588,Spain,Male,37,2,0,2,0,1,187816.59,0 -9874,15610454,Poole,724,Germany,Female,33,9,119278.44,1,1,1,197148.24,0 -9875,15671358,Fletcher,720,France,Male,44,4,0,2,1,0,163471.01,0 -9876,15747130,Tsao,521,France,Male,39,7,0,2,0,1,653.58,0 -9877,15578374,Gilroy,620,Spain,Male,36,7,169312.72,1,1,0,45414.09,0 -9878,15572182,Onwuamaeze,505,Germany,Female,33,3,106506.77,3,1,0,45445.78,1 -9879,15770041,Manna,728,Spain,Female,43,8,128412.61,1,0,1,139024.31,0 -9880,15669414,Pisano,486,Germany,Male,62,9,118356.89,2,1,0,168034.83,1 -9881,15777054,Thorpe,584,Germany,Male,42,3,137479.13,1,1,0,25669.1,0 -9882,15621021,Dwyer,687,Spain,Female,40,1,0,2,1,0,8207.36,0 -9883,15785490,Okeke,771,France,Male,50,3,105229.72,1,1,1,16281.68,1 -9884,15577695,Zito,678,France,Male,41,2,148088.11,1,1,0,14083.12,0 -9885,15686974,Sergeyeva,751,France,Female,48,4,0,1,0,1,30165.06,1 -9886,15574584,Fang,670,France,Male,33,8,126679.69,1,1,1,39451.09,0 -9887,15719541,Flannagan,675,Spain,Male,31,2,90826.27,2,1,0,60270.87,0 -9888,15646310,Mao,684,Spain,Male,24,8,143582.89,1,1,1,22527.27,0 -9889,15697606,Sturdee,637,France,Female,21,10,125712.2,1,0,0,175072.47,0 -9890,15711489,Azikiwe,760,Spain,Female,32,2,0,1,1,1,114565.35,0 -9891,15670427,Chidi,662,Spain,Male,37,4,155187.3,1,1,0,48930.8,0 -9892,15731755,Hull,680,France,Male,49,10,0,2,1,0,187008.45,0 -9893,15796370,Shah,604,Spain,Male,40,5,155455.43,1,0,1,113581.85,0 -9894,15598331,Morgan,764,France,Female,40,9,100480.53,1,1,0,124095.69,0 -9895,15704795,Vagin,521,France,Female,77,6,0,2,1,1,49054.1,0 -9896,15796764,Bruno,684,Germany,Female,56,3,127585.98,3,1,1,80593.49,1 -9897,15589420,Osinachi,795,France,Female,40,2,101891.1,1,1,1,183044.86,0 -9898,15810563,Ho,678,Spain,Female,61,8,0,2,1,1,159938.82,0 -9899,15746569,Tsui,589,France,Male,38,4,0,1,1,0,95483.48,1 -9900,15811594,Gordon,660,Spain,Female,28,3,128929.88,1,1,1,198069.71,0 -9901,15645896,Duncan,646,Germany,Male,39,6,121681.91,2,0,1,61793.47,0 -9902,15802909,Hu,706,Germany,Female,56,3,139603.22,1,1,1,86383.61,0 -9903,15797665,Docherty,730,France,Female,27,7,0,2,1,0,144099.48,0 -9904,15778959,Brookes,606,France,Female,36,10,0,2,0,1,155641.46,0 -9905,15722532,Angelo,690,Spain,Female,36,10,91760.11,1,1,1,135784.94,0 -9906,15784124,Emenike,645,Germany,Male,41,2,93925.3,1,1,0,123982.14,1 -9907,15776518,Pugh,579,France,Female,38,4,175739.36,1,1,1,193130.55,0 -9908,15611247,McKenzie,481,France,Female,28,10,0,2,1,0,145215.96,0 -9909,15721469,Mach,492,Germany,Male,45,9,170295.04,2,0,0,164741.81,0 -9910,15773338,Endrizzi,739,France,Male,58,2,101579.28,1,1,1,72168.53,0 -9911,15784042,L?,624,France,Male,55,7,118793.6,1,1,1,95022.02,1 -9912,15776229,MacPherson,682,France,Male,44,3,115282.3,1,0,0,23766.4,0 -9913,15655903,Michael,701,Spain,Female,34,6,107980.37,1,1,1,119374.74,0 -9914,15590177,Chiedozie,718,France,Female,44,1,133866.22,1,0,1,139049.24,0 -9915,15568876,Hughes,496,France,Female,34,1,102723.35,2,1,0,180844.81,0 -9916,15813140,Taylor,543,Spain,Male,41,5,0,2,0,1,143980.29,0 -9917,15770516,Evdokimov,616,Spain,Female,44,7,193213.02,2,1,1,137392.77,0 -9918,15755731,Davis,635,Germany,Male,53,8,117005.55,1,0,1,123646.57,1 -9919,15574480,Ubanwa,652,Spain,Male,31,1,132862.59,1,0,0,158054.49,0 -9920,15798084,Murray,688,France,Male,26,0,0,2,1,0,105784.85,0 -9921,15673020,Smith,678,France,Female,49,3,204510.94,1,0,1,738.88,1 -9922,15643575,Evseev,757,Germany,Male,36,1,65349.71,1,0,0,64539.64,0 -9923,15596811,Mitchell,667,France,Male,36,8,139753.35,1,1,0,79871.16,0 -9924,15786789,Ni,725,France,Female,29,6,0,2,1,1,190776.83,0 -9925,15578865,Palerma,632,Germany,Female,50,5,107959.39,1,1,1,6985.34,1 -9926,15605672,Yuan,694,France,Female,38,5,195926.39,1,1,1,85522.84,0 -9927,15603674,Knight,803,France,Male,36,1,0,2,1,1,149370.93,0 -9928,15759915,Rapuokwu,814,France,Female,31,6,87772.52,1,1,0,188516.45,0 -9929,15686219,Wan,611,France,Male,38,4,71018.6,2,1,0,2444.29,0 -9930,15696388,Artamonova,755,Germany,Male,38,4,111096.91,1,1,1,19762.88,0 -9931,15713604,Rossi,425,Germany,Male,40,9,166776.6,2,0,1,172646.88,0 -9932,15647800,Greco,850,France,Female,34,6,101266.51,1,1,0,33501.98,0 -9933,15813451,Fleetwood-Smith,677,Spain,Male,18,8,134796.87,2,1,1,114858.9,0 -9934,15765375,Butusov,797,France,Female,46,8,0,1,0,0,162668.33,0 -9935,15774586,West,692,Germany,Female,43,10,118588.83,1,1,1,161241.65,1 -9936,15603454,Sanders,735,Germany,Male,28,5,160454.15,2,0,1,114957.22,0 -9937,15653037,Parks,609,France,Male,77,1,0,1,0,1,18708.76,0 -9938,15782475,Edith,700,France,Female,42,8,0,2,1,1,105305.72,0 -9939,15593496,Korovin,526,Spain,Female,36,5,91132.18,1,0,0,58111.71,0 -9940,15808971,Lajoie,693,Spain,Female,57,9,0,2,1,1,135502.77,0 -9941,15791972,Bergamaschi,748,France,Female,20,7,0,2,0,0,10792.42,0 -9942,15676869,T'ien,657,Spain,Male,36,8,0,2,0,1,123866.43,0 -9943,15683007,Torode,739,Germany,Female,25,5,113113.12,1,1,0,129181.27,0 -9944,15659495,Fu,784,Spain,Male,23,2,0,1,1,1,6847.73,0 -9945,15703923,Cameron,744,Germany,Male,41,7,190409.34,2,1,1,138361.48,0 -9946,15674000,Cattaneo,645,France,Male,44,10,0,2,0,1,166707.22,0 -9947,15618171,James,669,France,Female,33,9,0,2,0,1,107221.03,0 -9948,15732202,Abramovich,615,France,Male,34,1,83503.11,2,1,1,73124.53,1 -9949,15735078,Onwughara,724,Germany,Female,53,1,139687.66,2,1,1,12913.92,0 -9950,15798615,Wan,850,France,Female,47,9,137301.87,1,1,0,44351.77,0 -9951,15638494,Salinas,625,Germany,Female,39,10,129845.26,1,1,1,96444.88,0 -9952,15763874,Ho,635,Spain,Male,46,8,0,2,1,1,60739.16,0 -9953,15696355,Cleveland,724,Germany,Male,37,6,125489.4,1,1,0,118570.53,0 -9954,15655952,Burke,550,France,Male,47,2,0,2,1,1,97057.28,0 -9955,15739850,Trentino,645,France,Male,45,6,155417.61,1,0,1,3449.22,0 -9956,15611338,Kashiwagi,714,Spain,Male,29,4,0,2,1,1,37605.9,0 -9957,15707861,Nucci,520,France,Female,46,10,85216.61,1,1,0,117369.52,1 -9958,15672237,Oluchi,633,France,Male,25,1,0,1,1,0,100598.98,0 -9959,15657771,Ts'ui,537,France,Male,37,6,0,1,1,1,17802.42,0 -9960,15677783,Graham,764,Spain,Male,38,4,113607.47,1,1,0,91094.46,0 -9961,15681026,Lucciano,795,Germany,Female,33,9,104552.72,1,1,1,120853.83,1 -9962,15566543,Aldridge,573,Spain,Male,44,9,0,2,1,0,107124.17,0 -9963,15594612,Flynn,702,Spain,Male,44,9,0,1,0,0,59207.41,1 -9964,15814664,Scott,740,Germany,Male,33,2,126524.11,1,1,0,136869.31,0 -9965,15642785,Douglas,479,France,Male,34,5,117593.48,2,0,0,113308.29,0 -9966,15690164,Shao,627,Germany,Female,33,4,83199.05,1,0,0,159334.93,0 -9967,15590213,Ch'en,479,Spain,Male,35,4,125920.98,1,1,1,20393.44,0 -9968,15603794,Pugliesi,623,France,Male,48,5,118469.38,1,1,1,158590.25,0 -9969,15733491,McGregor,512,Germany,Female,40,8,153537.57,2,0,0,23101.13,0 -9970,15806360,Hou,609,France,Male,41,6,0,1,0,1,112585.19,0 -9971,15587133,Thompson,518,France,Male,42,7,151027.05,2,1,0,119377.36,0 -9972,15721377,Chou,833,France,Female,34,3,144751.81,1,0,0,166472.81,0 -9973,15747927,Ch'in,758,France,Male,26,4,155739.76,1,1,0,171552.02,0 -9974,15806455,Miller,611,France,Male,27,7,0,2,1,1,157474.1,0 -9975,15695474,Barker,583,France,Male,33,7,122531.86,1,1,0,13549.24,0 -9976,15666295,Smith,610,Germany,Male,50,1,113957.01,2,1,0,196526.55,1 -9977,15656062,Azikiwe,637,France,Female,33,7,103377.81,1,1,0,84419.78,0 -9978,15579969,Mancini,683,France,Female,32,9,0,2,1,1,24991.92,0 -9979,15703563,P'eng,774,France,Male,40,9,93017.47,2,1,0,191608.97,0 -9980,15692664,Diribe,677,France,Female,58,1,90022.85,1,0,1,2988.28,0 -9981,15719276,T'ao,741,Spain,Male,35,6,74371.49,1,0,0,99595.67,0 -9982,15672754,Burbidge,498,Germany,Male,42,3,152039.7,1,1,1,53445.17,1 -9983,15768163,Griffin,655,Germany,Female,46,7,137145.12,1,1,0,115146.4,1 -9984,15656710,Cocci,613,France,Male,40,4,0,1,0,0,151325.24,0 -9985,15696175,Echezonachukwu,602,Germany,Male,35,7,90602.42,2,1,1,51695.41,0 -9986,15586914,Nepean,659,France,Male,36,6,123841.49,2,1,0,96833,0 -9987,15581736,Bartlett,673,Germany,Male,47,1,183579.54,2,0,1,34047.54,0 -9988,15588839,Mancini,606,Spain,Male,30,8,180307.73,2,1,1,1914.41,0 -9989,15589329,Pirozzi,775,France,Male,30,4,0,2,1,0,49337.84,0 -9990,15605622,McMillan,841,Spain,Male,28,4,0,2,1,1,179436.6,0 -9991,15798964,Nkemakonam,714,Germany,Male,33,3,35016.6,1,1,0,53667.08,0 -9992,15769959,Ajuluchukwu,597,France,Female,53,4,88381.21,1,1,0,69384.71,1 -9993,15657105,Chukwualuka,726,Spain,Male,36,2,0,1,1,0,195192.4,0 -9994,15569266,Rahman,644,France,Male,28,7,155060.41,1,1,0,29179.52,0 -9995,15719294,Wood,800,France,Female,29,2,0,2,0,0,167773.55,0 -9996,15606229,Obijiaku,771,France,Male,39,5,0,2,1,0,96270.64,0 -9997,15569892,Johnstone,516,France,Male,35,10,57369.61,1,1,1,101699.77,0 -9998,15584532,Liu,709,France,Female,36,7,0,1,0,1,42085.58,1 -9999,15682355,Sabbatini,772,Germany,Male,42,3,75075.31,2,1,0,92888.52,1 -10000,15628319,Walker,792,France,Female,28,4,130142.79,1,1,0,38190.78,0 diff --git a/docs/.gitkeep b/docs/.gitkeep new file mode 100644 index 00000000..e69de29b diff --git a/models/column_equivalence.pk b/models/column_equivalence.pk new file mode 100644 index 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- " \n", - " \n", - " \n", - " \n", - "
RowNumberCustomerIdSurnameCreditScoreGeographyGenderAgeTenureBalanceNumOfProductsHasCrCardIsActiveMemberEstimatedSalaryExited
0115634602Hargrave619FranceFemale4220.00111101348.881
1215647311Hill608SpainFemale41183807.86101112542.580
2315619304Onio502FranceFemale428159660.80310113931.571
3415701354Boni699FranceFemale3910.0020093826.630
4515737888Mitchell850SpainFemale432125510.8211179084.100
\n", - "" - ], - "text/plain": [ - " RowNumber CustomerId Surname CreditScore Geography Gender Age \\\n", - "0 1 15634602 Hargrave 619 France Female 42 \n", - "1 2 15647311 Hill 608 Spain Female 41 \n", - "2 3 15619304 Onio 502 France Female 42 \n", - "3 4 15701354 Boni 699 France Female 39 \n", - "4 5 15737888 Mitchell 850 Spain Female 43 \n", - "\n", - " Tenure Balance NumOfProducts HasCrCard IsActiveMember \\\n", - "0 2 0.00 1 1 1 \n", - "1 1 83807.86 1 0 1 \n", - "2 8 159660.80 3 1 0 \n", - "3 1 0.00 2 0 0 \n", - "4 2 125510.82 1 1 1 \n", - "\n", - " EstimatedSalary Exited \n", - "0 101348.88 1 \n", - "1 112542.58 0 \n", - "2 113931.57 1 \n", - "3 93826.63 0 \n", - "4 79084.10 0 " - ] - }, - "execution_count": 21, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "data.head(5)" - ] - }, - { - "cell_type": "code", - "execution_count": 22, - "id": "3da27622-b70d-45bb-9efb-bd94bd4fb0a7", - "metadata": {}, - "outputs": [], - "source": [ - "# Nos deshacemos de las columnas que no contribuyen en mucho\n", - "data = data.drop(data.columns[0:3], axis=1)" - ] - }, - { - "cell_type": "code", - "execution_count": 25, - "id": "c6519a08-642b-4ce3-8800-bfd80be89989", - "metadata": {}, - "outputs": [], - "source": [ - "# Convertimos los datos en formato categorico, para más info: shorturl.at/y0269\n", - "column_equivalence = {}\n", - "features = list(data.columns)\n", - "for i, column in enumerate(list([str(d) for d in data.dtypes])):\n", - " if column == \"object\":\n", - " data[data.columns[i]] = data[data.columns[i]].fillna(data[data.columns[i]].mode())\n", - " categorical_column = data[data.columns[i]].astype(\"category\")\n", - " current_column_equivalence = dict(enumerate(categorical_column.cat.categories))\n", - " column_equivalence[i] = dict((v,k) for k,v in current_column_equivalence.items())\n", - " data[data.columns[i]] = categorical_column.cat.codes\n", - " else:\n", - " data[data.columns[i]] = data[data.columns[i]].fillna(data[data.columns[i]].median())" - ] - }, - { - "cell_type": "code", - "execution_count": 26, - "id": "1d48b3b8-f48c-4340-8d77-93e35054ecaf", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "{1: {'France': 0, 'Germany': 1, 'Spain': 2}, 2: {'Female': 0, 'Male': 1}}" - ] - }, - "execution_count": 26, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "column_equivalence" - ] - }, - { - "cell_type": "code", - "execution_count": 27, - "id": "21e4ba90-1206-4ce6-bdc8-6986e6b93ef5", - "metadata": {}, - "outputs": [], - "source": [ - "# Vamos a crear un modelo de regresion logistica\n", - "from sklearn.model_selection import train_test_split\n", - "from sklearn.linear_model import LogisticRegression\n" - ] - }, - { - "cell_type": "code", - "execution_count": 28, - "id": "f45f3df3-bcbe-45f3-820c-82867e36d012", - "metadata": {}, - "outputs": [], - "source": [ - "# Generar los datos para poder separar la variable de respuesta de los datos que tenemos disponibles\n", - "X = data.copy()\n", - "y = X.pop(data.columns[-1])" - ] - }, - { - "cell_type": "code", - "execution_count": 29, - "id": "8a6ee78f-7c8b-4810-a763-c8b20155ec28", - "metadata": {}, - "outputs": [], - "source": [ - "# Separar los datos en datos de entrenamiento y testing\n", - "X_train, X_test, y_train, y_test = train_test_split( X, y, test_size=0.33, random_state=42)" - ] - }, - { - "cell_type": "code", - "execution_count": 30, - "id": "409f0391-4500-41fd-85a9-e501ecdd9329", - "metadata": {}, - "outputs": [], - "source": [ - "# Crear el modelo y entrenarlo\n", - "clf_lin = LogisticRegression(random_state=0, solver='lbfgs', multi_class='multinomial').fit(X, y)\n" - ] - }, - { - "cell_type": "code", - "execution_count": 31, - "id": "753ab797-0b07-4e27-a497-9518034451a9", - "metadata": {}, - "outputs": [ - { - "data": { - "text/plain": [ - "array([[2599, 58],\n", - " [ 597, 46]])" - ] - }, - "execution_count": 31, - "metadata": {}, - "output_type": "execute_result" - } - ], - "source": [ - "# Medir los resultados obtenidos\n", - "from sklearn.metrics import confusion_matrix\n", - "confusion_matrix(y_test, clf_lin.predict(X_test))\n" - ] - }, - { - "cell_type": "code", - "execution_count": 32, - "id": "20f25624-4ba7-4c0d-a79a-590d1884b7d0", - "metadata": {}, - "outputs": [], - "source": [ - "# Generar el binario del modelo para reutilizarlo, equivalencia de variables categoricas y caracteristicas del modelo\n", - "import pickle\n", - "pickle.dump(clf_lin, open(\"churn/models/model.pk\", \"wb\"))\n", - "pickle.dump(column_equivalence, open(\"churn/models/column_equivalence.pk\", \"wb\"))\n", - "pickle.dump(features, open(\"churn/models/features.pk\", \"wb\"))" - ] - } - ], - "metadata": { - "kernelspec": { - "display_name": "Python 3", - "language": "python", - "name": "python3" - }, - "language_info": { - "codemirror_mode": { - "name": "ipython", - "version": 3 - }, - "file_extension": ".py", - "mimetype": "text/x-python", - "name": "python", - "nbconvert_exporter": "python", - "pygments_lexer": "ipython3", - "version": "3.7.3" - } - }, - "nbformat": 4, - "nbformat_minor": 5 -} diff --git a/notebooks/modelgeneration_27092023_ricalanis.ipynb b/notebooks/modelgeneration_27092023_ricalanis.ipynb index bbffdcd9..fab768ee 100644 --- a/notebooks/modelgeneration_27092023_ricalanis.ipynb +++ b/notebooks/modelgeneration_27092023_ricalanis.ipynb @@ -38,7 +38,7 @@ "outputs": [], "source": [ "# Cargar los datos que tenemos disponibles\n", - "data = pd.read_csv(\"data/churn.csv\")\n" + "data = pd.read_csv(\"data/raw/churn.csv\")\n" ] }, { @@ -359,7 +359,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 13, "id": "1e21c8b3", "metadata": {}, "outputs": [ @@ -413,9 +413,9 @@ "#Tener en cuenta esta nota de la documentación de Python\n", "#\"Warning: The pickle module is not secure. Only unpickle data you trust.\"\n", "\n", - "pickle.dump(clf_lin, open(\"churn/models/model.pk\", \"wb\"))\n", - "pickle.dump(column_equivalence, open(\"churn/models/column_equivalence.pk\", \"wb\"))\n", - "pickle.dump(features, open(\"churn/models/features.pk\", \"wb\"))" + "pickle.dump(clf_lin, open(\"models/model.pk\", \"wb\"))\n", + "pickle.dump(column_equivalence, open(\"models/column_equivalence.pk\", \"wb\"))\n", + "pickle.dump(features, open(\"models/features.pk\", \"wb\"))" ] } ], diff --git a/references/.gitkeep b/references/.gitkeep new file mode 100644 index 00000000..e69de29b diff --git a/reports/.gitkeep b/reports/.gitkeep new file mode 100644 index 00000000..e69de29b diff --git a/reports/figures/.gitkeep b/reports/figures/.gitkeep new file mode 100644 index 00000000..e69de29b From 56efb480938d0bdbaa06ece45d6931f5eb39b3d3 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Angel=20Mart=C3=ADnez?= <76793458+AFMartinezF@users.noreply.github.com> Date: Sun, 20 Oct 2024 20:40:11 +0000 Subject: [PATCH 5/9] Add scaler and oultlier analisis to slightly improve metrics --- models/model.pk | Bin 1006 -> 972 bytes .../modelgeneration_27092023_ricalanis.ipynb | 380 +++++++++++++++++- 2 files changed, 364 insertions(+), 16 deletions(-) diff --git a/models/model.pk b/models/model.pk index b2964c11f32d2b0879255c803ce0852e5a3960d6..91665e4ce3112a359db522918c4068526630bee7 100644 GIT binary patch delta 143 zcmV;A0C4~A2h0ZqfCQDnu>^Pm0cMkZ0xSps000000PsJPu>wi~7L)t}CsaO(Lr|gz zqa+sN#J>Y8NA(2MwLkp-+qjof(Z5dPAFOgG1weC8%;&(7vcCf-ndqg%<3BXZ+Wo{e xufI?RF-`TNjK5_0)mB0y;lE9ir6c_-sXvpM11AeUi9-l$xfmi@pYxN;10!bgKBWKv delta 150 zcmX@Z{*Ilcfo1CBjVu*RjG2>bnRGZ986aTtMkX&t-N}EL)LB(}n9?jJ-(pe-3=o!^ zl%q2@Wxrue)@(LkC3^=u8>t!p9rpL1^vsq^pJu=K%Z@wkoL>81JMbE|X795*R~0uU z-cWbH^3|$og(VXEo#cNf7#X|of9%FtZg*+fzRBgx>fE87&K!m1" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "import matplotlib.pyplot as plt\n", + "import seaborn as sns\n", + "import numpy as np\n", + "\n", + "num_cols = data.select_dtypes(include=np.number)# Selecciona todas las columnas numéricas\n", + "num_rows = 6 # Número de filas de la cuadrícula de gráficos\n", + "num_cols_grid = 4 # Número de columnas de la cuadrícula de gráficos\n", + "\n", + "fig, axes = plt.subplots(num_rows, num_cols_grid, figsize=(15, 10))\n", + "\n", + "# Bucle para iterar sobre todas las columnas numéricas y crear un diagrama de caja (boxplot) para cada una\n", + "for i, colname in enumerate(num_cols.columns):\n", + " # Calcula la posición (fila y columna) en la cuadrícula del gráfico actual\n", + " row = i // num_cols_grid # Fila correspondiente en la cuadrícula\n", + " col = i % num_cols_grid # Columna correspondiente en la cuadrícula\n", + " \n", + " # Crea el gráfico de boxplot para la columna 'colname' en la posición (row, col)\n", + " ax = sns.boxplot(x=data[colname], showmeans=True, ax=axes[row, col], \n", + " boxprops={\"facecolor\": \"#8ac6de\", \"linewidth\": 1.2}, # Color y grosor de las cajas\n", + " capprops={\"color\": \"black\", \"linewidth\": 1.5}, # Color y grosor de los bigotes\n", + " flierprops={\"marker\": \"o\", \"markersize\": 3}) # Marcador y tamaño de los valores atípicos\n", + "\n", + "# Eliminando los ejes vacíos si hay menos columnas numéricas que las posiciones de la cuadrícula\n", + "for j in range(i+1, num_rows*num_cols_grid):\n", + " row = j // num_cols_grid # Calcula la fila del gráfico vacío\n", + " col = j % num_cols_grid # Calcula la columna del gráfico vacío\n", + " fig.delaxes(axes[row, col]) # Elimina el gráfico vacío en la posición (row, col)\n", + "\n", + "fig.suptitle('Boxplot o diagrama de caja para cada una de las variables numéricas', fontsize=16)\n", + "plt.tight_layout() # Ajusta la distribución de espacios vacios\n", + "plt.show()\n" + ] + }, + { + "cell_type": "markdown", + "id": "d8a1140d", + "metadata": {}, + "source": [ + "Visualmente podemos identificar algunos valores atipicos, que tienen sentido y probablemente no se deben a errores en la información. Por lo que no hace falta alterarlos." + ] + }, + { + "cell_type": "code", + "execution_count": 14, + "id": "cb8dcb36", + "metadata": {}, + "outputs": [ + { + "data": { + "text/html": [ + "
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CreditScoreGeographyGenderAgeTenureBalanceNumOfProductsHasCrCardIsActiveMemberEstimatedSalaryExited
74820.7360.51.00.3378380.50.5285640.3333331.00.00.1649530.0
1750.2681.00.00.2297300.70.5335560.0000001.01.00.1363860.0
86350.6020.51.00.1486490.30.4858150.0000001.00.00.2726211.0
35840.3120.51.00.1351350.80.2114550.0000000.01.00.1228410.0
56810.3581.00.00.2837840.20.3298810.0000001.01.00.6146280.0
51651.0000.01.00.2027030.70.5618100.0000000.00.00.0174950.0
23350.7480.50.00.4054050.60.4402710.3333331.01.00.4027411.0
49300.5540.51.00.1621620.60.4478830.0000001.01.00.5901440.0
56590.3920.00.00.4594590.20.0000000.0000001.00.00.6866701.0
38990.8040.00.00.2432430.20.4779330.0000001.00.00.6217760.0
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" + ], + "text/plain": [ + " CreditScore Geography Gender Age Tenure Balance \\\n", + "7482 0.736 0.5 1.0 0.337838 0.5 0.528564 \n", + "175 0.268 1.0 0.0 0.229730 0.7 0.533556 \n", + "8635 0.602 0.5 1.0 0.148649 0.3 0.485815 \n", + "3584 0.312 0.5 1.0 0.135135 0.8 0.211455 \n", + "5681 0.358 1.0 0.0 0.283784 0.2 0.329881 \n", + "5165 1.000 0.0 1.0 0.202703 0.7 0.561810 \n", + "2335 0.748 0.5 0.0 0.405405 0.6 0.440271 \n", + "4930 0.554 0.5 1.0 0.162162 0.6 0.447883 \n", + "5659 0.392 0.0 0.0 0.459459 0.2 0.000000 \n", + "3899 0.804 0.0 0.0 0.243243 0.2 0.477933 \n", + "\n", + " NumOfProducts HasCrCard IsActiveMember EstimatedSalary Exited \n", + "7482 0.333333 1.0 0.0 0.164953 0.0 \n", + "175 0.000000 1.0 1.0 0.136386 0.0 \n", + "8635 0.000000 1.0 0.0 0.272621 1.0 \n", + "3584 0.000000 0.0 1.0 0.122841 0.0 \n", + "5681 0.000000 1.0 1.0 0.614628 0.0 \n", + "5165 0.000000 0.0 0.0 0.017495 0.0 \n", + "2335 0.333333 1.0 1.0 0.402741 1.0 \n", + "4930 0.000000 1.0 1.0 0.590144 0.0 \n", + "5659 0.000000 1.0 0.0 0.686670 1.0 \n", + "3899 0.000000 1.0 0.0 0.621776 0.0 " + ] + }, + "execution_count": 14, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Normalizando los datos aplicando un scaler \n", + "from sklearn.preprocessing import MinMaxScaler\n", + "\n", + "scaler = MinMaxScaler()\n", + "data = pd.DataFrame(scaler.fit_transform(data), columns=data.columns)\n", + "data.sample(10)" + ] + }, { "cell_type": "markdown", "id": "106c84df", @@ -272,7 +620,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 15, "id": "21e4ba90-1206-4ce6-bdc8-6986e6b93ef5", "metadata": {}, "outputs": [], @@ -284,7 +632,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 16, "id": "f45f3df3-bcbe-45f3-820c-82867e36d012", "metadata": {}, "outputs": [], @@ -296,7 +644,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 17, "id": "8a6ee78f-7c8b-4810-a763-c8b20155ec28", "metadata": {}, "outputs": [], @@ -307,7 +655,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 18, "id": "409f0391-4500-41fd-85a9-e501ecdd9329", "metadata": {}, "outputs": [], @@ -326,13 +674,13 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 19, "id": "753ab797-0b07-4e27-a497-9518034451a9", "metadata": {}, "outputs": [ { "data": { - "image/png": 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vC5f7haWoHn74YdlsNi1cuFDz589XmTJlNGTIkEJV+QEA/8NuJwAKqFevnt555x3de++9atiwodMTLjdv3qwPPvjAsfNG8+bNNWjQIM2fP19paWlq3769tm7dqsWLF6tPnz5OO538Vf3799eECRN05513atSoUTp//rzmzp2rG264wWmh4bPPPqv4+HhFRUUpLCxMJ06c0Jw5c1SjRg3ddtttf3j9F198Ud27d1dERISGDBmiCxcuaPbs2fL399fkyZOL7Xv8VT179tTbb78tf39/NWrUSAkJCVqzZo2qVq3qNK9Fixby9vbWtGnTdPbsWVmtVt1+++0KDAws0uctWrRIq1atUmxsrGrUqCEpP9l/4IEHNHfuXA0bNqzYvhsA9/Lkx7qXFCTfAC7rjjvu0I4dO/Tiiy/q448/1ty5c2W1WtWsWTPNmDFDDz/8sGPuggULVLduXcXGxmr58uUKDg5WdHS0Jk2aVKwxVa1aVcuXL9fYsWM1fvx41alTRzExMdq3b59T8n3HHXfo0KFDevPNN3Xq1ClVq1ZN7du315QpUxwLGC+nc+fOWr16tSZNmqSJEyeqbNmyat++vaZNm1bkxYmuNHPmTHl7e2vJkiW6ePGibr31Vsce5b8VHBysefPmKSYmRkOGDFFeXp7Wr19fpOT76NGjGjNmjHr16qVBgwY5xgcMGKAPP/xQ48ePV/fu3UvU/QGAksxi52+GAAAAkLSjRwd3h+DQ7LMN7g7BJah8AwAAQJI8epeRkoLGHgAAAMAQKt8AAACQxOPlTaDyDQAAABhC8g0AAAAYQtsJAAAAJLHg0gQq3wAAAIAhJN8AAACAIbSdAAAAQBKPlzfBY5PvVWXD3R0CAA8TlZOktr2/cncYADzMVx+3dXcIMMhjk28AAAAUDQsuXY+/LQAAAACGkHwDAAAAhtB2AgAAAEm0nZhA5RsAAAAwhOQbAAAAMIS2EwAAAEii7cQEKt8AAACAISTfAAAAgCG0nQAAAEASj5c3gTsMAAAAGELlGwAAAJIkL28WXLoalW8AAADAEJJvAAAAwBDaTgAAACCJfb5NoPINAAAAGELyDQAAABhC2wkAAAAksc+3CdxhAAAAwBAq3wAAAJDEgksTqHwDAAAAhpB8AwAAAIbQdgIAAABJtJ2YQOUbAAAAMITkGwAAADCEthMAAABIYp9vE7jDAAAAgCFUvgEAACCJBZcmUPkGAAAADCH5BgAAAAyh7QQAAACSWHBpAncYAAAAMITkGwAAADCEthMAAADks7DbiatR+QYAAAAMIfkGAAAADKHtBAAAAJJ4yI4JVL4BAAAAQ6h8AwAAQBL7fJvAHQYAAAAMIfkGAAAADKHtBAAAAJJYcGkClW8AAADAEJJvAAAAwBDaTgAAACCJ3U5M4A4DAAAAhlD5BgAAgCQWXJpA5RsAAAAwhOQbAAAAMIS2EwAAAEii7cQEKt8AAACAISTfAAAAgCG0nQAAACAf+3y7HHcYAAAAMITkGwAAADCEthMAAABIkiwWdjtxNSrfAAAAgCFUvgEAACBJsrDg0uW4wwAAAIAhJN8AAACAIbSdAAAAQBKPlzeByjcAAABgCMk3AAAAYAhtJwAAAMjHbicuxx0GAAAADKHyDQAAAEksuDSByjcAAABgCMk3AAAAYAhtJwAAAJAkWSzUZV2NOwwAAAAYQvINAAAAGELbCQAAAPKx24nLUfkGAAAADKHyDQAAAEmShSdcuhx3GAAAADCE5BsAAAAwhLYTAAAASOLx8iZQ+QYAAAAMIfkGAAAADKHtBAAAAPl4vLzLcYcBAAAAQ0i+AQAAAENoOwEAAIAkdjsxgco3AAAAYAiVbwAAAOTj8fIuxx0GAAAADCH5BgAAAAyh7QQAAACSJIuFBZeuRuUbAAAApVpMTIxuuukmVapUSYGBgerTp4+SkpKc5ly8eFHDhw9X1apVVbFiRd11111KTU11mpOcnKyoqCiVL19egYGBGjdunHJzc53mbNiwQS1btpTValX9+vUVGxtbpFhJvgEAAFCqbdy4UcOHD9eWLVsUFxennJwcde3aVZmZmY45Y8aM0aeffqoPPvhAGzdu1LFjx9S3b1/H+by8PEVFRSk7O1ubN2/W4sWLFRsbq4kTJzrmHDx4UFFRUerYsaMSExM1evRoDR06VF988UWhY7XY7XZ78XztkmVV2XB3hwDAw0TlJKlt76/cHQYAD/PVx23dHYLDudnj3B2CQ6WRL/7p9548eVKBgYHauHGj2rVrp7Nnz6p69ep65513dPfdd0uSfvzxRzVs2FAJCQm65ZZb9Pnnn6tnz546duyYgoKCJEnz5s3ThAkTdPLkSfn4+GjChAlatWqVdu3a5fis/v37Ky0tTatXry5UbFS+AQAA4FHOnj0rSapSpYokafv27crJyVHnzp0dcxo0aKBatWopISFBkpSQkKCmTZs6Em9JioyMVHp6unbv3u2Y89trXJpz6RqFwYJLAAAASCpZT7jMyspSVlaW05jVapXVar3i+2w2m0aPHq1bb71VTZo0kSSlpKTIx8dHAQEBTnODgoKUkpLimPPbxPvS+UvnrjQnPT1dFy5ckK+v71W/F5VvAAAAlDgxMTHy9/d3OmJiYq76vuHDh2vXrl167733DERZdFS+AQAAUOJER0dr7NixTmNXq3qPGDFCK1euVHx8vGrUqOEYDw4OVnZ2ttLS0pyq36mpqQoODnbM2bp1q9P1Lu2G8ts5v98hJTU1VX5+foWqektUvgEAAHCJxavEHFarVX5+fk7HHyXfdrtdI0aM0PLly7Vu3TrVqVPH6XyrVq1UtmxZrV271jGWlJSk5ORkRURESJIiIiK0c+dOnThxwjEnLi5Ofn5+atSokWPOb69xac6laxQGlW8AAACUasOHD9c777yjjz/+WJUqVXL0aPv7+8vX11f+/v4aMmSIxo4dqypVqsjPz08jR45URESEbrnlFklS165d1ahRIw0cOFDTp09XSkqKnn76aQ0fPtyR9D/66KP6z3/+o/Hjx+uhhx7SunXr9P7772vVqlWFjpXKNwAAAEq1uXPn6uzZs+rQoYNCQkIcx9KlSx1zXnnlFfXs2VN33XWX2rVrp+DgYH300UeO897e3lq5cqW8vb0VERGhBx54QA8++KCeffZZx5w6depo1apViouLU/PmzTVjxgwtWLBAkZGRhY6Vfb4BoJDY5xuAK5Skfb4z5kW7OwSHio9efXFlaUTlGwAAADCE5BsAAAAwhAWXAAAAkCRZLNRlXY07DAAAABhC5RsAAAD5StDj5T0VlW8AAADAEJJvAAAAwBDaTgAAACBJsnhRl3U17jAAAABgCMk3AAAAYAhtJwAAAMhnYbcTV6PyDQAAABhC5RsAAAD5WHDpctxhAAAAwBCSbwAAAMAQ2k4AAACQjwWXLkflGwAAADCE5BsAAAAwhLYTAAAASOLx8iZwhwEAAABDqHwDAAAgn4W6rKtxhwEAAABDSL4BAAAAQ2g7AQAAQD4v9vl2NSrfAAAAgCEk3wAAAIAhtJ0AAABAkmRhtxOX4w4DAAAAhpB8AwAAAIbQdgIAAIB87HbiclS+AQAAAEOofAMAACAfCy5djuQbpVq98Y8o+M6uqhheV3kXLurXhO/141MvKfOng445t6x5S1Xbt3F63+H572nX8EmO11U73qLwKY+rUpNw5Wae1y9vr1DSM6/InpfnmBNyd3fV++c/VPH62so6eUaH5yzRzy8vdP2XBFAi/b1/LT10X5jT2OGj5/XA8O2SpCoBZTVscB21blFZ5X29deSXC3rrg2RtTDjtjnABlBAk3yjVqrS7WYfnLlHatp2ylPFWg+fG6ubPFiq+WZTyzl9wzEtesFQ/TZ7leP3bc5WaheumT9/Q/ph5Svz7BJULDVLT16bI4u2lvROmS5KqR7ZTi7de1O7R/9bJuE2q1KCems77t/IuXtThOUvMfWEAJcrPhzM1ZuJOx+u8PLvj3/8aHa6KFcoo+vndSkvPVZd21TVlXEM9/MT32ncw0x3hAigB+NsCSrVvew7V0beWK2PPfp3bkaQfhvxT5cOuk3/Lxk7z8s5fVFbqKceRe+5//+ELvaeHzu1M0v7nX9P5A8k689W32hv9osIeGyDvihUkSdcNuEOpH69V8vz3dOHgUZ34fKMOTH9d9Z582Oj3BVCy5OXZdSYtx3GcPZfrONekgZ8+WnVMe/dl6HjqRb31wRFlZOYqvH5FN0YMXIXFUnIOD+XWyvepU6f05ptvKiEhQSkpKZKk4OBg/e1vf9PgwYNVvXp1d4aHUqiMfyVJUvavZ53GQ+/rpevuv0NZKSeVumq99j0/R7YLFyVJXlYf2S5mOc3Pu3BR3r7l5N+ysc7Eb5WX1Ud5/53/2zm+NUPkG3adLhz+xYXfCkBJVSPUV8sX3azsbJt2JZ3T628d0olT+T9Pdv2Yrttvq6bN284oIzNXt99WXT4+Xvp+59mrXBWAJ3Nb5fvbb7/VDTfcoFmzZsnf31/t2rVTu3bt5O/vr1mzZqlBgwbatm2bu8JDaWSxqNGMp3Tm6+3K2L3PMfzLeyuVOGictnR5UPunz9d1A3rrxsUvOs6f/HKTKkfcqNB7oyQvL1lDA3X908MlSeVC8n8BPBm3ScF9uqhqx1ski0UVrq+tuqMfkiRZQ/glEbgW7fnpnKbO/ElPTt6lGfP2KySonF6LaSZfX29J0qQX96pMGS99tiRC65bdqicfq69/xezRLykXr3JlAJ7MbZXvkSNH6p577tG8efNk+d2fFux2ux599FGNHDlSCQkJV7xOVlaWsrKcq5ZWq7XY40XJ12T2JFVqfL0SOtzvNH5kwfuOf5/b9ZOyjp/ULXGLVb5uTZ3/+YhOrflae/85XU1em6LmsdNly8rW/ufnqGrbm2S32RzXqFC3lm76+HVZypZRbnqGDs1+SzdMGiX9dw6Aa8s33/3q+PeBw+e156dz+uCNm3X7rdW0ak2qht5fWxUreGv0MzuVlp6jtm2qasq4hhrx1A/6+fB5N0YOXIEXHcmu5rY7/MMPP2jMmDEFEm9JslgsGjNmjBITE696nZiYGPn7+zsdMTExLogYJVnjmc8osEcHbekySBd/Sb3i3LStP0iSytf73y4FB1+N1ZfVWmtd3Y6KC75FqZ+ulSSdP3jUMefHp17S6oAbta5eR62pcZvSvs1fZHX+5yPF/XUAlEIZmXk6cuyCaoT4KjS4nO7qGaqYWfu0fUeaDhzKVOzSZCUdOKc7e4S6O1QAbuS25Ds4OFhbt279w/Nbt25VUFDQVa8THR2ts2fPOh3R0dHFGSpKuMYzn1Fw7y7a0nWQLhw6etX5fi0aSpKyUk4WOJd1/IRsF7MUem9PXUg+prPf7XaeYLMp69gJ2XNyFNo/Sr8mfKfsU78WuA6Aa49vOS9dF1xOp37NVjlr/n9e7Xa70xybjQcIooSzeJWcw0O5re3kySef1COPPKLt27erU6dOjkQ7NTVVa9eu1RtvvKGXXnrpqtexWq20mVzDmsyepND+PbWt7zDlncuUNaiaJCnn7DnZLmapfN2aCu3fSydWb1TO6TRVahquRi9F63T8Vp3bmeS4Tt2xQ3Tyy69kt9kU3Ker6o1/WN/dN9rRUlK2amWF3BWp0xu3yrucj2oMukshd3VTQqcH3PG1AZQAwwbX0eZvzyjl5EVVq+Kjh+4Lk80mrY0/qXOZuTpy7IKeHHa95iz6WWfP5aptm6pq3TxAE/69++oXB+Cx3JZ8Dx8+XNWqVdMrr7yiOXPmKO+/DzPx9vZWq1atFBsbq379+rkrPJQSYY/m93dHrPs/p/EfhvxTR99aLlt2jqp1ilCdUQ/Ku0J5XTxyXCnLv9T+qXOc5lfv1k71ox+Vl9VH6Tt+1La+w3Xyi3inOTUG9lHDaeMli0VpWxK1pfNAnf12pwBcmwKrWTXpyXD5VSqrtLM52rk3Xf8Yn6i09BxJ0vhnd+kfD9bRC083lm85b/1y/IKmzvxJW7bz1zLgWmax//5vYm6Qk5OjU6dOSZKqVaumsmXL/uVrriob/pevAQC/FZWTpLa9v3J3GAA8zFcft3V3CA4XV8y6+iRDyvUZ5e4QXKJEPOGybNmyCgkJcXcYAAAAgEt5bjc7AAAAUMKUiMo3AAAASgAP3mWkpOAOAwAAAIaQfAMAAACG0HYCAACAfJd58jiKF5VvAAAAwBAq3wAAAMjnRV3W1bjDAAAAgCEk3wAAAIAhtJ0AAAAgHwsuXY7KNwAAAGAIyTcAAABgCG0nAAAAyMfj5V2OOwwAAAAYQuUbAAAA+djn2+W4wwAAAIAhJN8AAACAIbSdAAAAIB/7fLsclW8AAADAEJJvAAAAwBDaTgAAAJCPfb5djjsMAAAAGELyDQAAABhC2wkAAADysduJy1H5BgAAAAyh8g0AAIB8PF7e5bjDAAAAgCEk3wAAAIAhtJ0AAABAkmRnwaXLUfkGAAAADCH5BgAAAAyh7QQAAAD5eLy8y3GHAQAAAEOofAMAACAflW+X4w4DAAAAhpB8AwAAAIbQdgIAAABJ7PNtApVvAAAAwBCSbwAAAMAQ2k4AAACQj91OXI47DAAAABhC5RsAAAD5WHDpclS+AQAAAENIvgEAAABDaDsBAABAPi/qsq7GHQYAAAAMIfkGAAAADKHtBAAAAJJ4vLwJVL4BAAAAQ0i+AQAAAENoOwEAAEA+Hi/vctxhAAAAwBAq3wAAAJAk2al8uxx3GAAAADCE5BsAAAAwhLYTAAAA5GOfb5ej8g0AAAAYQvINAAAAGELbCQAAACSx24kJ3GEAAADAECrfAAAAyMeCS5ej8g0AAAAYQvINAAAAGELbCQAAAPKx4NLluMMAAACAISTfAAAAgCG0nQAAAECSZGe3E5ej8g0AAAAYQvINAAAAGELbCQAAAPKx24nLcYcBAAAAQ6h8AwAAQJJkFwsuXY3KNwAAAGAIyTcAAABgCG0nAAAAkCTZWXDpctxhAAAAwBCSbwAAAMAQ2k4AAACQj7YTl+MOAwAAAIZQ+QYAAIAkyW5hn29Xo/INAAAAGELyDQAAgFItPj5evXr1UmhoqCwWi1asWOF0fvDgwbJYLE5Ht27dnOacOXNGAwYMkJ+fnwICAjRkyBBlZGQ4zdmxY4fatm2rcuXKqWbNmpo+fXqRYyX5BgAAgKT8fb5LylEUmZmZat68uV577bU/nNOtWzcdP37ccbz77rtO5wcMGKDdu3crLi5OK1euVHx8vB555BHH+fT0dHXt2lVhYWHavn27XnzxRU2ePFnz588vUqz0fAMAAKBU6969u7p3737FOVarVcHBwZc9t3fvXq1evVrffvutWrduLUmaPXu2evTooZdeekmhoaFasmSJsrOz9eabb8rHx0eNGzdWYmKiXn75Zack/WqofAMAAKDEycrKUnp6utORlZX1p6+3YcMGBQYGKjw8XI899phOnz7tOJeQkKCAgABH4i1JnTt3lpeXl7755hvHnHbt2snHx8cxJzIyUklJSfr1118LHQfJNwAAAPJZLCXmiImJkb+/v9MRExPzp75Wt27d9NZbb2nt2rWaNm2aNm7cqO7duysvL0+SlJKSosDAQKf3lClTRlWqVFFKSopjTlBQkNOcS68vzSkM2k4AAABQ4kRHR2vs2LFOY1ar9U9dq3///o5/N23aVM2aNVO9evW0YcMGderU6S/FWVQk3wAAAJCkIi90dCWr1fqnk+2rqVu3rqpVq6b9+/erU6dOCg4O1okTJ5zm5Obm6syZM44+8eDgYKWmpjrNufT6j3rJL6fk3GEAAADAgKNHj+r06dMKCQmRJEVERCgtLU3bt293zFm3bp1sNpvatGnjmBMfH6+cnBzHnLi4OIWHh6ty5cqF/mySbwAAAJRqGRkZSkxMVGJioiTp4MGDSkxMVHJysjIyMjRu3Dht2bJFhw4d0tq1a9W7d2/Vr19fkZGRkqSGDRuqW7duevjhh7V161Z9/fXXGjFihPr376/Q0FBJ0v333y8fHx8NGTJEu3fv1tKlSzVz5swCrTFXQ9sJAAAAJEl2lc7Hy2/btk0dO3Z0vL6UEA8aNEhz587Vjh07tHjxYqWlpSk0NFRdu3bVc88959TWsmTJEo0YMUKdOnWSl5eX7rrrLs2aNctx3t/fX19++aWGDx+uVq1aqVq1apo4cWKRthmUJIvdbrf/xe9bIq0qG+7uEAB4mKicJLXt/ZW7wwDgYb76uK27Q3A4tSvB3SE4VGsS4e4QXIK2EwAAAMAQ2k4AAAAgqWTtduKpCpV8/7bf5WpGjRr1p4MBAAAAPFmhku9XXnmlUBezWCwk3wAAAMAfKFTyffDgQVfHAQAAAHezlM7dTkqTP93Yk52draSkJOXm5hZnPAAAAIDHKnLyff78eQ0ZMkTly5dX48aNlZycLEkaOXKkXnjhhWIPEAAAAGbY5VViDk9V5G8WHR2tH374QRs2bFC5cuUc4507d9bSpUuLNTgAAADAkxR5q8EVK1Zo6dKluuWWW2T5TV9Q48aNdeDAgWINDgAAAPAkRU6+T548qcDAwALjmZmZTsk4AAAAShc7uZzLFbntpHXr1lq1apXj9aWEe8GCBYqI8MzHgAIAAADFociV76lTp6p79+7as2ePcnNzNXPmTO3Zs0ebN2/Wxo0bXREjAAAA4BGKXPm+7bbblJiYqNzcXDVt2lRffvmlAgMDlZCQoFatWrkiRgAAABhgt3iVmMNTFbnyLUn16tXTG2+8UdyxAAAAAB7tTyXfeXl5Wr58ufbu3StJatSokXr37q0yZf7U5QAAAFAC2MWCS1crcra8e/du3XHHHUpJSVF4eLgkadq0aapevbo+/fRTNWnSpNiDBAAAADxBkRtqhg4dqsaNG+vo0aP67rvv9N133+nIkSNq1qyZHnnkEVfECAAAAHiEIle+ExMTtW3bNlWuXNkxVrlyZT3//PO66aabijU4AAAAmOPJCx1LiiLf4RtuuEGpqakFxk+cOKH69esXS1AAAACAJypU8p2enu44YmJiNGrUKC1btkxHjx7V0aNHtWzZMo0ePVrTpk1zdbwAAABAqVWotpOAgACnR8fb7Xb169fPMWa32yVJvXr1Ul5engvCBAAAgKvxeHnXK1TyvX79elfHAQAAAHi8QiXf7du3d3UcAAAAgMf700/FOX/+vJKTk5Wdne003qxZs78cFAAAAMzjITuuV+Tk++TJk/r73/+uzz///LLn6fkGAAAALq/IWw2OHj1aaWlp+uabb+Tr66vVq1dr8eLFuv766/XJJ5+4IkYAAAAYYLd4lZjDUxW58r1u3Tp9/PHHat26tby8vBQWFqYuXbrIz89PMTExioqKckWcAAAAQKlX5F8rMjMzFRgYKCn/yZYnT56UJDVt2lTfffdd8UYHAAAAeJAiJ9/h4eFKSkqSJDVv3lyvv/66fvnlF82bN08hISHFHiAAAADMsMtSYg5PVeS2k8cff1zHjx+XJE2aNEndunXTkiVL5OPjo9jY2OKODwAAAPAYRU6+H3jgAce/W7VqpcOHD+vHH39UrVq1VK1atWINDgAAAPAkf3qf70vKly+vli1bFkcsAAAAcCNP3mWkpChU8j127NhCX/Dll1/+08EAAAAAnqxQyff3339fqItZLJ7bHA8AAODpPHmhY0lRqOR7/fr1ro4DAAAA8Hg09gAAAACG/OUFlwAAAPAMLLh0Pe4wAAAAYAjJNwAAAGAIbScAAACQxG4nJhQq+f7kk08KfcE77rjjTwcDAAAAeLJCJd99+vQp1MUsFovy8vL+SjwAAACAx7LY7Xa7u4MAAACA+x34+Wd3h+BQr25dd4fgEh7b8/3sklx3hwDAw0wcUEa39dro7jAAeJhNn7Z3dwgw6E8l35mZmdq4caOSk5OVnZ3tdG7UqFHFEhgAAADMsttZcOlqRU6+v//+e/Xo0UPnz59XZmamqlSpolOnTql8+fIKDAwk+QYAAAD+QJH3+R4zZox69eqlX3/9Vb6+vtqyZYsOHz6sVq1a6aWXXnJFjAAAAIBHKHLynZiYqCeeeEJeXl7y9vZWVlaWatasqenTp+upp55yRYwAAAAwwC6vEnN4qiJ/s7Jly8rLK/9tgYGBSk5OliT5+/vryJEjxRsdAAAA4EGK3PN944036ttvv9X111+v9u3ba+LEiTp16pTefvttNWnSxBUxAgAAAB6hyJXvqVOnKiQkRJL0/PPPq3Llynrsscd08uRJzZ8/v9gDBAAAgBl2WUrM4amKXPlu3bq149+BgYFavXp1sQYEAAAAeCqPfcgOAAAAisaTK84lRZGT7zp16shi+eP/YX4uQY8lBQAAAEqSIiffo0ePdnqdk5Oj77//XqtXr9a4ceOKKy4AAADA4xQ5+X788ccvO/7aa69p27ZtfzkgAAAAuAdtJ65XbDuYd+/eXR9++GFxXQ4AAADwOMWWfC9btkxVqlQprssBAAAAHudPPWTntwsu7Xa7UlJSdPLkSc2ZM6dYgwMAAIA5tJ24XpGT7969ezsl315eXqpevbo6dOigBg0aFGtwAAAAgCcpcvI9efJkF4QBAAAAd7PbqXy7WpF7vr29vXXixIkC46dPn5a3t3exBAUAAAB4oiIn33a7/bLjWVlZ8vHx+csBAQAAAJ6q0G0ns2bNkiRZLBYtWLBAFStWdJzLy8tTfHw8Pd8AAAClGAsuXa/Qyfcrr7wiKb/yPW/ePKcWEx8fH9WuXVvz5s0r/ggBAAAAD1Ho5PvgwYOSpI4dO+qjjz5S5cqVXRYUAAAA4ImKvNvJ+vXrXREHAAAA3Iy2E9cr8oLLu+66S9OmTSswPn36dN1zzz3FEhQAAADgiYqcfMfHx6tHjx4Fxrt37674+PhiCQoAAADwREVuO8nIyLjsloJly5ZVenp6sQQFAAAA82g7cb0iV76bNm2qpUuXFhh/77331KhRo2IJCgAAAPBERa58P/PMM+rbt68OHDig22+/XZK0du1avfvuu/rggw+KPUAAAACYwePlXa/IyXevXr20YsUKTZ06VcuWLZOvr6+aNWumNWvWqH379q6IEQAAAPAIRU6+JSkqKkpRUVEFxnft2qUmTZr85aAAAAAAT1Tknu/fO3funObPn6+bb75ZzZs3L46YAAAA4AY2WUrM4an+dPIdHx+vBx98UCEhIXrppZd0++23a8uWLcUZGwAAAOBRitR2kpKSotjYWC1cuFDp6enq16+fsrKytGLFCnY6AQAAAK6i0JXvXr16KTw8XDt27NCrr76qY8eOafbs2a6MDQAAAAbZZSkxh6cqdOX7888/16hRo/TYY4/p+uuvd2VMAAAAgEcqdOV706ZNOnfunFq1aqU2bdroP//5j06dOuXK2AAAAGCQ3W4pMYenKnTyfcstt+iNN97Q8ePH9Y9//EPvvfeeQkNDZbPZFBcXp3PnzrkyTgAAAKDUK/JuJxUqVNBDDz2kTZs2aefOnXriiSf0wgsvKDAwUHfccYcrYgQAAAA8wl/a5zs8PFzTp0/X0aNH9e677xZXTAAAAHADdy+yvBYWXP7lh+xIkre3t/r06aNPPvmkOC4HAAAAeKRiSb4BAAAAXF2RHrIDAAAAz+XJu4yUFFS+AQAAAENIvgEAAABDaDsBAACAJHn0LiMlBZVvAAAAwBAq3wAAAJDEgksTqHwDAAAAhpB8AwAAAIbQdgIAAABJks3dAVwDqHwDAAAAhpB8AwAAAIbQdgIAAABJ7HZiApVvAAAAwBAq3wAAAJDEEy5NoPINAAAAGELyDQAAABhC2wkAAAAkseDSBCrfAAAAgCEk3wAAAIAhtJ0AAABAErudmEDlGwAAADCEyjcAAAAkSTa7uyPwfFS+AQAAAENIvgEAAABDaDsBAACAJBZcmkDlGwAAADCE5BsAAAAwhLYTAAAASOLx8iZQ+QYAAAAMIfkGAAAADKHtBAAAAJIkOw/ZcTkq3wAAAIAhVL4BAAAgSbKxz7fLUfkGAAAADCH5BgAAAAyh7QQAAACS2OfbBCrfAAAAgCEk3wAAAIAhtJ0AAABAEvt8m0DlGwAAADCE5BsAAACSJLssJeYoivj4ePXq1UuhoaGyWCxasWKF8/ey2zVx4kSFhITI19dXnTt31r59+5zmnDlzRgMGDJCfn58CAgI0ZMgQZWRkOM3ZsWOH2rZtq3LlyqlmzZqaPn16ke8xyTcAAABKtczMTDVv3lyvvfbaZc9Pnz5ds2bN0rx58/TNN9+oQoUKioyM1MWLFx1zBgwYoN27dysuLk4rV65UfHy8HnnkEcf59PR0de3aVWFhYdq+fbtefPFFTZ48WfPnzy9SrPR8AwAAoFTr3r27unfvftlzdrtdr776qp5++mn17t1bkvTWW28pKChIK1asUP/+/bV3716tXr1a3377rVq3bi1Jmj17tnr06KGXXnpJoaGhWrJkibKzs/Xmm2/Kx8dHjRs3VmJiol5++WWnJP1qqHwDAABAkmSzl5wjKytL6enpTkdWVlaRv9PBgweVkpKizp07O8b8/f3Vpk0bJSQkSJISEhIUEBDgSLwlqXPnzvLy8tI333zjmNOuXTv5+Pg45kRGRiopKUm//vproeMh+QYAAECJExMTI39/f6cjJiamyNdJSUmRJAUFBTmNBwUFOc6lpKQoMDDQ6XyZMmVUpUoVpzmXu8ZvP6MwaDsBAABAiRMdHa2xY8c6jVmtVjdFU3xIvgEAACCpZD1e3mr1KZZkOzg4WJKUmpqqkJAQx3hqaqpatGjhmHPixAmn9+Xm5urMmTOO9wcHBys1NdVpzqXXl+YUBm0nAAAA8Fh16tRRcHCw1q5d6xhLT0/XN998o4iICElSRESE0tLStH37dsecdevWyWazqU2bNo458fHxysnJccyJi4tTeHi4KleuXOh4SL4BAABQqmVkZCgxMVGJiYmS8hdZJiYmKjk5WRaLRaNHj9a///1vffLJJ9q5c6cefPBBhYaGqk+fPpKkhg0bqlu3bnr44Ye1detWff311xoxYoT69++v0NBQSdL9998vHx8fDRkyRLt379bSpUs1c+bMAq0xV0PbCQAAACSV3sfLb9u2TR07dnS8vpQQDxo0SLGxsRo/frwyMzP1yCOPKC0tTbfddptWr16tcuXKOd6zZMkSjRgxQp06dZKXl5fuuusuzZo1y3He399fX375pYYPH65WrVqpWrVqmjhxYpG2GZQki91eWm/zlT27JNfdIQDwMBMHlNFtvTa6OwwAHmbTp+3dHYLDZ9/lXH2SIT1alnV3CC5B5RsAAACSJFsRH+uOoqPnGwAAADCE5BsAAAAwhLYTAAAASCq9Cy5LEyrfAAAAgCEk3wAAAIAhtJ0AAABAUsl6vLynovINAAAAGELlGwAAAJIkGwsuXY7KNwAAAGAIyTcAAABgCG0nAAAAkMQ+3yZQ+QYAAAAMIfkGAAAADKHtBAAAAJIku9jn29WofAMAAACGUPkGAACAJPb5NoHKNwAAAGAIyTcAAABgCG0nAAAAkMQ+3yZQ+QYAAAAMIfkGAAAADKHtBAAAAJJoOzGByjcAAABgCMk3AAAAYAhtJwAAAJAk2ew8Xt7VqHwDAAAAhlD5BgAAgCQWXJpA5RsAAAAwhOQbAAAAMIS2EwAAAEii7cQEKt8AAACAISTfAAAAgCG0nQAAAECSZKPtxOWofAMAAACGUPkGAACAJMnOEy5djso3AAAAYAjJNwAAAGAIbScAAACQxD7fJpB8w+O0b+ql9s2c/6hz6qxdc1bmSZIqV5S6tPRSzeoWlfGW9h+za/U2mzIv5s8NC7RoUBfvy157wee5OnbGpeEDKKUeuLumHh1UV+9/fFSzFhxwjDcO99MjA2urUbifbDa79v2cobGTdio72+bGaAG4C8k3PNKJNLveXpvneH1p66Sy3tKA272V+uv/zndo5qX+7b218Iv810dO2TXjw1yn63Vs7qU6QRYSbwCX1eD6SrqjW4j2H8xwGm8c7qcZU5rq/5Yl69X5+5WbZ9f1dSrKzn5uwDWL5BseyWaTo5L9WzWrWxRQQZr/mU3Z/82vP06wafw93qoTbNHBFHuB93pZpPAaFm1NokoFoCDfcl6a9EQDTZ/9kwbdG+Z0btTQelr26S/6v2VHHGNHfrlgOkSg0Pi90PVYcAmPVMVPGnOnt0be4a07/+Ylv/L542X+202S95s8Ojcvv8etVvXLb690Qw2LfH2kxAP8RAJQ0NhHr9fmbWe07Yc0p/EA/7Jq3MBPv57N1tzpLfTJWxGaHdNczRr5uSdQACVCiU6+jxw5ooceesjdYaCU+eW0XR8n2LRkfZ4++9amgIoWDe7qLZ8y0tFTdmXnSp1u9FIZ7/w2lC4tveTlZVFF38tf78Z6Fh04btc5ilUAfqdT2+q6oV5Fvb745wLnrgsuJ0l66L7a+vSL43pi8k79dCBDr/67uWqE/MEPHAAer0S3nZw5c0aLFy/Wm2+++YdzsrKylJWV5TRmtVolXX7BHDzf/mP/q1CfSLPr6Kk8Pd7HW43CLEo8YNeyr2zqcbOX2oR7y26Xdh2269hp+2VXeFfyleqFWLRsEy0nAJwFVrPq8Yfra8zEHcrOKfgDxGLJ/2vax6uP67O1qZKkfT9nqFWzAEV1Cdbrbx00Gi9QGOx24npuTb4/+eSTK57/+eeClYTfi4mJ0ZQpU5zGJk2aJK/rn/5LscFzZOVIp89JVSpZJNn1c4pd//kkT77W/N7wrBxpbF9v7T5c8CdOi3oWXciWfjrKTyMAzsLrV1SVyj5a+Gorx1gZb4uaN/ZX357X6f5Ht0qSDh3JdHrf4aPnFVTdajRWACWHW5PvPn36yGKxyH6FX7MuVQ7+SHR0tMaOHes0ZrVaNW1ZsYQID1C2jFSlorTzgvP/zy789w8mtYMsqlDu8gl2i7pe2vGznQUoAArY9kOaBg7/1mnsqdHhOnz0gpYsS9axlIs6eTpLta4r7zSnZqivtmz/1WSoQKFR+XY9tybfISEhmjNnjnr37n3Z84mJiWrVqtVlz11itVr/22bye7mXGcO1oMuNXvrpF5vSMvPbRjo085LNLu06lP8TpXldi06dtet8llSjmkWRrb205Ue7Tp9zvk6dIIsqV7LouwN5l/kUANe6CxfydDD5vNPYxYs2pafnOMbf+eiIhtxfW/sPZmjfwQx1vz1YYTXK6+kX9rgjZAAlgFuT71atWmn79u1/mHxfrSoOXE6l8lLfW73la5XOZ0nJJ+x684s8nf9vpbuan0WdWnjJ10dKy5Q27bJpy4+XqXrXt+jISbtOpxv+AgA8xgef/CKrj5dGDq0nv0pltf9ghsZM3KFjKZfZCxXANcGtyfe4ceOUmZn5h+fr16+v9evXG4wInuCjr6+8OHJtok1rE69+neVXuQ4A/N7Ip34oMPZ/y4447fMNlGS0WbqeW5Pvtm3bXvF8hQoV1L59e0PRAAAAAK5Vovf5BgAAADxJid7nGwAAAOaw1M71qHwDAAAAhlD5BgAAgKT8h8/Btah8AwAAAIaQfAMAAACG0HYCAAAASSy4NIHKNwAAAGAIyTcAAABgCG0nAAAAkETbiQlUvgEAAABDSL4BAAAAQ2g7AQAAgCTJRtuJy1H5BgAAAAyh8g0AAABJkr1Erbi0uDsAl6DyDQAAABhC8g0AAAAYQtsJAAAAJLHPtwlUvgEAAABDSL4BAAAAQ2g7AQAAgCTJZnN3BJ6PyjcAAABgCJVvAAAASGLBpQlUvgEAAABDSL4BAAAAQ2g7AQAAgCTJRtuJy1H5BgAAAAwh+QYAAAAMoe0EAAAAktjtxAQq3wAAAIAhVL4BAAAgSbKXqBWXFncH4BJUvgEAAABDSL4BAAAAQ2g7AQAAgCT2+TaByjcAAABgCMk3AAAAYAhtJwAAAJDEPt8mUPkGAAAADCH5BgAAAAyh7QQAAACSJBvbnbgclW8AAADAECrfAAAAkMSCSxOofAMAAACGkHwDAAAAhtB2AgAAAEm0nZhA5RsAAAAwhOQbAAAAMIS2EwAAAEiSbPSduByVbwAAAMAQKt8AAACQJNlt7o7A81H5BgAAAAwh+QYAAAAMoe0EAAAAkiQ7Cy5djso3AAAAYAjJNwAAAGAIbScAAACQJNnY7cTlqHwDAAAAhpB8AwAAAIbQdgIAAABJ7HZiApVvAAAAwBAq3wAAAJAk2Sh8uxyVbwAAAMAQkm8AAADAENpOAAAAIEmy03ficlS+AQAAAENIvgEAAABDaDsBAACAJIltvl2PyjcAAABgCJVvAAAASJJsLLh0OSrfAAAAgCEk3wAAAIAhtJ0AAABAkmRnxaXLUfkGAAAADCH5BgAAQKk2efJkWSwWp6NBgwaO8xcvXtTw4cNVtWpVVaxYUXfddZdSU1OdrpGcnKyoqCiVL19egYGBGjdunHJzc4s9VtpOAAAAIEmy29wdwZ/XuHFjrVmzxvG6TJn/pbljxozRqlWr9MEHH8jf318jRoxQ37599fXXX0uS8vLyFBUVpeDgYG3evFnHjx/Xgw8+qLJly2rq1KnFGifJNwAAAEq9MmXKKDg4uMD42bNntXDhQr3zzju6/fbbJUmLFi1Sw4YNtWXLFt1yyy368ssvtWfPHq1Zs0ZBQUFq0aKFnnvuOU2YMEGTJ0+Wj49PscVJ2wkAAAAkSTa7vcQcRbVv3z6Fhoaqbt26GjBggJKTkyVJ27dvV05Ojjp37uyY26BBA9WqVUsJCQmSpISEBDVt2lRBQUGOOZGRkUpPT9fu3bv/4l11RuUbAAAAJU5WVpaysrKcxqxWq6xWa4G5bdq0UWxsrMLDw3X8+HFNmTJFbdu21a5du5SSkiIfHx8FBAQ4vScoKEgpKSmSpJSUFKfE+9L5S+eKE5VvAAAAlDgxMTHy9/d3OmJiYi47t3v37rrnnnvUrFkzRUZG6rPPPlNaWpref/99w1FfHZVvAAAASCpZ+3xHR0dr7NixTmOXq3pfTkBAgG644Qbt379fXbp0UXZ2ttLS0pyq36mpqY4e8eDgYG3dutXpGpd2Q7lcH/lfQeUbAAAAJY7VapWfn5/TUdjkOyMjQwcOHFBISIhatWqlsmXLau3atY7zSUlJSk5OVkREhCQpIiJCO3fu1IkTJxxz4uLi5Ofnp0aNGhXr96LyDQAAgFLtySefVK9evRQWFqZjx45p0qRJ8vb21n333Sd/f38NGTJEY8eOVZUqVeTn56eRI0cqIiJCt9xyiySpa9euatSokQYOHKjp06crJSVFTz/9tIYPH17ohL+wSL4BAAAgSbLZSk7bSVEcPXpU9913n06fPq3q1avrtttu05YtW1S9enVJ0iuvvCIvLy/dddddysrKUmRkpObMmeN4v7e3t1auXKnHHntMERERqlChggYNGqRnn3222GMl+QYAAECp9t57713xfLly5fTaa6/ptdde+8M5YWFh+uyzz4o7tALo+QYAAAAMofINAAAASVIJ2uzEY1H5BgAAAAyh8g0AAABJkr2ULrgsTah8AwAAAIaQfAMAAACG0HYCAAAASZKNFZcuR+UbAAAAMITkGwAAADCEthMAAABIYrcTE6h8AwAAAIZQ+QYAAIAkKt8mUPkGAAAADCH5BgAAAAyh7QQAAACSJLpOXI/KNwAAAGAIyTcAAABgCG0nAAAAkMRuJyZQ+QYAAAAMIfkGAAAADKHtBAAAAJIku522E1ej8g0AAAAYQuUbAAAAkiQbCy5djso3AAAAYAjJNwAAAGAIbScAAACQxIJLE6h8AwAAAIaQfAMAAACG0HYCAAAASTxe3gQq3wAAAIAhVL4BAAAgicq3CVS+AQAAAENIvgEAAABDaDsBAACAJMnGPt8uR+UbAAAAMITkGwAAADCEthMAAABIYrcTE6h8AwAAAIZQ+QYAAIAkyc6CS5ej8g0AAAAYQvINAAAAGELbCQAAACRJNhZcuhyVbwAAAMAQkm8AAADAENpOAAAAIIl9vk2g8g0AAAAYQvINAAAAGELbCQAAACTxkB0TqHwDAAAAhlD5BgAAgCTJbrO5OwSP57HJ98QBHvvVUIyysrIUExOj6OhoWa1Wd4eDUmDTp+3dHQJKAX62APgjFjvNPbiGpaeny9/fX2fPnpWfn5+7wwHgIfjZgtLqvvHJ7g7B4d3ptdwdgktQHgYAAIAkHi9vAgsuAQAAAENIvgEAAABDaDvBNc1qtWrSpEksiAJQrPjZgtKKpYCux4JLAAAASJL6PXHI3SE4vD+jtrtDcAkq3wAAAJAk2Vlw6XL0fAMAAACGkHwDAAAAhpB845r12muvqXbt2ipXrpzatGmjrVu3ujskAKVcfHy8evXqpdDQUFksFq1YscLdIQFFYrfZS8zhqUi+cU1aunSpxo4dq0mTJum7775T8+bNFRkZqRMnTrg7NAClWGZmppo3b67XXnvN3aEAKKHY7QTXpDZt2uimm27Sf/7zH0mSzWZTzZo1NXLkSP3zn/90c3QAPIHFYtHy5cvVp08fd4cCFNrdj//s7hAcls2s6+4QXILdTnDNyc7O1vbt2xUdHe0Y8/LyUufOnZWQkODGyAAAcC+b3ebuEDwebSe45pw6dUp5eXkKCgpyGg8KClJKSoqbogIAANcCkm8AAADAENpOcM2pVq2avL29lZqa6jSempqq4OBgN0UFAID7efIuIyUFlW9cc3x8fNSqVSutXbvWMWaz2bR27VpFRES4MTIAAODpqHzjmjR27FgNGjRIrVu31s0336xXX31VmZmZ+vvf/+7u0ACUYhkZGdq/f7/j9cGDB5WYmKgqVaqoVq1abowMKBwq365H8o1r0r333quTJ09q4sSJSklJUYsWLbR69eoCizABoCi2bdumjh07Ol6PHTtWkjRo0CDFxsa6KSoAJQn7fAMAAECS1GfYT+4OwWHFnBvcHYJLUPkGAACAJImarOux4BIAAAAwhOQbAAAAMIS2EwAAAEjK33oXrkXlGwAAADCEyjcAAAAksc+3CVS+AQAAAENIvgEAAABDSL4BeJTBgwerT58+jtcdOnTQ6NGjjcexYcMGWSwWpaWl/eEci8WiFStWFPqakydPVosWLf5SXIcOHZLFYlFiYuJfug4Az2S320rM4alIvgG43ODBg2WxWGSxWOTj46P69evr2WefVW5urss/+6OPPtJzzz1XqLmFSZgBAPgrWHAJwIhu3bpp0aJFysrK0meffabhw4erbNmyio6OLjA3OztbPj4+xfK5VapUKZbrAABQHKh8AzDCarUqODhYYWFheuyxx9S5c2d98sknkv7XKvL8888rNDRU4eHhkqQjR46oX79+CggIUJUqVdS7d28dOnTIcc28vDyNHTtWAQEBqlq1qsaPH1/g0ci/bzvJysrShAkTVLNmTVmtVtWvX18LFy7UoUOH1LFjR0lS5cqVZbFYNHjwYEn5+97GxMSoTp068vX1VfPmzbVs2TKnz/nss890ww03yNfXVx07dnSKs7AmTJigG264QeXLl1fdunX1zDPPKCcnp8C8119/XTVr1lT58uXVr18/nT171un8ggUL1LBhQ5UrV04NGjTQnDlzihwLgGuT3WYvMYenIvkG4Ba+vr7Kzs52vF67dq2SkpIUFxenlStXKicnR5GRkapUqZK++uorff3116pYsaK6devmeN+MGTMUGxurN998U5s2bdKZM2e0fPnyK37ugw8+qHfffVezZs3S3r179frrr6tixYqqWbOmPvzwQ0lSUlKSjh8/rpkzZ0qSYmJi9NZbb2nevHnavXu3xowZowceeEAbN26UlP9LQt++fdWrVy8lJiZq6NCh+uc//1nke1KpUiXFxsZqz549mjlzpt544w298sorTnP279+v999/X59++qlWr16t77//XsOGDXOcX7JkiSZOnKjnn39ee/fu1dSpU/XMM89o8eLFRY4HAFD8aDsBYJTdbtfatWv1xRdfaOTIkY7xChUqaMGCBY52k//7v/+TzWbTggULZLFYJEmLFi1SQECANmzYoK5du+rVV19VdHS0+vbtK0maN2+evvjiiz/87J9++knvv/++4uLi1LlzZ0lS3bp1HecvtagEBgYqICBAUn6lfOrUqVqzZo0iIiIc79m0aZNef/11tW/fXnPnzlW9evU0Y8YMSVJ4eLh27typadOmFenePP30045/165dW08++aTee+89jR8/3jF+8eJFvfXWW7ruuuskSbNnz1ZUVJRmzJih4OBgTZo0STNmzHDckzp16mjPnj16/fXXNWjQoCLFAwAofiTfAIxYuXKlKlasqJycHNlsNt1///2aPHmy43zTpk2d+rx/+OEH7d+/X5UqVXK6zsWLF3XgwAGdPXtWx48fV5s2bRznypQpo9atWxdoPbkkMTFR3t7eat++faHj3r9/v86fP68uXbo4jWdnZ+vGG2+UJO3du9cpDkmORL0oli5dqlmzZunAgQPKyMhQbm6u/Pz8nObUqlXLkXhf+hybzaakpCRVqlRJBw4c0JAhQ/Twww875uTm5srf37/I8QC49nhyu0dJQfINwIiOHTtq7ty58vHxUWhoqMqUcf7xU6FCBafXGRkZatWqlZYsWVLgWtWrV/9TMfj6+hb5PRkZGZKkVatWOSW9Un4fe3FJSEjQgAEDNGXKFEVGRsrf31/vvfeeo5pelFjfeOONAr8MeHt7F1usAIA/j+QbgBEVKlRQ/fr1Cz2/ZcuWWrp0qQIDAwtUfy8JCQnRN998o3bt2knKr/Bu375dLVu2vOz8pk2bymazaePGjY62k9+6VHnPy8tzjDVq1EhWq1XJycl/WDFv2LChY/HoJVu2bLn6l/yNzZs3KywsTP/6178cY4cPHy4wLzk5WceOHVNoaKjjc7y8vBQeHq6goCCFhobq559/1oABA4r0+QAgSTYP3l+7pGDBJYASacCAAapWrZp69+6tr776SgcPHtSGDRs0atQoHT16VJL0+OOP64UXXtCKFSv0448/atiwYVfco7t27doaNGiQHnroIa1YscJxzffff1+SFBYWJovFopUrV+rkyZPKyMhQpUqV9OSTT2rMmDFavHixDhw4oO+++06zZ892LGJ89NFHtW/fPo0bN05JSUl65513FBsbW6Tve/311ys5OVnvvfeeDhw4oFmzZl128Wi5cuU0aNAg/fDDD/rqq680atQo9evXT8HBwZKkKVOmKCYmRrNmzdJPP/2knTt3atGiRXr55ZeLFA8AwDVIvgGUSOXLl1d8fLxq1aqlvn37qmHDhhoyZIguXrzoqIQ/8cQTGjhwoAYNGqSIiAhVqlRJd9555xWvO3fuXN19990aNmyYGjRooIcffliZmZmSpOuuu05TpkzRP//5TwUFBWnEiBGSpOeee07PPPOMYmJi1LBhQ3Xr1k2rVq1SnTp1JOX3YX/44YdasWKFmjdvrnnz5mnq1KlF+r533HGHxowZoxEjRqhFixbavHmznnnmmQLz6tevr759+6pHjx7q2rWrmjVr5rSV4NChQ7VgwQItWrRITZs2Vfv27RUbG+uIFQDgXhb7H61MAgAAwDWl68Dv3R2Cw5dv3+juEFyCyjcAAABgCMk3AAAAYAi7nQAAAECSZLex24mrUfkGAAAADKHyDQAAAEk84dIEKt8AAACAISTfAAAAgCG0nQAAAECSZOfx8i5H5RsAAAAwhOQbAAAAMIS2EwAAAEiSbOx24nJUvgEAAABDqHwDAABAEk+4NIHKNwAAAGAIyTcAAABgCG0nAAAAkMTj5U2g8g0AAAAYQvINAAAAGELbCQAAACTxeHkTqHwDAAAAhpB8AwAAAIbQdgIAAABJ7HZiApVvAAAAwBAq3wAAAJDE4+VNoPINAAAAGELyDQAAABhisdvtdNYDAAAABlD5BgAAAAwh+QYAAAAMIfkGAAAADCH5BgAAAAwh+QYAAAAMIfkGAAAADCH5BgAAAAwh+QYAAAAMIfkGAAAADPl/9ohMvzNGzBQAAAAASUVORK5CYII=", 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", 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" ] @@ -359,7 +707,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 20, "id": "1e21c8b3", "metadata": {}, "outputs": [ @@ -367,10 +715,10 @@ "name": "stdout", "output_type": "stream", "text": [ - "Accuracy model: 0.802\n", - "Exited Churn='NO': 0.978\n", - "Exited Churn='YES': 0.072\n", - "F1 Score: 0.123\n" + "Accuracy model: 0.817\n", + "Exited Churn='NO': 0.973\n", + "Exited Churn='YES': 0.173\n", + "F1 Score: 0.269\n" ] } ], @@ -403,7 +751,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 21, "id": "20f25624-4ba7-4c0d-a79a-590d1884b7d0", "metadata": {}, "outputs": [], From 9e886040063eb3389dd19ec6b04cb44cdab52dd5 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Angel=20Mart=C3=ADnez?= <76793458+AFMartinezF@users.noreply.github.com> Date: Sun, 20 Oct 2024 21:38:45 +0000 Subject: [PATCH 6/9] Used randomized search and grid search to improve model --- models/model.pk | Bin 972 -> 1001 bytes .../modelgeneration_27092023_ricalanis.ipynb | 588 ++++++++++++++---- 2 files changed, 470 insertions(+), 118 deletions(-) diff --git a/models/model.pk b/models/model.pk index 91665e4ce3112a359db522918c4068526630bee7..73824ebaf0a69377a59b74c79357b541dd6591b0 100644 GIT binary patch delta 456 zcmX@Z{*s-gfo1Bwi7ZKzofsu$*ou=Aa}tZDOrFxinpc`zPzj_{N-7Idfg+Qum{io9 zIcCiSft~hK+NK0e>0xx9lEIxJ=*$tgL$398;0cKE#2R;gtsb`G{G77XqA5Mh#fj+? zujH9!aQ5)T7o{fW=M|R}l_r+}4b9-`Vb4oREGkN@1oFHYTBkTOCQWGv8m-~Y=*`tS zC4+DBJjP>US{XVZ$qYT16cdmmIC&nEQay$gBS=>dQ>Mw3&JKuj<_sY}KR>VkKmaDZ z8A_%kbvm=KFfcGo0Wy17lk-#4;-_R_n&r*a2DGTtIbcW1hDGVtTlR;YY&OcvUt_=T z`~LTd&oA$e?nwnFG_Osr<^ET?tBYVlTrjmK8GxpootK|OpT(|$F z%A}vSCOz11vsP>00nSzX!4`96=9Q!tC8rjYV6`3O$xdeurNW#8JrN%uS_I;YvvX1t Qi}K=ufm@t8c^@+$0BS3}G5`Po delta 420 zcmaFKeukZ;fo1B!i7ZKC?)Fk-I1@PjR>ZzyJmlpSlY&^sp7@=ai)uP3d9H zNlHsEo@~vSXV@c}SDIT;sh6Bzl&Y6onp2XQSX7i)Ii-guz9=<0Kd-o?s5H4`%4DD> zu)-;m_c1DPOZTv*lvEa^0>vlaXFMh*l_BfR&^jeUzI{s26b)}iZzdo|W#Vj=$-9}9 z>M>*)L9#tenI=;@J0LokGwl8R{Jj1H0hsV+D4CMf>C7Sqbp8||vxhY~KQ%3WN(QD` z-dt@{GVD5?0~WC_RuOxAWIwaE`&X7LTkZe+zrAC6(8c}revjqX6sfa16#JifeqiFJ z{mkk!Uo1WR*xuyyt-nW1*Y6KtGxYtssAqr5&#Pfh$`AMZPFkw`S9_&B*kZ2Cypq(S t+Os}cYJ diff --git a/notebooks/modelgeneration_27092023_ricalanis.ipynb b/notebooks/modelgeneration_27092023_ricalanis.ipynb index 8727d6bc..5f98ab25 100644 --- a/notebooks/modelgeneration_27092023_ricalanis.ipynb +++ b/notebooks/modelgeneration_27092023_ricalanis.ipynb @@ -219,7 +219,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": null, "id": "b8f22789", "metadata": {}, "outputs": [ @@ -251,7 +251,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": null, "id": "e757c386", "metadata": {}, "outputs": [ @@ -283,7 +283,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 8, "id": "c6519a08-642b-4ce3-8800-bfd80be89989", "metadata": {}, "outputs": [], @@ -307,7 +307,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": null, "id": "fe0bc646", "metadata": {}, "outputs": [ @@ -317,7 +317,7 @@ "{1: {'France': 0, 'Germany': 1, 'Spain': 2}, 2: {'Female': 0, 'Male': 1}}" ] }, - "execution_count": 12, + "execution_count": 9, "metadata": {}, "output_type": "execute_result" } @@ -328,7 +328,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 10, "id": "fbb5d4f3", "metadata": {}, "outputs": [ @@ -387,7 +387,7 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 11, "id": "cb8dcb36", "metadata": {}, "outputs": [ @@ -427,143 +427,143 @@ " \n", " \n", " \n", - " 7482\n", - " 0.736\n", - " 0.5\n", + " 7923\n", + " 0.760\n", + " 1.0\n", " 1.0\n", - " 0.337838\n", + " 0.270270\n", " 0.5\n", - " 0.528564\n", - " 0.333333\n", + " 0.473764\n", + " 0.000000\n", " 1.0\n", - " 0.0\n", - " 0.164953\n", + " 1.0\n", + " 0.816608\n", " 0.0\n", " \n", " \n", - " 175\n", - " 0.268\n", + " 3386\n", + " 0.832\n", " 1.0\n", - " 0.0\n", - " 0.229730\n", - " 0.7\n", - " 0.533556\n", - " 0.000000\n", " 1.0\n", + " 0.310811\n", + " 0.6\n", + " 0.395413\n", + " 0.333333\n", " 1.0\n", - " 0.136386\n", + " 0.0\n", + " 0.311984\n", " 0.0\n", " \n", " \n", - " 8635\n", - " 0.602\n", - " 0.5\n", - " 1.0\n", - " 0.148649\n", - " 0.3\n", - " 0.485815\n", - " 0.000000\n", - " 1.0\n", + " 3497\n", + " 0.212\n", + " 0.0\n", " 0.0\n", - " 0.272621\n", + " 0.608108\n", + " 0.1\n", + " 0.659035\n", + " 0.333333\n", + " 0.0\n", + " 0.0\n", + " 0.703800\n", " 1.0\n", " \n", " \n", - " 3584\n", - " 0.312\n", - " 0.5\n", - " 1.0\n", - " 0.135135\n", - " 0.8\n", - " 0.211455\n", - " 0.000000\n", + " 7302\n", + " 0.282\n", + " 0.0\n", " 0.0\n", + " 0.729730\n", + " 0.6\n", + " 0.363834\n", + " 0.000000\n", " 1.0\n", - " 0.122841\n", + " 1.0\n", + " 0.035110\n", " 0.0\n", " \n", " \n", - " 5681\n", - " 0.358\n", - " 1.0\n", + " 6983\n", + " 0.712\n", " 0.0\n", - " 0.283784\n", - " 0.2\n", - " 0.329881\n", + " 1.0\n", + " 0.229730\n", + " 0.5\n", " 0.000000\n", + " 0.333333\n", " 1.0\n", " 1.0\n", - " 0.614628\n", + " 0.408573\n", " 0.0\n", " \n", " \n", - " 5165\n", - " 1.000\n", + " 6935\n", + " 0.640\n", " 0.0\n", " 1.0\n", " 0.202703\n", - " 0.7\n", - " 0.561810\n", + " 0.1\n", " 0.000000\n", - " 0.0\n", - " 0.0\n", - " 0.017495\n", + " 0.333333\n", + " 1.0\n", + " 1.0\n", + " 0.432049\n", " 0.0\n", " \n", " \n", - " 2335\n", - " 0.748\n", - " 0.5\n", + " 3826\n", + " 0.848\n", " 0.0\n", - " 0.405405\n", - " 0.6\n", - " 0.440271\n", - " 0.333333\n", " 1.0\n", + " 0.783784\n", + " 0.4\n", + " 0.448433\n", + " 0.000000\n", " 1.0\n", - " 0.402741\n", " 1.0\n", + " 0.715676\n", + " 0.0\n", " \n", " \n", - " 4930\n", - " 0.554\n", + " 9227\n", + " 0.852\n", + " 0.0\n", + " 0.0\n", + " 0.175676\n", " 0.5\n", - " 1.0\n", - " 0.162162\n", - " 0.6\n", - " 0.447883\n", " 0.000000\n", + " 0.333333\n", " 1.0\n", - " 1.0\n", - " 0.590144\n", + " 0.0\n", + " 0.463226\n", " 0.0\n", " \n", " \n", - " 5659\n", - " 0.392\n", + " 1341\n", + " 0.888\n", " 0.0\n", " 0.0\n", - " 0.459459\n", - " 0.2\n", - " 0.000000\n", - " 0.000000\n", + " 0.310811\n", + " 0.7\n", + " 0.704850\n", + " 0.666667\n", " 1.0\n", " 0.0\n", - " 0.686670\n", + " 0.832653\n", " 1.0\n", " \n", " \n", - " 3899\n", - " 0.804\n", - " 0.0\n", + " 7466\n", + " 0.700\n", + " 0.5\n", " 0.0\n", - " 0.243243\n", - " 0.2\n", - " 0.477933\n", + " 0.162162\n", + " 0.4\n", + " 0.463844\n", " 0.000000\n", " 1.0\n", - " 0.0\n", - " 0.621776\n", + " 1.0\n", + " 0.672093\n", " 0.0\n", " \n", " \n", @@ -572,31 +572,31 @@ ], "text/plain": [ " CreditScore Geography Gender Age Tenure Balance \\\n", - "7482 0.736 0.5 1.0 0.337838 0.5 0.528564 \n", - "175 0.268 1.0 0.0 0.229730 0.7 0.533556 \n", - "8635 0.602 0.5 1.0 0.148649 0.3 0.485815 \n", - "3584 0.312 0.5 1.0 0.135135 0.8 0.211455 \n", - "5681 0.358 1.0 0.0 0.283784 0.2 0.329881 \n", - "5165 1.000 0.0 1.0 0.202703 0.7 0.561810 \n", - "2335 0.748 0.5 0.0 0.405405 0.6 0.440271 \n", - "4930 0.554 0.5 1.0 0.162162 0.6 0.447883 \n", - "5659 0.392 0.0 0.0 0.459459 0.2 0.000000 \n", - "3899 0.804 0.0 0.0 0.243243 0.2 0.477933 \n", + "7923 0.760 1.0 1.0 0.270270 0.5 0.473764 \n", + "3386 0.832 1.0 1.0 0.310811 0.6 0.395413 \n", + "3497 0.212 0.0 0.0 0.608108 0.1 0.659035 \n", + "7302 0.282 0.0 0.0 0.729730 0.6 0.363834 \n", + "6983 0.712 0.0 1.0 0.229730 0.5 0.000000 \n", + "6935 0.640 0.0 1.0 0.202703 0.1 0.000000 \n", + "3826 0.848 0.0 1.0 0.783784 0.4 0.448433 \n", + "9227 0.852 0.0 0.0 0.175676 0.5 0.000000 \n", + "1341 0.888 0.0 0.0 0.310811 0.7 0.704850 \n", + "7466 0.700 0.5 0.0 0.162162 0.4 0.463844 \n", "\n", " NumOfProducts HasCrCard IsActiveMember EstimatedSalary Exited \n", - "7482 0.333333 1.0 0.0 0.164953 0.0 \n", - "175 0.000000 1.0 1.0 0.136386 0.0 \n", - "8635 0.000000 1.0 0.0 0.272621 1.0 \n", - "3584 0.000000 0.0 1.0 0.122841 0.0 \n", - "5681 0.000000 1.0 1.0 0.614628 0.0 \n", - "5165 0.000000 0.0 0.0 0.017495 0.0 \n", - "2335 0.333333 1.0 1.0 0.402741 1.0 \n", - "4930 0.000000 1.0 1.0 0.590144 0.0 \n", - "5659 0.000000 1.0 0.0 0.686670 1.0 \n", - "3899 0.000000 1.0 0.0 0.621776 0.0 " + "7923 0.000000 1.0 1.0 0.816608 0.0 \n", + "3386 0.333333 1.0 0.0 0.311984 0.0 \n", + "3497 0.333333 0.0 0.0 0.703800 1.0 \n", + "7302 0.000000 1.0 1.0 0.035110 0.0 \n", + "6983 0.333333 1.0 1.0 0.408573 0.0 \n", + "6935 0.333333 1.0 1.0 0.432049 0.0 \n", + "3826 0.000000 1.0 1.0 0.715676 0.0 \n", + "9227 0.333333 1.0 0.0 0.463226 0.0 \n", + "1341 0.666667 1.0 0.0 0.832653 1.0 \n", + "7466 0.000000 1.0 1.0 0.672093 0.0 " ] }, - "execution_count": 14, + "execution_count": 11, "metadata": {}, "output_type": "execute_result" } @@ -620,7 +620,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 12, "id": "21e4ba90-1206-4ce6-bdc8-6986e6b93ef5", "metadata": {}, "outputs": [], @@ -632,7 +632,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 13, "id": "f45f3df3-bcbe-45f3-820c-82867e36d012", "metadata": {}, "outputs": [], @@ -644,7 +644,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 14, "id": "8a6ee78f-7c8b-4810-a763-c8b20155ec28", "metadata": {}, "outputs": [], @@ -653,6 +653,358 @@ "X_train, X_test, y_train, y_test = train_test_split( X, y, test_size=0.33, random_state=42)" ] }, + { + "cell_type": "code", + "execution_count": 15, + "id": "8cd168ca", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Fitting 5 folds for each of 100 candidates, totalling 500 fits\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py:425: FitFailedWarning: \n", + "370 fits failed out of a total of 500.\n", + "The score on these train-test partitions for these parameters will be set to 0.\n", + "If these failures are not expected, you can try to debug them by setting error_score='raise'.\n", + "\n", + "Below are more details about the failures:\n", + "--------------------------------------------------------------------------------\n", + "35 fits failed with the following error:\n", + "Traceback (most recent call last):\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", + " estimator.fit(X_train, y_train, **fit_params)\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1151, in wrapper\n", + " return fit_method(estimator, *args, **kwargs)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 1168, in fit\n", + " solver = _check_solver(self.solver, self.penalty, self.dual)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 56, in _check_solver\n", + " raise ValueError(\n", + "ValueError: Solver newton-cg supports only 'l2' or 'none' penalties, got elasticnet penalty.\n", + "\n", + "--------------------------------------------------------------------------------\n", + "25 fits failed with the following error:\n", + "Traceback (most recent call last):\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", + " estimator.fit(X_train, y_train, **fit_params)\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1151, in wrapper\n", + " return fit_method(estimator, *args, **kwargs)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 1168, in fit\n", + " solver = _check_solver(self.solver, self.penalty, self.dual)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 56, in _check_solver\n", + " raise ValueError(\n", + "ValueError: Solver sag supports only 'l2' or 'none' penalties, got l1 penalty.\n", + "\n", + "--------------------------------------------------------------------------------\n", + "20 fits failed with the following error:\n", + "Traceback (most recent call last):\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", + " estimator.fit(X_train, y_train, **fit_params)\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1151, in wrapper\n", + " return fit_method(estimator, *args, **kwargs)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 1168, in fit\n", + " solver = _check_solver(self.solver, self.penalty, self.dual)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 56, in _check_solver\n", + " raise ValueError(\n", + "ValueError: Solver lbfgs supports only 'l2' or 'none' penalties, got elasticnet penalty.\n", + "\n", + "--------------------------------------------------------------------------------\n", + "72 fits failed with the following error:\n", + "Traceback (most recent call last):\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", + " estimator.fit(X_train, y_train, **fit_params)\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1144, in wrapper\n", + " estimator._validate_params()\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 637, in _validate_params\n", + " validate_parameter_constraints(\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/utils/_param_validation.py\", line 95, in validate_parameter_constraints\n", + " raise InvalidParameterError(\n", + "sklearn.utils._param_validation.InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'l1', 'none' (deprecated), 'elasticnet', 'l2'} or None. Got 'None' instead.\n", + "\n", + "--------------------------------------------------------------------------------\n", + "44 fits failed with the following error:\n", + "Traceback (most recent call last):\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", + " estimator.fit(X_train, y_train, **fit_params)\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1144, in wrapper\n", + " estimator._validate_params()\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 637, in _validate_params\n", + " validate_parameter_constraints(\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/utils/_param_validation.py\", line 95, in validate_parameter_constraints\n", + " raise InvalidParameterError(\n", + "sklearn.utils._param_validation.InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'l2', 'none' (deprecated), 'elasticnet', 'l1'} or None. Got 'None' instead.\n", + "\n", + "--------------------------------------------------------------------------------\n", + "25 fits failed with the following error:\n", + "Traceback (most recent call last):\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", + " estimator.fit(X_train, y_train, **fit_params)\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1151, in wrapper\n", + " return fit_method(estimator, *args, **kwargs)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 1178, in fit\n", + " raise ValueError(\"l1_ratio must be specified when penalty is elasticnet.\")\n", + "ValueError: l1_ratio must be specified when penalty is elasticnet.\n", + "\n", + "--------------------------------------------------------------------------------\n", + "34 fits failed with the following error:\n", + "Traceback (most recent call last):\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", + " estimator.fit(X_train, y_train, **fit_params)\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1144, in wrapper\n", + " estimator._validate_params()\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 637, in _validate_params\n", + " validate_parameter_constraints(\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/utils/_param_validation.py\", line 95, in validate_parameter_constraints\n", + " raise InvalidParameterError(\n", + "sklearn.utils._param_validation.InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'l2', 'l1', 'elasticnet', 'none' (deprecated)} or None. Got 'None' instead.\n", + "\n", + "--------------------------------------------------------------------------------\n", + "35 fits failed with the following error:\n", + "Traceback (most recent call last):\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", + " estimator.fit(X_train, y_train, **fit_params)\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1151, in wrapper\n", + " return fit_method(estimator, *args, **kwargs)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 1218, in fit\n", + " multi_class = _check_multi_class(self.multi_class, solver, len(self.classes_))\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 92, in _check_multi_class\n", + " raise ValueError(\"Solver %s does not support a multinomial backend.\" % solver)\n", + "ValueError: Solver liblinear does not support a multinomial backend.\n", + "\n", + "--------------------------------------------------------------------------------\n", + "10 fits failed with the following error:\n", + "Traceback (most recent call last):\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", + " estimator.fit(X_train, y_train, **fit_params)\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1151, in wrapper\n", + " return fit_method(estimator, *args, **kwargs)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 1168, in fit\n", + " solver = _check_solver(self.solver, self.penalty, self.dual)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 56, in _check_solver\n", + " raise ValueError(\n", + "ValueError: Solver lbfgs supports only 'l2' or 'none' penalties, got l1 penalty.\n", + "\n", + "--------------------------------------------------------------------------------\n", + "15 fits failed with the following error:\n", + "Traceback (most recent call last):\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", + " estimator.fit(X_train, y_train, **fit_params)\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1151, in wrapper\n", + " return fit_method(estimator, *args, **kwargs)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 1168, in fit\n", + " solver = _check_solver(self.solver, self.penalty, self.dual)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 56, in _check_solver\n", + " raise ValueError(\n", + "ValueError: Solver sag supports only 'l2' or 'none' penalties, got elasticnet penalty.\n", + "\n", + "--------------------------------------------------------------------------------\n", + "25 fits failed with the following error:\n", + "Traceback (most recent call last):\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", + " estimator.fit(X_train, y_train, **fit_params)\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1151, in wrapper\n", + " return fit_method(estimator, *args, **kwargs)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 1168, in fit\n", + " solver = _check_solver(self.solver, self.penalty, self.dual)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 56, in _check_solver\n", + " raise ValueError(\n", + "ValueError: Solver newton-cg supports only 'l2' or 'none' penalties, got l1 penalty.\n", + "\n", + "--------------------------------------------------------------------------------\n", + "30 fits failed with the following error:\n", + "Traceback (most recent call last):\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", + " estimator.fit(X_train, y_train, **fit_params)\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1151, in wrapper\n", + " return fit_method(estimator, *args, **kwargs)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 1168, in fit\n", + " solver = _check_solver(self.solver, self.penalty, self.dual)\n", + " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 66, in _check_solver\n", + " raise ValueError(\n", + "ValueError: Only 'saga' solver supports elasticnet penalty, got solver=liblinear.\n", + "\n", + " warnings.warn(some_fits_failed_message, FitFailedWarning)\n" + ] + }, + { + "data": { + "text/html": [ + "
RandomizedSearchCV(error_score=0,\n",
+       "                   estimator=LogisticRegression(multi_class='multinomial',\n",
+       "                                                random_state=42),\n",
+       "                   n_iter=100, n_jobs=-1,\n",
+       "                   param_distributions={'C': array([1.00000000e-04, 2.63665090e-04, 6.95192796e-04, 1.83298071e-03,\n",
+       "       4.83293024e-03, 1.27427499e-02, 3.35981829e-02, 8.85866790e-02,\n",
+       "       2.33572147e-01, 6.15848211e-01, 1.62377674e+00, 4.28133240e+00,\n",
+       "       1.12883789e+...\n",
+       "                                                   'liblinear', 'sag', 'saga'],\n",
+       "                                        'tol': array([1.00000000e-04, 1.83298071e-04, 3.35981829e-04, 6.15848211e-04,\n",
+       "       1.12883789e-03, 2.06913808e-03, 3.79269019e-03, 6.95192796e-03,\n",
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+       "       1.62377674e+00, 2.97635144e+00, 5.45559478e+00, 1.00000000e+01])},\n",
+       "                   random_state=42, verbose=1)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" + ], + "text/plain": [ + "RandomizedSearchCV(error_score=0,\n", + " estimator=LogisticRegression(multi_class='multinomial',\n", + " random_state=42),\n", + " n_iter=100, n_jobs=-1,\n", + " param_distributions={'C': array([1.00000000e-04, 2.63665090e-04, 6.95192796e-04, 1.83298071e-03,\n", + " 4.83293024e-03, 1.27427499e-02, 3.35981829e-02, 8.85866790e-02,\n", + " 2.33572147e-01, 6.15848211e-01, 1.62377674e+00, 4.28133240e+00,\n", + " 1.12883789e+...\n", + " 'liblinear', 'sag', 'saga'],\n", + " 'tol': array([1.00000000e-04, 1.83298071e-04, 3.35981829e-04, 6.15848211e-04,\n", + " 1.12883789e-03, 2.06913808e-03, 3.79269019e-03, 6.95192796e-03,\n", + " 1.27427499e-02, 2.33572147e-02, 4.28133240e-02, 7.84759970e-02,\n", + " 1.43844989e-01, 2.63665090e-01, 4.83293024e-01, 8.85866790e-01,\n", + " 1.62377674e+00, 2.97635144e+00, 5.45559478e+00, 1.00000000e+01])},\n", + " random_state=42, verbose=1)" + ] + }, + "execution_count": 15, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "#Aproximandonos a los mejores hiperparametros con una busqueda aleatoria\n", + "from sklearn.model_selection import RandomizedSearchCV\n", + "\n", + "# Definir el espacio de búsqueda de hiperparámetros\n", + "param_dist = {\n", + " 'solver': ['newton-cg', 'lbfgs', 'liblinear', 'sag', 'saga'],\n", + " 'penalty': ['l1', 'l2', 'elasticnet', 'None'], \n", + " 'C': np.logspace(-4, 4, 20),\n", + " 'tol': np.logspace(-4, 1, 20)\n", + "}\n", + "\n", + "# Crear el modelo base\n", + "log_reg = LogisticRegression(random_state=42, multi_class='multinomial')\n", + "\n", + "# Configurar la búsqueda aleatoria\n", + "\n", + "random_search = RandomizedSearchCV(log_reg, param_distributions=param_dist, n_iter=100, verbose=1, n_jobs=-1, random_state=42, error_score=0)\n", + "\n", + "# Ejecutar la búsqueda aleatoria\n", + "random_search.fit(X_train, y_train)\n", + "#Tener en cuenta que algunas combinaciones de hiperparametros pueden no ser posible" + ] + }, + { + "cell_type": "code", + "execution_count": 16, + "id": "64b64908", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Las 5 mejores combinaciones de hiperparámetros:\n", + "Combinación 13: {'tol': 0.0069519279617756054, 'solver': 'saga', 'penalty': 'l2', 'C': 0.08858667904100823}, Puntuación: 0.806\n", + "Combinación 44: {'tol': 0.023357214690901212, 'solver': 'lbfgs', 'penalty': 'l2', 'C': 0.08858667904100823}, Puntuación: 0.806\n", + "Combinación 51: {'tol': 0.00018329807108324357, 'solver': 'lbfgs', 'penalty': 'l2', 'C': 0.08858667904100823}, Puntuación: 0.806\n", + "Combinación 45: {'tol': 0.0003359818286283781, 'solver': 'sag', 'penalty': 'l2', 'C': 0.23357214690901212}, Puntuación: 0.804\n", + "Combinación 82: {'tol': 0.04281332398719392, 'solver': 'saga', 'penalty': 'l1', 'C': 0.23357214690901212}, Puntuación: 0.803\n" + ] + } + ], + "source": [ + "results = random_search.cv_results_\n", + "\n", + "# Crear un DataFrame a partir de los resultados\n", + "results_df = pd.DataFrame(results)\n", + "\n", + "# Filtrar y ordenar los mejores resultados\n", + "top_results = results_df[['params', 'mean_test_score']].sort_values(by='mean_test_score', ascending=False)\n", + "\n", + "# Mostrar las 5 mejores combinaciones\n", + "print(\"Las 5 mejores combinaciones de hiperparámetros:\")\n", + "for index, row in top_results.head(5).iterrows():\n", + " print(f\"Combinación {index + 1}: {row['params']}, Puntuación: {row['mean_test_score']:.3f}\")" + ] + }, + { + "cell_type": "code", + "execution_count": 17, + "id": "d0ee8400", + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Fitting 5 folds for each of 1350 candidates, totalling 6750 fits\n", + "Mejores hiperparámetros: {'C': 0.18999999999999997, 'penalty': 'l2', 'solver': 'sag', 'tol': 0.1}\n", + "Mejor puntuación: 0.807\n" + ] + } + ], + "source": [ + "from sklearn.model_selection import GridSearchCV\n", + "\n", + "# Definir el espacio de búsqueda de hiperparámetros alrededor de los mejores encontrados\n", + "param_grid = {\n", + " 'solver': ['lbfgs', 'sag', 'saga'],\n", + " 'penalty': ['l2'], \n", + " 'C': np.linspace(0.01, 0.3, 30),\n", + " 'tol': np.logspace(-5, -1, 15) \n", + "}\n", + "\n", + "# Crear el modelo base\n", + "log_reg = LogisticRegression(random_state=42, multi_class='multinomial')\n", + "\n", + "# Configurar la búsqueda en cuadrícula\n", + "grid_search = GridSearchCV(log_reg, param_grid=param_grid, cv=5, verbose=1, n_jobs=-1)\n", + "\n", + "# Ejecutar la búsqueda en cuadrícula\n", + "grid_search.fit(X_train, y_train)\n", + "\n", + "# Mostrar los mejores hiperparámetros encontrados\n", + "print(f\"Mejores hiperparámetros: {grid_search.best_params_}\")\n", + "print(f\"Mejor puntuación: {grid_search.best_score_:.3f}\")" + ] + }, { "cell_type": "code", "execution_count": 18, @@ -660,8 +1012,8 @@ "metadata": {}, "outputs": [], "source": [ - "# Crear el modelo y entrenarlo\n", - "clf_lin = LogisticRegression(random_state=0, solver='lbfgs', multi_class='multinomial').fit(X, y)" + "# Entrenar el modelo con los mejores hiperparametros\n", + "clf_lin = LogisticRegression(random_state=42, multi_class='multinomial', **grid_search.best_params_).fit(X_train, y_train)" ] }, { @@ -680,7 +1032,7 @@ "outputs": [ { "data": { - "image/png": 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", + "image/png": 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"text/plain": [ "
" ] @@ -707,7 +1059,7 @@ }, { "cell_type": "code", - "execution_count": 20, + "execution_count": null, "id": "1e21c8b3", "metadata": {}, "outputs": [ @@ -715,10 +1067,10 @@ "name": "stdout", "output_type": "stream", "text": [ - "Accuracy model: 0.817\n", + "Accuracy model: 0.818\n", "Exited Churn='NO': 0.973\n", - "Exited Churn='YES': 0.173\n", - "F1 Score: 0.269\n" + "Exited Churn='YES': 0.177\n", + "F1 Score: 0.275\n" ] } ], From 06e683c8a53f296b03d87de8a9afe13fda1cf7f0 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Angel=20Mart=C3=ADnez?= <76793458+AFMartinezF@users.noreply.github.com> Date: Mon, 21 Oct 2024 00:57:57 +0000 Subject: [PATCH 7/9] Changed multi_class parameter to improve model performance --- models/model.pk | Bin 1001 -> 993 bytes .../modelgeneration_27092023_ricalanis.ipynb | 311 +++++++++--------- 2 files changed, 159 insertions(+), 152 deletions(-) diff --git a/models/model.pk b/models/model.pk index 73824ebaf0a69377a59b74c79357b541dd6591b0..d51d99c14d769fa94b8a368777a8d7b8ee032669 100644 GIT binary patch delta 136 zcmV;30C)fC2jK?5KmC2%oen@b8xXDjru#&-+2rRZFOvPX>M&GQ_rLF9=hMFdX8\n", " \n", " \n", - " 7923\n", - " 0.760\n", - " 1.0\n", + " 4335\n", + " 0.716\n", " 1.0\n", - " 0.270270\n", + " 0.0\n", + " 0.621622\n", " 0.5\n", - " 0.473764\n", " 0.000000\n", + " 0.666667\n", + " 0.0\n", " 1.0\n", + " 0.562596\n", " 1.0\n", - " 0.816608\n", - " 0.0\n", " \n", " \n", - " 3386\n", - " 0.832\n", - " 1.0\n", + " 3186\n", + " 0.574\n", + " 0.5\n", + " 0.0\n", + " 0.243243\n", " 1.0\n", - " 0.310811\n", - " 0.6\n", - " 0.395413\n", + " 0.580915\n", " 0.333333\n", " 1.0\n", - " 0.0\n", - " 0.311984\n", + " 1.0\n", + " 0.483292\n", " 0.0\n", " \n", " \n", - " 3497\n", - " 0.212\n", - " 0.0\n", - " 0.0\n", - " 0.608108\n", - " 0.1\n", - " 0.659035\n", - " 0.333333\n", + " 40\n", + " 0.244\n", + " 1.0\n", + " 1.0\n", + " 0.297297\n", + " 0.4\n", + " 0.000000\n", + " 0.000000\n", + " 1.0\n", " 0.0\n", + " 0.350747\n", " 0.0\n", - " 0.703800\n", - " 1.0\n", " \n", " \n", - " 7302\n", - " 0.282\n", - " 0.0\n", - " 0.0\n", - " 0.729730\n", - " 0.6\n", - " 0.363834\n", + " 4404\n", + " 0.508\n", + " 1.0\n", + " 1.0\n", + " 0.337838\n", + " 0.2\n", + " 0.578250\n", " 0.000000\n", " 1.0\n", " 1.0\n", - " 0.035110\n", + " 0.119362\n", " 0.0\n", " \n", " \n", - " 6983\n", - " 0.712\n", + " 5114\n", + " 0.656\n", " 0.0\n", " 1.0\n", - " 0.229730\n", - " 0.5\n", + " 0.567568\n", + " 0.8\n", + " 0.739936\n", " 0.000000\n", - " 0.333333\n", - " 1.0\n", - " 1.0\n", - " 0.408573\n", " 0.0\n", + " 0.0\n", + " 0.960817\n", + " 1.0\n", " \n", " \n", - " 6935\n", - " 0.640\n", + " 4508\n", + " 0.498\n", " 0.0\n", - " 1.0\n", - " 0.202703\n", + " 0.0\n", + " 0.310811\n", " 0.1\n", " 0.000000\n", " 0.333333\n", " 1.0\n", - " 1.0\n", - " 0.432049\n", + " 0.0\n", + " 0.480337\n", " 0.0\n", " \n", " \n", - " 3826\n", - " 0.848\n", + " 5379\n", + " 0.554\n", " 0.0\n", - " 1.0\n", - " 0.783784\n", - " 0.4\n", - " 0.448433\n", + " 0.0\n", + " 0.040541\n", + " 0.7\n", + " 0.394555\n", " 0.000000\n", " 1.0\n", " 1.0\n", - " 0.715676\n", + " 0.845806\n", " 0.0\n", " \n", " \n", - " 9227\n", - " 0.852\n", - " 0.0\n", - " 0.0\n", - " 0.175676\n", + " 4091\n", + " 0.498\n", " 0.5\n", - " 0.000000\n", - " 0.333333\n", " 1.0\n", + " 0.283784\n", + " 0.2\n", + " 0.753202\n", + " 0.333333\n", " 0.0\n", - " 0.463226\n", + " 1.0\n", + " 0.880737\n", " 0.0\n", " \n", " \n", - " 1341\n", - " 0.888\n", + " 1831\n", + " 0.564\n", " 0.0\n", " 0.0\n", - " 0.310811\n", + " 0.243243\n", " 0.7\n", - " 0.704850\n", - " 0.666667\n", + " 0.000000\n", + " 0.333333\n", " 1.0\n", - " 0.0\n", - " 0.832653\n", " 1.0\n", + " 0.262600\n", + " 0.0\n", " \n", " \n", - " 7466\n", - " 0.700\n", + " 8254\n", + " 0.574\n", " 0.5\n", - " 0.0\n", - " 0.162162\n", - " 0.4\n", - " 0.463844\n", + " 1.0\n", + " 0.135135\n", + " 0.3\n", + " 0.492932\n", " 0.000000\n", " 1.0\n", " 1.0\n", - " 0.672093\n", + " 0.832314\n", " 0.0\n", " \n", " \n", @@ -572,28 +572,28 @@ ], "text/plain": [ " CreditScore Geography Gender Age Tenure Balance \\\n", - "7923 0.760 1.0 1.0 0.270270 0.5 0.473764 \n", - "3386 0.832 1.0 1.0 0.310811 0.6 0.395413 \n", - "3497 0.212 0.0 0.0 0.608108 0.1 0.659035 \n", - "7302 0.282 0.0 0.0 0.729730 0.6 0.363834 \n", - "6983 0.712 0.0 1.0 0.229730 0.5 0.000000 \n", - "6935 0.640 0.0 1.0 0.202703 0.1 0.000000 \n", - "3826 0.848 0.0 1.0 0.783784 0.4 0.448433 \n", - "9227 0.852 0.0 0.0 0.175676 0.5 0.000000 \n", - "1341 0.888 0.0 0.0 0.310811 0.7 0.704850 \n", - "7466 0.700 0.5 0.0 0.162162 0.4 0.463844 \n", + "4335 0.716 1.0 0.0 0.621622 0.5 0.000000 \n", + "3186 0.574 0.5 0.0 0.243243 1.0 0.580915 \n", + "40 0.244 1.0 1.0 0.297297 0.4 0.000000 \n", + "4404 0.508 1.0 1.0 0.337838 0.2 0.578250 \n", + "5114 0.656 0.0 1.0 0.567568 0.8 0.739936 \n", + "4508 0.498 0.0 0.0 0.310811 0.1 0.000000 \n", + "5379 0.554 0.0 0.0 0.040541 0.7 0.394555 \n", + "4091 0.498 0.5 1.0 0.283784 0.2 0.753202 \n", + "1831 0.564 0.0 0.0 0.243243 0.7 0.000000 \n", + "8254 0.574 0.5 1.0 0.135135 0.3 0.492932 \n", "\n", " NumOfProducts HasCrCard IsActiveMember EstimatedSalary Exited \n", - "7923 0.000000 1.0 1.0 0.816608 0.0 \n", - "3386 0.333333 1.0 0.0 0.311984 0.0 \n", - "3497 0.333333 0.0 0.0 0.703800 1.0 \n", - "7302 0.000000 1.0 1.0 0.035110 0.0 \n", - "6983 0.333333 1.0 1.0 0.408573 0.0 \n", - "6935 0.333333 1.0 1.0 0.432049 0.0 \n", - "3826 0.000000 1.0 1.0 0.715676 0.0 \n", - "9227 0.333333 1.0 0.0 0.463226 0.0 \n", - "1341 0.666667 1.0 0.0 0.832653 1.0 \n", - "7466 0.000000 1.0 1.0 0.672093 0.0 " + "4335 0.666667 0.0 1.0 0.562596 1.0 \n", + "3186 0.333333 1.0 1.0 0.483292 0.0 \n", + "40 0.000000 1.0 0.0 0.350747 0.0 \n", + "4404 0.000000 1.0 1.0 0.119362 0.0 \n", + "5114 0.000000 0.0 0.0 0.960817 1.0 \n", + "4508 0.333333 1.0 0.0 0.480337 0.0 \n", + "5379 0.000000 1.0 1.0 0.845806 0.0 \n", + "4091 0.333333 0.0 1.0 0.880737 0.0 \n", + "1831 0.333333 1.0 1.0 0.262600 0.0 \n", + "8254 0.000000 1.0 1.0 0.832314 0.0 " ] }, "execution_count": 11, @@ -671,7 +671,7 @@ "output_type": "stream", "text": [ "/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py:425: FitFailedWarning: \n", - "370 fits failed out of a total of 500.\n", + "335 fits failed out of a total of 500.\n", "The score on these train-test partitions for these parameters will be set to 0.\n", "If these failures are not expected, you can try to debug them by setting error_score='raise'.\n", "\n", @@ -722,7 +722,7 @@ "ValueError: Solver lbfgs supports only 'l2' or 'none' penalties, got elasticnet penalty.\n", "\n", "--------------------------------------------------------------------------------\n", - "72 fits failed with the following error:\n", + "31 fits failed with the following error:\n", "Traceback (most recent call last):\n", " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", " estimator.fit(X_train, y_train, **fit_params)\n", @@ -732,10 +732,10 @@ " validate_parameter_constraints(\n", " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/utils/_param_validation.py\", line 95, in validate_parameter_constraints\n", " raise InvalidParameterError(\n", - "sklearn.utils._param_validation.InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'l1', 'none' (deprecated), 'elasticnet', 'l2'} or None. Got 'None' instead.\n", + "sklearn.utils._param_validation.InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'elasticnet', 'l1', 'none' (deprecated), 'l2'} or None. Got 'None' instead.\n", "\n", "--------------------------------------------------------------------------------\n", - "44 fits failed with the following error:\n", + "41 fits failed with the following error:\n", "Traceback (most recent call last):\n", " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", " estimator.fit(X_train, y_train, **fit_params)\n", @@ -745,22 +745,23 @@ " validate_parameter_constraints(\n", " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/utils/_param_validation.py\", line 95, in validate_parameter_constraints\n", " raise InvalidParameterError(\n", - "sklearn.utils._param_validation.InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'l2', 'none' (deprecated), 'elasticnet', 'l1'} or None. Got 'None' instead.\n", + "sklearn.utils._param_validation.InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'l2', 'none' (deprecated), 'l1', 'elasticnet'} or None. Got 'None' instead.\n", "\n", "--------------------------------------------------------------------------------\n", - "25 fits failed with the following error:\n", + "32 fits failed with the following error:\n", "Traceback (most recent call last):\n", " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", " estimator.fit(X_train, y_train, **fit_params)\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1151, in wrapper\n", - " return fit_method(estimator, *args, **kwargs)\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 1178, in fit\n", - " raise ValueError(\"l1_ratio must be specified when penalty is elasticnet.\")\n", - "ValueError: l1_ratio must be specified when penalty is elasticnet.\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1144, in wrapper\n", + " estimator._validate_params()\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 637, in _validate_params\n", + " validate_parameter_constraints(\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/utils/_param_validation.py\", line 95, in validate_parameter_constraints\n", + " raise InvalidParameterError(\n", + "sklearn.utils._param_validation.InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'elasticnet', 'none' (deprecated), 'l2', 'l1'} or None. Got 'None' instead.\n", "\n", "--------------------------------------------------------------------------------\n", - "34 fits failed with the following error:\n", + "46 fits failed with the following error:\n", "Traceback (most recent call last):\n", " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", " estimator.fit(X_train, y_train, **fit_params)\n", @@ -770,22 +771,19 @@ " validate_parameter_constraints(\n", " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/utils/_param_validation.py\", line 95, in validate_parameter_constraints\n", " raise InvalidParameterError(\n", - "sklearn.utils._param_validation.InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'l2', 'l1', 'elasticnet', 'none' (deprecated)} or None. Got 'None' instead.\n", + "sklearn.utils._param_validation.InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'none' (deprecated), 'l2', 'l1', 'elasticnet'} or None. Got 'None' instead.\n", "\n", "--------------------------------------------------------------------------------\n", - "35 fits failed with the following error:\n", + "25 fits failed with the following error:\n", "Traceback (most recent call last):\n", " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", " estimator.fit(X_train, y_train, **fit_params)\n", " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1151, in wrapper\n", " return fit_method(estimator, *args, **kwargs)\n", " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 1218, in fit\n", - " multi_class = _check_multi_class(self.multi_class, solver, len(self.classes_))\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 92, in _check_multi_class\n", - " raise ValueError(\"Solver %s does not support a multinomial backend.\" % solver)\n", - "ValueError: Solver liblinear does not support a multinomial backend.\n", + " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 1178, in fit\n", + " raise ValueError(\"l1_ratio must be specified when penalty is elasticnet.\")\n", + "ValueError: l1_ratio must be specified when penalty is elasticnet.\n", "\n", "--------------------------------------------------------------------------------\n", "10 fits failed with the following error:\n", @@ -854,13 +852,13 @@ "data": { "text/html": [ "
RandomizedSearchCV(error_score=0,\n",
-       "                   estimator=LogisticRegression(multi_class='multinomial',\n",
+       "                   estimator=LogisticRegression(multi_class='ovr',\n",
        "                                                random_state=42),\n",
        "                   n_iter=100, n_jobs=-1,\n",
        "                   param_distributions={'C': array([1.00000000e-04, 2.63665090e-04, 6.95192796e-04, 1.83298071e-03,\n",
        "       4.83293024e-03, 1.27427499e-02, 3.35981829e-02, 8.85866790e-02,\n",
        "       2.33572147e-01, 6.15848211e-01, 1.62377674e+00, 4.28133240e+00,\n",
-       "       1.12883789e+...\n",
+       "       1.12883789e+01, 2.976...\n",
        "                                                   'liblinear', 'sag', 'saga'],\n",
        "                                        'tol': array([1.00000000e-04, 1.83298071e-04, 3.35981829e-04, 6.15848211e-04,\n",
        "       1.12883789e-03, 2.06913808e-03, 3.79269019e-03, 6.95192796e-03,\n",
@@ -868,30 +866,30 @@
        "       1.43844989e-01, 2.63665090e-01, 4.83293024e-01, 8.85866790e-01,\n",
        "       1.62377674e+00, 2.97635144e+00, 5.45559478e+00, 1.00000000e+01])},\n",
        "                   random_state=42, verbose=1)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" + " random_state=42, verbose=1)
LogisticRegression(multi_class='ovr', random_state=42)
LogisticRegression(multi_class='ovr', random_state=42)
" ], "text/plain": [ "RandomizedSearchCV(error_score=0,\n", - " estimator=LogisticRegression(multi_class='multinomial',\n", + " estimator=LogisticRegression(multi_class='ovr',\n", " random_state=42),\n", " n_iter=100, n_jobs=-1,\n", " param_distributions={'C': array([1.00000000e-04, 2.63665090e-04, 6.95192796e-04, 1.83298071e-03,\n", " 4.83293024e-03, 1.27427499e-02, 3.35981829e-02, 8.85866790e-02,\n", " 2.33572147e-01, 6.15848211e-01, 1.62377674e+00, 4.28133240e+00,\n", - " 1.12883789e+...\n", + " 1.12883789e+01, 2.976...\n", " 'liblinear', 'sag', 'saga'],\n", " 'tol': array([1.00000000e-04, 1.83298071e-04, 3.35981829e-04, 6.15848211e-04,\n", " 1.12883789e-03, 2.06913808e-03, 3.79269019e-03, 6.95192796e-03,\n", @@ -919,7 +917,7 @@ "}\n", "\n", "# Crear el modelo base\n", - "log_reg = LogisticRegression(random_state=42, multi_class='multinomial')\n", + "log_reg = LogisticRegression(random_state=42, multi_class='ovr')\n", "\n", "# Configurar la búsqueda aleatoria\n", "\n", @@ -941,11 +939,11 @@ "output_type": "stream", "text": [ "Las 5 mejores combinaciones de hiperparámetros:\n", - "Combinación 13: {'tol': 0.0069519279617756054, 'solver': 'saga', 'penalty': 'l2', 'C': 0.08858667904100823}, Puntuación: 0.806\n", - "Combinación 44: {'tol': 0.023357214690901212, 'solver': 'lbfgs', 'penalty': 'l2', 'C': 0.08858667904100823}, Puntuación: 0.806\n", - "Combinación 51: {'tol': 0.00018329807108324357, 'solver': 'lbfgs', 'penalty': 'l2', 'C': 0.08858667904100823}, Puntuación: 0.806\n", - "Combinación 45: {'tol': 0.0003359818286283781, 'solver': 'sag', 'penalty': 'l2', 'C': 0.23357214690901212}, Puntuación: 0.804\n", - "Combinación 82: {'tol': 0.04281332398719392, 'solver': 'saga', 'penalty': 'l1', 'C': 0.23357214690901212}, Puntuación: 0.803\n" + "Combinación 45: {'tol': 0.0003359818286283781, 'solver': 'sag', 'penalty': 'l2', 'C': 0.23357214690901212}, Puntuación: 0.806\n", + "Combinación 84: {'tol': 0.0001, 'solver': 'liblinear', 'penalty': 'l1', 'C': 0.08858667904100823}, Puntuación: 0.805\n", + "Combinación 82: {'tol': 0.04281332398719392, 'solver': 'saga', 'penalty': 'l1', 'C': 0.23357214690901212}, Puntuación: 0.805\n", + "Combinación 10: {'tol': 0.00018329807108324357, 'solver': 'sag', 'penalty': 'l2', 'C': 0.615848211066026}, Puntuación: 0.804\n", + "Combinación 37: {'tol': 5.455594781168514, 'solver': 'newton-cg', 'penalty': 'l2', 'C': 29.763514416313132}, Puntuación: 0.803\n" ] } ], @@ -966,7 +964,7 @@ }, { "cell_type": "code", - "execution_count": 17, + "execution_count": 22, "id": "d0ee8400", "metadata": {}, "outputs": [ @@ -974,9 +972,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "Fitting 5 folds for each of 1350 candidates, totalling 6750 fits\n", - "Mejores hiperparámetros: {'C': 0.18999999999999997, 'penalty': 'l2', 'solver': 'sag', 'tol': 0.1}\n", - "Mejor puntuación: 0.807\n" + "Fitting 5 folds for each of 1500 candidates, totalling 7500 fits\n", + "Mejores hiperparámetros: {'C': 0.12999999999999998, 'penalty': 'l2', 'solver': 'sag', 'tol': 0.1}\n", + "Mejor puntuación: 0.809\n" ] } ], @@ -984,15 +982,24 @@ "from sklearn.model_selection import GridSearchCV\n", "\n", "# Definir el espacio de búsqueda de hiperparámetros alrededor de los mejores encontrados\n", - "param_grid = {\n", - " 'solver': ['lbfgs', 'sag', 'saga'],\n", - " 'penalty': ['l2'], \n", - " 'C': np.linspace(0.01, 0.3, 30),\n", - " 'tol': np.logspace(-5, -1, 15) \n", - "}\n", + "\n", + "param_grid = [\n", + " {\n", + " 'solver': ['liblinear','saga'], # liblinear soporta tanto l1 como l2\n", + " 'penalty': ['l1', 'l2'],\n", + " 'C': np.linspace(0.01, 0.3, 30),\n", + " 'tol': np.logspace(-4, -1, 10)\n", + " },\n", + " {\n", + " 'solver': ['sag'], # sag solo soporta l2\n", + " 'penalty': ['l2'],\n", + " 'C': np.linspace(0.01, 0.3, 30),\n", + " 'tol': np.logspace(-4, -1, 10)\n", + " }\n", + "]\n", "\n", "# Crear el modelo base\n", - "log_reg = LogisticRegression(random_state=42, multi_class='multinomial')\n", + "log_reg = LogisticRegression(random_state=42, multi_class='ovr')\n", "\n", "# Configurar la búsqueda en cuadrícula\n", "grid_search = GridSearchCV(log_reg, param_grid=param_grid, cv=5, verbose=1, n_jobs=-1)\n", @@ -1007,13 +1014,13 @@ }, { "cell_type": "code", - "execution_count": 18, + "execution_count": 23, "id": "409f0391-4500-41fd-85a9-e501ecdd9329", "metadata": {}, "outputs": [], "source": [ "# Entrenar el modelo con los mejores hiperparametros\n", - "clf_lin = LogisticRegression(random_state=42, multi_class='multinomial', **grid_search.best_params_).fit(X_train, y_train)" + "clf_lin = LogisticRegression(random_state=42, multi_class='ovr', **grid_search.best_params_).fit(X_train, y_train)" ] }, { @@ -1026,13 +1033,13 @@ }, { "cell_type": "code", - "execution_count": 19, + "execution_count": 24, "id": "753ab797-0b07-4e27-a497-9518034451a9", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -1059,7 +1066,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 25, "id": "1e21c8b3", "metadata": {}, "outputs": [ @@ -1067,10 +1074,10 @@ "name": "stdout", "output_type": "stream", "text": [ - "Accuracy model: 0.818\n", - "Exited Churn='NO': 0.973\n", - "Exited Churn='YES': 0.177\n", - "F1 Score: 0.275\n" + "Accuracy model: 0.819\n", + "Exited Churn='NO': 0.971\n", + "Exited Churn='YES': 0.190\n", + "F1 Score: 0.290\n" ] } ], @@ -1103,7 +1110,7 @@ }, { "cell_type": "code", - "execution_count": 21, + "execution_count": 26, "id": "20f25624-4ba7-4c0d-a79a-590d1884b7d0", "metadata": {}, "outputs": [], From 5a606f35bfbefd6f440dda61f70f409c42e8c2f1 Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Angel=20Mart=C3=ADnez?= <76793458+AFMartinezF@users.noreply.github.com> Date: Mon, 21 Oct 2024 01:06:55 +0000 Subject: [PATCH 8/9] Add SMOTE to balance data, improve f1 but decreases accuracy --- models/model.pk | Bin 993 -> 994 bytes .../modelgeneration_27092023_ricalanis.ipynb | 86 ++++++++++-------- requirements.txt | 1 + 3 files changed, 51 insertions(+), 36 deletions(-) diff --git a/models/model.pk b/models/model.pk index d51d99c14d769fa94b8a368777a8d7b8ee032669..62552a2f469d2dcf40e712a4591748b34c5ed872 100644 GIT binary patch delta 141 zcmV;80CNA~2jT|=fCQD-kpxl!F_Bk+2QxD>Gcz;Ok>6Ma1ao0$VY52{)d2wllMw?e zPd0+mYvrBXzpJG0KlLTxKl2#iJ}*MfzYd)*xlN`TKqzc}eyW1dzs$G?Y1Pp7KeNq> vbg)m{zr|d$$Qf*vzqOFvv1MWDzjk&a?$<)elZyi^2hAb>v}OhRlfDBZz#Kvk delta 140 zcmV;70CWH12jK?6MZ19M?#vpfOS0RaP(5(6tw z41Y4BhppGYyMy-d)G*OMIBrtdtZLxD`9J-A+no+TIU5kI{^Y^GWilEQ^Um-;-aAjw u8}i4$v=CM6R@bpVbv8HptcCEu>zHaTJnfZ}i~}qO0H98?l)3wpzXKyc+d`B8 diff --git a/notebooks/modelgeneration_27092023_ricalanis.ipynb b/notebooks/modelgeneration_27092023_ricalanis.ipynb index bfed5152..8a1dbad5 100644 --- a/notebooks/modelgeneration_27092023_ricalanis.ipynb +++ b/notebooks/modelgeneration_27092023_ricalanis.ipynb @@ -219,7 +219,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 6, "id": "b8f22789", "metadata": {}, "outputs": [ @@ -251,7 +251,7 @@ }, { "cell_type": "code", - "execution_count": null, + "execution_count": 7, "id": "e757c386", "metadata": {}, "outputs": [ @@ -644,7 +644,21 @@ }, { "cell_type": "code", - "execution_count": 14, + "execution_count": 28, + "id": "8721e498", + "metadata": {}, + "outputs": [], + "source": [ + "from imblearn.over_sampling import SMOTE\n", + "\n", + "#Aplicamos balanceo de clases con SMOTE\n", + "oversample = SMOTE()\n", + "X, y = oversample.fit_resample(X, y)" + ] + }, + { + "cell_type": "code", + "execution_count": 29, "id": "8a6ee78f-7c8b-4810-a763-c8b20155ec28", "metadata": {}, "outputs": [], @@ -655,7 +669,7 @@ }, { "cell_type": "code", - "execution_count": 15, + "execution_count": 30, "id": "8cd168ca", "metadata": {}, "outputs": [ @@ -722,7 +736,7 @@ "ValueError: Solver lbfgs supports only 'l2' or 'none' penalties, got elasticnet penalty.\n", "\n", "--------------------------------------------------------------------------------\n", - "31 fits failed with the following error:\n", + "52 fits failed with the following error:\n", "Traceback (most recent call last):\n", " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", " estimator.fit(X_train, y_train, **fit_params)\n", @@ -732,10 +746,10 @@ " validate_parameter_constraints(\n", " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/utils/_param_validation.py\", line 95, in validate_parameter_constraints\n", " raise InvalidParameterError(\n", - "sklearn.utils._param_validation.InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'elasticnet', 'l1', 'none' (deprecated), 'l2'} or None. Got 'None' instead.\n", + "sklearn.utils._param_validation.InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'l1', 'none' (deprecated), 'l2', 'elasticnet'} or None. Got 'None' instead.\n", "\n", "--------------------------------------------------------------------------------\n", - "41 fits failed with the following error:\n", + "33 fits failed with the following error:\n", "Traceback (most recent call last):\n", " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", " estimator.fit(X_train, y_train, **fit_params)\n", @@ -745,10 +759,10 @@ " validate_parameter_constraints(\n", " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/utils/_param_validation.py\", line 95, in validate_parameter_constraints\n", " raise InvalidParameterError(\n", - "sklearn.utils._param_validation.InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'l2', 'none' (deprecated), 'l1', 'elasticnet'} or None. Got 'None' instead.\n", + "sklearn.utils._param_validation.InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'none' (deprecated), 'l1', 'elasticnet', 'l2'} or None. Got 'None' instead.\n", "\n", "--------------------------------------------------------------------------------\n", - "32 fits failed with the following error:\n", + "25 fits failed with the following error:\n", "Traceback (most recent call last):\n", " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", " estimator.fit(X_train, y_train, **fit_params)\n", @@ -761,7 +775,7 @@ "sklearn.utils._param_validation.InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'elasticnet', 'none' (deprecated), 'l2', 'l1'} or None. Got 'None' instead.\n", "\n", "--------------------------------------------------------------------------------\n", - "46 fits failed with the following error:\n", + "40 fits failed with the following error:\n", "Traceback (most recent call last):\n", " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", " estimator.fit(X_train, y_train, **fit_params)\n", @@ -771,7 +785,7 @@ " validate_parameter_constraints(\n", " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/utils/_param_validation.py\", line 95, in validate_parameter_constraints\n", " raise InvalidParameterError(\n", - "sklearn.utils._param_validation.InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'none' (deprecated), 'l2', 'l1', 'elasticnet'} or None. Got 'None' instead.\n", + "sklearn.utils._param_validation.InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'l1', 'l2', 'none' (deprecated), 'elasticnet'} or None. Got 'None' instead.\n", "\n", "--------------------------------------------------------------------------------\n", "25 fits failed with the following error:\n", @@ -851,7 +865,7 @@ { "data": { "text/html": [ - "
RandomizedSearchCV(error_score=0,\n",
+       "
RandomizedSearchCV(error_score=0,\n",
        "                   estimator=LogisticRegression(multi_class='ovr',\n",
        "                                                random_state=42),\n",
        "                   n_iter=100, n_jobs=-1,\n",
@@ -865,7 +879,7 @@
        "       1.27427499e-02, 2.33572147e-02, 4.28133240e-02, 7.84759970e-02,\n",
        "       1.43844989e-01, 2.63665090e-01, 4.83293024e-01, 8.85866790e-01,\n",
        "       1.62377674e+00, 2.97635144e+00, 5.45559478e+00, 1.00000000e+01])},\n",
-       "                   random_state=42, verbose=1)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook. 
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
LogisticRegression(multi_class='ovr', random_state=42)
LogisticRegression(multi_class='ovr', random_state=42)
" ], "text/plain": [ "RandomizedSearchCV(error_score=0,\n", @@ -899,7 +913,7 @@ " random_state=42, verbose=1)" ] }, - "execution_count": 15, + "execution_count": 30, "metadata": {}, "output_type": "execute_result" } @@ -930,7 +944,7 @@ }, { "cell_type": "code", - "execution_count": 16, + "execution_count": 31, "id": "64b64908", "metadata": {}, "outputs": [ @@ -939,11 +953,11 @@ "output_type": "stream", "text": [ "Las 5 mejores combinaciones de hiperparámetros:\n", - "Combinación 45: {'tol': 0.0003359818286283781, 'solver': 'sag', 'penalty': 'l2', 'C': 0.23357214690901212}, Puntuación: 0.806\n", - "Combinación 84: {'tol': 0.0001, 'solver': 'liblinear', 'penalty': 'l1', 'C': 0.08858667904100823}, Puntuación: 0.805\n", - "Combinación 82: {'tol': 0.04281332398719392, 'solver': 'saga', 'penalty': 'l1', 'C': 0.23357214690901212}, Puntuación: 0.805\n", - "Combinación 10: {'tol': 0.00018329807108324357, 'solver': 'sag', 'penalty': 'l2', 'C': 0.615848211066026}, Puntuación: 0.804\n", - "Combinación 37: {'tol': 5.455594781168514, 'solver': 'newton-cg', 'penalty': 'l2', 'C': 29.763514416313132}, Puntuación: 0.803\n" + "Combinación 82: {'tol': 0.04281332398719392, 'solver': 'saga', 'penalty': 'l1', 'C': 0.23357214690901212}, Puntuación: 0.711\n", + "Combinación 99: {'tol': 0.8858667904100823, 'solver': 'saga', 'penalty': 'l2', 'C': 545.5594781168514}, Puntuación: 0.709\n", + "Combinación 37: {'tol': 5.455594781168514, 'solver': 'newton-cg', 'penalty': 'l2', 'C': 29.763514416313132}, Puntuación: 0.708\n", + "Combinación 43: {'tol': 0.0006158482110660267, 'solver': 'sag', 'penalty': 'l2', 'C': 29.763514416313132}, Puntuación: 0.708\n", + "Combinación 64: {'tol': 0.0003359818286283781, 'solver': 'saga', 'penalty': 'l1', 'C': 0.08858667904100823}, Puntuación: 0.708\n" ] } ], @@ -964,7 +978,7 @@ }, { "cell_type": "code", - "execution_count": 22, + "execution_count": 41, "id": "d0ee8400", "metadata": {}, "outputs": [ @@ -972,9 +986,9 @@ "name": "stdout", "output_type": "stream", "text": [ - "Fitting 5 folds for each of 1500 candidates, totalling 7500 fits\n", - "Mejores hiperparámetros: {'C': 0.12999999999999998, 'penalty': 'l2', 'solver': 'sag', 'tol': 0.1}\n", - "Mejor puntuación: 0.809\n" + "Fitting 5 folds for each of 1200 candidates, totalling 6000 fits\n", + "Mejores hiperparámetros: {'C': 0.3, 'penalty': 'l1', 'solver': 'saga', 'tol': 0.1}\n", + "Mejor puntuación: 0.712\n" ] } ], @@ -985,13 +999,13 @@ "\n", "param_grid = [\n", " {\n", - " 'solver': ['liblinear','saga'], # liblinear soporta tanto l1 como l2\n", + " 'solver': ['saga'], # saga soporta tanto l1 como l2\n", " 'penalty': ['l1', 'l2'],\n", " 'C': np.linspace(0.01, 0.3, 30),\n", " 'tol': np.logspace(-4, -1, 10)\n", " },\n", " {\n", - " 'solver': ['sag'], # sag solo soporta l2\n", + " 'solver': ['sag','newton-cg'], # sag y newton-cg solo soportan l2\n", " 'penalty': ['l2'],\n", " 'C': np.linspace(0.01, 0.3, 30),\n", " 'tol': np.logspace(-4, -1, 10)\n", @@ -1014,7 +1028,7 @@ }, { "cell_type": "code", - "execution_count": 23, + "execution_count": 42, "id": "409f0391-4500-41fd-85a9-e501ecdd9329", "metadata": {}, "outputs": [], @@ -1033,13 +1047,13 @@ }, { "cell_type": "code", - "execution_count": 24, + "execution_count": 43, "id": "753ab797-0b07-4e27-a497-9518034451a9", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", + "image/png": 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", "text/plain": [ "
" ] @@ -1066,7 +1080,7 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 44, "id": "1e21c8b3", "metadata": {}, "outputs": [ @@ -1074,10 +1088,10 @@ "name": "stdout", "output_type": "stream", "text": [ - "Accuracy model: 0.819\n", - "Exited Churn='NO': 0.971\n", - "Exited Churn='YES': 0.190\n", - "F1 Score: 0.290\n" + "Accuracy model: 0.698\n", + "Exited Churn='NO': 0.626\n", + "Exited Churn='YES': 0.772\n", + "F1 Score: 0.716\n" ] } ], @@ -1110,7 +1124,7 @@ }, { "cell_type": "code", - "execution_count": 26, + "execution_count": 45, "id": "20f25624-4ba7-4c0d-a79a-590d1884b7d0", "metadata": {}, "outputs": [], diff --git a/requirements.txt b/requirements.txt index 30ba043f..3e995629 100644 --- a/requirements.txt +++ b/requirements.txt @@ -3,3 +3,4 @@ pandas==2.1.4 scikit-learn==1.3.0 flask==2.3.3 +imbalanced-learn==0.11.0 \ No newline at end of file From 7c6362024fa1e203f72d392fdf08b2ebc97d6acf Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?Angel=20Mart=C3=ADnez?= <76793458+AFMartinezF@users.noreply.github.com> Date: Mon, 21 Oct 2024 02:35:32 +0000 Subject: [PATCH 9/9] Changed the model for SVM obtaining good results --- .gitignore | 3 - README.md | 3 +- data/processed/.gitkeep | 0 data/raw/.gitkeep | 0 data/raw/churn.csv | 10001 ++++++++++++++++ models/model.pk | Bin 994 -> 369831 bytes .../modelgeneration_27092023_ricalanis.ipynb | 602 +- 7 files changed, 10211 insertions(+), 398 deletions(-) create mode 100644 data/processed/.gitkeep create mode 100644 data/raw/.gitkeep create mode 100644 data/raw/churn.csv diff --git a/.gitignore b/.gitignore index a5df42ba..820d3d0f 100644 --- a/.gitignore +++ b/.gitignore @@ -1,6 +1,3 @@ -# Data -/data/ - # Mac OS-specific storage files .DS_Store diff --git a/README.md b/README.md index 34e5548a..9104005b 100644 --- a/README.md +++ b/README.md @@ -29,13 +29,14 @@ curl --location --request GET 'http://localhost:3001/query?feats=465,France,Fema Si todo esta bien, deberías de obtener una respuesta así ``` -{"response": [1]} +{"response": [0]} ``` #### Equipo * Juan Perez Nombrefalso * Ricardo Alanís Tamez +* Angel Martínez #### Contribuir diff --git a/data/processed/.gitkeep b/data/processed/.gitkeep new file mode 100644 index 00000000..e69de29b diff --git a/data/raw/.gitkeep b/data/raw/.gitkeep new file mode 100644 index 00000000..e69de29b diff --git a/data/raw/churn.csv b/data/raw/churn.csv new file mode 100644 index 00000000..3cbdbd08 --- /dev/null +++ b/data/raw/churn.csv @@ -0,0 +1,10001 @@ +RowNumber,CustomerId,Surname,CreditScore,Geography,Gender,Age,Tenure,Balance,NumOfProducts,HasCrCard,IsActiveMember,EstimatedSalary,Exited +1,15634602,Hargrave,619,France,Female,42,2,0,1,1,1,101348.88,1 +2,15647311,Hill,608,Spain,Female,41,1,83807.86,1,0,1,112542.58,0 +3,15619304,Onio,502,France,Female,42,8,159660.8,3,1,0,113931.57,1 +4,15701354,Boni,699,France,Female,39,1,0,2,0,0,93826.63,0 +5,15737888,Mitchell,850,Spain,Female,43,2,125510.82,1,1,1,79084.1,0 +6,15574012,Chu,645,Spain,Male,44,8,113755.78,2,1,0,149756.71,1 +7,15592531,Bartlett,822,France,Male,50,7,0,2,1,1,10062.8,0 +8,15656148,Obinna,376,Germany,Female,29,4,115046.74,4,1,0,119346.88,1 +9,15792365,He,501,France,Male,44,4,142051.07,2,0,1,74940.5,0 +10,15592389,H?,684,France,Male,27,2,134603.88,1,1,1,71725.73,0 +11,15767821,Bearce,528,France,Male,31,6,102016.72,2,0,0,80181.12,0 +12,15737173,Andrews,497,Spain,Male,24,3,0,2,1,0,76390.01,0 +13,15632264,Kay,476,France,Female,34,10,0,2,1,0,26260.98,0 +14,15691483,Chin,549,France,Female,25,5,0,2,0,0,190857.79,0 +15,15600882,Scott,635,Spain,Female,35,7,0,2,1,1,65951.65,0 +16,15643966,Goforth,616,Germany,Male,45,3,143129.41,2,0,1,64327.26,0 +17,15737452,Romeo,653,Germany,Male,58,1,132602.88,1,1,0,5097.67,1 +18,15788218,Henderson,549,Spain,Female,24,9,0,2,1,1,14406.41,0 +19,15661507,Muldrow,587,Spain,Male,45,6,0,1,0,0,158684.81,0 +20,15568982,Hao,726,France,Female,24,6,0,2,1,1,54724.03,0 +21,15577657,McDonald,732,France,Male,41,8,0,2,1,1,170886.17,0 +22,15597945,Dellucci,636,Spain,Female,32,8,0,2,1,0,138555.46,0 +23,15699309,Gerasimov,510,Spain,Female,38,4,0,1,1,0,118913.53,1 +24,15725737,Mosman,669,France,Male,46,3,0,2,0,1,8487.75,0 +25,15625047,Yen,846,France,Female,38,5,0,1,1,1,187616.16,0 +26,15738191,Maclean,577,France,Male,25,3,0,2,0,1,124508.29,0 +27,15736816,Young,756,Germany,Male,36,2,136815.64,1,1,1,170041.95,0 +28,15700772,Nebechi,571,France,Male,44,9,0,2,0,0,38433.35,0 +29,15728693,McWilliams,574,Germany,Female,43,3,141349.43,1,1,1,100187.43,0 +30,15656300,Lucciano,411,France,Male,29,0,59697.17,2,1,1,53483.21,0 +31,15589475,Azikiwe,591,Spain,Female,39,3,0,3,1,0,140469.38,1 +32,15706552,Odinakachukwu,533,France,Male,36,7,85311.7,1,0,1,156731.91,0 +33,15750181,Sanderson,553,Germany,Male,41,9,110112.54,2,0,0,81898.81,0 +34,15659428,Maggard,520,Spain,Female,42,6,0,2,1,1,34410.55,0 +35,15732963,Clements,722,Spain,Female,29,9,0,2,1,1,142033.07,0 +36,15794171,Lombardo,475,France,Female,45,0,134264.04,1,1,0,27822.99,1 +37,15788448,Watson,490,Spain,Male,31,3,145260.23,1,0,1,114066.77,0 +38,15729599,Lorenzo,804,Spain,Male,33,7,76548.6,1,0,1,98453.45,0 +39,15717426,Armstrong,850,France,Male,36,7,0,1,1,1,40812.9,0 +40,15585768,Cameron,582,Germany,Male,41,6,70349.48,2,0,1,178074.04,0 +41,15619360,Hsiao,472,Spain,Male,40,4,0,1,1,0,70154.22,0 +42,15738148,Clarke,465,France,Female,51,8,122522.32,1,0,0,181297.65,1 +43,15687946,Osborne,556,France,Female,61,2,117419.35,1,1,1,94153.83,0 +44,15755196,Lavine,834,France,Female,49,2,131394.56,1,0,0,194365.76,1 +45,15684171,Bianchi,660,Spain,Female,61,5,155931.11,1,1,1,158338.39,0 +46,15754849,Tyler,776,Germany,Female,32,4,109421.13,2,1,1,126517.46,0 +47,15602280,Martin,829,Germany,Female,27,9,112045.67,1,1,1,119708.21,1 +48,15771573,Okagbue,637,Germany,Female,39,9,137843.8,1,1,1,117622.8,1 +49,15766205,Yin,550,Germany,Male,38,2,103391.38,1,0,1,90878.13,0 +50,15771873,Buccho,776,Germany,Female,37,2,103769.22,2,1,0,194099.12,0 +51,15616550,Chidiebele,698,Germany,Male,44,10,116363.37,2,1,0,198059.16,0 +52,15768193,Trevisani,585,Germany,Male,36,5,146050.97,2,0,0,86424.57,0 +53,15683553,O'Brien,788,France,Female,33,5,0,2,0,0,116978.19,0 +54,15702298,Parkhill,655,Germany,Male,41,8,125561.97,1,0,0,164040.94,1 +55,15569590,Yoo,601,Germany,Male,42,1,98495.72,1,1,0,40014.76,1 +56,15760861,Phillipps,619,France,Male,43,1,125211.92,1,1,1,113410.49,0 +57,15630053,Tsao,656,France,Male,45,5,127864.4,1,1,0,87107.57,0 +58,15647091,Endrizzi,725,Germany,Male,19,0,75888.2,1,0,0,45613.75,0 +59,15623944,T'ien,511,Spain,Female,66,4,0,1,1,0,1643.11,1 +60,15804771,Velazquez,614,France,Male,51,4,40685.92,1,1,1,46775.28,0 +61,15651280,Hunter,742,Germany,Male,35,5,136857,1,0,0,84509.57,0 +62,15773469,Clark,687,Germany,Female,27,9,152328.88,2,0,0,126494.82,0 +63,15702014,Jeffrey,555,Spain,Male,33,1,56084.69,2,0,0,178798.13,0 +64,15751208,Pirozzi,684,Spain,Male,56,8,78707.16,1,1,1,99398.36,0 +65,15592461,Jackson,603,Germany,Male,26,4,109166.37,1,1,1,92840.67,0 +66,15789484,Hammond,751,Germany,Female,36,6,169831.46,2,1,1,27758.36,0 +67,15696061,Brownless,581,Germany,Female,34,1,101633.04,1,1,0,110431.51,0 +68,15641582,Chibugo,735,Germany,Male,43,10,123180.01,2,1,1,196673.28,0 +69,15638424,Glauert,661,Germany,Female,35,5,150725.53,2,0,1,113656.85,0 +70,15755648,Pisano,675,France,Female,21,8,98373.26,1,1,0,18203,0 +71,15703793,Konovalova,738,Germany,Male,58,2,133745.44,4,1,0,28373.86,1 +72,15620344,McKee,813,France,Male,29,6,0,1,1,0,33953.87,0 +73,15812518,Palermo,657,Spain,Female,37,0,163607.18,1,0,1,44203.55,0 +74,15779052,Ballard,604,Germany,Female,25,5,157780.84,2,1,1,58426.81,0 +75,15770811,Wallace,519,France,Male,36,9,0,2,0,1,145562.4,0 +76,15780961,Cavenagh,735,France,Female,21,1,178718.19,2,1,0,22388,0 +77,15614049,Hu,664,France,Male,55,8,0,2,1,1,139161.64,0 +78,15662085,Read,678,France,Female,32,9,0,1,1,1,148210.64,0 +79,15575185,Bushell,757,Spain,Male,33,5,77253.22,1,0,1,194239.63,0 +80,15803136,Postle,416,Germany,Female,41,10,122189.66,2,1,0,98301.61,0 +81,15706021,Buley,665,France,Female,34,1,96645.54,2,0,0,171413.66,0 +82,15663706,Leonard,777,France,Female,32,2,0,1,1,0,136458.19,1 +83,15641732,Mills,543,France,Female,36,3,0,2,0,0,26019.59,0 +84,15701164,Onyeorulu,506,France,Female,34,4,90307.62,1,1,1,159235.29,0 +85,15738751,Beit,493,France,Female,46,4,0,2,1,0,1907.66,0 +86,15805254,Ndukaku,652,Spain,Female,75,10,0,2,1,1,114675.75,0 +87,15762418,Gant,750,Spain,Male,22,3,121681.82,1,1,0,128643.35,1 +88,15625759,Rowley,729,France,Male,30,9,0,2,1,0,151869.35,0 +89,15622897,Sharpe,646,France,Female,46,4,0,3,1,0,93251.42,1 +90,15767954,Osborne,635,Germany,Female,28,3,81623.67,2,1,1,156791.36,0 +91,15757535,Heap,647,Spain,Female,44,5,0,3,1,1,174205.22,1 +92,15731511,Ritchie,808,France,Male,45,7,118626.55,2,1,0,147132.46,0 +93,15809248,Cole,524,France,Female,36,10,0,2,1,0,109614.57,0 +94,15640635,Capon,769,France,Male,29,8,0,2,1,1,172290.61,0 +95,15676966,Capon,730,Spain,Male,42,4,0,2,0,1,85982.47,0 +96,15699461,Fiorentini,515,Spain,Male,35,10,176273.95,1,0,1,121277.78,0 +97,15738721,Graham,773,Spain,Male,41,9,102827.44,1,0,1,64595.25,0 +98,15693683,Yuille,814,Germany,Male,29,8,97086.4,2,1,1,197276.13,0 +99,15604348,Allard,710,Spain,Male,22,8,0,2,0,0,99645.04,0 +100,15633059,Fanucci,413,France,Male,34,9,0,2,0,0,6534.18,0 +101,15808582,Fu,665,France,Female,40,6,0,1,1,1,161848.03,0 +102,15743192,Hung,623,France,Female,44,6,0,2,0,0,167162.43,0 +103,15580146,Hung,738,France,Male,31,9,82674.15,1,1,0,41970.72,0 +104,15776605,Bradley,528,Spain,Male,36,7,0,2,1,0,60536.56,0 +105,15804919,Dunbabin,670,Spain,Female,65,1,0,1,1,1,177655.68,1 +106,15613854,Mauldon,622,Spain,Female,46,4,107073.27,2,1,1,30984.59,1 +107,15599195,Stiger,582,Germany,Male,32,1,88938.62,1,1,1,10054.53,0 +108,15812878,Parsons,785,Germany,Female,36,2,99806.85,1,0,1,36976.52,0 +109,15602312,Walkom,605,Spain,Male,33,5,150092.8,1,0,0,71862.79,0 +110,15744689,T'ang,479,Germany,Male,35,9,92833.89,1,1,0,99449.86,1 +111,15803526,Eremenko,685,Germany,Male,30,3,90536.81,1,0,1,63082.88,0 +112,15665790,Rowntree,538,Germany,Male,39,7,108055.1,2,1,0,27231.26,0 +113,15715951,Thorpe,562,France,Male,42,2,100238.35,1,0,0,86797.41,0 +114,15591100,Chiemela,675,Spain,Male,36,9,106190.55,1,0,1,22994.32,0 +115,15609618,Fanucci,721,Germany,Male,28,9,154475.54,2,0,1,101300.94,1 +116,15675522,Ko,628,Germany,Female,30,9,132351.29,2,1,1,74169.13,0 +117,15705512,Welch,668,Germany,Female,37,6,167864.4,1,1,0,115638.29,0 +118,15698028,Duncan,506,France,Female,41,1,0,2,1,0,31766.3,0 +119,15661670,Chidozie,524,Germany,Female,31,8,107818.63,1,1,0,199725.39,1 +120,15600781,Wu,699,Germany,Male,34,4,185173.81,2,1,0,120834.48,0 +121,15682472,Culbreth,828,France,Male,34,8,129433.34,2,0,0,38131.77,0 +122,15580203,Kennedy,674,Spain,Male,39,6,120193.42,1,0,0,100130.95,0 +123,15690673,Cameron,656,France,Female,39,6,0,2,1,0,141069.88,0 +124,15760085,Calabresi,684,Germany,Female,48,10,126384.42,1,1,1,198129.36,0 +125,15779659,Zetticci,625,France,Female,28,3,0,1,0,0,183646.41,0 +126,15627360,Fuller,432,France,Male,42,9,152603.45,1,1,0,110265.24,1 +127,15671137,MacDonald,549,France,Female,52,1,0,1,0,1,8636.05,1 +128,15782688,Piccio,625,Germany,Male,56,0,148507.24,1,1,0,46824.08,1 +129,15575492,Kennedy,828,France,Female,41,7,0,2,1,0,171378.77,0 +130,15591607,Fernie,770,France,Male,24,9,101827.07,1,1,0,167256.35,0 +131,15740404,He,758,France,Female,34,3,0,2,1,1,124226.16,0 +132,15718369,Kaodilinakachukwu,795,Germany,Female,33,9,130862.43,1,1,1,114935.21,0 +133,15677871,Cocci,687,France,Male,38,9,122570.87,1,1,1,35608.88,0 +134,15642004,Alekseeva,686,France,Male,25,1,0,2,0,1,16459.37,0 +135,15712543,Chinweike,789,Germany,Male,39,7,124828.46,2,1,1,124411.08,0 +136,15584518,Arthur,589,Germany,Female,50,5,144895.05,2,1,1,34941.23,0 +137,15802381,Li,461,Germany,Female,34,5,63663.93,1,0,1,167784.28,0 +138,15610156,Ma,637,France,Male,40,2,133463.1,1,0,1,93165.34,0 +139,15594408,Chia,584,Spain,Female,48,2,213146.2,1,1,0,75161.25,1 +140,15640905,Vasin,579,Spain,Female,35,1,129490.36,2,0,1,8590.83,1 +141,15698932,Groves,756,Germany,Male,44,10,137452.09,1,1,0,189543.9,0 +142,15724944,Tien,663,France,Male,34,7,0,2,1,1,180427.24,0 +143,15628145,Forwood,682,France,Female,43,5,125851.93,1,1,1,193318.33,0 +144,15713483,Greeves,793,Spain,Male,52,2,0,1,1,0,159123.82,1 +145,15612350,Taylor,691,France,Female,31,5,40915.55,1,1,0,126213.84,1 +146,15800703,Madukwe,485,Spain,Female,21,5,113157.22,1,1,1,54141.5,0 +147,15705707,Bennelong,635,Spain,Female,29,8,138296.94,2,1,0,141075.51,0 +148,15754105,Olisanugo,650,France,Male,37,5,106967.18,1,0,0,24495.03,0 +149,15703264,Chukwufumnanya,735,France,Male,44,9,120681.63,1,1,0,74836.34,0 +150,15794413,Harris,416,France,Male,32,0,0,2,0,1,878.87,0 +151,15650237,Morgan,754,Spain,Female,32,7,0,2,1,0,89520.75,0 +152,15759618,Alexeeva,535,France,Female,48,9,0,1,1,0,149892.79,1 +153,15811589,Metcalfe,716,Spain,Male,42,8,0,2,1,0,180800.42,0 +154,15689044,Humphries,539,France,Male,37,2,127609.59,1,1,0,98646.22,0 +155,15709368,Milne,614,France,Female,43,6,0,2,1,1,109041.53,0 +156,15679145,Chou,706,Spain,Male,57,7,0,1,1,0,17941.16,1 +157,15655007,Li,758,France,Female,33,7,0,2,0,0,82996.47,0 +158,15623595,Clayton,586,Spain,Female,28,2,0,2,1,1,92067.35,0 +159,15589975,Maclean,646,France,Female,73,6,97259.25,1,0,1,104719.66,0 +160,15804017,Chigolum,631,Germany,Female,33,4,123246.7,1,0,0,112687.57,0 +161,15692132,Wilkinson,717,Spain,Female,22,6,101060.25,1,0,1,84699.56,0 +162,15641122,Wei,684,France,Male,30,2,0,2,1,0,83473.82,0 +163,15630910,Treacy,800,France,Female,49,7,108007.36,1,0,0,47125.11,0 +164,15680772,Hu,721,Spain,Female,36,2,0,2,1,1,106977.8,0 +165,15658929,Taverner,683,Spain,Male,29,0,133702.89,1,1,0,55582.54,1 +166,15585388,Sherman,660,Germany,Male,31,9,125189.75,2,1,1,139874.43,0 +167,15724623,Taubman,704,Germany,Female,24,7,113034.22,1,1,0,162503.48,1 +168,15588537,Robinson,615,Spain,Female,41,9,109013.23,1,1,0,196499.96,0 +169,15574692,Pinto,667,Spain,Female,39,2,0,2,1,0,40721.24,1 +170,15611325,Wood,682,Germany,Male,24,9,57929.81,2,0,0,53134.3,0 +171,15587562,Hawkins,484,France,Female,29,4,130114.39,1,1,0,164017.89,0 +172,15613172,Sun,628,Germany,Male,27,5,95826.49,2,1,0,155996.96,0 +173,15651022,Yost,480,Germany,Male,44,10,129608.57,1,1,0,5472.7,1 +174,15586310,Ting,578,France,Male,30,4,169462.09,1,1,0,112187.11,0 +175,15625524,Rowe,512,France,Male,40,5,0,2,1,1,146457.83,0 +176,15755209,Fu,484,Spain,Female,35,7,133868.21,1,1,1,27286.1,0 +177,15645248,Ho,510,France,Female,30,0,0,2,1,1,130553.47,0 +178,15790355,Okechukwu,606,Germany,Male,36,5,190479.48,2,0,0,179351.89,0 +179,15762615,Campbell,597,Spain,Female,40,8,101993.12,1,0,1,94774.12,0 +180,15625426,Ashbolt,754,Germany,Female,55,3,161608.81,1,1,0,8080.85,1 +181,15716334,Rozier,850,Spain,Female,45,2,122311.21,1,1,1,19482.5,0 +182,15789669,Hsia,510,France,Male,65,2,0,2,1,1,48071.61,0 +183,15621075,Ogbonnaya,778,Germany,Female,45,1,162150.42,2,1,0,174531.27,0 +184,15810845,T'ang,636,France,Male,42,2,0,2,1,1,55470.78,0 +185,15719377,Cocci,804,France,Female,50,4,0,1,1,1,8546.87,1 +186,15654506,Chang,514,France,Male,32,8,0,2,1,0,95857.18,0 +187,15771977,T'ao,730,France,Female,39,1,99010.67,1,1,0,194945.8,0 +188,15708710,Ford,525,Spain,Female,37,0,0,1,0,1,131521.72,0 +189,15726676,Marshall,616,Spain,Male,30,5,0,2,0,1,196108.51,0 +190,15587421,Tsai,687,Germany,Female,34,7,111388.18,2,1,0,148564.76,0 +191,15726931,Onwumelu,715,France,Female,41,8,56214.85,2,0,0,92982.61,1 +192,15771086,Graham,512,France,Female,36,3,84327.77,2,1,0,17675.36,0 +193,15756850,Golovanov,479,France,Male,40,1,0,2,0,0,114996.43,0 +194,15702741,Potts,601,France,Male,32,8,93012.89,1,1,0,86957.42,0 +195,15679200,Crawford,580,Spain,Male,29,9,61710.44,2,1,0,128077.8,0 +196,15594815,Aleshire,807,France,Male,35,3,174790.15,1,1,1,600.36,0 +197,15635905,Moran,616,Spain,Female,32,6,0,2,1,1,43001.46,0 +198,15777892,Samsonova,721,Germany,Male,37,3,107720.64,1,1,1,158591.12,0 +199,15656176,Jenkins,501,France,Male,57,10,0,2,1,1,47847.19,0 +200,15811127,Volkov,521,France,Male,35,6,96423.84,1,1,0,10488.44,0 +201,15604482,Chiemezie,850,Spain,Male,30,2,141040.01,1,1,1,5978.2,0 +202,15622911,Jude,759,France,Male,42,4,105420.18,1,0,1,121409.06,0 +203,15600974,He,516,Spain,Male,50,5,0,1,0,1,146145.93,1 +204,15727868,Onuora,711,France,Female,38,2,129022.06,2,1,1,14374.86,1 +205,15627801,Ginikanwa,512,Spain,Male,33,3,176666.62,1,1,0,94670.77,0 +206,15773039,Ku,550,France,Male,37,3,0,1,1,1,179670.31,0 +207,15755262,McDonald,608,Spain,Female,41,3,89763.84,1,0,0,199304.74,1 +208,15679531,Collins,618,France,Male,34,5,134954.53,1,1,1,151954.39,0 +209,15684181,Hackett,643,France,Male,45,5,0,1,1,0,142513.5,1 +210,15612087,Dike,671,France,Male,45,2,106376.85,1,0,1,158264.62,0 +211,15752047,Trevisano,689,Germany,Male,33,2,161814.64,2,1,0,169381.9,0 +212,15624592,Tan,603,France,Male,31,8,0,2,1,1,169915.02,0 +213,15573152,Glassman,620,France,Female,41,9,0,2,0,0,88852.47,0 +214,15594917,Miller,676,France,Female,34,1,63095.01,1,1,1,40645.81,0 +215,15785542,Kornilova,572,Germany,Male,26,4,118287.01,2,0,0,60427.3,0 +216,15723488,Watson,668,Germany,Male,47,7,106854.21,1,0,1,157959.02,1 +217,15680920,Marchesi,695,France,Male,46,7,49512.55,1,1,0,133007.34,0 +218,15786308,Millar,730,Spain,Female,33,9,0,2,0,0,176576.62,0 +219,15659366,Shih,807,France,Male,43,1,105799.32,2,1,0,34888.04,1 +220,15774854,Fuller,592,France,Male,54,8,0,1,1,1,28737.71,1 +221,15725311,Hay,726,France,Female,31,9,114722.05,2,1,1,98178.57,0 +222,15787155,Yang,514,Spain,Male,30,7,0,1,0,1,125010.24,0 +223,15727829,McIntyre,567,France,Male,42,2,0,2,1,1,167984.61,0 +224,15733247,Stevenson,850,France,Male,33,10,0,1,1,0,4861.72,1 +225,15568748,Poole,671,Germany,Male,45,6,99564.22,1,1,1,108872.45,1 +226,15699029,Bagley,670,France,Male,37,4,170557.91,2,1,0,198252.88,0 +227,15774393,Ch'ien,694,France,Female,30,9,0,2,1,1,26960.31,0 +228,15676895,Cattaneo,547,Germany,Female,39,6,74596.15,3,1,1,85746.52,1 +229,15637753,O'Sullivan,751,Germany,Male,50,2,96888.39,1,1,0,77206.25,1 +230,15605461,Lucas,594,Germany,Female,29,3,130830.22,1,1,0,61048.53,0 +231,15808473,Ringrose,673,France,Male,72,1,0,2,0,1,111981.19,0 +232,15627000,Freeman,610,France,Male,40,0,0,2,1,0,62232.6,0 +233,15787174,Sergeyev,512,France,Female,37,1,0,2,0,1,156105.03,0 +234,15723886,Fiore,767,Germany,Male,20,3,119714.25,2,0,1,150135.38,0 +235,15704769,Smith,585,France,Female,67,5,113978.97,2,0,1,93146.11,0 +236,15772896,Dumetochukwu,763,Germany,Male,42,6,100160.75,1,1,0,33462.94,1 +237,15711540,Pacheco,712,France,Female,29,2,0,1,1,1,144375,0 +238,15764866,Synnot,539,Germany,Female,43,3,116220.5,3,1,0,55803.96,1 +239,15794056,Johnston,668,France,Female,46,2,0,3,1,0,89048.46,1 +240,15795149,Stevens,703,France,Male,28,2,81173.83,2,0,1,162812.16,0 +241,15812009,Grant,662,Spain,Male,38,4,0,2,1,0,136259.65,0 +242,15651001,Tsao,725,Germany,Female,39,5,116803.8,1,1,0,124052.97,0 +243,15813844,Barnes,703,France,Male,37,8,105961.68,2,0,1,74158.8,0 +244,15596175,McIntosh,659,Germany,Male,67,6,117411.6,1,1,1,45071.09,1 +245,15576269,Madison,523,Spain,Male,34,7,0,2,1,0,62030.06,0 +246,15797219,Ifesinachi,635,France,Female,40,10,123497.58,1,1,0,131953.23,1 +247,15685500,Glazkov,772,Germany,Male,26,7,152400.51,2,1,0,79414,0 +248,15599792,Dimauro,545,France,Female,26,1,0,2,1,1,199638.56,0 +249,15657566,Wieck,634,Germany,Male,24,8,103097.85,1,1,1,157577.29,0 +250,15772423,Liao,739,Germany,Male,54,8,126418.14,1,1,0,134420.75,1 +251,15628112,Hughes,771,Germany,Female,36,5,77846.9,1,0,0,99805.99,0 +252,15753754,Morrison,587,Spain,Female,34,1,0,2,1,1,97932.68,0 +253,15793726,Matveyeva,681,France,Female,79,0,0,2,0,1,170968.99,0 +254,15694717,Ku,544,Germany,Male,37,2,79731.91,1,1,1,57558.95,0 +255,15665834,Cheatham,696,Spain,Male,28,8,0,1,0,0,176713.47,0 +256,15765297,Yao,766,Spain,Male,41,0,0,2,0,1,34283.23,0 +257,15636684,Kirkland,727,France,Male,34,10,0,2,1,1,198637.34,0 +258,15592979,Rose,671,Germany,Female,34,6,37266.67,2,0,0,156917.12,0 +259,15750803,Jess,693,France,Female,30,6,127992.25,1,1,1,50457.2,0 +260,15607178,Welch,850,Germany,Male,38,3,54901.01,1,1,1,140075.55,0 +261,15713853,Ifeajuna,732,Germany,Male,42,9,108748.08,2,1,1,65323.11,0 +262,15673481,Morton,726,Spain,Female,48,6,99906.19,1,1,0,64323.24,0 +263,15686776,Rossi,557,France,Female,32,6,184686.41,2,1,0,14956.44,0 +264,15673693,Reppert,682,France,Female,26,0,110654.02,1,0,1,111879.21,0 +265,15700696,Kang,738,Spain,Male,31,9,79019.8,1,1,1,18606.23,0 +266,15813163,Ch'iu,531,Spain,Female,36,9,99240.51,1,1,0,123137.01,0 +267,15653857,Wallis,498,France,Male,34,2,0,2,1,1,148528.24,0 +268,15777076,Clark,651,France,Male,36,7,0,2,1,0,13898.31,0 +269,15717398,Fielding,549,Spain,Female,39,7,0,1,0,0,81259.25,1 +270,15799217,Zetticci,791,Germany,Female,35,7,52436.2,1,1,0,161051.75,0 +271,15787071,Dulhunty,650,Spain,Male,41,9,0,2,0,1,191599.67,0 +272,15619955,Bevington,733,Germany,Male,34,3,100337.96,3,1,0,48559.19,1 +273,15796505,Boyle,811,Germany,Female,34,1,149297.19,2,1,1,186339.74,0 +274,15725166,Newton,707,France,Male,30,8,0,2,1,0,33159.37,0 +275,15800116,Bowman,712,Germany,Male,28,4,145605.44,1,0,1,93883.53,0 +276,15758685,Dubinina,706,Spain,Female,37,7,0,2,1,1,110899.3,0 +277,15694456,Toscani,756,France,Male,62,3,0,1,1,1,11199.04,1 +278,15767339,Chiazagomekpere,777,France,Female,53,10,0,2,1,0,189992.97,0 +279,15683562,Allen,646,France,Male,35,6,84026.86,1,0,1,164255.69,0 +280,15782210,K'ung,714,France,Male,46,1,0,1,1,0,152167.79,1 +281,15668893,Wilsmore,782,France,Male,39,8,0,2,1,1,33949.67,0 +282,15669169,Hargreaves,775,Spain,Male,29,10,0,2,1,1,68143.93,0 +283,15643024,Huang,479,Germany,Male,35,4,138718.92,1,1,1,47251.79,1 +284,15699389,Ch'ien,807,France,Male,42,7,118274.71,1,1,1,25885.72,0 +285,15708608,Wallwork,799,France,Female,22,8,174185.98,2,0,1,192633.85,0 +286,15626144,Chu,675,France,Male,40,7,113208.86,2,1,0,34577.36,0 +287,15573112,Kang,602,Spain,Male,29,5,103907.28,1,1,0,161229.84,0 +288,15790678,Davidson,475,France,Female,32,8,119023.28,1,1,0,100816.29,0 +289,15727556,O'Donnell,744,Spain,Female,26,5,166297.89,1,1,1,181694.44,0 +290,15697307,Nnachetam,588,Spain,Male,34,10,0,2,1,0,79078.91,0 +291,15652266,Chidiebele,703,Germany,Male,42,9,63227,1,0,1,137316.32,0 +292,15607098,Ahmed,747,Spain,Female,41,5,94521.17,2,1,0,194926.86,0 +293,15655774,Booth,583,France,Male,27,7,0,2,1,0,51285.49,0 +294,15590241,Chuang,750,Spain,Female,34,9,112822.26,1,0,0,150401.53,1 +295,15785819,Shao,681,France,Male,38,3,0,2,1,1,112491.96,0 +296,15723654,Tsao,773,France,Male,25,2,135903.33,1,1,0,73656.38,0 +297,15774510,Tien,714,France,Female,31,4,125169.26,1,1,1,106636.89,0 +298,15684173,Chang,687,Spain,Female,44,7,0,3,1,0,155853.52,1 +299,15650068,Johnson,511,France,Male,58,0,149117.31,1,1,1,162599.51,0 +300,15811490,French,627,France,Male,33,5,0,2,1,1,103737.82,0 +301,15803976,Efremov,694,France,Female,31,10,0,2,1,0,160990.27,0 +302,15682541,Hartley,616,Spain,Female,36,6,132311.71,1,0,0,15462.84,0 +303,15695699,Calabrese,687,France,Male,35,8,0,2,1,0,10334.05,0 +304,15624188,Chiu,712,France,Female,33,6,0,2,1,1,190686.16,0 +305,15812191,Brennan,553,France,Male,33,4,118082.89,1,0,0,94440.45,0 +306,15636673,Onwuatuegwu,667,France,Male,31,1,119266.69,1,1,1,28257.63,0 +307,15594898,Hewitt,731,France,Male,43,2,0,1,1,1,170034.95,1 +308,15660211,Shih,629,Germany,Male,35,7,156847.29,2,1,0,31824.29,0 +309,15773972,Balashov,614,France,Male,50,4,137104.47,1,1,0,127166.49,1 +310,15746726,Doyle,438,Germany,Male,31,8,78398.69,1,1,0,44937.01,0 +311,15712287,Pokrovskii,652,France,Female,80,4,0,2,1,1,188603.07,0 +312,15702919,Collins,729,Germany,Male,30,6,63669.42,1,1,0,145111.37,0 +313,15674398,Russo,642,France,Male,38,3,0,2,0,0,171463.83,0 +314,15797960,Skinner,806,Germany,Female,59,0,135296.33,1,1,0,182822.5,0 +315,15631868,Robertson,744,Spain,Male,36,2,153804.44,1,1,1,87213.33,0 +316,15581539,Atkinson,474,Spain,Male,37,3,0,2,0,0,57175.32,0 +317,15662736,Doyle,559,France,Male,49,2,147069.78,1,1,0,120540.83,1 +318,15666252,Ritchie,706,Spain,Male,42,9,0,2,1,1,28714.34,0 +319,15677512,McEncroe,628,Spain,Female,22,3,0,1,1,0,85426.28,0 +320,15626114,Pearson,429,France,Male,24,4,95741.75,1,1,0,46170.75,0 +321,15810834,Gordon,525,Spain,Female,57,2,145965.33,1,1,1,64448.36,0 +322,15678910,Ts'ai,680,France,Female,30,8,141441.75,1,1,1,16278.97,0 +323,15694408,Lung,749,France,Male,40,1,139290.41,1,1,0,182855.42,1 +324,15585215,Yuan,763,France,Female,31,4,0,2,0,0,50404.72,0 +325,15682757,Pardey,734,France,Male,30,3,0,2,1,0,107640.25,0 +326,15736601,Tai,716,France,Male,35,4,144428.87,1,1,0,134132.65,0 +327,15601848,Scott,594,France,Male,35,2,0,2,1,0,103480.69,0 +328,15736008,Hunter,644,France,Female,46,9,95441.27,1,1,0,108761.05,1 +329,15669064,Mazzanti,671,Germany,Male,35,1,144848.74,1,1,1,179012.3,0 +330,15624528,L?,664,Germany,Male,26,7,116244.14,2,1,1,95145.14,0 +331,15598493,Beach,656,France,Male,50,7,0,2,0,1,72143.44,0 +332,15601274,Hsieh,667,Spain,Female,40,1,146502.07,1,1,0,19162.89,0 +333,15702669,Faulkner,663,Germany,Male,44,2,117028.6,2,0,1,144680.18,0 +334,15728669,Knowles,584,Germany,Female,30,8,112013.81,1,1,0,177772.03,1 +335,15742668,Day,626,Spain,Female,37,6,108269.37,1,1,0,5597.94,0 +336,15697441,Hsueh,485,France,Male,29,7,182123.79,1,1,0,116828.51,1 +337,15740476,Tsao,659,Germany,Female,32,3,150923.74,2,0,1,174652.51,0 +338,15648064,Kennedy,649,France,Male,33,2,0,2,1,0,2010.98,0 +339,15636624,Nwabugwu,805,Spain,Female,39,5,165272.13,1,1,0,14109.85,1 +340,15807923,Young,716,Germany,Female,39,10,115301.31,1,1,0,43527.4,1 +341,15745844,Kerr,642,Germany,Female,40,6,129502.49,2,0,1,86099.23,1 +342,15786170,Tien,659,France,Male,31,4,118342.26,1,0,0,161574.19,0 +343,15681081,Marrero,545,Spain,Female,47,5,0,2,1,1,38970.14,0 +344,15684484,White,543,France,Male,22,8,0,2,0,0,127587.22,0 +345,15785869,Pisano,718,France,Female,25,7,0,2,1,0,30380.12,0 +346,15763859,Brown,840,France,Female,43,7,0,2,1,0,90908.95,0 +347,15658935,Freeman,630,Germany,Female,34,9,106937.05,2,1,0,138275.01,0 +348,15747358,Russell,643,Germany,Male,59,3,170331.37,1,1,1,32171.79,0 +349,15735203,Seleznyov,654,Germany,Female,32,1,114510.85,1,1,1,126143.23,0 +350,15576256,Yusupova,582,France,Male,39,5,0,2,1,1,129892.93,0 +351,15659420,Foley,659,Spain,Male,32,3,107594.11,2,1,1,102416.84,0 +352,15593365,Shih,762,Spain,Male,39,2,81273.13,1,1,1,18719.67,0 +353,15777352,Ikedinachukwu,568,Spain,Female,32,7,169399.6,1,1,0,61936.22,0 +354,15812007,Power,670,Spain,Male,25,6,0,2,1,1,78358.94,0 +355,15625461,Amos,613,France,Female,45,1,187841.99,2,1,1,147224.27,0 +356,15739438,Reed,539,France,Male,30,0,0,2,1,0,160979.66,0 +357,15611759,Simmons,850,Spain,Female,57,8,126776.3,2,1,1,132298.49,0 +358,15661629,Ricci,522,Spain,Male,34,9,126436.29,1,1,0,174248.52,1 +359,15633950,Yen,737,France,Male,41,1,101960.74,1,1,1,123547.28,0 +360,15592386,Campbell,520,France,Male,58,3,0,2,0,1,32790.02,0 +361,15803716,West,706,Spain,Male,28,3,0,2,0,1,181543.67,0 +362,15696674,Robinson,643,Germany,Female,45,2,150842.93,1,0,1,2319.96,1 +363,15706365,Bianchi,648,France,Female,50,9,102535.57,1,1,1,189543.19,0 +364,15745088,Chen,443,Germany,Female,29,9,99027.61,2,1,0,10940.4,0 +365,15676715,Madukaego,640,France,Male,68,9,0,2,1,1,199493.38,0 +366,15613085,Ibrahimova,628,Spain,Female,33,3,0,1,1,1,188193.25,0 +367,15633537,Nolan,540,Germany,Female,42,9,87271.41,2,1,0,172572.64,0 +368,15594720,Scott,460,Germany,Female,35,8,102742.91,2,1,1,189339.6,0 +369,15684042,Blair,636,Germany,Male,34,2,40105.51,2,0,1,53512.16,0 +370,15583303,Monaldo,593,France,Female,29,2,152265.43,1,1,0,34004.44,0 +371,15611579,Sutherland,801,Spain,Male,42,4,141947.67,1,1,1,10598.29,0 +372,15774696,Cole,640,Germany,Female,75,1,106307.91,2,0,1,113428.77,0 +373,15694506,Briggs,611,Germany,Male,31,0,107884.81,2,1,1,183487.98,0 +374,15688074,Gregory,802,Germany,Male,31,1,125013.72,1,1,1,187658.09,0 +375,15759537,Bianchi,717,Germany,Male,35,7,58469.37,2,1,1,172459.39,0 +376,15758449,Angelo,769,France,Female,39,8,0,1,0,1,21016,0 +377,15583456,Gardiner,745,Germany,Male,45,10,117231.63,3,1,1,122381.02,1 +378,15667871,Kerr,572,Spain,Male,35,4,152390.26,1,1,0,128123.66,0 +379,15677371,Ko,629,Spain,Female,30,2,34013.63,1,1,0,19570.63,0 +380,15629677,Distefano,687,Spain,Female,39,2,0,3,0,0,188150.6,1 +381,15713578,Farrell,483,France,Female,50,9,0,2,1,1,111020.24,0 +382,15591509,Milano,690,France,Male,36,7,101583.11,2,1,0,123775.15,0 +383,15568240,Ting,492,Germany,Female,30,10,77168.87,2,0,1,146700.22,0 +384,15622993,Boyd,709,Germany,Male,28,8,124695.72,2,1,0,145251.35,0 +385,15689294,Onyemaechi,705,Germany,Male,44,3,105934.96,1,1,0,82463.69,0 +386,15720910,Black,560,France,Female,66,9,0,1,1,1,15928.49,0 +387,15721181,Oliver,611,Spain,Male,46,6,0,2,1,0,45886.33,0 +388,15776433,Greco,730,Spain,Male,62,2,0,2,1,1,186489.95,0 +389,15748936,Whitehead,709,Spain,Female,45,2,0,2,0,1,162922.65,0 +390,15717225,Ikemefuna,544,France,Female,21,10,161525.96,2,1,0,9262.77,0 +391,15685226,Morrison,712,Germany,Female,29,7,147199.07,1,1,1,84932.4,0 +392,15785611,Onyeoruru,752,Germany,Male,38,3,183102.29,1,1,1,71557.12,0 +393,15573456,Cunningham,648,Spain,Male,46,9,127209,2,1,0,77405.95,1 +394,15684548,Demidov,556,Spain,Male,38,8,0,2,0,0,417.41,1 +395,15620505,Celis,594,Spain,Female,24,0,97378.54,1,1,1,71405.17,0 +396,15807432,Cheng,645,Germany,Female,37,2,136925.09,2,0,1,153400.24,0 +397,15584766,Knight,557,France,Male,33,3,54503.55,1,1,1,371.05,0 +398,15612187,Morin,547,Germany,Male,32,8,155726.85,1,1,0,67789.99,0 +399,15762218,Mills,701,France,Female,39,9,0,2,0,1,145894.9,0 +400,15646372,Outhwaite,616,France,Female,66,1,135842.41,1,1,0,183840.51,1 +401,15690452,Tung,605,France,Male,52,1,63349.75,1,1,0,108887.44,0 +402,15747795,Pai,593,Germany,Female,38,4,129499.42,1,1,1,154071.27,0 +403,15781589,Carpenter,751,Spain,Male,52,8,0,2,0,1,179291.85,0 +404,15732674,Fennell,443,Spain,Male,36,6,70438.01,2,0,1,56937.43,0 +405,15642291,Fontaine,685,France,Male,23,8,0,2,1,1,112239.03,0 +406,15692761,Pratt,718,France,Male,36,9,0,1,1,0,45909.87,0 +407,15578045,Mitchell,538,Spain,Female,49,9,141434.04,1,0,0,173779.25,1 +408,15745354,Franklin,611,Spain,Female,37,4,0,2,1,0,125696.26,0 +409,15701376,K'ung,668,Germany,Male,37,10,152958.29,2,1,1,159585.61,0 +410,15691625,Ko,537,Germany,Female,41,3,138306.34,1,1,0,106761.47,0 +411,15566594,McKenzie,709,Spain,Male,23,10,0,2,0,0,129590.18,0 +412,15760431,Pino,850,France,Male,38,1,0,2,1,1,80006.65,0 +413,15686302,Fisk,745,Spain,Female,31,3,124328.84,1,1,1,140451.52,0 +414,15801559,Chiang,693,Germany,Female,41,9,181461.48,3,1,1,187929.43,1 +415,15810432,Moseley,795,Spain,Male,35,8,0,2,1,0,167155.36,0 +416,15809616,Hsiung,626,Spain,Male,26,8,0,2,0,0,191420.71,0 +417,15720559,Heath,487,Germany,Female,61,5,110368.03,1,0,0,11384.45,1 +418,15695632,Dellucci,556,France,Female,39,9,89588.35,1,1,1,94898.1,0 +419,15659843,Li,643,France,Female,46,6,0,2,0,0,106781.59,0 +420,15615624,De Salis,605,France,Female,28,6,0,2,0,0,159508.52,0 +421,15810418,T'ang,756,Germany,Female,60,3,115924.89,1,1,0,93524.19,1 +422,15716186,Richardson,586,France,Female,38,2,0,2,1,0,87168.46,0 +423,15674551,Fitch,535,Germany,Male,40,7,111756.5,1,1,0,8128.32,1 +424,15622834,Stevenson,678,France,Female,35,4,0,1,1,0,125518.32,0 +425,15566111,Estes,596,France,Male,39,9,0,1,1,0,48963.59,0 +426,15784597,Lattimore,648,France,Male,26,9,162923.85,1,1,0,98368.24,0 +427,15652883,Chung,492,Germany,Male,39,10,124576.65,2,1,0,148584.61,0 +428,15806964,Utz,702,France,Male,45,0,80793.58,1,1,1,27474.81,0 +429,15576313,Wei,486,Germany,Female,40,9,71340.09,1,1,0,76192.21,0 +430,15806467,Boyle,568,Germany,Male,40,1,99282.63,1,0,0,134600.94,1 +431,15597602,Nwachinemelu,619,Germany,Male,57,3,137946.39,1,1,1,72467.99,1 +432,15743040,Kuznetsova,724,Germany,Male,41,2,127892.57,2,0,1,199645.45,0 +433,15705521,Pisani,548,Germany,Female,33,0,101084.36,1,1,0,42749.85,0 +434,15595039,Manna,545,Germany,Female,37,8,114754.08,1,1,0,136050.44,1 +435,15799384,Collier,683,France,Male,33,8,0,1,0,0,73564.44,0 +436,15581197,Ricci,762,France,Female,51,3,99286.98,1,0,1,85578.63,0 +437,15693737,Carr,627,Germany,Female,30,4,79871.02,2,1,0,129826.89,0 +438,15624623,Hs?,516,France,Male,35,10,104088.59,2,0,0,119666,0 +439,15783501,Findlay,800,France,Female,38,2,168190.33,2,1,0,68052.08,0 +440,15690134,Hughes,464,Germany,Female,42,3,85679.25,1,1,1,164104.74,0 +441,15782735,Chukwuemeka,626,France,Female,35,3,0,1,0,0,80190.36,0 +442,15611088,Genovese,790,France,Female,31,9,0,2,1,0,84126.75,0 +443,15672145,Swift,534,France,Female,34,7,121551.58,2,1,1,70179,0 +444,15732628,Ugoji,745,France,Male,46,2,122220.19,1,1,1,118024.1,0 +445,15787470,Parkinson,553,Spain,Male,47,3,116528.15,1,0,0,145704.19,1 +446,15803406,Ross,748,France,Female,26,1,77780.29,1,0,1,183049.41,0 +447,15730460,Oleary,722,France,Male,37,2,0,1,0,0,120906.83,0 +448,15644572,Turnbull,501,France,Male,40,4,125832.2,1,1,1,100433.83,0 +449,15694860,Uspensky,675,France,Female,38,6,68065.8,1,0,0,138777,1 +450,15658169,Cook,778,Spain,Female,47,6,127299.34,2,1,0,124694.99,0 +451,15794396,Newbold,494,Germany,Female,38,7,174937.64,1,1,0,40084.32,0 +452,15785798,Uchechukwu,850,France,Male,40,9,0,2,0,1,119232.33,0 +453,15710825,Ch'en,592,Spain,Male,31,7,110071.1,1,0,0,43921.36,0 +454,15668444,He,590,Spain,Female,44,3,139432.37,1,1,0,62222.81,0 +455,15726631,Hilton,758,France,Female,39,6,127357.76,1,0,1,56577,0 +456,15733797,Sal,506,France,Male,36,5,0,2,1,0,164253.35,0 +457,15747960,Eluemuno,733,France,Male,33,3,0,1,1,1,7666.73,0 +458,15634632,Titus,711,France,Male,38,3,0,2,1,0,68487.51,0 +459,15707362,Yin,514,Germany,Male,43,1,95556.31,1,0,1,199273.98,1 +460,15662976,Lettiere,637,Spain,Male,37,8,0,1,1,1,186062.36,0 +461,15732778,Templeman,468,Germany,Male,29,1,111681.98,2,1,1,195711.16,0 +462,15718443,Chibuzo,539,France,Male,39,3,0,2,1,0,36692.17,0 +463,15670039,Sun,509,Spain,Female,25,3,108738.71,2,1,0,106920.57,0 +464,15773792,Evans,662,France,Female,32,4,133950.37,1,1,1,48725.68,1 +465,15613786,Ogbonnaya,818,Spain,Male,26,4,0,2,1,1,167036.94,0 +466,15726032,Enyinnaya,608,France,Male,33,9,89968.69,1,1,0,68777.26,0 +467,15663252,Olisanugo,850,Spain,Female,32,9,0,2,1,1,18924.92,0 +468,15593782,Brookes,816,Germany,Female,38,5,130878.75,3,1,0,71905.77,1 +469,15633283,Padovano,536,France,Male,35,8,0,2,1,0,64833.28,0 +470,15749167,Fisk,753,France,Male,35,3,0,2,1,1,184843.77,0 +471,15759298,Shih,631,Spain,Male,27,10,134169.62,1,1,1,176730.02,0 +472,15683625,Hare,703,France,Male,37,1,149762.08,1,1,0,20629.4,1 +473,15635367,Muir,774,France,Male,26,2,93844.69,1,1,0,28415.36,0 +474,15681705,Fanucci,785,France,Male,28,8,0,2,1,0,77231.27,0 +475,15603156,Elewechi,571,France,Female,33,1,0,2,1,0,102750.7,0 +476,15591986,Johnston,621,Germany,Male,46,6,141078.37,1,0,0,34580.8,1 +477,15798888,Pisano,605,Germany,Female,31,1,117992.59,1,1,1,183598.77,0 +478,15809722,Ankudinov,611,France,Female,40,8,100812.33,2,1,0,147358.27,0 +479,15677538,Nwokike,569,France,Male,38,7,0,1,1,1,108469.2,0 +480,15797736,Smith,658,France,Male,29,4,80262.6,1,1,1,20612.82,0 +481,15695585,Atkins,788,Spain,Male,34,6,156478.62,1,0,1,181196.76,0 +482,15744398,Burns,525,France,Female,23,5,0,2,1,0,160249.1,0 +483,15750658,Obiuto,798,France,Male,37,8,0,3,0,0,110783.28,0 +484,15578186,Pirozzi,486,Germany,Male,37,9,115217.99,2,1,0,144995.33,0 +485,15676519,George,615,Spain,Male,61,9,0,2,1,0,150227.85,1 +486,15637954,Lewis,730,France,Female,35,0,155470.55,1,1,1,53718.28,0 +487,15758639,Moran,641,France,Male,37,7,0,2,1,0,75248.3,0 +488,15613772,Dalrymple,542,France,Male,39,3,135096.77,1,1,1,14353.43,1 +489,15731744,Carslaw,692,France,Male,30,2,0,2,0,1,130486.57,0 +490,15807709,Kirby,714,Germany,Female,55,9,180075.22,1,1,1,100127.71,0 +491,15714689,Houghton,591,Spain,Male,29,1,97541.24,1,1,1,196356.17,0 +492,15699005,Martin,710,France,Female,41,2,156067.05,1,1,1,9983.88,0 +493,15624170,Tan,639,France,Female,38,4,81550.94,2,0,1,118974.77,0 +494,15725679,Hsia,531,France,Female,47,6,0,1,0,0,194998.34,1 +495,15585865,Westerberg,673,France,Female,38,2,170061.92,2,0,0,134901.34,1 +496,15804256,Hale,765,Germany,Male,36,8,92310.54,2,1,1,72924.56,0 +497,15662403,Kryukova,622,France,Female,32,6,169089.38,2,1,0,101057.95,0 +498,15733616,Sopuluchukwu,806,France,Male,40,5,80613.93,1,1,1,142838.64,0 +499,15591995,Barry,757,Germany,Male,26,8,121581.56,2,1,1,127059.04,0 +500,15677020,Selezneva,570,France,Female,58,8,0,1,0,1,116503.92,1 +501,15727688,Chizuoke,555,Spain,Male,32,4,0,2,1,1,54405.79,0 +502,15715941,Lueck,692,France,Male,54,5,0,2,1,1,88721.84,0 +503,15714485,Udinese,774,France,Male,60,5,85891.55,1,1,0,74135.48,1 +504,15730059,Udobata,638,Spain,Male,44,9,77637.35,2,1,1,111346.22,0 +505,15715527,Freeman,543,Spain,Female,41,4,0,1,0,0,194902.16,0 +506,15576623,Outlaw,584,France,Male,31,5,0,2,1,0,31474.27,0 +507,15805565,Obiuto,691,Germany,Male,30,7,116927.89,1,1,0,21198.39,0 +508,15677307,Lo,684,Germany,Female,40,6,137326.65,1,1,0,186976.6,0 +509,15773890,Okechukwu,733,France,Male,22,5,0,2,1,1,117202.19,0 +510,15598883,King,599,Spain,Female,37,2,0,2,1,1,143739.29,0 +511,15568506,Forbes,524,Germany,Female,31,10,67238.98,2,1,1,161811.23,0 +512,15761043,Macleod,632,Germany,Female,38,6,86569.76,2,1,0,98090.91,0 +513,15782236,Gibbs,735,Spain,Male,34,5,0,2,0,0,71095.41,0 +514,15593601,Isayev,734,France,Male,34,6,133598.4,1,1,1,13107.24,0 +515,15682048,Pisano,605,France,Female,51,3,136188.78,1,1,1,67110.59,1 +516,15746902,Belstead,793,Spain,Male,38,9,0,2,1,0,88225.02,0 +517,15752081,Vassiliev,468,France,Female,56,10,0,3,0,1,62256.87,1 +518,15781307,Schneider,779,Germany,Male,37,7,120092.52,2,1,0,135925.72,0 +519,15775912,Mazzanti,698,France,Male,48,4,101238.24,2,0,1,177815.87,1 +520,15745417,Knipe,707,France,Male,58,6,89685.92,1,0,1,126471.13,0 +521,15671256,Macartney,850,France,Female,35,1,211774.31,1,1,0,188574.12,1 +522,15653547,Madukwe,850,France,Male,56,7,131317.48,1,1,1,119175.45,0 +523,15595766,Watts,527,Spain,Male,37,5,93722.73,2,1,1,139093.73,0 +524,15742358,Humphreys,696,Germany,Male,32,8,101160.99,1,1,1,115916.55,0 +525,15763274,Wu,661,France,Male,48,3,120320.54,1,0,0,96463.25,0 +526,15786063,Chin,776,France,Female,31,2,0,2,1,1,112349.51,0 +527,15600258,Chesnokova,701,France,Male,43,2,0,2,1,1,165303.79,0 +528,15573318,Kung,610,France,Male,26,8,0,2,1,0,166031.08,0 +529,15653849,Lu,572,Germany,Female,48,3,152827.99,1,1,0,38411.79,1 +530,15694272,Nkemakolam,673,France,Male,30,1,64097.75,1,1,1,77783.35,0 +531,15736112,Walton,519,Spain,Female,57,2,119035.35,2,1,1,29871.79,0 +532,15749851,Brookes,702,Spain,Female,26,4,135219.57,1,0,1,59747.63,0 +533,15663478,Baldwin,729,France,Male,32,6,93694.42,1,1,1,79919.13,0 +534,15592300,Mai,543,Spain,Male,35,10,59408.63,1,1,0,76773.53,0 +535,15567832,Shih,550,France,Female,40,7,114354.95,1,1,0,54018.93,0 +536,15776780,He,608,France,Male,59,1,0,1,1,0,70649.64,1 +537,15592846,Fiorentini,639,Germany,Male,35,10,128173.9,2,1,0,59093.39,0 +538,15739803,Lucciano,686,Spain,Male,34,9,0,2,1,0,127569.8,0 +539,15794142,Ferreira,564,Germany,Female,62,5,114931.35,3,0,1,18260.98,1 +540,15762729,Ukaegbunam,745,Germany,Female,28,1,111071.36,1,1,0,73275.96,1 +541,15667896,De Luca,833,France,Male,37,8,151226.18,2,1,1,136129.49,0 +542,15626578,Milne,622,France,Male,26,9,0,2,1,1,153237.59,0 +543,15776223,Davide,597,France,Female,42,4,64740.12,1,1,1,106841.12,0 +544,15705953,Kodilinyechukwu,721,Spain,Male,51,0,169312.13,1,1,0,109078.35,1 +545,15802593,Little,504,France,Female,49,7,0,3,0,1,87822.14,1 +546,15615457,Burns,842,Spain,Female,44,2,112652.08,2,1,0,126644.98,0 +547,15708916,Paterson,587,France,Male,38,0,0,2,1,0,47414.15,0 +548,15720187,Han,479,Germany,Female,30,7,143964.36,2,1,0,41879.99,0 +549,15595440,Kryukova,508,France,Male,49,7,122451.46,2,1,1,75808.1,0 +550,15600651,Ijendu,749,France,Male,24,1,0,3,1,1,47911.03,0 +551,15750141,Reichard,721,Germany,Female,36,3,65253.07,2,1,0,28737.78,0 +552,15657284,Day,674,Germany,Male,47,6,106901.94,1,1,1,2079.2,1 +553,15763063,Price,685,Spain,Female,25,10,128509.63,1,1,0,121562.33,0 +554,15709324,Bruce,417,France,Male,34,7,0,2,1,0,55003.79,0 +555,15711309,Sumrall,574,Germany,Male,33,3,129834.67,1,1,0,193131.42,0 +556,15775318,Lu,590,Spain,Female,51,3,154962.99,3,0,1,191932.27,1 +557,15705515,Lazarev,587,Germany,Male,40,5,138241.9,2,1,0,159418.1,0 +558,15634844,Miller,598,Germany,Male,41,3,91536.93,1,1,0,191468.78,1 +559,15717046,Wentworth-Shields,741,Spain,Male,53,3,0,2,1,1,38913.68,0 +560,15571816,Ritchie,850,Spain,Female,70,5,0,1,1,1,705.18,0 +561,15670080,Mackenzie,584,Germany,Female,29,7,105204.01,1,0,1,138490.03,0 +562,15800440,Power,650,Spain,Male,61,1,152968.73,1,0,1,82970.69,0 +563,15665678,Tan,607,Spain,Male,36,8,158261.68,1,1,1,76744.72,0 +564,15665956,Pendergrass,509,France,Female,46,1,0,1,1,0,71244.59,1 +565,15788126,Evans,689,Spain,Female,38,6,121021.05,1,1,1,12182.15,0 +566,15811773,Hsia,543,France,Male,36,4,0,2,1,1,141210.5,0 +567,15651674,Billson,438,Spain,Female,54,2,0,1,0,0,191763.07,1 +568,15689614,Teng,687,Spain,Female,63,1,137715.66,1,1,1,37938.74,0 +569,15795564,Moretti,737,Germany,Male,31,5,121192.22,2,1,1,74890.58,0 +570,15706647,Jordan,761,France,Male,31,7,0,3,1,1,166698.18,0 +571,15728505,Ts'ao,601,France,Male,44,1,100486.18,2,1,1,62678.53,0 +572,15730076,Osborne,651,France,Male,45,1,0,1,1,0,67740.08,1 +573,15622003,Carslaw,745,France,Male,35,9,92566.53,2,1,0,161519.77,0 +574,15607312,Ch'ang,648,Spain,Female,49,10,0,2,1,1,159835.78,1 +575,15644753,Hung,848,Spain,Male,40,3,110929.96,1,1,1,30876.84,0 +576,15653620,Gordon,546,France,Female,27,8,0,2,1,1,14858.1,0 +577,15761986,Obialo,439,Spain,Female,32,3,138901.61,1,1,0,75685.97,0 +578,15633922,Gray,755,France,Male,30,4,123217.66,2,0,1,144183.1,0 +579,15734674,Lin,593,France,Female,41,6,0,1,1,0,65170.66,0 +580,15658032,Hopkins,701,France,Male,39,2,0,2,1,1,82526.92,0 +581,15692671,Dobson,701,Spain,Male,36,8,0,2,1,0,169161.46,0 +582,15737741,McKay,607,Spain,Female,33,2,108431.87,2,0,1,109291.39,1 +583,15576352,Revell,586,Spain,Female,57,3,0,2,0,1,6057.81,0 +584,15753719,Rickards,547,Germany,Female,30,9,72392.41,1,1,0,77077.14,0 +585,15803689,Begum,647,Germany,Female,51,1,119741.77,2,0,0,54954.51,1 +586,15718057,Onyinyechukwuka,760,France,Female,51,2,100946.71,1,0,0,179614.8,1 +587,15722010,Zuyev,621,Spain,Male,53,9,170491.84,1,1,0,35588.07,1 +588,15680998,Nwankwo,725,France,Male,44,5,0,1,1,1,117356.14,0 +589,15614782,Hao,526,France,Male,36,1,0,1,1,0,160696.72,0 +590,15591047,Ma,519,Spain,Female,47,6,157296.02,2,0,0,147278.43,1 +591,15788291,Okwuadigbo,713,Germany,Female,38,7,144606.22,1,1,1,56594.36,1 +592,15604044,Mitchell,700,France,Male,38,8,134811.3,1,1,0,1299.75,0 +593,15679587,Chan,666,France,Female,34,9,115897.12,1,1,1,25095.03,0 +594,15775153,Buchi,630,Spain,Male,32,4,82034,1,0,0,146326.45,0 +595,15603925,Greco,779,Spain,Female,26,4,174318.13,2,0,1,38296.21,0 +596,15680970,Lombardi,611,Germany,Female,41,2,114206.84,1,1,0,164061.6,0 +597,15697183,Uchenna,685,Spain,Male,43,9,0,2,1,0,107811.28,0 +598,15567446,Coffman,646,Germany,Male,39,9,111574.41,1,1,1,30838.51,0 +599,15637476,Alexandrova,683,Germany,Female,57,5,162448.69,1,0,0,9221.78,1 +600,15714939,Fallaci,484,Germany,Female,34,4,148249.54,1,0,1,33738.27,0 +601,15683503,Hudson,601,France,Female,43,8,0,3,0,1,110916.15,1 +602,15645569,Mai,762,Spain,Female,26,7,123709.46,2,1,1,169654.57,0 +603,15782569,Stout,687,France,Female,72,9,0,1,0,1,69829.4,0 +604,15592387,Burke,566,France,Male,30,5,0,1,1,0,54926.51,1 +605,15609286,Chadwick,702,France,Male,37,10,150525.8,1,1,1,94728.49,0 +606,15814035,Lawrence,601,France,Male,29,9,0,1,1,1,80393.27,0 +607,15661249,Bellucci,699,France,Male,53,4,0,2,0,1,111307.98,0 +608,15629117,Harper,584,France,Male,28,10,0,2,1,0,19834.32,0 +609,15607170,Boyle,699,France,Male,35,5,0,2,1,1,78397.24,0 +610,15586585,Duncan,698,Germany,Female,51,2,111018.98,1,1,0,86410.28,0 +611,15686611,Moss,495,France,Male,30,10,129755.99,1,0,0,172749.65,0 +612,15603203,Avdeyeva,650,France,Female,27,6,0,2,1,0,1002.39,0 +613,15619857,Crawford,605,France,Female,64,2,129555.7,1,1,1,13601.79,0 +614,15805062,Lynton,667,Spain,Male,38,1,87202.38,1,1,1,77866.91,0 +615,15660271,Duncan,688,Germany,Male,26,8,146133.39,1,1,1,175296.76,0 +616,15745295,Gether,727,Spain,Female,31,0,0,1,1,0,121751.04,1 +617,15719352,Davidson,754,Spain,Male,39,6,170184.99,2,1,0,89593.26,0 +618,15766575,Larionova,612,Germany,Female,62,8,140745.33,1,1,0,193437.89,1 +619,15594594,Loggia,546,Spain,Male,42,7,139070.51,1,1,1,86945,0 +620,15646161,Steinhoff,673,Spain,Female,37,8,0,2,1,1,183318.79,0 +621,15682585,Guerra,593,France,Male,35,9,114193.24,1,1,0,71154.1,0 +622,15603134,Pai,656,Spain,Female,40,10,167878.5,1,0,1,151887.16,0 +623,15636444,Craig,535,Germany,Female,53,5,141616.55,2,1,1,75888.65,0 +624,15773456,Lazareva,678,Germany,Male,36,3,145747.67,2,0,1,89566.74,0 +625,15745307,Ch'iu,477,Spain,Female,48,2,129120.64,1,0,1,26475.79,0 +626,15604119,Alderete,850,Spain,Male,35,7,110349.82,1,0,0,126355.8,0 +627,15626900,Kung,427,France,Male,29,1,141325.56,1,1,1,93839.3,0 +628,15605447,Palermo,752,France,Male,49,2,78653.84,1,1,0,7698.6,0 +629,15589030,Ts'ai,649,France,Male,47,1,0,2,1,1,145593.85,0 +630,15692463,Rahman,799,Spain,Female,28,3,142253.65,1,1,0,45042.56,0 +631,15712403,McMillan,589,France,Female,61,1,0,1,1,0,61108.56,1 +632,15811762,Pickering,583,Germany,Female,54,6,115988.86,1,1,0,57553.98,1 +633,15718673,Mirams,839,Spain,Female,33,10,75592.43,1,1,0,62674.42,0 +634,15724282,Tsao,540,Germany,Male,44,3,164113.04,2,1,1,12120.79,0 +635,15738181,Douglas,850,France,Male,31,6,67996.23,2,0,0,50129.87,1 +636,15633648,Jideofor,696,Spain,Female,51,5,0,2,1,0,55022.43,0 +637,15603323,Bell,660,Spain,Female,33,1,0,2,0,0,117834.91,0 +638,15583725,Mairinger,682,France,Male,48,1,138778.15,1,0,1,168840.23,0 +639,15588350,McIntyre,744,France,Female,43,10,147832.15,1,0,1,24234.11,0 +640,15798398,Pagnotto,785,France,Female,36,4,135438.4,1,0,0,190627.01,0 +641,15784844,K'ung,752,Spain,Male,48,5,116060.08,1,1,0,156618.38,1 +642,15580684,Feng,706,France,Female,29,5,112564.62,1,1,0,42334.38,0 +643,15809663,Donaldson,583,France,Female,27,1,125406.58,1,1,1,110784.42,0 +644,15640078,Chambers,660,Germany,Female,39,5,135134.99,1,1,0,173683,1 +645,15698786,Marcelo,819,France,Female,39,9,133102.92,1,1,0,27046.46,1 +646,15569807,Ejimofor,673,France,Female,34,8,42157.08,1,1,0,20598.59,1 +647,15730830,Dale,752,France,Female,30,3,0,2,1,1,104991.28,0 +648,15805112,Pokrovsky,578,France,Male,38,7,82259.29,1,1,0,8996.97,0 +649,15633064,Stonebraker,438,France,Female,36,4,0,2,1,0,64420.5,0 +650,15703119,Liang,652,France,Male,38,6,0,2,1,1,145700.22,0 +651,15730447,Anderson,629,France,Female,49,4,0,2,1,1,196335.48,0 +652,15813850,Christian,720,France,Male,52,7,0,1,1,1,14781.12,0 +653,15711889,Mao,668,France,Male,42,3,150461.07,1,1,0,108139.23,0 +654,15664610,Campbell,459,Germany,Male,48,4,133994.52,1,1,1,19287.06,1 +655,15751710,Ginikanwa,729,Spain,Male,31,8,164870.81,2,1,1,9567.39,0 +656,15692926,Toscani,498,Germany,Male,25,8,121702.73,1,1,1,132210.49,0 +657,15813741,Nnachetam,549,Spain,Male,25,6,193858.2,1,0,1,21600.11,0 +658,15698474,Sagese,601,Germany,Female,54,1,131039.97,2,1,1,199661.5,0 +659,15568595,Fleming,544,France,Male,64,9,113829.45,1,1,1,124341.49,0 +660,15603065,Grubb,751,France,Female,30,6,0,2,1,0,15766.1,0 +661,15592937,Napolitani,632,Germany,Female,41,3,81877.38,1,1,1,33642.21,0 +662,15699637,Anenechi,694,Spain,Male,57,8,116326.07,1,1,1,117704.65,0 +663,15667215,Chandler,678,France,Male,31,2,0,2,1,1,58803.28,0 +664,15788659,Howells,695,France,Male,46,4,0,2,1,1,137537.22,0 +665,15763218,Akeroyd,661,France,Female,41,1,0,2,0,1,131300.68,0 +666,15645772,Onwumelu,661,France,Male,33,9,0,2,1,1,84174.81,0 +667,15725511,Wallace,559,France,Female,31,3,127070.73,1,0,1,160941.78,0 +668,15575024,Uwaezuoke,503,France,Male,29,3,0,2,1,1,143954.99,0 +669,15640825,Loyau,695,Spain,Male,46,3,122549.64,1,1,1,56297.85,0 +670,15662397,Small,640,France,Female,42,5,176099.13,1,1,1,8404.73,0 +671,15576368,Bledsoe,624,Germany,Female,48,3,122388.38,2,0,0,30020.09,0 +672,15674991,Kao,667,France,Male,42,9,0,2,0,1,58137.42,0 +673,15721024,Wickens,642,France,Male,26,0,0,1,0,0,47472.68,0 +674,15745621,Wertheim,640,Spain,Female,32,6,118879.35,2,1,1,19131.71,0 +675,15642394,He,529,Spain,Male,35,5,0,2,1,1,187288.5,0 +676,15754605,Jarvis,563,France,Female,39,5,0,2,1,1,17603.81,0 +677,15607040,P'an,593,Spain,Female,38,4,88736.44,2,1,0,67020.03,0 +678,15715142,Repina,739,Germany,Male,45,7,102703.62,1,0,1,147802.94,1 +679,15810978,Pugliesi,788,Spain,Female,70,1,0,2,1,1,41610.62,0 +680,15668886,Blakey,684,Spain,Female,38,3,0,2,1,0,44255.65,0 +681,15780804,Nucci,482,France,Male,55,5,97318.25,1,0,1,78416.14,0 +682,15613880,Higinbotham,591,Spain,Male,58,5,128468.69,1,0,1,137254.55,0 +683,15775238,Achebe,651,Germany,Female,41,4,133432.59,1,0,1,151303.48,0 +684,15786905,Russo,749,Germany,Female,40,8,141782.57,2,0,0,86333.63,0 +685,15747867,Trevisani,583,France,Male,24,9,135125.28,1,0,0,89801.9,0 +686,15600337,Dobie,661,Spain,Male,42,2,178820.91,1,0,0,29358.57,1 +687,15801277,Maccallum,715,France,Female,31,2,112212.14,2,1,1,181600.72,0 +688,15579334,Watkins,769,Germany,Female,45,5,126674.81,1,1,0,124118.71,1 +689,15802741,Mitchel,625,France,Female,51,7,136294.97,1,1,0,38867.46,1 +690,15720649,Ferdinand,641,France,Female,36,5,66392.64,1,1,0,31106.67,0 +691,15589493,Otitodilinna,716,Germany,Male,27,1,122552.34,2,1,0,67611.36,0 +692,15688251,Mamelu,767,France,Male,43,1,76408.85,2,1,0,77837.63,0 +693,15665238,Beneventi,745,Germany,Male,36,8,145071.24,1,0,0,6078.46,0 +694,15740900,Perrodin,589,France,Male,34,6,0,2,1,1,177896.92,0 +695,15681068,Chinagorom,796,France,Female,45,2,109730.22,1,1,1,123882.73,0 +696,15748625,Napolitano,664,France,Male,57,6,0,2,1,1,15304.08,0 +697,15727299,Edgar,445,Spain,Male,62,1,64119.38,1,1,1,76569.64,1 +698,15620204,Walker,543,Germany,Female,57,1,106138.33,2,1,1,120657.32,1 +699,15669516,Steele,746,Spain,Male,36,2,0,2,1,1,16436.56,0 +700,15736534,Elkins,742,Germany,Male,33,0,181656.51,1,1,1,107667.91,0 +701,15803457,Hao,750,France,Female,32,5,0,2,1,0,95611.47,0 +702,15659098,Toscano,669,France,Male,30,7,95128.86,1,0,0,19799.26,0 +703,15603436,Savage,594,Spain,Female,49,2,126615.94,2,0,1,123214.74,0 +704,15566292,Okwuadigbo,574,Spain,Male,36,1,0,2,0,1,71709.12,0 +705,15808621,Mordvinova,659,Germany,Male,36,2,76190.48,2,1,1,149066.14,0 +706,15580148,Welch,750,Germany,Male,40,5,168286.81,3,1,0,20451.99,1 +707,15776231,Kent,626,Germany,Male,35,4,88109.81,1,1,1,32825.5,0 +708,15773809,Campbell,620,France,Male,42,4,0,2,1,0,6232.31,0 +709,15649423,Cooper,580,France,Female,35,8,0,2,0,1,10357.03,0 +710,15734886,Mazzi,686,France,Female,34,3,123971.51,2,1,0,147794.63,0 +711,15722548,Fisher,540,France,Male,48,0,148116.48,1,0,0,116973.48,0 +712,15650288,Summers,634,Germany,Male,35,6,116269.01,1,1,0,129964.94,0 +713,15629448,Brady,632,Spain,Male,38,1,120599.21,1,1,0,92816.86,0 +714,15716164,Nicholls,501,France,Female,41,3,144260.5,1,1,0,172114.67,0 +715,15807609,Yuan,650,Spain,Female,25,3,86605.5,3,1,0,16649.31,1 +716,15578977,Robinson,786,France,Male,34,9,0,2,1,0,144517.19,0 +717,15677369,Golubov,554,Germany,Female,37,4,58629.97,1,0,0,182038.6,0 +718,15804072,Chen,701,Spain,Female,42,5,0,2,0,0,24210.56,0 +719,15696859,Oldham,474,France,Male,45,10,0,2,0,0,172175.9,0 +720,15653780,Kambinachi,621,France,Female,43,5,0,1,1,1,47578.45,0 +721,15721658,Fleming,672,Spain,Female,56,2,209767.31,2,1,1,150694.42,1 +722,15578761,Cunningham,459,Spain,Female,42,6,129634.25,2,1,1,177683.02,1 +723,15736879,Obinna,669,France,Male,23,1,0,2,0,0,66088.83,0 +724,15571973,Chinwemma,776,France,Female,38,2,169824.46,1,1,0,169291.7,0 +725,15626742,Carpenter,694,France,Male,36,3,97530.25,1,1,1,117140.41,0 +726,15672692,Yin,787,France,Female,42,10,145988.65,2,1,1,79510.37,0 +727,15673570,Olsen,580,France,Male,37,9,0,2,0,1,77108.66,0 +728,15767432,Ts'ai,711,France,Female,25,7,0,3,1,1,9679.28,0 +729,15654238,Jen,673,France,Female,40,5,137494.28,1,1,0,81753.92,0 +730,15612525,Preston,499,France,Female,57,1,0,1,0,0,131372.38,1 +731,15812750,Ozioma,591,France,Male,24,6,147360,1,1,1,25310.82,0 +732,15790757,Cody,769,France,Female,25,10,0,2,0,0,187925.75,0 +733,15723873,Ponomarev,657,Spain,Male,31,3,125167.02,1,0,0,98820.39,0 +734,15744607,Martin,738,Germany,Male,43,9,121152.05,2,1,0,64166.7,1 +735,15612966,Milani,545,Germany,Female,60,7,128981.07,1,0,1,176924.21,1 +736,15784209,Tang,497,France,Male,47,6,0,1,1,1,90055.08,0 +737,15794278,Romani,816,Spain,Male,67,6,151858.98,1,1,1,72814.31,0 +738,15766741,McIntyre,525,France,Male,36,2,114628.4,1,0,1,168290.06,0 +739,15661036,Davis,725,France,Male,46,6,0,2,1,0,161767.38,0 +740,15705639,Onyemauchechukwu,692,France,Female,28,8,95059.02,2,1,0,44420.18,0 +741,15637414,Gell,618,France,Female,24,7,128736.39,1,0,1,37147.61,0 +742,15716835,Rossi,546,France,Male,24,8,156325.38,1,1,1,125381.02,0 +743,15696231,Chiwetelu,635,France,Male,29,7,105405.97,1,1,1,149853.89,0 +744,15641675,Kirillova,611,France,Female,49,2,88915.37,3,0,0,161435.02,1 +745,15670755,Shaw,650,France,Male,60,8,0,2,1,1,102925.76,0 +746,15640059,Smith,606,France,Male,40,5,0,2,1,1,70899.27,0 +747,15787619,Hsieh,844,France,Male,18,2,160980.03,1,0,0,145936.28,0 +748,15587535,Onyemauchechukwu,450,Spain,Female,46,5,177619.71,1,1,0,54227.06,0 +749,15813034,Martin,727,Spain,Male,38,2,62276.99,1,1,1,59280.79,0 +750,15698839,Okwudilichukwu,460,Germany,Male,46,4,127559.97,2,1,1,126952.5,0 +751,15790314,Onuoha,649,France,Male,41,0,0,2,0,1,130567.02,0 +752,15634245,Muecke,758,Germany,Female,47,9,95523.16,1,1,0,73294.48,0 +753,15677305,Hsieh,490,France,Female,35,7,107749.03,1,1,1,3937.37,0 +754,15661526,Anderson,815,Germany,Male,37,2,110777.26,2,1,0,2383.59,0 +755,15685997,Azubuike,838,Spain,Female,39,5,166733.92,2,1,0,14279.44,0 +756,15660101,Nnonso,803,France,Male,31,9,157120.86,2,1,0,141300.53,0 +757,15637979,Fuller,664,Germany,Female,36,2,127160.78,2,1,0,78140.75,0 +758,15815364,Ashley,736,Spain,Female,28,2,0,2,1,1,117431.1,0 +759,15647099,Ts'ui,633,France,Female,37,9,156091.97,1,1,0,72008.61,0 +760,15625944,Buccho,664,France,Male,58,5,98668.18,1,1,1,60887.58,0 +761,15583212,Chidozie,600,France,Female,43,5,134022.06,1,1,0,194764.83,0 +762,15582741,Maclean,693,France,Female,35,5,124151.09,1,1,0,88705.14,1 +763,15637876,Burns,663,Germany,Female,36,6,77253.5,1,0,0,35817.97,1 +764,15622750,Chu,742,Germany,Female,21,1,114292.48,1,1,0,31520.4,0 +765,15672056,Kenenna,710,Germany,Male,43,2,140080.32,3,1,1,157908.19,1 +766,15812351,Beluchi,710,Spain,Female,27,2,135277.96,1,1,0,142200.15,0 +767,15810864,Williamson,700,France,Female,82,2,0,2,0,1,182055.36,0 +768,15677921,Bobrov,720,Germany,Male,60,9,115920.62,2,0,0,157552.08,1 +769,15724296,Kerr,684,Spain,Male,41,2,119782.72,2,0,0,120284.67,0 +770,15685329,McKenzie,531,France,Female,63,1,114715.71,1,0,1,24506.95,1 +771,15584091,Pitts,742,Germany,Female,36,2,129748.54,2,0,0,47271.61,1 +772,15640442,Standish,717,France,Male,31,4,129722.57,1,0,0,41176.6,0 +773,15639314,Cartwright,589,France,Male,32,2,0,2,0,1,9468.64,0 +774,15685320,Johnstone,767,France,Male,36,3,139180.2,1,0,0,123880.19,0 +775,15789158,Nikitina,636,Germany,Male,49,6,113599.74,2,1,0,158887.09,1 +776,15752137,McElroy,648,France,Male,33,7,134944,1,1,1,117036.38,0 +777,15712551,Shen,622,Germany,Female,58,7,116922.25,1,1,0,120415.61,1 +778,15628936,Archer,692,Spain,Male,28,9,118945.09,1,0,0,16064.25,1 +779,15797227,Otutodilinna,754,France,Male,28,8,0,2,1,1,52615.62,0 +780,15769974,Shih,679,Spain,Female,35,8,119182.73,1,0,0,121210.09,0 +781,15737051,Denisov,639,France,Male,27,8,0,2,1,0,192247.35,0 +782,15585595,Owens,774,France,Female,28,1,71264.02,2,0,1,68759.57,0 +783,15654060,P'eng,517,France,Male,41,2,0,2,0,1,75937.47,0 +784,15745196,Verco,571,France,Female,35,8,0,2,0,0,84569.13,0 +785,15571221,Bergamaschi,747,Germany,Male,58,7,116313.57,1,1,1,190696.35,1 +786,15660155,Lorenzo,792,Spain,Male,36,5,92140.15,1,0,1,67468.67,0 +787,15605284,Outtrim,688,France,Male,26,1,0,2,1,1,104435.94,0 +788,15694366,Hou,714,Germany,Male,42,2,177640.09,1,0,1,47166.55,0 +789,15600739,Galkin,562,Spain,Female,35,0,0,2,1,0,119899.52,0 +790,15653253,Pagnotto,704,Spain,Male,48,8,167997.6,1,1,1,173498.45,0 +791,15763431,Echezonachukwu,698,France,Male,36,2,82275.35,2,1,1,93249.26,0 +792,15643696,Young,611,France,Male,49,3,0,2,1,1,142917.54,0 +793,15707473,Summers,850,Germany,Female,48,6,111962.99,1,1,0,111755.8,0 +794,15769504,Munro,743,Germany,Female,34,1,131736.88,1,1,1,108543.21,0 +795,15776807,Brennan,654,France,Male,29,1,0,1,1,0,180345.44,0 +796,15686870,Ball,761,Germany,Male,36,8,108239.11,2,0,0,99444.02,0 +797,15668747,Virgo,702,France,Female,46,9,98444.19,1,0,1,109563.28,0 +798,15766908,Trevisani,488,Germany,Male,32,3,114540.38,1,1,0,92568.07,0 +799,15570134,Padovano,683,France,Female,35,6,187530.66,2,1,1,37976.36,0 +800,15567367,Tao,601,Germany,Female,42,9,133636.16,1,0,1,103315.74,0 +801,15747542,Perez,605,France,Male,52,7,0,2,1,1,173952.5,0 +802,15762238,Fraser,671,Germany,Female,44,0,84745.03,2,0,1,34673.98,0 +803,15681554,Alley,614,Germany,Female,31,7,120599.38,2,1,1,46163.44,0 +804,15712825,Howells,511,Spain,Female,29,9,0,2,0,1,140676.98,0 +805,15640280,Cameron,850,France,Male,39,4,127771.35,2,0,1,151738.54,0 +806,15756026,Hooper,790,Spain,Female,46,9,0,1,0,0,14679.81,1 +807,15613319,Rice,793,France,Female,33,0,0,1,0,0,175544.02,0 +808,15798906,Cox,628,France,Male,69,5,0,2,1,1,181964.6,0 +809,15708917,Martin,598,Germany,Male,53,10,167772.96,1,1,1,136886.86,0 +810,15778463,Ikenna,657,France,Female,37,6,95845.6,1,1,0,122218.23,0 +811,15699430,Davide,618,France,Female,35,10,0,2,1,0,180439.75,0 +812,15649992,Alexander,681,Spain,Male,65,7,134714.7,2,0,1,190419.81,0 +813,15578980,Piazza,516,Spain,Female,33,3,0,2,1,1,58685.59,0 +814,15775306,Ni,421,Germany,Male,28,8,122384.22,3,1,1,89017.38,1 +815,15641655,Black,700,France,Female,26,2,0,2,0,0,50051.42,0 +816,15619708,Harker,745,France,Male,25,5,157993.15,2,1,0,146041.45,0 +817,15734565,Hughes,696,France,Male,29,8,0,2,1,0,191166.09,0 +818,15806438,Chiabuotu,580,Germany,Female,42,2,123331.36,1,0,0,103516.08,1 +819,15591969,Kuo,497,Spain,Male,27,9,75263.16,1,1,1,164825.04,0 +820,15747807,Gallagher,720,France,Female,43,6,137824.03,2,1,0,172557.77,0 +821,15596939,Calabresi,659,Germany,Male,36,4,132578.92,2,1,0,84320.94,0 +822,15716155,Shaw,841,France,Female,36,5,156021.31,1,0,0,122662.98,0 +823,15765311,Zhirov,642,Spain,Male,34,8,0,1,1,0,72085.1,0 +824,15757811,Lloyd,732,Spain,Female,69,9,137453.43,1,0,1,110932.24,1 +825,15603830,Palmer,600,Spain,Male,36,4,0,2,1,0,143635.36,0 +826,15660602,Ch'eng,464,Germany,Male,33,8,164284.72,2,1,1,3710.34,0 +827,15660535,Avent,680,France,Female,47,5,0,2,1,1,179843.33,0 +828,15666633,Huang,758,Spain,Male,56,1,0,2,1,1,10643.38,0 +829,15596914,Shaw,630,Germany,Female,31,2,112373.49,2,1,1,131167.98,0 +830,15639788,Yuan,577,France,Female,39,10,0,2,1,0,10553.31,0 +831,15695846,Hawkins,684,France,Female,34,6,0,2,1,1,130928.22,0 +832,15726234,Trentini,708,Spain,Female,41,5,0,1,0,1,157003.99,0 +833,15797964,Cameron,732,Germany,Female,29,1,154333.82,1,1,1,138527.56,0 +834,15625881,Koehler,634,Germany,Male,37,3,111432.77,2,1,1,167032.49,0 +835,15780628,Wu,633,France,Female,30,6,0,2,0,0,41642.29,0 +836,15575883,Manna,559,France,Male,34,2,137390.11,2,1,0,9677,0 +837,15585036,Okoli,694,Spain,Female,37,3,0,2,1,1,147012.22,0 +838,15589488,Ch'eng,686,Germany,Female,56,5,111642.08,1,1,1,80553.87,0 +839,15585888,Nwokezuike,553,Spain,Female,48,3,0,1,0,1,30730.95,1 +840,15727915,Artemiev,507,France,Male,36,4,83543.37,1,0,0,140134.43,0 +841,15707567,Esposito,732,Germany,Male,50,6,145338.76,1,0,0,91936.1,1 +842,15737792,Abbie,818,France,Female,31,1,186796.37,1,0,0,178252.63,0 +843,15599433,Fanucci,660,Germany,Male,35,8,58641.43,1,0,1,198674.08,0 +844,15672012,Jen,773,Spain,Female,41,5,0,1,1,0,28266.9,1 +845,15806983,Moss,640,France,Male,44,3,137148.68,1,1,0,92381.01,0 +846,15592222,Lo,505,France,Male,49,7,80001.23,1,0,0,135180.11,0 +847,15608968,Averyanov,714,Germany,Male,21,6,86402.52,2,0,0,27330.59,0 +848,15586959,Unaipon,468,France,Female,42,5,0,2,1,0,125305.34,0 +849,15646558,Clamp,611,Spain,Male,51,1,122874.74,1,1,1,149648.45,0 +850,15725811,Lim,705,France,Male,25,0,97544.29,1,0,1,59887.15,0 +851,15572265,Wu,646,Germany,Male,46,1,170826.55,2,1,0,45041.32,0 +852,15794048,Wan,667,Germany,Female,48,1,97133.92,2,0,0,113316.77,1 +853,15677610,Chambers,511,Germany,Female,41,8,153895.65,1,1,1,39087.42,0 +854,15745012,Pettit,653,France,Female,43,6,0,2,1,1,7330.59,0 +855,15601589,Baresi,675,France,Female,57,8,0,2,0,1,95463.29,0 +856,15686436,Newbery,523,Spain,Male,32,4,0,2,1,0,167848.02,0 +857,15693864,Iheanacho,567,Germany,Female,49,5,134956.02,1,1,0,93953.84,1 +858,15760550,Duncan,741,Spain,Male,39,7,143637.58,2,0,1,174227.66,0 +859,15686137,Barry,456,Spain,Male,32,9,147506.25,1,1,1,135399.21,0 +860,15809087,Landry,598,France,Male,64,1,0,2,1,0,195635.3,1 +861,15807663,McGregor,667,France,Male,43,8,190227.46,1,1,0,97508.04,1 +862,15809100,Nucci,548,France,Female,32,2,172448.77,1,1,0,188083.77,1 +863,15794916,Pirogov,725,France,Male,41,7,113980.21,1,1,1,116704.25,0 +864,15614215,Oguejiofor,717,France,Male,53,6,0,2,0,1,97614.87,0 +865,15805449,Ugochukwu,594,France,Male,38,4,0,2,0,0,186884.04,0 +866,15686983,Rohu,678,Germany,Female,25,10,76968.12,2,0,1,131501.72,0 +867,15808017,Cary,545,France,Male,38,1,88293.13,2,1,1,24302.95,0 +868,15756804,O'Loghlen,636,France,Female,48,1,170833.46,1,1,0,110510.28,1 +869,15646810,Quinn,603,Germany,Male,44,6,108122.39,2,1,0,108488.33,1 +870,15710424,Page,435,France,Male,36,4,0,1,1,1,197015.2,0 +871,15799422,Evans,535,France,Female,40,8,0,1,1,1,27689.77,0 +872,15692750,McGregor,629,Germany,Female,45,7,129818.39,3,1,0,9217.55,1 +873,15794549,Andrews,722,France,Female,35,2,163943.89,2,1,1,15068.18,0 +874,15803764,Stanley,561,France,Male,28,7,0,2,1,0,7797.01,0 +875,15674840,Chiazagomekpere,645,France,Female,38,5,101430.3,2,0,1,4400.32,0 +876,15653762,Chidiebele,501,France,Female,39,9,117301.66,1,0,0,182025.95,0 +877,15581229,Gregory,502,Germany,Female,32,1,173340.83,1,0,1,122763.95,0 +878,15800228,Bednall,652,Spain,Female,42,4,0,2,1,1,38152.01,0 +879,15656333,Jen,574,France,Female,33,3,134348.57,1,1,0,63163.99,0 +880,15697497,She,518,France,Female,45,9,105525.65,2,1,1,73418.29,0 +881,15585362,Simmons,749,France,Female,60,6,0,1,1,0,17978.68,1 +882,15571928,Fraser,679,France,Female,43,4,0,3,1,0,115136.51,1 +883,15785519,May,565,France,Male,36,6,106192.1,1,1,0,149575.59,0 +884,15743007,Seabrook,643,France,Female,45,4,45144.43,1,1,0,60917.24,1 +885,15777211,Herrera,515,France,Male,65,7,92113.61,1,1,1,142548.33,0 +886,15721935,Kincaid,521,France,Male,25,7,0,2,1,1,157878.67,0 +887,15591711,Sleeman,739,Spain,Male,38,0,128366.44,1,1,0,12796.43,0 +888,15625021,Hung,585,France,Male,42,2,0,2,1,1,18657.77,0 +889,15702968,Artemieva,733,Germany,Male,74,3,106545.53,1,1,1,134589.58,0 +890,15600462,Barwell,542,France,Female,43,8,145618.37,1,0,1,10350.74,0 +891,15768104,Wright,788,Spain,Male,37,8,141541.25,1,0,0,66013.27,0 +892,15780140,Bellucci,435,Germany,Male,32,2,57017.06,2,1,1,5907.11,0 +893,15585255,Moore,577,France,Male,42,9,0,1,1,0,74077.91,0 +894,15772781,Ball,703,France,Female,51,3,0,3,1,1,77294.56,1 +895,15669987,Sung,728,Germany,Female,35,8,125884.95,2,1,0,54359.02,1 +896,15697000,Mello,728,Germany,Male,32,5,61825.5,1,1,1,156124.93,0 +897,15733119,Mistry,718,France,Male,35,8,0,2,1,0,94820.85,0 +898,15782390,T'ien,621,France,Female,40,6,0,1,1,0,155155.25,0 +899,15654700,Fallaci,523,France,Female,40,2,102967.41,1,1,0,128702.1,1 +900,15632210,Hill,657,Germany,Male,25,2,171770.55,1,1,0,22745.5,0 +901,15642041,Burns,727,Germany,Male,40,1,93051.64,2,1,0,71865.31,1 +902,15709737,Hunter,643,France,Male,36,7,161064.64,2,0,1,84294.82,0 +903,15792388,Li,645,France,Female,48,7,90612.34,1,1,1,149139.13,0 +904,15786014,Ku,568,France,Male,28,5,145105.64,2,1,0,185489.11,0 +905,15794580,Ch'en,599,France,Male,58,4,0,1,0,0,176407.15,1 +906,15675964,Chukwukadibia,672,France,Female,45,9,0,1,1,1,92027.69,1 +907,15814275,Zikoranachidimma,685,France,Male,33,6,174912.72,1,1,1,43932.54,0 +908,15724848,Oluchukwu,516,France,Female,46,1,104947.72,1,1,0,115789.25,1 +909,15754713,Rivera,685,Spain,Male,31,10,135213.71,1,1,1,125777.28,0 +910,15693814,Niu,806,Spain,Male,25,7,0,2,1,0,18461.9,0 +911,15599660,Bennett,604,France,Male,36,6,116229.85,2,1,1,79633.38,0 +912,15746490,Wollstonecraft,648,Spain,Female,53,6,111201.41,1,1,1,121542.29,0 +913,15566091,Thomsen,545,Spain,Female,32,4,0,1,1,0,94739.2,0 +914,15655961,Palermo,756,Germany,Male,27,1,131899,1,1,0,93302.29,0 +915,15710404,Chinwendu,569,France,Male,35,10,124525.52,1,1,1,193793.78,0 +916,15775625,McKenzie,596,France,Male,47,6,0,1,1,0,74835.65,0 +917,15792328,James,475,France,Male,39,6,0,1,1,1,56999.9,1 +918,15719856,Lamb,646,France,Female,45,3,47134.75,1,1,1,57236.44,0 +919,15593773,Olejuru,784,Spain,Male,35,3,0,2,0,0,81483.64,0 +920,15733114,Hay,552,Spain,Male,45,9,0,2,1,0,26752.56,0 +921,15797748,Lu,729,France,Male,44,5,0,2,0,1,9200.54,0 +922,15743411,Chiawuotu,609,Spain,Male,61,1,0,1,1,0,22447.85,1 +923,15753337,Yeates,555,France,Male,51,5,0,3,1,0,189122.89,1 +924,15601026,Gallagher,572,Germany,Female,19,1,138657.08,1,1,1,16161.82,0 +925,15658485,Heath,785,France,Female,34,9,70302.48,1,1,1,68600.36,0 +926,15636731,Ts'ai,714,Germany,Female,36,1,101609.01,2,1,1,447.73,0 +927,15628303,Thurgood,738,Spain,Male,35,3,0,1,1,1,15650.73,0 +928,15633461,Pai,639,Germany,Male,38,5,130170.82,1,1,1,149599.62,0 +929,15677135,Lorenzo,520,Germany,Male,61,8,133802.29,2,1,1,90304.01,0 +930,15590876,Knupp,764,France,Female,24,7,106234.02,1,0,0,115676.38,0 +931,15790782,Baryshnikov,661,Spain,Male,39,6,132628.98,1,0,0,38812.67,0 +932,15700476,Azubuike,564,Germany,Male,41,9,103522.75,2,1,1,34338.21,0 +933,15634141,Shephard,708,Germany,Female,42,8,192390.52,2,1,0,823.36,0 +934,15737795,Scott,512,Spain,Male,36,1,0,1,0,1,135482.26,1 +935,15790299,Williamson,592,Spain,Male,37,9,0,3,1,1,10656.89,0 +936,15675316,Avdeeva,619,France,Female,38,3,0,2,0,1,116467.35,0 +937,15613630,Tang,775,France,Male,52,8,109922.61,1,1,1,96823.32,1 +938,15662100,Hsu,850,Germany,Female,44,5,128605.32,1,0,1,171096.2,0 +939,15668032,Buchanan,577,France,Female,37,4,0,1,1,1,79881.39,0 +940,15599289,Yeh,724,France,Female,37,10,68598.56,1,1,0,157862.82,0 +941,15754084,Palazzi,710,Spain,Male,35,1,106518.52,1,1,1,127951.81,0 +942,15676521,Y?an,696,France,Female,31,8,0,2,0,0,191074.11,0 +943,15804586,Lin,376,France,Female,46,6,0,1,1,0,157333.69,1 +944,15781465,Schofield,675,Germany,Female,29,8,121326.42,1,1,0,133457.52,0 +945,15729362,Lombardi,745,France,Male,36,8,67226.37,1,1,0,130789.6,0 +946,15709295,Wall,697,Spain,Female,25,5,82931.85,2,1,1,128373.88,0 +947,15745324,Milani,599,Spain,Female,39,4,0,1,1,0,194273.2,1 +948,15741336,Ejimofor,715,France,Female,38,5,118590.41,1,1,1,5684.17,1 +949,15783659,Blackburn,659,France,Male,67,4,145981.87,1,1,1,131043.2,0 +950,15620981,Wickham,684,France,Female,48,3,73309.38,1,0,0,21228.34,1 +951,15630328,Bird,635,France,Female,48,8,130796.33,2,1,1,43250.3,0 +952,15785899,Ch'en,789,Germany,Male,33,8,151607.56,1,1,0,4389.4,0 +953,15606149,Wood,571,Germany,Female,66,9,111577.01,1,0,1,189271.9,0 +954,15671139,Brizendine,694,Spain,Male,39,0,107042.74,1,1,1,102284.2,0 +955,15660429,Ch'in,665,Spain,Female,42,2,156371.61,2,0,1,156774.94,1 +956,15571002,Yusupov,706,France,Female,44,4,129605.99,1,0,0,69865.49,0 +957,15631681,Jibunoh,807,Spain,Female,43,0,0,2,0,1,85523.24,0 +958,15731522,Ts'ui,771,Spain,Female,67,8,0,2,1,1,51219.8,0 +959,15619529,Ndukaku,531,Spain,Male,27,8,132576.25,1,0,0,7222.92,0 +960,15628034,Wilder,629,France,Female,37,6,129101.3,1,1,1,23971.33,0 +961,15686164,Maclean,850,Germany,Female,31,1,108822.4,1,1,1,132173.31,0 +962,15582797,Ch'iu,685,Spain,Male,35,4,137948.51,1,1,0,113639.64,0 +963,15753831,Cox,642,Spain,Male,32,7,100433.8,1,1,1,39768.59,0 +964,15731815,Nepean,529,Spain,Male,63,4,96134.11,3,1,0,108732.96,1 +965,15580956,McNess,683,Germany,Female,43,4,115888.04,1,1,1,117349.19,1 +966,15602084,Coles,663,France,Female,42,5,124626.07,1,1,1,78004.5,0 +967,15589805,Benson,563,France,Female,34,6,139810.34,1,1,1,152417.79,0 +968,15720893,Gilbert,637,Spain,Female,34,9,0,2,0,0,26057.08,0 +969,15641009,Wilhelm,544,France,Male,37,3,84496.71,1,0,0,79972.09,0 +970,15605926,Sinclair,649,Germany,Male,70,9,116854.71,2,0,1,107125.79,0 +971,15805955,L?,638,France,Female,48,10,138333.03,1,1,1,47679.14,0 +972,15801488,Buckner,723,France,Male,25,3,0,2,1,1,134509.47,0 +973,15605918,Padovesi,635,Germany,Male,43,5,78992.75,2,0,0,153265.31,0 +974,15779711,Gray,750,Spain,Female,38,7,97257.41,2,0,1,179883.04,0 +975,15705620,Lu,730,France,Male,34,5,122453.37,2,1,0,138882.98,0 +976,15685357,Wright,750,Spain,Female,36,8,112940.07,1,0,1,9855.81,0 +977,15570060,Palerma,586,France,Female,43,8,132558.26,1,1,0,67046.83,1 +978,15582616,Y?an,520,France,Female,38,4,0,2,1,0,56388.63,0 +979,15799515,Wei,652,France,Female,48,8,133297.24,1,1,0,77764.37,0 +980,15642937,Padovesi,550,France,Female,46,7,0,2,1,0,130590.35,0 +981,15624729,Tsao,594,France,Male,27,0,197041.8,1,0,0,151912.49,0 +982,15566156,Franklin,749,Germany,Female,44,0,71497.79,2,0,0,151083.8,0 +983,15792360,Clark,668,France,Male,32,7,0,2,1,1,777.37,0 +984,15807008,McGregor,614,Germany,Female,35,6,128100.28,1,0,0,69454.24,1 +985,15704770,Pan,773,France,Male,25,1,124532.78,2,0,1,11723.57,0 +986,15756475,Kenniff,551,Germany,Male,31,9,82293.82,2,1,1,91565.25,0 +987,15655339,Spencer,566,France,Male,36,1,142120.91,1,1,0,79616.37,0 +988,15613749,Lees,569,Spain,Male,34,0,151839.26,1,1,0,102299.81,1 +989,15664521,David,659,Spain,Male,31,7,149620.88,2,1,1,104533.51,0 +990,15681206,Hsing,722,France,Female,49,3,168197.66,1,1,0,140765.57,1 +991,15745527,Burke,655,France,Male,37,5,93147,2,1,0,66214.13,0 +992,15806926,Watson,615,France,Female,35,2,97440.02,2,1,1,139816.1,0 +993,15724563,Hawkins,752,Germany,Female,42,3,65046.08,2,0,1,140139.28,0 +994,15782899,Ginn,661,Spain,Female,28,7,95357.49,1,0,0,102297.15,0 +995,15623521,Sozonov,838,Spain,Male,43,9,123105.88,2,1,0,145765.83,0 +996,15810218,Sun,610,Spain,Male,29,9,0,3,0,1,83912.24,0 +997,15645621,Hunter,811,Spain,Male,44,3,0,2,0,1,78439.73,0 +998,15608114,Manfrin,587,Spain,Male,62,7,121286.27,1,0,1,6776.92,0 +999,15659557,Artamonova,811,Germany,Female,28,4,167738.82,2,1,1,9903.42,0 +1000,15787772,Hansen,759,France,Female,38,1,104091.29,1,0,0,91561.91,0 +1001,15691111,Pai,648,Germany,Female,42,8,121980.56,2,1,0,4027.02,0 +1002,15592089,Larsen,788,France,Female,43,10,0,2,1,1,116111.51,0 +1003,15633897,Owen,725,Germany,Male,39,1,50880.98,2,1,1,184023.54,0 +1004,15701301,Murphy,646,France,Female,42,3,175159.9,2,0,0,67124.48,1 +1005,15723685,Ekechukwu,601,Germany,Female,26,7,105514.69,2,1,0,50070.59,0 +1006,15701602,Ayers,521,Germany,Male,52,5,116497.31,3,0,0,53793.1,1 +1007,15739189,Johnson,561,Spain,Female,33,6,0,2,1,0,45261.47,0 +1008,15573086,Millar,564,France,Male,42,7,99824.45,1,1,1,36721.4,0 +1009,15569050,Farrell,444,France,Male,45,6,0,1,1,0,130009.85,1 +1010,15750765,Sanders,650,Spain,Male,71,0,0,1,1,1,175380.77,0 +1011,15799811,Herrera,724,France,Male,40,10,0,1,1,0,127847.25,1 +1012,15698442,Eberechukwu,719,Spain,Male,35,3,122964.88,1,1,1,138231.7,0 +1013,15655274,Bardin,548,France,Female,29,4,0,2,0,1,48673.18,0 +1014,15603594,Nwankwo,635,Spain,Male,24,4,0,2,1,1,70668.77,0 +1015,15585961,Talbot,496,Spain,Female,43,3,0,2,0,1,199505.53,0 +1016,15686936,McGregor,676,France,Female,37,5,89634.69,1,1,1,169583.18,1 +1017,15770424,Onyeorulu,541,Germany,Male,40,7,95710.11,2,1,0,49063.42,0 +1018,15587451,Goold,778,Germany,Male,41,7,139706.31,1,1,0,63337.19,0 +1019,15602010,Zikoranaudodimma,850,Germany,Female,45,5,103909.86,1,1,0,60083.11,1 +1020,15600583,Garner,633,France,Male,31,1,0,1,1,0,48606.71,0 +1021,15654673,Onyinyechukwuka,625,France,Male,49,6,173434.9,1,1,0,165580.93,1 +1022,15717164,Genovese,485,Spain,Male,32,6,102238.01,2,1,1,194010.12,0 +1023,15765014,Mai,547,France,Female,48,1,179380.74,2,0,1,69263.1,0 +1024,15682639,Marshall,642,France,Male,32,3,0,2,1,1,88698.83,0 +1025,15729279,Naylor,718,France,Female,25,4,108691.95,1,1,0,63030.97,0 +1026,15759805,Pinto,582,France,Female,32,4,0,2,1,0,59668.81,0 +1027,15767864,Fulton,628,France,Male,33,6,0,2,0,0,184230.23,0 +1028,15769948,Palerma,737,Germany,Male,35,0,133377.8,1,0,1,64050.19,0 +1029,15686345,McCaffrey,828,Spain,Male,34,9,0,2,1,1,81853.98,0 +1030,15688071,Collins,609,Spain,Male,53,10,0,1,1,1,154642.91,0 +1031,15681174,Zuev,730,France,Male,39,1,116537.6,1,0,0,145679.6,0 +1032,15667521,Crawford,631,France,Female,22,3,0,2,0,0,30781.77,0 +1033,15750243,Genovese,830,Spain,Male,40,4,0,2,0,1,81622.52,0 +1034,15695475,Maclean,645,France,Male,29,1,130131.08,2,0,1,196474.35,0 +1035,15689176,Fabro,663,France,Male,46,3,0,2,0,1,176276.1,0 +1036,15652955,Price,678,Spain,Male,30,0,0,1,1,0,35113.08,0 +1037,15668958,Chatfield,521,France,Male,30,2,107316.09,1,1,0,64299.82,0 +1038,15631054,Volkova,625,France,Female,24,1,0,2,1,1,180969.55,0 +1039,15581479,Archer,523,France,Male,30,1,83181.29,1,1,1,138176.78,0 +1040,15577478,Ch'iu,714,France,Female,72,3,0,1,1,1,86733.61,0 +1041,15780870,McKay,580,Spain,Male,67,3,153946.14,1,1,1,7418.92,0 +1042,15692317,Craig,722,France,Male,30,5,0,2,1,0,166376.54,0 +1043,15593969,Abramovich,630,Spain,Female,39,7,135483.17,1,1,0,140881.2,1 +1044,15570417,Chien,579,France,Male,35,1,0,2,1,0,4460.2,0 +1045,15779059,Timms,670,France,Female,38,4,119624.54,2,1,1,110472.12,0 +1046,15785980,Williford,588,Spain,Male,34,6,121132.26,2,1,0,86460.28,0 +1047,15644200,Hamilton,807,Spain,Female,42,1,0,1,1,0,16500.66,1 +1048,15793949,Cheng,726,France,Female,48,4,0,1,1,0,114020.06,1 +1049,15645103,Su,812,Germany,Male,25,5,54817.55,1,1,0,131660.31,0 +1050,15705860,McKenzie,631,Germany,Male,40,3,107949.45,1,1,0,52449.62,1 +1051,15623828,Akobundu,682,France,Male,30,4,0,1,0,1,161465.31,0 +1052,15715003,Ko,625,Spain,Female,49,2,80816.45,1,1,1,20018.79,0 +1053,15623471,Marcelo,607,Germany,Male,38,3,98205.77,1,1,0,176318.27,0 +1054,15798348,Chukwuebuka,600,Spain,Female,50,6,94684.27,1,1,1,50488.91,0 +1055,15743016,MacDonald,602,Spain,Female,22,7,141604.76,1,1,0,30379.6,0 +1056,15769499,Lampungmeiua,545,Spain,Female,74,3,0,2,1,1,161326.73,0 +1057,15798521,Tai,675,Spain,Male,33,3,0,2,1,0,45348.08,0 +1058,15706534,Enyinnaya,581,France,Female,47,1,122949.14,1,0,0,180251.68,1 +1059,15706186,McKenzie,640,Germany,Male,33,8,81677.22,2,0,0,34925.56,0 +1060,15812197,Kline,850,France,Male,38,7,80293.98,1,0,0,126555.74,0 +1061,15650933,Ma,490,Spain,Female,48,8,155413.06,1,1,0,187921.3,0 +1062,15692991,Wood,710,Spain,Female,38,4,0,2,1,1,136390.88,0 +1063,15631189,Riggs,613,Germany,Male,38,9,67111.65,1,1,0,78566.64,1 +1064,15762198,Capon,812,France,Male,34,5,103818.43,1,1,1,166038.27,0 +1065,15699598,Smith,723,France,Female,20,4,0,2,1,1,140385.33,0 +1066,15692744,Davison,512,France,Male,36,4,152169.12,2,0,0,38629.3,1 +1067,15688963,Ingram,731,France,Female,52,10,0,1,1,1,24998.75,1 +1068,15599131,Dilke,650,Germany,Male,26,4,214346.96,2,1,0,128815.33,0 +1069,15680303,Gibson,594,France,Male,57,6,0,1,1,0,19376.56,1 +1070,15628674,Iadanza,844,France,Male,40,7,113348.14,1,1,0,31904.31,1 +1071,15648075,Hebert,686,Germany,Female,47,5,170935.94,1,1,0,173179.79,1 +1072,15586970,Pinto,695,Germany,Male,52,8,103023.26,1,1,1,22485.64,0 +1073,15625698,Dumetochukwu,624,Spain,Female,23,6,0,2,0,1,196668.51,0 +1074,15790497,Ross,503,Spain,Male,37,6,0,2,0,0,136506.86,0 +1075,15682618,Jamieson,535,France,Female,31,7,111855.04,2,1,1,36278.89,0 +1076,15762937,Chiganu,743,Germany,Female,32,6,140348.56,2,1,1,163254.39,0 +1077,15750929,Burgess,702,Spain,Male,39,8,0,2,1,0,99654.13,0 +1078,15729832,Cheng,658,France,Male,29,3,145512.84,1,1,0,20207.02,0 +1079,15633650,Woods,677,Germany,Female,41,8,146720.98,2,1,1,4195.84,0 +1080,15748856,Liang,664,France,Male,32,10,107209.73,1,1,1,112340.2,0 +1081,15589195,Bluett,766,Germany,Female,38,7,130933.74,1,0,1,2035.94,0 +1082,15699911,Chapman,461,Spain,Female,35,8,0,1,1,0,132295.95,0 +1083,15663438,Andrejew,688,Spain,Male,36,0,89772.3,1,1,0,177383.68,1 +1084,15692583,Udobata,678,France,Female,32,5,0,2,1,0,90284.47,0 +1085,15591257,Ejimofor,796,France,Male,24,8,0,2,1,0,61349.37,0 +1086,15646513,Spyer,803,France,Male,42,5,0,1,1,0,196466.83,1 +1087,15708063,Walker,712,France,Male,36,2,100749.5,3,0,0,70758.37,1 +1088,15696098,Palermo,498,France,Female,31,10,0,2,1,0,13892.57,0 +1089,15645517,Philip,850,Spain,Male,22,2,0,2,1,1,9684.52,0 +1090,15649744,Fallaci,628,France,Female,51,3,123981.31,2,1,1,40546.15,0 +1091,15604304,Perry,539,Germany,Female,34,4,91622.42,1,1,1,136603.42,0 +1092,15784092,Henderson,732,France,Male,36,7,126195.81,1,1,1,133172.48,0 +1093,15585198,Bergamaschi,715,France,Male,41,4,94267.9,1,0,1,152821.12,1 +1094,15624347,Fokine,651,France,Male,40,4,0,2,1,1,147715.83,0 +1095,15621687,Mackay,813,France,Male,34,0,0,2,1,0,43169.15,0 +1096,15689081,Wu,692,France,Male,29,4,0,1,1,0,76755.99,1 +1097,15813168,Maslova,756,Germany,Female,39,3,100717.85,3,1,1,73406.04,1 +1098,15604295,Wei,543,France,Male,36,6,0,2,1,0,176728.28,0 +1099,15724127,McLean,790,France,Female,26,4,141581.71,2,0,0,98309.27,0 +1100,15673055,Sung,494,Spain,Male,38,7,0,2,1,1,6203.66,0 +1101,15768201,Paterson,850,France,Female,39,2,148586.64,1,1,1,176791.27,0 +1102,15782219,Fanucci,703,Spain,Male,29,9,0,2,1,0,50679.48,0 +1103,15746410,Thompson,432,Spain,Male,38,7,0,2,1,0,150580.88,0 +1104,15780144,Tisdall,512,Germany,Female,32,2,123403.85,2,1,0,80120.19,0 +1105,15590476,Onochie,589,France,Male,28,7,0,2,1,0,151645.96,0 +1106,15624293,Mironova,514,France,Female,46,3,106511.85,1,1,0,55072.32,0 +1107,15618182,Ndubueze,678,France,Female,38,2,0,2,0,0,115068.99,0 +1108,15660316,Stephenson,420,Germany,Female,34,1,135549.9,1,0,0,149471.13,1 +1109,15678886,Golubev,679,Germany,Male,38,7,110555.37,2,1,0,46522.68,0 +1110,15616330,Liao,595,France,Male,31,4,0,2,1,0,189995.86,0 +1111,15592229,Mullan,713,France,Female,52,0,185891.54,1,1,1,46369.57,1 +1112,15798424,Glover,833,Germany,Male,59,1,130854.59,1,1,1,30722.52,1 +1113,15714750,Northey,690,France,Female,42,3,92578.14,2,0,0,70810.6,0 +1114,15648800,Paterson,731,Germany,Female,21,8,132312.06,1,1,0,106663.46,1 +1115,15626147,Maclean,608,France,Female,62,8,144976.5,1,0,0,175836.03,1 +1116,15626608,Howarde,479,Spain,Male,48,5,87070.23,1,0,1,85646.41,0 +1117,15723250,Teng,519,France,Male,42,8,0,2,1,1,101485.72,0 +1118,15592583,Colman,731,France,Female,47,1,115414.19,3,0,0,191734.67,1 +1119,15759381,Johnson,617,Spain,Male,61,7,91070.43,1,1,1,101839.77,0 +1120,15585241,Butcher,756,Spain,Male,29,2,117412.19,2,1,0,4888.91,0 +1121,15589358,Stanley,848,Germany,Male,31,4,90018.45,2,1,0,193132.98,0 +1122,15672704,Jackson,809,France,Female,24,4,0,2,1,0,193518.76,0 +1123,15789955,Hu,698,Germany,Male,56,1,112414.81,2,0,0,93982.02,1 +1124,15596800,Hill,779,Germany,Male,33,1,158456.76,1,1,1,197000.92,1 +1125,15627305,Pan,606,Spain,Male,35,7,0,1,1,0,106837.06,1 +1126,15645316,Han,612,Germany,Female,58,1,149641.53,1,1,1,115161.28,0 +1127,15593973,Wilkie,663,Spain,Female,33,8,122528.18,1,1,0,196260.3,0 +1128,15647301,Bray,549,Germany,Female,45,3,143734.01,2,1,1,96404.38,0 +1129,15750258,Ann,675,France,Female,32,2,155663.31,1,1,0,97658.66,0 +1130,15685309,Souter,669,France,Female,35,7,0,1,1,1,49108.23,1 +1131,15628205,Greco,571,Germany,Female,34,1,101736.66,1,0,1,195651.66,0 +1132,15733974,Mao,500,Spain,Male,37,9,125822.21,1,1,0,111698,0 +1133,15762110,Anderson,628,France,Male,37,0,0,2,1,1,171707.93,0 +1134,15706899,Ma,559,France,Male,34,4,0,2,1,1,66721.98,0 +1135,15732660,Black,769,France,Female,27,2,0,1,1,1,57876.05,0 +1136,15656121,Medvedeva,733,Germany,Male,31,6,157791.07,2,0,0,177994.81,0 +1137,15614220,Benson,750,France,Male,22,5,0,2,0,1,105125.65,0 +1138,15645269,Duncan,583,France,Female,42,4,0,2,1,0,17439.66,0 +1139,15698510,Onwudiwe,468,Germany,Male,42,9,181627.14,2,1,0,172668.39,0 +1140,15569247,Mitchell,727,Spain,Female,57,1,109679.72,1,0,1,753.37,0 +1141,15566251,Ferrari,618,France,Female,37,5,96652.86,1,1,0,98686.4,1 +1142,15716134,Russo,617,France,Male,40,5,190008.32,2,1,1,107047.92,0 +1143,15763625,Hazon,793,Spain,Male,41,9,0,2,1,0,152153.74,0 +1144,15605965,Henderson,630,France,Male,43,9,0,2,1,1,34338.04,0 +1145,15694821,Hardy,765,Germany,Male,43,4,148962.76,1,0,1,173878.87,1 +1146,15601688,Piccio,546,France,Male,28,8,0,1,1,0,159254.29,0 +1147,15575581,Dickson,614,Germany,Female,30,3,131344.52,2,1,0,54776.64,0 +1148,15671209,Holden,593,Germany,Female,29,5,101713.84,3,1,0,134594.99,0 +1149,15616529,Hsieh,613,Spain,Male,34,3,0,1,1,1,41724.72,0 +1150,15773906,Doherty,655,France,Male,38,4,0,2,0,0,110527.71,0 +1151,15722993,Page,700,France,Female,27,6,137963.07,1,0,0,8996.79,0 +1152,15752463,Samuel,826,Spain,Female,29,4,129938.07,1,0,1,190200.53,0 +1153,15589754,Malloy,652,Germany,Male,45,2,151421.44,1,0,1,115333.43,0 +1154,15669899,Fitts,755,Germany,Female,45,7,135643,1,0,0,143619.52,1 +1155,15766887,Iadanza,538,Spain,Male,39,2,122773.5,2,1,1,58467.08,0 +1156,15768006,Wu,729,France,Male,34,3,152303.8,1,1,0,12128.69,0 +1157,15741295,Yefimova,615,France,Male,49,3,0,2,1,1,49872.33,0 +1158,15811327,Pan,700,Spain,Male,54,1,79415.67,1,0,1,139735.54,0 +1159,15690007,Ts'ui,434,Germany,Female,58,9,125801.03,2,1,0,60891.8,1 +1160,15690664,Liang,729,Spain,Male,37,10,0,2,1,0,100862.54,0 +1161,15719348,Tsao,513,France,Male,35,8,0,1,1,0,76640.29,1 +1162,15781802,Abramov,755,France,Male,41,6,104817.41,1,1,0,126013.58,1 +1163,15752731,Millar,615,France,Female,30,9,0,1,1,0,87347.82,0 +1164,15600997,Demuth,747,Germany,Female,32,5,67495.04,2,0,1,77370.37,0 +1165,15750776,Genovese,850,France,Female,36,0,164850.54,1,1,1,62722.44,0 +1166,15723907,Lawless,712,Germany,Female,49,5,154776.42,2,0,0,196257.68,0 +1167,15633419,Brooks,622,Germany,Female,28,1,143124.63,2,1,0,81723.8,0 +1168,15702430,Ignatyeva,548,France,Female,35,10,0,1,1,1,31299.71,0 +1169,15710456,Balmain,607,France,Female,27,2,0,2,1,0,63495.86,0 +1170,15650351,Millar,653,France,Female,38,8,102133.38,1,1,1,166520.96,0 +1171,15590820,Ecuyer,699,Spain,Male,26,6,79932.41,1,0,0,150242.44,0 +1172,15640454,Parkhill,693,Germany,Male,40,0,120711.73,1,0,0,27345.18,1 +1173,15697789,Li Fonti,647,Germany,Female,43,3,122717.53,2,1,1,87000.39,0 +1174,15808182,Beneventi,478,Spain,Female,36,3,92363.3,2,1,0,44912.7,0 +1175,15588670,Despeissis,705,Spain,Female,40,5,203715.15,1,1,0,179978.68,1 +1176,15721292,Atkins,719,Spain,Male,39,5,0,2,1,0,145759.7,0 +1177,15604217,Williams,726,France,Male,34,9,0,2,0,0,14121.61,0 +1178,15651369,Wright,626,France,Male,21,1,0,2,1,0,66232.23,0 +1179,15782454,Hancock,552,France,Male,49,4,0,1,1,1,190296.76,1 +1180,15814032,Hsieh,807,Germany,Female,31,1,93460.47,2,0,0,172782.69,0 +1181,15570326,Wilkins,621,France,Male,34,6,0,2,1,1,99128.13,0 +1182,15624428,Longo,651,Germany,Female,24,7,40224.7,1,1,1,178341.33,0 +1183,15755638,Mancini,673,France,Female,43,5,168069.73,1,1,1,146992.24,1 +1184,15600992,Madukaego,652,France,Male,36,1,0,2,1,1,151314.98,0 +1185,15755649,Winter-Irving,584,Germany,Male,47,7,130538.77,1,1,0,92915.84,0 +1186,15795228,Stewart,756,France,Male,37,3,132623.6,1,1,1,58974,0 +1187,15589257,Grant,670,France,Female,35,3,103465.02,2,1,1,174627.06,0 +1188,15719302,Brennan,765,France,Female,50,9,126547.8,1,1,1,79579.94,1 +1189,15639882,She,528,France,Male,30,2,128262.72,2,1,0,50771.16,0 +1190,15791279,Murray,701,France,Male,40,5,169742.64,1,1,1,153537.55,1 +1191,15636935,Rischbieth,797,France,Female,29,1,0,2,1,1,132975.39,0 +1192,15686909,Lung,639,Germany,Male,27,3,150795.81,1,0,1,85208.93,0 +1193,15589572,Otutodilichukwu,785,Spain,Female,61,4,129855.72,2,1,0,170214.82,1 +1194,15779947,Thomas,363,Spain,Female,28,6,146098.43,3,1,0,100615.14,1 +1195,15573769,Fiorentini,764,France,Female,24,7,0,2,1,0,186105.99,0 +1196,15578866,Hughes,676,France,Female,43,2,0,1,1,1,55119.53,0 +1197,15739131,Whitworth,718,Germany,Male,28,4,65643.3,1,1,0,28760.99,0 +1198,15813444,McIntosh,590,Spain,Female,34,6,0,2,1,0,171021.44,0 +1199,15678058,Ayers,584,France,Male,38,9,104584.16,1,1,0,176678.72,0 +1200,15769169,Trentino,645,France,Male,41,7,0,1,0,1,28667.56,0 +1201,15804602,Boyd,772,Germany,Male,30,6,99785.28,2,0,0,197238.03,0 +1202,15651052,McMasters,399,Germany,Male,46,2,127655.22,1,1,0,139994.68,1 +1203,15724334,Alekseyeva,529,France,Male,22,5,0,1,1,0,151169.83,0 +1204,15569451,Miller,463,France,Male,35,2,101257.16,1,1,1,118113.64,0 +1205,15650098,Baranova,630,France,Female,40,7,0,2,1,1,34453.17,0 +1206,15724307,Mitchell,780,France,Male,76,10,121313.88,1,0,1,64872.33,0 +1207,15599268,Yobachi,584,Spain,Male,32,5,0,2,1,0,10956.82,0 +1208,15594864,Huang,752,Germany,Male,30,4,81523.38,1,1,1,36885.85,0 +1209,15616451,Genovese,697,France,Female,47,6,128252.66,1,1,1,168053.4,0 +1210,15715667,Sorokina,850,France,Female,32,7,0,2,0,0,155227,0 +1211,15658969,Gray,711,France,Male,51,7,0,3,1,0,38409.79,1 +1212,15738174,Ervin,452,France,Female,32,5,0,2,0,1,75279.39,0 +1213,15813590,Vance,610,Spain,Male,42,6,0,2,1,0,158302.59,1 +1214,15624229,Noble,694,France,Female,22,4,0,2,1,1,11525.72,0 +1215,15674148,Milanesi,579,Spain,Male,33,6,0,1,1,0,94993.04,1 +1216,15625080,Parkin,745,Spain,Female,54,8,0,1,1,0,173912.29,1 +1217,15682528,Cremonesi,572,France,Male,33,5,0,1,0,1,41139.05,0 +1218,15696900,Burns,505,Germany,Male,29,3,145541.56,2,1,1,58019.95,0 +1219,15730038,Docherty,706,France,Female,23,5,0,1,0,0,164128.41,1 +1220,15812272,Ugonna,693,Germany,Male,44,5,124601.58,2,1,1,46998.13,1 +1221,15654654,L?,725,Germany,Female,33,7,115182.84,2,1,1,177279.41,0 +1222,15697625,Bevan,791,France,Male,37,2,163789.49,2,1,0,75832.53,0 +1223,15616280,Hsia,536,France,Male,46,1,65733.41,1,1,0,61094.53,0 +1224,15654229,O'Neill,699,Spain,Male,47,1,0,2,0,1,30117.44,0 +1225,15628298,Johnstone,500,Spain,Female,47,8,128486.11,1,1,0,179227.12,0 +1226,15733387,Pham,707,Spain,Female,53,6,109663.47,1,1,1,52110.45,0 +1227,15775572,Bergamaschi,531,Germany,Female,42,6,88324.31,2,1,0,75248.75,0 +1228,15613844,Murphy,557,France,Female,28,7,146445.24,2,1,0,184317.74,0 +1229,15578515,Osinachi,659,France,Female,38,3,0,2,1,0,158553.1,0 +1230,15607598,Muravyov,575,Spain,Female,31,6,0,2,1,1,95686.42,0 +1231,15742480,Igwebuike,775,Germany,Male,36,2,109949.05,2,0,1,71682.54,0 +1232,15749482,Zack,772,Spain,Male,30,4,78653.05,1,1,0,1790.48,0 +1233,15607537,Crawford,587,Germany,Male,46,9,107850.82,1,1,0,139431,1 +1234,15575410,Chidiegwu,667,Germany,Female,39,4,83765.35,2,1,0,118358.54,0 +1235,15684865,Lucchesi,771,France,Female,66,7,143773.07,1,1,1,130827.88,0 +1236,15600700,Pan,523,Germany,Male,63,6,116227.27,1,1,1,119404.63,0 +1237,15774155,Trevisani,662,Germany,Male,33,0,103471.52,1,1,1,162703,0 +1238,15634267,Yudin,717,France,Male,42,5,0,2,1,0,172665.21,0 +1239,15619626,Wade,746,France,Male,24,3,137492.35,2,0,1,170142.09,0 +1240,15660422,Chung,569,France,Male,28,7,0,2,1,0,73977.23,0 +1241,15617934,Septimus,579,France,Male,36,9,129829.59,1,1,1,60906.12,0 +1242,15760774,Hargraves,519,France,Female,21,1,146329.57,2,1,1,194867.27,0 +1243,15813132,Chukwukadibia,696,Germany,Male,30,4,114027.7,1,1,1,193716.56,0 +1244,15593331,Sidorov,693,Germany,Male,25,6,146580.69,1,0,1,14633.35,0 +1245,15616709,Bunton,587,Germany,Female,38,0,132122.42,2,0,0,31730.32,0 +1246,15658052,Cameron,626,France,Female,44,10,81553.93,1,1,0,20063.63,1 +1247,15721189,Kung,666,France,Female,66,7,0,2,1,1,99792.82,0 +1248,15711288,Hay,512,France,Male,24,6,0,2,1,0,37654.31,0 +1249,15770030,Conti,689,Spain,Female,28,3,0,2,1,1,192449.02,0 +1250,15803681,Sims,803,France,Female,26,4,0,2,1,1,181208.47,0 +1251,15702789,Carter,548,Germany,Male,32,5,175214.71,1,1,1,155165.61,0 +1252,15814930,McGregor,588,Germany,Female,40,10,125534.51,1,1,0,121504.18,1 +1253,15658306,Lo,693,France,Male,68,4,97705.99,1,1,1,61569.07,0 +1254,15699523,Chu,499,Germany,Female,55,4,126817.65,2,1,0,123269.71,0 +1255,15610383,Dumetolisa,628,France,Female,46,1,46870.43,4,1,0,31272.14,1 +1256,15615032,Peng,624,Spain,Male,46,3,0,2,1,1,62825.03,0 +1257,15781989,Drake-Brockman,733,France,Male,42,9,120094.93,1,1,0,184056.45,0 +1258,15647402,Wan,628,France,Female,38,3,0,2,1,1,48924.73,0 +1259,15740494,Cameron,633,France,Female,33,3,0,2,1,0,191111.02,0 +1260,15701265,Tretiakov,559,Germany,Female,36,1,104356.94,2,0,1,54184.06,0 +1261,15743532,Ball,704,Germany,Male,27,5,147004.34,1,1,0,64381.33,1 +1262,15794870,Sal,744,Germany,Male,38,6,73023.17,2,1,0,78770.86,0 +1263,15747591,Chung,665,Spain,Female,40,1,173432.55,1,0,1,116766.79,0 +1264,15726557,Lai,638,France,Female,42,7,165679.92,1,0,0,32916.29,0 +1265,15732199,Gether,837,Spain,Male,31,9,104678.62,1,0,1,50972.6,0 +1266,15662291,Davidson,534,France,Female,55,8,116973.26,3,1,0,122066.5,1 +1267,15749050,Justice,548,France,Female,36,3,0,1,1,0,65996.9,0 +1268,15781586,Osonduagwuike,837,Germany,Male,38,2,126732.85,1,1,1,79577.38,0 +1269,15617078,Ewing,658,France,Female,44,6,148481.09,1,1,0,130529.13,0 +1270,15723339,Chin,554,France,Female,38,4,137654.05,2,1,1,172629.67,0 +1271,15671322,Chiang,724,Germany,Male,30,7,115315.04,1,1,0,15216.53,0 +1272,15793854,Ahmed,723,France,Male,42,2,99095.73,1,1,1,17512.53,0 +1273,15756539,Marshall,585,Germany,Female,39,7,165610.41,2,0,0,131852.01,0 +1274,15612064,Tsou,474,France,Male,33,5,0,2,1,0,181945.52,1 +1275,15625916,Chien,562,Spain,Male,32,6,161628.66,1,1,0,91482.5,0 +1276,15683195,Ubanwa,719,France,Male,32,9,146605.27,1,1,1,77119.45,0 +1277,15690182,Kapustin,635,Germany,Male,37,5,113488.68,1,1,0,95611.74,1 +1278,15721719,Calabresi,743,France,Male,42,7,77002.2,2,1,1,80428.42,0 +1279,15641690,Hsiao,681,Spain,Male,67,7,0,2,0,1,163714.92,0 +1280,15634896,Grant,521,France,Female,39,6,0,2,0,1,27375.15,0 +1281,15671590,H?,741,Spain,Male,25,4,0,2,1,1,73873.65,0 +1282,15779182,Chia,790,Spain,Male,46,8,182364.53,1,0,0,139266.48,1 +1283,15778287,Ugoji,622,France,Male,35,8,0,2,1,1,131772.51,0 +1284,15609510,Gregory,669,France,Male,45,7,149364.58,1,0,1,173454.07,0 +1285,15742229,Mackay,583,France,Male,59,7,127450.14,1,0,1,67552.71,0 +1286,15658532,Nnamutaezinwa,520,Spain,Female,63,5,162278.32,1,1,1,34765.33,0 +1287,15590993,Findlay,579,Spain,Male,37,5,152212.88,2,0,0,120219.14,0 +1288,15565701,Ferri,698,Spain,Female,39,9,161993.89,1,0,0,90212.38,0 +1289,15597239,Ku,548,Spain,Male,39,7,131468.44,1,1,0,164975.82,0 +1290,15688880,Amechi,672,Germany,Male,40,10,102980.44,1,1,0,1285.81,1 +1291,15813917,Kirk,653,Germany,Male,31,9,143321.97,1,1,0,83679.46,0 +1292,15679611,Andrews,734,Spain,Female,37,2,130404.92,1,0,0,34548.74,0 +1293,15636589,Murray,794,France,Female,41,7,0,2,1,1,74275.08,0 +1294,15687752,Griffin,641,France,Male,30,2,87505.47,2,0,1,7278.57,0 +1295,15584363,Longstaff,824,France,Male,30,0,133634.02,1,1,1,162053.92,0 +1296,15737748,McWilliam,534,Spain,Female,33,3,151233.62,1,0,0,199336.63,0 +1297,15803365,Coffee,653,Spain,Male,55,2,70263.83,1,0,1,62347.71,0 +1298,15793247,Hancock,498,France,Male,34,5,0,2,1,1,91711.66,0 +1299,15572360,Clark,683,France,Male,30,10,57657.49,1,0,0,79240.9,0 +1300,15795166,Creswell,618,Germany,Male,42,8,153572.31,2,1,1,76679.6,0 +1301,15724620,Dodds,538,France,Male,37,1,134752.08,1,1,0,162511.55,0 +1302,15800856,Ewen,643,Spain,Male,34,3,83132.09,1,1,1,21360.88,0 +1303,15671097,Carter,428,France,Female,31,2,0,2,1,0,54487.43,0 +1304,15683930,Ch'iu,593,Germany,Female,32,9,134096.53,2,1,0,53931.05,1 +1305,15749004,Tsao,718,France,Female,31,0,118100.59,2,1,0,103165.15,0 +1306,15800434,Burgess,811,Germany,Male,52,10,76915.4,1,0,0,146359.81,1 +1307,15709117,Fanucci,823,Spain,Female,46,3,81576.75,1,1,1,28370.95,1 +1308,15638806,Blackburn,645,Spain,Male,49,2,0,2,0,0,10023.15,0 +1309,15662294,Bennett,710,France,Male,33,10,118327.17,2,1,1,192928.82,0 +1310,15690079,Boniwell,591,Spain,Male,30,8,124857.69,2,0,0,50485.7,0 +1311,15759317,Vasilieva,748,Germany,Female,27,2,90971.85,1,1,1,131662.47,0 +1312,15750497,Longo,850,France,Female,37,7,153147.75,1,1,1,152235.3,0 +1313,15596181,Kwemto,542,France,Male,38,8,65942.26,1,1,1,68093.23,1 +1314,15576602,Lawrence,809,France,Male,38,3,0,2,1,1,80061.31,0 +1315,15644833,Duncan,675,France,Male,54,2,0,1,1,0,149583.67,1 +1316,15734634,Bocharova,607,Spain,Female,27,5,100912.19,1,0,0,7631.27,0 +1317,15808689,Morres,850,France,Female,31,4,0,2,1,1,33082.81,0 +1318,15720702,Shih,789,France,Male,37,3,0,1,1,0,121883.87,1 +1319,15665077,Vogel,598,France,Female,43,5,0,3,1,1,100722.72,1 +1320,15763612,T'an,756,Germany,Male,41,2,124439.49,2,0,1,47093.11,0 +1321,15596493,Wisdom,687,France,Female,47,7,0,2,1,1,177624.01,0 +1322,15704483,Lorenzo,724,France,Male,40,6,0,2,0,0,106149.48,0 +1323,15598846,Shahan,700,France,Female,44,2,58781.76,1,1,0,16874.92,0 +1324,15629244,Bryant,635,Spain,Male,50,7,159453.64,2,0,0,54560.79,1 +1325,15765537,Liang,687,Germany,Male,26,2,142721.52,1,1,1,153605.75,0 +1326,15729975,Chidozie,613,France,Female,46,8,167795.6,1,0,1,44390.38,0 +1327,15682773,Hayward,781,France,Female,38,3,128345.69,2,1,0,63218.85,0 +1328,15688007,Liu,703,Spain,Male,20,3,165260.98,1,1,1,41626.78,0 +1329,15574331,Alexeeva,593,Germany,Female,62,3,118233.81,1,0,1,24765.53,1 +1330,15645572,Calabresi,743,France,Female,40,6,0,1,1,0,28280.8,1 +1331,15742854,Lettiere,640,Spain,Female,46,8,0,2,1,0,89043.19,0 +1332,15575417,Chou,849,Germany,Male,37,7,143452.74,2,1,1,17294.12,0 +1333,15796721,Nnamutaezinwa,778,France,Male,38,3,145018.49,2,1,1,126702.41,0 +1334,15734942,Nnamutaezinwa,539,Germany,Female,38,8,82407.51,1,1,0,13123.41,0 +1335,15664772,Greece,489,Germany,Male,28,1,79460.98,2,1,1,167973.63,0 +1336,15576683,Yin,568,Spain,Female,43,9,0,1,1,0,125870.79,1 +1337,15682563,Larionova,618,Spain,Male,38,5,126473.99,1,1,0,91972.49,0 +1338,15650889,Golubev,710,Germany,Female,30,10,133537.1,2,1,0,155593.74,0 +1339,15612108,Norman,625,France,Male,52,5,164978.01,1,1,1,67788.49,0 +1340,15761132,Capon,682,Spain,Male,46,7,128029.72,1,1,1,62615.35,0 +1341,15645511,Chukwudi,727,Spain,Male,43,2,97403.18,1,1,1,107415.02,1 +1342,15609824,Fedorov,794,France,Female,41,7,176845.41,3,1,0,166526.26,1 +1343,15640268,Avdeeva,652,Spain,Male,71,4,0,1,1,1,120107.1,0 +1344,15645778,Reid,670,Spain,Male,42,3,81589.04,1,1,0,188227.8,0 +1345,15691104,Kennedy,460,Germany,Female,40,6,119507.58,2,1,0,91560.63,1 +1346,15714567,Chan,568,Spain,Female,26,6,0,2,0,0,166495.2,0 +1347,15777826,Wofford,643,France,Male,30,5,94443.77,1,1,1,165614.4,0 +1348,15668445,Mai,521,France,Male,37,2,0,2,1,1,86372.24,0 +1349,15576162,King,615,France,Male,32,7,92199.84,1,1,1,2755.53,0 +1350,15778135,T'ao,575,Spain,Male,43,3,0,1,1,0,83594.51,0 +1351,15613141,Hsu,717,France,Female,41,3,135756.96,1,1,1,103706.41,0 +1352,15635435,White,648,France,Female,54,9,120633.42,1,0,0,5924.38,1 +1353,15596552,Stephens,535,Germany,Male,48,5,134542.73,1,1,1,58203.67,1 +1354,15623644,Frolov,626,Spain,Male,29,7,0,2,1,0,49361.84,0 +1355,15683403,Lombardi,611,Spain,Male,52,7,0,1,0,1,73585.18,1 +1356,15615029,Munro,734,Spain,Male,39,6,0,1,1,1,95135.27,0 +1357,15769005,Hayward,709,France,Male,49,4,154344.49,2,1,1,38794.57,0 +1358,15746326,Fields,591,France,Male,43,3,0,2,0,1,198926.36,0 +1359,15722364,Onwumelu,664,France,Male,43,9,189026.53,2,1,1,56099.86,0 +1360,15704954,Suffolk,431,France,Male,37,0,120764.08,1,1,1,117023.08,0 +1361,15694409,Tsao,647,Germany,Female,22,3,97975.82,2,0,1,62083,0 +1362,15754068,Judd,578,France,Male,32,4,0,2,1,1,141822.8,0 +1363,15683841,Hamilton,555,Germany,Male,41,10,113270.2,2,1,1,185387.14,0 +1364,15789095,T'ang,775,Spain,Male,30,4,0,2,0,1,57461.13,0 +1365,15719958,Degtyarev,850,Germany,Male,39,3,124548.99,2,1,1,120380.12,0 +1366,15689514,Kang,625,France,Male,43,8,201696.07,1,1,0,133020.9,1 +1367,15621353,Hudson,645,Spain,Female,37,7,0,2,1,0,13589.93,0 +1368,15627232,Jibunoh,608,Germany,Male,44,7,114203.47,1,1,1,77830.36,1 +1369,15745843,Kinlaw,689,Spain,Female,31,4,0,2,1,1,136610.02,0 +1370,15722902,Chizuoke,652,Germany,Male,50,8,125437.64,1,1,1,17160.94,1 +1371,15791767,Lucciano,769,France,Female,26,7,0,2,1,0,176843.53,0 +1372,15792722,Omeokachie,611,France,Female,43,8,64897.75,1,1,0,114996.33,0 +1373,15723006,Gorbunova,489,France,Male,38,8,0,2,0,1,196990.79,0 +1374,15771942,Tikhonov,528,Germany,Female,46,9,135555.66,1,1,0,133146.03,1 +1375,15774738,Campa,632,France,Male,44,3,107764.75,1,1,0,185667.72,0 +1376,15574004,Mancini,429,France,Female,27,6,117307.44,2,1,1,24020.49,0 +1377,15587233,Donoghue,457,France,Male,41,8,73700.12,3,1,1,185750.02,1 +1378,15808228,Tuan,768,Spain,Female,44,6,60603.4,1,1,1,178045.97,0 +1379,15682834,Johnstone,715,Spain,Female,35,4,40169.88,2,1,1,199857.47,0 +1380,15571752,Romani,668,Germany,Female,32,10,92041.87,1,1,1,43595.9,0 +1381,15743067,Fuller,625,Germany,Male,26,3,130483.95,1,1,0,122810.53,0 +1382,15714466,Baxter,846,France,Female,41,5,0,3,1,0,3440.47,1 +1383,15617982,Pirozzi,661,Spain,Female,42,3,0,2,1,0,35989.41,0 +1384,15696637,Sung,571,France,Female,23,10,151097.28,1,0,1,17163.75,0 +1385,15690647,Rogers,582,Spain,Female,46,8,67563.31,1,1,0,44506.09,1 +1386,15672756,Mills,716,France,Female,35,8,112808.18,1,0,1,17848.3,0 +1387,15704586,Osonduagwuike,758,France,Female,42,7,0,2,0,1,76209.56,0 +1388,15674526,Byrne,725,France,Male,66,4,86459.8,1,1,1,141476.56,0 +1389,15775295,McIntyre,630,France,Female,40,0,118633.08,1,0,1,60032.46,1 +1390,15684196,Aitken,627,France,Female,55,2,159441.27,1,1,0,100686.11,1 +1391,15727281,Macintyre,653,France,Female,27,9,0,2,1,0,96429.29,0 +1392,15787835,Simpson,775,Germany,Female,38,4,125212.65,2,1,1,15795.88,1 +1393,15730540,Simpson,794,Spain,Male,45,8,88656.37,2,1,0,116547.31,0 +1394,15646276,Metcalfe,831,France,Female,32,2,146033.62,1,1,0,191260.74,0 +1395,15582180,Lees,561,France,Male,29,9,120268.13,1,1,1,173870.39,0 +1396,15697095,Zetticci,705,Spain,Male,46,7,0,2,1,0,117273.35,0 +1397,15748797,Dale,636,Spain,Female,33,0,0,1,1,0,92277.47,1 +1398,15754796,Byrne,487,Germany,Female,46,4,135070.58,2,1,1,44244.49,1 +1399,15628947,Praed,693,France,Female,38,3,0,2,0,0,78133.48,1 +1400,15775546,Laurens,517,Spain,Female,29,5,0,2,1,0,103402.88,0 +1401,15670481,Woods,684,France,Female,27,9,122550.05,2,0,1,137835.82,0 +1402,15619029,Bykov,620,Spain,Female,43,2,0,2,1,0,20670.1,0 +1403,15613282,Vorobyova,757,France,Male,29,8,130306.49,1,1,0,77469.38,0 +1404,15721487,Pirogova,739,France,Female,27,6,0,1,1,1,57572.38,0 +1405,15797276,Sturt,662,Spain,Female,41,4,90350.77,1,1,0,75884.65,1 +1406,15612494,Panicucci,359,France,Female,44,6,128747.69,1,1,0,146955.71,1 +1407,15629617,Cook,572,Spain,Male,23,2,126873.52,1,0,1,67040.12,0 +1408,15600821,Hardy,721,France,Male,69,2,108424.19,1,1,1,178418.35,0 +1409,15579062,Chu,707,France,Male,32,9,0,2,0,0,30807.02,0 +1410,15814268,Franklin,444,France,Female,40,5,84350.07,1,1,0,143835.76,0 +1411,15710164,P'eng,523,France,Female,73,7,0,2,0,0,130883.9,1 +1412,15693904,Chiang,685,Germany,Female,30,4,84958.6,2,0,1,194343.72,0 +1413,15588986,Grant,673,Germany,Female,29,4,99097.36,1,1,1,9796.69,0 +1414,15797733,Udobata,503,Germany,Male,30,10,136622.55,2,0,0,47310.24,0 +1415,15620507,Siciliani,485,Germany,Female,30,5,156771.68,1,1,1,141148.21,0 +1416,15685150,Evans,799,Germany,Male,28,7,167658.33,2,1,1,111138.25,0 +1417,15667651,Young,585,Spain,Female,33,8,0,2,1,0,114182.07,0 +1418,15774166,Mitchell,607,Germany,Female,24,2,109483.54,2,0,1,127560.77,0 +1419,15649280,Lucchese,521,Germany,Female,40,9,134504.78,1,1,0,18082.06,0 +1420,15705657,Hewitt,535,France,Female,44,2,114427.86,1,1,1,136330.26,0 +1421,15753969,K'ung,724,Spain,Male,45,5,83888.54,1,0,1,34121.81,0 +1422,15742378,Swaim,520,Germany,Male,32,5,110029.77,1,1,0,56246.69,0 +1423,15794874,Quinones,696,Spain,Male,41,9,127523.75,1,0,1,191417.42,0 +1424,15589221,Kennedy,657,Germany,Male,30,1,139762.13,2,1,1,23317.88,0 +1425,15596671,Endrizzi,603,Spain,Female,42,8,91611.12,1,0,0,144675.3,1 +1426,15583668,Ludowici,726,France,Female,42,2,109471.79,1,0,1,175161.05,0 +1427,15710206,Larson,591,France,Female,39,4,150500.64,1,1,0,14928.8,0 +1428,15799966,Chigolum,792,Germany,Female,59,9,101609.77,1,0,0,161479.19,1 +1429,15794560,Maclean,550,France,Male,57,5,0,1,1,1,133501.94,0 +1430,15626485,Lu,601,France,Female,26,8,78892.23,1,1,1,23703.52,0 +1431,15703143,Tuan,820,France,Female,29,3,82344.84,1,0,1,115985.38,0 +1432,15809772,Glover,667,France,Male,48,2,0,1,1,0,43229.2,0 +1433,15687959,Landman,573,Spain,Female,44,4,0,1,1,1,94862.93,0 +1434,15585282,Trevisano,755,France,Male,62,1,127706.33,2,0,1,142377.69,0 +1435,15714993,Longo,552,France,Female,41,9,124349.34,1,1,0,135635.25,0 +1436,15596021,K?,598,Spain,Male,44,8,0,2,1,0,148487.9,0 +1437,15646615,Muir,576,Germany,Male,28,1,119336.29,2,0,1,58976.85,0 +1438,15742632,Alexeyeva,670,France,Female,31,9,0,1,0,1,76254.83,0 +1439,15574068,Norman,504,Germany,Male,56,9,104217.3,1,0,0,55857.48,1 +1440,15806967,Simmons,778,France,Female,65,7,0,1,1,1,77867.23,0 +1441,15796334,Chukwualuka,558,Germany,Male,39,10,144757.02,1,1,0,22878.16,1 +1442,15688713,McCall,627,Spain,Male,44,6,0,1,1,1,114469.55,0 +1443,15796179,Moore,683,France,Male,43,8,0,1,1,0,96754.8,0 +1444,15598751,Ingram,556,France,Female,43,6,0,3,0,0,125154.57,1 +1445,15703019,Okeke,583,France,Female,38,10,0,2,0,1,113597.64,0 +1446,15646302,Shao,705,France,Female,24,7,100169.51,1,1,0,121408.55,0 +1447,15680855,Iloabuchi,637,France,Male,33,2,145731.83,1,0,1,109219.43,0 +1448,15697311,Nebechukwu,697,Spain,Male,56,5,110802.03,1,1,1,50230.31,1 +1449,15585367,Diribe,555,Germany,Female,46,4,120392.99,1,1,0,177719.88,1 +1450,15726556,Macgroarty,594,Germany,Female,26,6,135067.52,2,0,0,131211.86,0 +1451,15676242,Artemova,632,Spain,Male,31,3,136556.44,1,1,0,82152.83,1 +1452,15684198,McDonald,551,France,Female,38,10,0,2,1,1,216.27,0 +1453,15774882,Mazzanti,687,France,Female,35,3,99587.43,1,1,1,1713.1,1 +1454,15714227,Kelly,672,France,Female,53,7,0,1,1,1,136910.18,0 +1455,15608653,Davison,521,Spain,Female,34,7,70731.07,1,1,1,20243.97,1 +1456,15784280,Reilly,686,Germany,Male,35,2,109342.82,2,0,1,86043.27,0 +1457,15789546,Ojiofor,639,Spain,Male,28,8,0,2,1,0,126561.07,0 +1458,15590320,Shelton,850,France,Male,66,4,0,2,0,1,64350.8,0 +1459,15678385,Lange,465,France,Male,25,2,78247.31,2,1,1,10472.31,0 +1460,15571778,Trentini,817,France,Female,55,10,117561.49,1,1,0,95941.55,1 +1461,15657085,Gardiner,578,France,Male,23,10,88980.32,1,1,1,125222.36,0 +1462,15640627,Wan,611,Spain,Male,34,4,0,2,1,0,170950.58,0 +1463,15566211,Hsu,616,Germany,Female,41,1,103560.57,1,1,0,236.45,1 +1464,15669293,Hovell,517,France,Male,37,5,113308.84,1,0,1,31517.16,0 +1465,15595067,Zhirov,637,Spain,Female,40,6,0,2,1,1,181610.6,0 +1466,15753566,Espinosa,806,France,Female,32,3,63763.49,1,1,0,156593.09,0 +1467,15650391,Wallace,633,France,Female,29,7,169988.35,1,1,0,4272,0 +1468,15681843,Barbour,624,Germany,Female,35,0,180303.24,2,1,0,163587.9,0 +1469,15814846,Ozerova,691,France,Male,52,3,0,1,1,0,175843.68,1 +1470,15670374,Wright,819,Germany,Female,49,1,120656.86,4,0,0,166164.3,1 +1471,15762332,Ulyanova,568,Germany,Female,31,1,61592.14,2,1,1,61796.64,0 +1472,15700223,Steiner,806,France,Male,48,4,164701.68,1,1,1,21439.49,0 +1473,15729956,Akabueze,726,Spain,Female,26,1,80780.16,1,1,1,19225.85,0 +1474,15594862,Aleksandrova,552,France,Male,36,8,0,2,0,0,132547.02,0 +1475,15598782,Pinto,755,Germany,Female,30,6,154221.37,2,0,1,62688.55,0 +1476,15745080,Griffiths,634,France,Male,26,8,0,1,1,0,21760.96,0 +1477,15703399,McNeil,756,France,Female,26,5,101641.14,2,0,1,154460.68,0 +1478,15732175,Bruno,776,France,Male,37,2,0,1,0,1,8065,0 +1479,15630725,Johnson,649,France,Female,45,5,92786.66,1,1,0,173365.9,1 +1480,15640260,Okorie,595,Germany,Male,32,8,131081.66,2,1,1,69428.79,0 +1481,15716822,Moen,646,France,Male,30,5,98014.74,1,1,1,12757.14,0 +1482,15583748,McGuigan,592,Spain,Male,38,8,0,2,1,0,180426.2,0 +1483,15605968,Fancher,574,France,Male,26,8,97460.1,1,1,1,43093.67,0 +1484,15790683,Matthews,850,France,Male,36,1,104077.19,2,0,1,68594,0 +1485,15607713,Kaeppel,850,Spain,Female,29,1,0,2,1,1,197996.65,0 +1486,15700212,Shih,475,France,Female,46,10,0,2,0,0,122953,1 +1487,15626710,Yudina,642,France,Female,39,4,0,1,1,1,76821.24,0 +1488,15716491,Akabueze,710,Spain,Female,51,4,93656.95,1,0,1,141400.51,1 +1489,15625824,Kornilova,596,Spain,Male,30,6,121345.88,4,1,0,41921.75,1 +1490,15617705,Ozioma,609,France,Female,39,8,141675.23,1,0,1,175664.25,0 +1491,15761976,Su,797,Spain,Female,31,8,0,2,1,0,117916.63,0 +1492,15634891,Jamison,504,Germany,Female,43,7,102365.49,1,1,0,194690.77,1 +1493,15744517,Esposito,735,Spain,Male,50,9,0,1,0,0,166677.35,1 +1494,15686963,Hardiman,680,Spain,Female,30,3,0,1,1,0,160131.58,0 +1495,15808189,Woodard,449,France,Male,52,6,0,2,0,1,123622,0 +1496,15580845,Chienezie,685,Germany,Male,57,7,101868.51,1,0,1,113483.96,0 +1497,15799156,Okwuadigbo,569,Spain,Male,38,8,0,2,0,0,79618.79,0 +1498,15694296,Chineze,631,France,Male,35,9,112392.45,2,1,0,24472.23,0 +1499,15677049,O'Brien,595,Germany,Female,25,7,106570.34,2,0,1,177025.79,0 +1500,15583595,Tao,461,France,Female,28,8,0,1,1,1,103349.74,0 +1501,15590146,Mao,630,France,Male,50,1,81947.76,1,0,1,63606.22,1 +1502,15801548,Buckland,661,France,Female,31,7,144162.3,2,1,1,14490.79,0 +1503,15660833,Flannery,796,Germany,Male,39,5,86350.87,2,0,0,105080.53,0 +1504,15762277,Jamieson,710,France,Male,47,5,158623.14,1,0,0,83499.89,1 +1505,15791302,Swift,741,France,Male,32,8,0,2,1,0,143598.7,0 +1506,15798975,Doherty,606,Germany,Male,48,4,132403.56,1,0,0,36091.91,1 +1507,15599956,Payne,747,France,Male,27,10,0,2,0,0,13007.89,0 +1508,15577274,Genovese,549,Germany,Female,43,3,134985.66,1,1,0,6101.41,0 +1509,15701200,Lucciano,576,France,Male,36,6,0,2,1,1,48314,0 +1510,15638149,Rowley,528,France,Male,37,6,103772.45,1,1,0,197111.99,0 +1511,15786199,Hsing,535,France,Male,33,2,133040.32,1,1,1,110299.78,0 +1512,15701765,Vincent,575,Spain,Female,37,0,0,2,0,0,30114.32,0 +1513,15586974,Pearce,656,France,Male,39,10,0,2,1,1,98894.64,0 +1514,15729040,Lamb,440,France,Male,42,2,0,2,1,0,49826.68,0 +1515,15788676,Riley,539,Spain,Male,38,8,71460.67,2,1,1,10074.05,0 +1516,15602497,Honore,850,Spain,Male,39,6,133214.13,1,0,1,20769.88,0 +1517,15701333,Blackburn,646,France,Female,37,7,96558.66,1,0,0,163427.18,0 +1518,15812071,Endrizzi,744,France,Male,54,6,93806.31,2,0,1,140068.77,0 +1519,15634375,Duncan,710,Spain,Female,36,8,0,2,0,0,83206.19,0 +1520,15738267,Macarthur,544,France,Female,64,3,124043.8,1,1,1,111402.97,1 +1521,15786800,Gould,723,Germany,Male,52,5,131694.97,1,0,1,92873.5,1 +1522,15591130,Medvedev,507,Spain,Female,29,6,0,2,0,1,94780.9,0 +1523,15720662,Sholes,787,France,Female,35,1,106266.8,1,1,1,16607.15,0 +1524,15751531,Shaw,598,Spain,Male,41,8,0,2,1,1,161954.43,0 +1525,15653595,Ts'ai,796,France,Male,51,6,0,2,0,1,194733.28,0 +1526,15568360,Rolon,569,Spain,Female,41,4,139840.36,1,1,1,163524.7,0 +1527,15781210,Reid,711,France,Male,34,8,0,2,0,0,48260.19,0 +1528,15668058,Chinwendu,661,Germany,Male,35,8,124098.54,1,1,0,86678.48,0 +1529,15597131,Fu,415,France,Male,32,5,145807.59,1,1,1,3064.65,0 +1530,15697283,Mackenzie,578,Spain,Male,23,8,0,2,1,0,112124.98,0 +1531,15640953,Bligh,611,France,Female,26,2,107508.93,2,1,1,120801.65,0 +1532,15715031,Davidson,600,France,Female,28,6,0,2,0,1,52193.23,0 +1533,15589660,Lamble,661,Germany,Female,32,1,145980.23,1,0,1,56636.28,0 +1534,15769818,Moore,850,France,Female,37,3,212778.2,1,0,1,69372.88,0 +1535,15782736,Jose,573,Germany,Female,47,4,152522.47,1,0,1,164038.07,1 +1536,15614818,Trevisani,764,Spain,Female,33,9,168964.77,1,0,1,118982.51,0 +1537,15794014,Schofield,838,France,Female,34,8,0,2,1,0,27472.07,0 +1538,15732448,Stewart,821,France,Female,28,8,0,1,1,1,36754.13,0 +1539,15723411,Jamieson,607,Spain,Female,36,4,98266.3,1,1,1,46416.36,0 +1540,15797686,Howard,558,France,Male,38,8,113000.92,1,1,1,152872.39,0 +1541,15605950,Onwuamaeze,530,Germany,Male,23,1,137060.88,2,1,1,165227.23,0 +1542,15812497,D'Albertis,654,Germany,Male,37,5,112146.12,1,1,0,75927.35,0 +1543,15690678,Brooks,530,France,Female,33,4,129307.32,1,1,1,172930.28,0 +1544,15747677,Gordon,656,Spain,Male,69,6,163975.09,1,1,1,36108.5,0 +1545,15618926,Nwachukwu,520,Spain,Male,43,7,0,2,1,1,36202.74,0 +1546,15673908,Chinweike,602,Germany,Female,42,6,158414.85,1,1,1,131886.46,0 +1547,15727944,Simpkinson,701,Germany,Female,48,1,92072.68,1,1,1,133992.36,0 +1548,15807294,Walker,653,Spain,Female,30,2,88243.29,2,1,1,96658.26,0 +1549,15618581,Diribe,668,Spain,Male,25,8,0,2,1,1,135112.09,0 +1550,15584364,Trentini,652,France,Male,48,4,59486.31,1,1,0,163944.18,1 +1551,15599552,Conway,639,Spain,Female,54,2,0,2,1,1,53843.71,0 +1552,15749177,Maslow,730,Spain,Female,52,7,0,2,0,1,122398.84,0 +1553,15718779,Clark,780,France,Male,34,1,0,1,1,1,64804.04,0 +1554,15568106,L?,592,France,Female,38,8,119278.01,2,0,1,19370.73,0 +1555,15779481,Swadling,628,France,Male,34,4,158741.43,2,1,1,126192.54,0 +1556,15709994,Gallo,658,France,Female,40,7,140596.95,1,0,1,135459.02,1 +1557,15772777,Onyemachukwu,850,Spain,Female,29,10,0,2,1,1,94815.04,0 +1558,15706815,Samoylova,515,Germany,Male,37,2,90432.92,1,1,1,188366.04,1 +1559,15618018,Dickson,571,France,Female,35,1,104783.81,2,0,1,178512.52,0 +1560,15671032,He,760,Germany,Male,42,0,77992.97,2,1,1,97906.38,0 +1561,15634281,P'an,720,Germany,Female,43,10,110822.9,1,0,0,72861.94,0 +1562,15766374,Leak,632,Germany,Male,42,4,119624.6,2,1,1,195978.86,0 +1563,15600991,Artemieva,694,Germany,Male,31,6,109052.59,2,1,1,19448.93,1 +1564,15777576,Frost,559,Spain,Female,40,5,139129.44,1,0,1,32635.54,0 +1565,15742613,Warner,773,Germany,Female,42,8,152324.66,2,1,0,171733.22,0 +1566,15649523,Kennedy,581,France,Male,38,1,0,2,1,0,46176.22,0 +1567,15651063,Ifeatu,524,Germany,Female,37,9,127480.58,2,1,0,179634.69,0 +1568,15683124,Evans,713,France,Male,53,6,115029.4,1,0,0,191521.32,1 +1569,15618314,Chu,676,France,Male,40,8,114005.78,1,1,1,67998.45,0 +1570,15670823,Hsueh,651,Germany,Female,42,1,116646.76,1,1,0,44731.8,1 +1571,15607133,Shih,717,Spain,Female,49,1,110864.38,2,1,1,124532.9,1 +1572,15615012,Fan,594,France,Male,23,5,156267.59,1,1,0,160968.44,0 +1573,15725141,Whiddon,716,France,Female,44,3,109528.28,1,1,0,27341.63,1 +1574,15623560,Onyekachukwu,668,France,Female,35,6,102482.76,1,1,1,53994.64,0 +1575,15693018,Ermakova,678,Germany,Male,23,10,115563.71,1,1,1,91633.53,0 +1576,15636756,Marino,545,France,Male,23,2,0,2,1,0,189613.12,0 +1577,15647474,Niu,613,France,Female,40,9,95624.36,2,1,1,60706.33,0 +1578,15576714,Manna,687,Spain,Female,21,8,0,2,1,1,154767.34,0 +1579,15585047,Onyemere,715,France,Male,28,7,160376.61,1,0,0,196853.11,0 +1580,15743976,Archer,618,Germany,Male,41,8,37702.79,1,1,1,195775.48,0 +1581,15793881,Mitchell,721,France,Female,35,6,118273.83,1,0,1,3086.89,0 +1582,15576517,Everingham,445,Germany,Female,34,7,131082.17,2,1,1,70618,0 +1583,15631072,Huie,690,France,Male,38,1,94456,2,0,1,55034.02,0 +1584,15730394,Crowther,709,France,Female,43,8,0,2,0,0,168035.62,1 +1585,15631460,Swift,671,Spain,Female,42,3,0,2,1,1,128449.33,0 +1586,15692002,Skelton,538,France,Male,33,6,93791.38,1,1,1,199249.29,0 +1587,15595282,White,735,France,Female,33,4,0,2,1,0,149474.69,0 +1588,15789548,Giordano,592,France,Female,37,7,0,2,1,1,126726.33,0 +1589,15758035,Bateson,747,France,Male,61,7,155973.13,1,0,1,147554.26,0 +1590,15617518,Hu,675,Germany,Male,36,7,89409.95,1,1,1,149399.7,0 +1591,15651802,Day,632,Spain,Female,39,5,97854.37,2,1,0,93536.38,0 +1592,15631813,Beneventi,621,France,Male,39,6,0,2,1,1,58883.91,0 +1593,15729668,Elizabeth,521,Spain,Male,29,3,60280.62,1,1,0,154271.41,0 +1594,15741728,Atkins,591,Spain,Male,36,7,135216.8,1,1,1,122022.89,0 +1595,15576676,Serrano,706,Germany,Female,28,6,124923.35,2,1,1,50299.14,0 +1596,15711378,Willis,677,France,Male,38,4,0,2,1,0,187800.63,0 +1597,15765520,Stevenson,769,Germany,Male,27,7,188614.07,1,1,0,171344.09,0 +1598,15656726,Ch'ien,771,France,Male,32,5,62321.62,1,1,1,40920.59,0 +1599,15647842,Cunningham,601,Germany,Female,48,8,120782.7,1,1,0,63940.68,1 +1600,15719309,Stephens,670,France,Female,42,1,115961.58,2,0,1,29483.87,0 +1601,15748718,Gordon,517,France,Male,28,2,115062.61,1,1,0,179056.23,0 +1602,15594404,Bevan,834,France,Female,49,8,160602.25,2,1,0,129273.94,0 +1603,15751158,Mashman,571,France,Female,42,4,108825.34,3,1,0,55558.51,1 +1604,15593470,Tu,576,Germany,Female,36,8,166287.85,1,1,1,23305.85,0 +1605,15695129,Milanesi,718,France,Female,31,1,152663.77,1,0,1,17128.64,0 +1606,15640865,Romano,636,Germany,Female,31,9,80844.69,2,1,1,74641.9,0 +1607,15714080,Goliwe,566,Germany,Female,40,2,97001.36,2,1,0,154486.01,0 +1608,15648721,Hsueh,711,France,Male,64,4,0,2,1,1,3185.67,0 +1609,15801466,Gray,574,France,Female,39,2,122524.61,2,1,0,88463.63,0 +1610,15750248,Wright,619,France,Female,35,8,132292.63,1,1,0,65682.93,0 +1611,15758726,Chiemeka,588,France,Female,24,0,0,2,1,1,140586.08,0 +1612,15781553,Chung,760,Germany,Female,49,9,91502.99,1,1,0,117232.9,1 +1613,15649121,Pinto,665,France,Male,52,3,0,1,1,0,116137.01,1 +1614,15674811,Kellway,739,Germany,Male,29,3,59385.98,2,1,1,105533.96,0 +1615,15646037,Sopuluchi,641,France,Male,77,9,0,3,1,1,81514.06,0 +1616,15722578,Spitzer,685,Germany,Female,21,6,97956.5,1,1,1,164966.27,0 +1617,15665695,Potter,594,France,Female,49,4,0,2,1,1,23631.55,0 +1618,15801062,Matthews,557,Spain,Female,40,4,0,2,0,1,105433.53,0 +1619,15662955,Nicholls,697,France,Male,27,8,141223.68,2,1,0,90591.15,0 +1620,15770309,McDonald,656,France,Male,18,10,151762.74,1,0,1,127014.32,0 +1621,15657386,Fiorentini,712,Germany,Male,43,1,141749.74,2,0,1,90905.26,0 +1622,15777797,Kovalyova,689,Spain,Male,38,5,75075.14,1,1,1,8651.92,1 +1623,15783955,Miah,697,France,Female,25,4,165686.11,2,1,0,15467.98,0 +1624,15804516,Builder,589,France,Male,38,2,0,1,1,0,79915.28,0 +1625,15681758,Baddeley,525,Spain,Female,25,10,0,2,1,0,69361.95,0 +1626,15630321,Hu,680,France,Male,44,3,0,2,1,0,86935.08,0 +1627,15588248,Hs?,617,France,Female,28,0,0,2,1,1,7597.83,1 +1628,15591932,Ford,680,France,Male,32,5,92961.61,1,1,0,116957.6,0 +1629,15810347,Todd,662,Spain,Female,30,9,0,2,0,1,157884.83,0 +1630,15595303,Johnston,736,Germany,Male,46,5,130812.91,1,1,1,77981.54,1 +1631,15634950,Obiajulu,657,Germany,Male,57,8,107174.58,1,1,1,126369.55,1 +1632,15685372,Azubuike,350,Spain,Male,54,1,152677.48,1,1,1,191973.49,1 +1633,15745827,Padovesi,617,France,Male,30,3,132005.77,1,1,0,142940.39,0 +1634,15755868,Farmer,562,France,Male,35,7,0,1,0,0,48869.67,0 +1635,15735222,Ignatieff,705,Spain,Female,23,5,0,2,1,1,73131.73,0 +1636,15604804,Lu,516,France,Female,33,7,127305.5,1,1,1,120037.36,0 +1637,15718944,Artemiev,573,France,Female,37,6,0,2,1,0,193995.37,0 +1638,15678626,Okonkwo,538,Spain,Female,31,0,0,2,0,0,179453.66,0 +1639,15571550,Dore,699,France,Male,39,9,0,1,1,0,80963.92,0 +1640,15723053,T'ang,504,Germany,Male,32,8,170291.22,2,0,1,15658.99,0 +1641,15661528,Ashbolt,583,Spain,Male,47,5,102562.23,1,1,0,92708.1,0 +1642,15754177,Bazarova,712,Spain,Male,53,2,111061.01,2,0,0,26542.17,0 +1643,15683544,Buccho,626,Spain,Male,62,3,0,1,1,1,65010.74,0 +1644,15708048,Burn,631,France,Female,34,4,124379.14,1,1,0,106892.91,0 +1645,15701109,Andreyev,663,France,Female,37,7,0,1,1,1,185210.63,0 +1646,15600110,Endrizzi,506,Germany,Female,41,3,57745.76,1,1,0,4035.46,0 +1647,15651533,Brown,570,Germany,Female,50,5,129293.74,1,1,0,177805.44,1 +1648,15777904,Nock,703,France,Female,45,7,0,2,1,1,68831.72,0 +1649,15655574,Okeke,698,Germany,Female,40,8,150777.1,1,1,0,114732.62,0 +1650,15569423,Cunningham,731,Spain,Male,41,4,0,2,1,0,22299.27,0 +1651,15718106,Kelley,625,France,Male,34,6,0,2,0,0,197283.2,0 +1652,15585067,Wilson,634,Spain,Male,31,9,108632.48,1,1,1,179485.96,1 +1653,15675501,Woods,616,France,Male,59,5,153861.1,1,1,1,17699.48,0 +1654,15633233,McFarland,500,France,Male,56,1,100374.58,1,1,0,118490.8,1 +1655,15667134,Cisneros,446,France,Male,32,8,0,2,0,0,133292.94,0 +1656,15659105,Borchgrevink,669,France,Female,47,9,61196.54,1,1,0,58170.24,0 +1657,15575409,Rozhkova,581,Germany,Male,31,6,116891.72,1,1,0,107137.3,0 +1658,15752342,Bradley,704,Germany,Female,54,6,133656.91,3,1,0,145071.33,1 +1659,15654851,Obialo,748,France,Male,44,2,92911.52,1,0,1,85495.24,0 +1660,15741429,Hudson,680,Spain,Female,31,9,119825.75,2,1,1,101139.3,0 +1661,15682356,Veltri,655,France,Female,37,7,111852.84,2,1,0,10511.13,0 +1662,15806447,Mazzanti,690,Germany,Male,32,0,106683.52,2,1,1,137916.49,0 +1663,15800229,Thorpe,695,Germany,Male,40,7,139022.24,1,0,1,193383.13,0 +1664,15663441,Golibe,700,Germany,Female,40,4,148571.07,1,1,0,189826.96,1 +1665,15791991,Udinesi,773,France,Male,52,4,0,1,0,1,144113.42,0 +1666,15775082,Stewart,749,France,Male,42,1,129776.72,2,0,1,143538.51,0 +1667,15579706,Curtis,611,France,Female,46,5,0,1,1,0,77677.14,1 +1668,15718247,Hayden,606,Spain,Female,46,8,0,2,1,1,183717.94,0 +1669,15755722,H?,554,France,Male,24,10,0,1,0,0,92180.62,0 +1670,15582259,Campbell,567,France,Female,37,7,0,2,1,1,28690.9,0 +1671,15716994,Green,559,Spain,Male,24,3,114739.92,1,1,0,85891.02,1 +1672,15586880,P'eng,594,Germany,Male,41,2,122545.65,2,1,1,42050.24,0 +1673,15713854,Cremonesi,513,France,Female,37,6,0,2,1,0,110142.34,0 +1674,15780835,Liang,652,Germany,Female,26,1,131908.35,1,1,1,179269.79,0 +1675,15675896,Gough,680,Germany,Female,42,7,105722.69,1,1,1,90558.24,1 +1676,15658459,Bates,784,Spain,Male,33,10,0,2,1,0,162022.47,0 +1677,15658057,Padovesi,812,Spain,Female,44,8,0,3,1,0,66926.83,1 +1678,15801767,Yin,784,Spain,Female,40,8,0,2,1,0,108891.3,0 +1679,15569178,Kharlamov,570,France,Female,18,4,82767.42,1,1,0,71811.9,0 +1680,15731478,Nicholls,712,France,Female,42,1,87842.98,1,0,0,92223.59,0 +1681,15811236,Burns,705,Spain,Male,39,6,133261.13,1,1,1,78065.9,0 +1682,15746749,Fleming,681,Spain,Female,32,3,0,2,1,1,59679.9,0 +1683,15662758,Watson,620,France,Male,41,0,97925.11,1,1,0,85000.32,0 +1684,15709387,Obiajulu,711,France,Male,52,5,0,1,1,1,159808.95,0 +1685,15572093,Han,613,France,Female,24,7,140453.91,1,1,0,129001.3,0 +1686,15713826,Ferguson,613,Germany,Female,20,0,117356.19,1,0,0,113557.7,1 +1687,15570205,Tao,682,Spain,Male,36,5,0,2,1,1,147758.51,0 +1688,15589348,Le Grand,850,Spain,Male,37,4,137204.77,1,1,1,28865.59,0 +1689,15804610,Valdez,601,France,Female,41,1,0,2,0,1,160607.06,0 +1690,15700854,Cunningham,595,Spain,Male,35,8,0,1,1,0,100015.79,1 +1691,15758836,Godfrey,675,Spain,Male,36,3,54098.18,2,0,1,54478.52,0 +1692,15772933,Mai,591,Spain,Male,31,8,0,1,1,1,141677.33,0 +1693,15809006,Walker,602,France,Male,23,7,113758.48,2,0,0,84077.6,0 +1694,15689612,Pirozzi,554,Spain,Female,34,8,0,1,0,1,106981.03,0 +1695,15744614,Feng,541,France,Male,37,9,118636.92,1,1,1,73551.44,0 +1696,15704250,Akabueze,506,France,Male,34,7,0,2,0,0,115842.1,0 +1697,15700255,Robson,814,Germany,Male,44,8,95488.82,2,0,0,107013.59,0 +1698,15669410,Yevdokimova,683,France,Male,30,8,110829.52,2,0,0,24938.84,0 +1699,15807595,Ijendu,485,Germany,Male,51,7,144244.59,2,1,0,51113.14,0 +1700,15664523,Colombo,696,Germany,Female,31,8,122021.92,2,1,0,33828.64,0 +1701,15642833,Akubundu,608,France,Female,30,8,0,2,1,0,128875.86,0 +1702,15605279,Francis,792,France,Male,50,9,0,4,1,1,194700.81,1 +1703,15713644,Marshall,686,Spain,Male,22,5,0,2,1,0,158974.45,0 +1704,15750466,Rhodes,790,Germany,Male,42,1,85839.62,1,1,0,198182.73,0 +1705,15739054,Y?,654,France,Female,29,4,96974.97,1,0,1,141404.07,0 +1706,15612771,Bell,452,France,Male,35,4,148172.44,1,1,1,4175.68,0 +1707,15788483,Kerr,719,Spain,Male,38,0,0,1,1,0,126876.47,0 +1708,15732832,Jideofor,707,France,Female,40,5,0,2,1,0,41052.82,0 +1709,15772892,Robertson,699,France,Female,49,2,0,1,0,0,105760.01,0 +1710,15713843,Kao,850,Spain,Male,30,2,0,2,0,1,27937.12,0 +1711,15567993,Palmer,828,Spain,Male,28,8,134766.85,1,1,0,79355.87,0 +1712,15617603,Mackay,850,Germany,Male,30,5,123210.56,2,1,1,102180.27,0 +1713,15744983,Burgmann,712,Spain,Male,47,1,139887.01,1,1,1,95719.73,0 +1714,15630419,Davis,634,France,Male,44,9,149961.11,1,1,0,57121.51,0 +1715,15738828,Milano,730,Germany,Male,45,6,152880.97,1,0,0,162478.11,0 +1716,15778025,Dellucci,685,Germany,Male,43,9,108589.47,2,0,1,194808.51,0 +1717,15799479,Coles,809,Spain,Male,33,9,0,1,1,1,124045.65,0 +1718,15684269,Gray,707,Spain,Female,35,3,56674.48,1,1,0,17987.4,1 +1719,15762745,Macvitie,648,Spain,Male,32,8,0,1,1,0,133653.38,0 +1720,15746970,Townsend,760,Spain,Female,57,1,0,2,1,1,25101.17,0 +1721,15725024,Pope,805,Germany,Female,33,3,105663.56,2,0,1,33330.89,0 +1722,15592116,Jensen,585,France,Female,39,7,0,2,1,0,2401.26,0 +1723,15624391,Thomson,595,Spain,Female,30,5,100683.54,1,1,1,178361.04,0 +1724,15567422,Chiazagomekpele,630,France,Male,42,6,0,2,1,0,162697.93,0 +1725,15612627,Ozuluonye,627,Germany,Male,29,5,139541.58,2,1,0,80607.33,0 +1726,15574879,Wright,631,Germany,Female,37,2,121801.72,2,0,1,23146.62,0 +1727,15745107,Lung,776,Germany,Male,38,5,112281.7,1,0,1,89893.6,0 +1728,15734491,Lombardo,676,Spain,Female,36,4,0,2,1,1,3173.31,0 +1729,15675320,Leonard,758,Spain,Female,40,5,93499.82,2,0,0,123218.81,0 +1730,15643824,Johnston,637,France,Male,33,0,132255.99,2,0,1,74588.41,0 +1731,15643438,P'eng,850,France,Male,20,7,0,2,1,0,31288.77,0 +1732,15721730,Amechi,601,Spain,Female,44,4,0,2,1,0,58561.31,0 +1733,15680727,Fang,735,France,Male,49,5,121973.28,1,1,0,148804.36,0 +1734,15752508,Docherty,614,Germany,Male,32,7,99462.8,2,1,1,51117.06,0 +1735,15808846,Horton,672,Germany,Female,21,3,165878.76,2,1,1,164537.17,0 +1736,15727251,Vincent,642,France,Male,30,8,117494.27,1,0,0,61977.82,0 +1737,15663489,Onio,633,Germany,Female,29,0,138577.34,1,1,0,193362.99,0 +1738,15683677,Schiavone,769,Spain,Male,39,9,0,1,1,1,47722.79,0 +1739,15596414,Chandler,796,Spain,Male,41,8,107525.07,1,1,0,18510.41,0 +1740,15730639,Fiorentino,715,France,Male,23,7,139224.92,2,1,0,65057.71,0 +1741,15672132,Butusov,695,France,Female,42,7,121453.63,1,0,0,46374.64,0 +1742,15742638,Wang,747,France,Female,25,4,0,2,0,1,42039.67,0 +1743,15578603,Alexeieva,584,Germany,Female,54,1,77354.37,1,0,0,138192.98,1 +1744,15726088,Vinogradova,476,France,Male,40,6,0,1,1,1,22735.45,0 +1745,15682533,Hughes,850,France,Female,39,7,79259.99,1,0,1,186910.74,0 +1746,15772995,Ts'ao,529,France,Male,30,2,116295.29,1,1,0,75285.47,0 +1747,15765694,Bage,584,Spain,Female,59,1,0,1,0,1,130260.11,1 +1748,15659486,Yudina,586,Germany,Male,34,9,74309.81,1,1,0,15034.93,0 +1749,15568963,Naquin,674,Germany,Male,34,2,152797.9,1,1,0,175709.4,1 +1750,15703820,Endrizzi,552,France,Male,42,9,133701.07,2,1,0,101069.71,1 +1751,15569410,Tang,601,Germany,Female,33,7,114430.18,2,1,1,153012.13,0 +1752,15632256,Schroeder,541,France,Male,29,7,127504.57,1,0,0,86173.92,0 +1753,15724466,Swearingen,744,Germany,Female,41,2,84113.41,1,1,0,197548.63,0 +1754,15777639,McGregor,595,Spain,Female,23,10,101126.66,2,0,0,37042.8,0 +1755,15802501,Onyeorulu,724,Germany,Male,33,5,103564.83,2,1,0,121085.72,0 +1756,15778410,Clarke,533,Spain,Female,52,7,0,1,0,1,194113.99,1 +1757,15670702,Smith,618,France,Male,37,2,168178.21,2,0,1,101273.23,0 +1758,15704763,Kozlova,523,Germany,Female,39,1,143903.11,1,1,1,118711.75,1 +1759,15645544,Nekrasov,642,Germany,Female,30,5,129753.69,1,1,0,582.53,0 +1760,15757646,Olague,584,France,Male,35,9,0,2,1,0,192381.21,0 +1761,15701121,Holt,521,France,Male,38,5,110641.18,1,0,1,136507.69,1 +1762,15796313,Olsen,662,France,Female,36,4,166909.2,2,1,0,138871.12,1 +1763,15815660,Mazzi,758,France,Female,34,1,154139.45,1,1,1,60728.89,0 +1764,15602844,Niu,717,France,Male,38,7,97459.06,1,0,0,189175.71,0 +1765,15636238,Graham,611,France,Male,40,1,0,2,1,1,102547.56,0 +1766,15770101,Millar,766,Germany,Male,43,6,112088.04,2,1,1,36706.56,0 +1767,15645543,Bell,636,France,Female,34,3,0,2,1,1,44756.25,0 +1768,15596397,Kelly,814,France,Female,48,7,0,2,1,1,132870.15,0 +1769,15770525,T'an,760,Spain,Male,28,1,141038.57,2,0,0,16287.38,0 +1770,15684267,Davila,607,Germany,Male,39,2,84468.67,2,1,1,121945.42,0 +1771,15689980,Willis,725,Spain,Female,36,4,118520.26,1,0,0,131173.9,1 +1772,15633260,Dumetochukwu,600,France,Male,37,1,142663.46,1,0,1,88669.89,0 +1773,15756471,Giles,656,Germany,Male,27,4,118627.16,2,1,1,160835.3,0 +1774,15721303,O'Meara,640,Spain,Male,34,1,137523.02,1,0,0,24761.36,0 +1775,15802256,Yao,439,France,Male,28,7,110976.23,2,1,0,138526.96,0 +1776,15725664,Wallace,549,France,Female,38,8,107283.4,1,0,0,157442.75,0 +1777,15674851,T'ien,622,France,Male,38,5,0,2,0,0,105295.77,0 +1778,15701946,Ndubueze,715,France,Male,34,4,124314.45,1,0,0,97782.92,0 +1779,15748947,Chukwuraenye,657,France,Female,41,5,95858.37,1,1,1,68255.88,0 +1780,15673342,K'ung,703,France,Male,36,2,0,2,1,0,108790.95,0 +1781,15601008,Stevenson,802,France,Male,33,8,0,2,1,0,143706.18,0 +1782,15771636,Marshall,793,Spain,Female,36,0,0,1,0,0,148993.47,0 +1783,15642002,Hayward,554,France,Female,35,6,117707.18,2,0,0,95277.15,1 +1784,15693381,Tipton,533,Spain,Male,38,1,135289.33,2,0,1,152956.33,0 +1785,15607691,Gibson,658,France,Male,36,8,174060.46,1,1,1,94925.62,0 +1786,15589380,Fraser,713,Germany,Male,40,3,114446.84,2,1,1,87308.18,0 +1787,15603846,Fang,711,Spain,Male,37,2,0,2,1,0,83978.86,1 +1788,15753549,Dubinina,669,France,Male,25,1,157848.53,1,0,0,37543.93,1 +1789,15725355,Morey,439,France,Female,43,8,0,1,0,1,104889.3,0 +1790,15773017,Todd,763,Spain,Female,37,6,0,2,1,1,149705.25,0 +1791,15625641,Forbes,697,Germany,Female,74,3,108071.36,2,1,1,16445.79,0 +1792,15776467,De Salis,702,Spain,Female,35,8,14262.8,2,1,0,54689.16,0 +1793,15746451,Barry,686,Spain,Male,41,7,102749.72,1,0,1,194913.86,0 +1794,15777922,Afamefuna,629,Spain,Male,36,1,161757.87,2,1,1,146371.72,0 +1795,15606841,Ibbott,823,France,Male,38,1,0,2,1,0,156603.7,0 +1796,15757648,Marshall,683,Germany,Female,35,5,95698.79,1,0,1,182566.76,0 +1797,15677173,Law,555,France,Male,37,9,124969.13,1,1,0,60194.05,0 +1798,15764170,Pinto,647,Germany,Male,44,4,93960.35,1,1,0,36579.53,1 +1799,15610446,Chinedum,714,France,Female,51,4,88308.87,3,0,0,5862.53,1 +1800,15612776,McKay,850,Spain,Female,39,10,0,2,1,1,143030.09,0 +1801,15794122,Otutodilinna,713,France,Female,59,3,0,2,1,1,62700.08,0 +1802,15774931,She,452,France,Male,30,7,112935.87,1,1,1,99017.34,0 +1803,15779247,Pai,683,Spain,Female,24,8,98567.1,1,1,0,187987.01,0 +1804,15707078,Kruglov,577,France,Female,26,1,180530.51,1,0,0,123454.62,0 +1805,15605263,Chin,552,France,Male,33,5,140931.57,1,0,1,10921.5,0 +1806,15607381,King,769,Germany,Female,31,7,148913.72,2,1,0,53817.23,0 +1807,15683471,Hansen,691,France,Male,38,7,0,2,0,0,81617.4,0 +1808,15605037,Ting,818,France,Female,49,2,0,1,0,1,192298.84,1 +1809,15576085,Stone,739,France,Male,41,5,0,2,0,0,143882.25,0 +1810,15770435,McLean,639,France,Female,50,6,115335.32,2,1,1,53130.41,0 +1811,15592994,Zikoranachidimma,651,France,Female,65,0,0,2,1,1,190454.04,0 +1812,15624068,Fu,779,France,Female,26,0,0,2,0,1,111906,0 +1813,15595221,Trevisano,850,Germany,Female,33,7,134678.13,1,1,0,113177.95,0 +1814,15637131,Fallaci,829,France,Male,38,9,0,2,1,0,30529.88,0 +1815,15613471,Wiley,579,Germany,Male,31,2,90547.48,2,1,1,18800.13,0 +1816,15583499,Chiagoziem,510,France,Male,32,9,103324.78,1,1,1,46127.7,0 +1817,15752816,Murray,531,France,Male,29,3,114590.58,1,0,0,75585.48,0 +1818,15804075,Chuang,628,Germany,Female,36,3,91286.51,1,1,0,63085.94,0 +1819,15800517,Huang,633,Spain,Male,32,5,163340.12,2,1,1,74415.2,0 +1820,15712319,Chukwukere,714,Spain,Male,45,8,150900.29,2,0,1,139889.15,0 +1821,15797389,Hsia,604,Spain,Male,23,9,124577.33,1,1,1,7267.25,0 +1822,15621432,Lee,630,Spain,Male,35,1,0,2,0,0,186826.22,0 +1823,15779390,Theus,850,Spain,Female,31,4,91292.7,1,1,1,162149.07,0 +1824,15711219,Jennings,788,Germany,Female,57,8,93716.72,1,1,1,180150.49,1 +1825,15770498,Parker,798,France,Female,37,4,111723.08,1,1,1,83478.12,0 +1826,15678727,Tan,770,Germany,Male,45,4,110765.68,1,1,0,26163.74,1 +1827,15573893,Barry,569,Germany,Male,25,9,173459.45,2,1,1,44381.06,0 +1828,15740104,Tuan,425,Spain,Female,22,7,169649.73,2,0,1,136365,1 +1829,15792649,Patterson,547,Spain,Female,31,9,0,2,0,0,99294.22,0 +1830,15605275,Ofodile,725,Germany,Male,45,8,116917.07,1,0,0,173464.43,1 +1831,15572467,Chandler,506,France,Male,37,5,0,2,1,1,127543.81,0 +1832,15738219,Nash,632,France,Female,36,7,0,2,1,1,52526.65,0 +1833,15600710,Atkinson,620,France,Male,22,0,0,1,1,0,32589.45,0 +1834,15804394,Brenan,663,Germany,Male,32,8,130627.66,1,1,0,47161.25,1 +1835,15694188,Obidimkpa,700,Spain,Female,46,5,56580.95,2,0,1,45424.13,0 +1836,15583718,Terry,696,Germany,Male,38,6,142316.14,1,1,1,8018.49,0 +1837,15802478,Spring,767,Spain,Male,31,6,0,2,1,1,195668,0 +1838,15619343,Mahmood,561,France,Male,56,7,152759,2,1,0,133167.11,1 +1839,15758813,Campbell,350,Germany,Male,39,0,109733.2,2,0,0,123602.11,1 +1840,15761374,Bellucci,706,France,Male,54,9,117444.51,1,1,1,186238.85,0 +1841,15569209,Amaechi,464,Spain,Female,34,5,76001.57,1,1,1,158668.87,0 +1842,15788539,Foxall,501,France,Female,34,3,107747.57,1,1,0,9249.36,0 +1843,15747222,Bentley,745,Spain,Female,35,8,0,2,1,1,116581.1,0 +1844,15769346,Baird,587,France,Female,36,1,134997.49,2,1,0,44688.08,0 +1845,15699634,Howard,667,France,Female,48,2,0,2,1,1,148608.39,0 +1846,15589076,Henry,737,France,Male,36,9,0,1,0,1,188670.9,1 +1847,15812338,Sopuluchukwu,485,Spain,Female,30,7,0,1,1,0,107067.37,0 +1848,15758845,Rocher,590,Spain,Female,37,0,64345.21,1,0,1,61759.33,1 +1849,15685844,White,518,Germany,Female,35,8,141665.63,1,0,1,192776.64,0 +1850,15583090,Komar,581,Spain,Female,29,8,0,2,1,0,46735.19,0 +1851,15587581,Russo,785,Germany,Female,33,5,136624.6,2,1,1,169117.74,0 +1852,15633640,Loewenthal,799,France,Female,52,4,161209.66,1,1,1,89081.41,0 +1853,15573741,Aliyeva,698,Spain,Male,38,10,95010.92,1,1,1,105227.86,0 +1854,15633574,Montes,730,France,Female,41,4,167545.32,1,1,0,128246.81,0 +1855,15711455,Kuo,740,Germany,Female,36,4,109044.6,1,0,0,94554.74,1 +1856,15570601,Cheng,785,France,Female,47,9,122031.55,1,1,1,33823.5,1 +1857,15690925,McIntosh,527,Spain,Female,29,2,27755.97,1,1,0,97468.44,1 +1858,15709338,T'ao,544,France,Female,29,1,118560.55,1,1,1,164137.36,0 +1859,15780746,Tyndall,705,France,Male,61,4,0,2,1,1,191313.7,0 +1860,15681956,Bailey,684,France,Male,34,9,0,2,1,1,65257.57,0 +1861,15778190,Onyekaozulu,639,Spain,Female,28,8,97840.72,1,1,1,178222.77,0 +1862,15786852,Nwachukwu,565,Germany,Female,38,2,158651.29,2,1,1,179445.28,0 +1863,15726494,Romani,481,France,Male,44,9,175303.06,1,1,0,65500.53,1 +1864,15641183,Chin,731,Spain,Male,25,8,96950.21,1,1,0,97877.92,0 +1865,15805312,Bellucci,607,France,Male,45,7,123859.6,1,0,1,113051.57,0 +1866,15636572,Christmas,760,France,Female,32,7,0,2,1,1,105969.05,0 +1867,15632575,Moore,559,France,Female,70,9,0,1,1,1,122996.76,0 +1868,15740164,Genovesi,715,France,Female,33,3,85227.84,1,1,1,68087.15,0 +1869,15574947,Cartwright,656,France,Male,36,8,97786.08,2,0,1,21478.36,0 +1870,15597909,Johnstone,652,Germany,Male,33,7,128135.99,1,1,0,158437.73,0 +1871,15782574,Warner,624,Spain,Male,33,6,0,2,0,0,76551.7,0 +1872,15734999,Stephenson,634,Spain,Male,36,2,85996.19,1,1,0,15887.68,0 +1873,15706593,Ellis,850,Spain,Female,50,10,0,2,1,1,33741.84,0 +1874,15766686,Nebechi,659,Germany,Female,39,1,104502.11,1,1,0,20652.69,0 +1875,15590268,Chu,529,Spain,Male,35,5,95772.97,1,1,1,112781.5,0 +1876,15763055,Onuchukwu,572,Spain,Male,31,5,98108.79,1,0,1,119996.95,0 +1877,15664754,Steele,640,Germany,Male,39,9,131607.28,4,0,1,6981.43,1 +1878,15643630,Quaife,770,Spain,Male,55,9,63127.41,2,1,0,185211.28,1 +1879,15641043,Scott,648,Spain,Male,35,7,0,2,1,1,78436.36,0 +1880,15768095,Yeh,579,France,Male,31,9,0,1,0,1,139048,0 +1881,15811314,Y?,589,Germany,Female,36,9,140355.56,2,1,0,136329.96,0 +1882,15669922,Conti,530,Spain,Female,36,2,0,2,1,1,14721.8,0 +1883,15707114,Holder,831,France,Male,30,2,0,2,0,1,3430.38,0 +1884,15670602,Burgess,790,Germany,Male,24,7,107418.27,1,0,1,160450.21,0 +1885,15713479,Ozuluonye,656,France,Male,35,6,0,2,1,0,1485.27,0 +1886,15663830,De Luca,563,Spain,Male,32,6,0,2,1,1,19720.08,0 +1887,15566958,Li Fonti,667,Spain,Male,39,7,167557.12,1,1,1,41183.02,0 +1888,15680918,Freeman,613,Spain,Male,34,8,117300.02,1,1,0,139410.08,0 +1889,15663921,Pisani,429,France,Male,60,7,0,2,1,1,163691.48,0 +1890,15716324,Ignatieff,665,France,Female,23,9,143672.9,1,1,1,115147.33,0 +1891,15796969,Lahti,731,France,Male,33,4,0,2,1,1,74945.11,0 +1892,15574783,Perkins,584,France,Female,37,1,0,2,1,1,180363.56,0 +1893,15773487,Conway,634,Germany,Female,31,8,76798.92,1,0,0,196021.73,0 +1894,15802486,Hayes,488,France,Male,34,3,0,2,1,1,125979.36,0 +1895,15783398,Rizzo,535,Spain,Female,49,7,115309.75,1,1,0,111421.77,0 +1896,15649418,Krylov,776,France,Female,29,7,178171.04,2,1,1,115818.51,0 +1897,15604588,Li Fonti,850,Spain,Female,38,3,0,2,0,1,179360.76,0 +1898,15735428,Talbot,673,Spain,Female,37,0,0,2,0,0,82351.06,0 +1899,15629078,Matthias,850,Germany,Female,45,5,127258.79,1,1,1,192744.23,1 +1900,15806880,Boyle,627,Spain,Female,30,6,0,1,1,1,113408.47,0 +1901,15754999,Ch'eng,570,France,Female,33,8,0,1,1,1,124641.42,0 +1902,15781034,Mason,796,Spain,Male,67,5,0,2,0,1,54871.02,0 +1903,15622017,Bruno,773,Spain,Female,33,10,0,1,1,1,98820.09,0 +1904,15705885,Smeaton,752,Spain,Male,36,2,0,2,1,1,45570.84,0 +1905,15677382,Miller,625,Spain,Female,69,1,107569.96,1,1,1,182336.45,0 +1906,15566843,Gotch,535,Germany,Male,20,9,134874.4,1,1,1,118825.56,0 +1907,15608387,Fu,786,France,Female,29,4,0,2,1,0,103372.79,0 +1908,15810786,O'Toole,620,France,Female,67,3,0,2,1,1,43486.73,0 +1909,15626983,Ledford,605,Spain,Female,48,6,0,2,1,1,40062.99,0 +1910,15773605,Iadanza,670,Spain,Female,32,3,0,2,1,0,46175.7,0 +1911,15811261,Alaniz,617,Spain,Male,42,0,70105.87,1,1,1,120830.73,0 +1912,15590606,Saunders,595,France,Male,41,9,0,2,1,0,5967.09,0 +1913,15576644,Lin,687,Germany,Female,29,4,78939.15,1,1,0,122134.56,1 +1914,15750264,Pinto,757,Germany,Male,30,6,105128.85,2,1,1,62972.13,0 +1915,15741554,Streeter,746,Spain,Male,31,2,113836.27,1,1,1,174815.54,0 +1916,15769051,Shaw,503,Spain,Male,25,7,0,1,0,1,192841.13,0 +1917,15812198,Chen,543,Germany,Male,48,1,100900.5,1,0,0,33310.72,1 +1918,15699772,Barclay,428,Germany,Female,40,3,129248.11,2,1,0,72876.43,1 +1919,15744105,Kodilinyechukwu,768,France,Female,28,3,109118.05,2,0,1,50911.41,0 +1920,15739858,Otitodilichukwu,618,France,Male,56,7,0,1,1,1,142400.27,1 +1921,15723720,McKenzie,591,France,Female,31,7,0,2,0,1,48778.46,0 +1922,15638355,Woods,658,France,Female,35,5,126397.66,1,0,0,156361.58,1 +1923,15805637,Hsing,625,France,Male,36,9,108546.16,3,1,0,133807.77,1 +1924,15629575,Wheare,717,France,Male,36,2,148061.89,1,1,0,179128.69,1 +1925,15586243,Yobachi,667,France,Male,44,8,122277.87,1,1,1,91810.71,0 +1926,15757931,Fang,804,France,Male,24,3,0,2,1,0,173195.33,0 +1927,15716023,Pearson,693,France,Male,31,1,0,2,0,1,182270.88,0 +1928,15647782,Brown,729,Germany,Male,36,8,152899.24,2,1,0,177130.33,0 +1929,15716609,L?,484,Germany,Male,54,3,134388.11,1,0,0,49954.79,1 +1930,15623791,Padovesi,632,Spain,Female,40,3,109740.62,1,1,0,141896.74,0 +1931,15627262,Soto,536,Germany,Male,23,6,92366.72,2,1,0,120661.71,0 +1932,15652693,Greco,573,France,Female,26,4,129109.02,1,0,0,149814.68,1 +1933,15586993,Giordano,655,Spain,Female,56,5,0,2,1,1,41782.7,0 +1934,15815560,Bogle,666,Germany,Male,74,7,105102.5,1,1,1,46172.47,0 +1935,15584930,Grimmett,726,Germany,Male,30,5,111375.32,2,1,0,2704.09,0 +1936,15799031,Ayers,523,France,Male,39,3,0,2,1,0,6726.53,0 +1937,15810457,Miller,728,Germany,Female,33,9,150412.14,2,1,0,170764.08,0 +1938,15697879,Webb,701,France,Male,30,3,156660.72,2,1,0,45742.42,0 +1939,15594902,Lombardi,518,France,Male,38,3,90957.81,1,0,1,162304.59,0 +1940,15799710,Wei,739,France,Male,37,7,104960.46,1,0,1,80883.82,0 +1941,15659651,Ross,531,Germany,Female,31,7,117052.82,1,1,0,118508.09,1 +1942,15645956,Jideofor,452,Spain,Male,44,3,88915.85,1,1,0,69697.74,0 +1943,15651713,King,684,France,Male,45,6,148071.39,1,1,0,183575.01,0 +1944,15737265,Nwokeocha,728,Germany,Male,39,6,152182.83,1,0,0,161203.6,0 +1945,15687310,Humphries,783,Spain,Male,39,9,0,2,1,0,143752.77,0 +1946,15607347,Olisaemeka,734,France,Male,22,5,130056.23,1,0,0,121894.31,1 +1947,15698321,Yobanna,648,Germany,Male,34,3,95039.73,2,1,1,147055.87,0 +1948,15657812,Ch'iu,688,France,Male,52,1,0,2,1,1,172033.57,0 +1949,15569187,Fleming,680,Spain,Male,35,9,0,2,0,0,143774.06,0 +1950,15681562,Trevisan,516,France,Female,43,2,112773.73,2,1,1,139366.58,0 +1951,15615456,Aleksandrova,680,France,Female,37,10,123806.28,1,1,0,81776.84,1 +1952,15589793,Onwuamaeze,604,France,Male,53,8,144453.75,1,1,0,190998.96,1 +1953,15781884,Knox,624,Germany,Male,27,9,94667.29,2,0,1,4470.52,0 +1954,15675190,Chia,623,France,Male,21,10,0,2,0,1,135851.3,0 +1955,15600734,Townsend,624,Spain,Male,51,5,174397.21,2,1,1,172372.63,0 +1956,15779176,Dike,565,Germany,Female,58,3,108888.24,3,0,1,135875.51,1 +1957,15605286,Moyes,565,France,Male,55,4,118803.35,2,1,1,128124.7,1 +1958,15674922,Beavers,710,France,Male,54,6,171137.62,1,1,1,167023.95,1 +1959,15737506,Tretiakova,645,France,Male,42,6,0,1,0,0,149807.01,0 +1960,15780514,Fuller,707,France,Male,33,8,136678.52,1,1,0,54290.62,0 +1961,15623647,Dellucci,655,Spain,Female,36,1,135515.76,1,1,0,86013.96,0 +1962,15668472,Ritchie,705,Spain,Female,24,5,177799.83,2,0,0,79886.06,0 +1963,15692416,Aikenhead,358,Spain,Female,52,8,143542.36,3,1,0,141959.11,1 +1964,15771139,Douglas,578,Germany,Male,34,8,147487.23,2,1,0,66680.77,0 +1965,15738318,Kung,800,France,Female,40,5,97764.41,1,1,0,98640.15,1 +1966,15772243,MacDonald,612,France,Female,33,9,0,1,0,0,142797.5,1 +1967,15638463,Okwudilichukwu,681,Germany,Female,48,8,139480.18,1,1,1,163581.67,0 +1968,15598088,Ni,559,Spain,Male,25,5,0,2,1,1,163221.22,0 +1969,15693468,Simmons,488,Spain,Female,39,9,140553.46,1,0,0,12440.44,0 +1970,15671930,H?,717,France,Female,36,5,0,2,1,1,145551.6,0 +1971,15762268,Hancock,666,France,Female,41,10,141162.08,1,1,0,50908.48,0 +1972,15780954,Cran,582,Spain,Male,26,4,65848.36,2,1,0,30149.21,0 +1973,15700174,McKay,733,Spain,Female,30,0,83319.28,1,0,0,57769.2,0 +1974,15635728,P'an,693,France,Male,41,4,0,2,0,0,156381.47,0 +1975,15679283,Parkhill,694,France,Female,33,4,129731.64,2,1,0,178123.86,0 +1976,15591386,Golubova,622,France,Female,35,5,0,2,1,0,51112.8,0 +1977,15694192,Nwankwo,598,Spain,Female,38,6,0,2,0,0,173783.38,0 +1978,15585901,Johnson,717,Spain,Male,35,1,0,3,0,0,174770.14,1 +1979,15792329,Mao,494,Germany,Male,37,5,107106.33,2,1,0,172063.09,0 +1980,15635597,Echezonachukwu,644,France,Male,33,8,0,2,1,1,155294.17,0 +1981,15775880,McElyea,554,France,Female,30,9,0,2,1,1,40320.3,0 +1982,15630913,Rosas,476,Spain,Female,69,1,105303.73,1,0,1,134260.34,0 +1983,15756680,Phillips,667,France,Male,28,6,165798.1,1,1,0,147090.9,0 +1984,15587913,Palerma,748,Spain,Female,40,4,0,2,1,0,132368.47,0 +1985,15737605,Morris,531,Spain,Female,45,1,126495.57,2,1,1,164741.5,0 +1986,15627876,Pavlova,719,Spain,Female,47,9,116393.59,1,1,0,63051.32,1 +1987,15772601,Lu,845,Germany,Female,41,2,81733.74,2,0,0,199761.29,0 +1988,15758606,Yamamoto,738,France,Male,54,4,0,1,0,1,55725.04,1 +1989,15657107,Angelo,563,Spain,Female,46,8,106171.68,1,1,0,163145.5,1 +1990,15622454,Zaitsev,695,Spain,Male,28,0,96020.86,1,1,1,57992.49,0 +1991,15775803,Cawker,841,Spain,Male,41,1,0,2,0,1,193093.77,0 +1992,15570859,Froggatt,626,Germany,Male,36,2,181671.16,2,1,1,57531.14,0 +1993,15748381,Gorbunov,613,France,Female,29,6,185709.28,2,1,1,77242.19,0 +1994,15787189,Tai,824,Germany,Male,60,8,134250.17,3,0,0,153046.16,1 +1995,15666055,Rowe,705,France,Female,49,7,0,1,1,0,63405.2,1 +1996,15617648,Mikkelsen,584,France,Female,44,5,95671.75,2,1,1,106564.88,0 +1997,15755678,Kovalyov,534,France,Male,62,2,0,2,0,0,42763.12,1 +1998,15624781,Mbanefo,672,France,Female,34,1,142151.75,2,1,1,168753.34,0 +1999,15779497,Ts'ai,603,France,Male,43,5,127823.93,1,1,1,19483.35,0 +2000,15567399,Enderby,633,Germany,Male,43,3,144164.29,1,1,1,158646.46,0 +2001,15613656,Lombardi,842,France,Male,58,1,63492.94,1,1,1,83172.19,0 +2002,15734311,Hamilton,661,France,Female,27,3,0,2,1,1,76889.79,0 +2003,15657214,Hsia,601,France,Male,74,2,0,2,0,1,51554.58,0 +2004,15799350,Mao,632,France,Male,41,0,106134.46,1,0,1,105570.39,0 +2005,15729970,Ugochukwu,684,Germany,Male,29,8,127269.75,1,0,1,79495.01,0 +2006,15725835,West,785,Germany,Female,32,3,124493.03,2,0,1,52583.79,1 +2007,15745543,Hughes,687,France,Male,39,7,0,2,1,0,26848.25,0 +2008,15727384,Chukwuemeka,705,Germany,Female,43,10,146547.78,1,0,1,10072.55,1 +2009,15666916,Lira,639,France,Male,43,6,99610.92,2,1,0,187296.78,0 +2010,15732917,Li,729,Germany,Male,46,5,117837.43,1,1,0,104016.61,1 +2011,15612050,Castiglione,556,Spain,Female,48,8,168522.37,1,1,1,151310.16,0 +2012,15726267,Paterson,570,France,Male,32,9,117337.54,2,0,1,62810.91,0 +2013,15780124,Blair,841,France,Male,74,9,108131.53,1,0,1,60830.38,0 +2014,15742238,Dellucci,705,Germany,Male,35,4,136496.12,2,1,0,116672.02,0 +2015,15679024,Udinesi,553,France,Male,32,3,116324.53,1,1,0,77304.49,0 +2016,15715297,Yuan,779,Germany,Female,40,2,75470.23,1,1,1,52894.01,0 +2017,15633612,Yuryeva,696,France,Male,28,4,172646.82,1,1,1,116471.43,0 +2018,15602929,Wilson,728,Spain,Female,37,4,0,1,0,0,4539.38,0 +2019,15696703,Dean,691,Germany,Male,27,3,160358.68,2,1,0,142367.72,0 +2020,15756668,Ross,706,France,Male,30,3,98415.37,1,1,1,110520.48,0 +2021,15565779,Kent,627,Germany,Female,30,6,57809.32,1,1,0,188258.49,0 +2022,15795519,Vasiliev,716,Germany,Female,18,3,128743.8,1,0,0,197322.13,0 +2023,15761477,Golibe,501,Germany,Male,24,4,130806.42,2,1,0,80241.14,0 +2024,15731890,Chukwukere,601,France,Male,41,1,123971.16,1,0,1,172814.99,0 +2025,15633043,Fedorova,545,Spain,Female,39,6,0,1,0,0,38410.74,1 +2026,15752953,Chien,634,France,Male,45,9,0,2,0,0,17622.82,0 +2027,15603088,Rossi,451,Spain,Female,23,9,0,2,0,1,48021.71,0 +2028,15606613,Samson,655,France,Female,59,7,0,1,1,0,88958.49,1 +2029,15635939,Fenton,458,France,Female,39,9,0,2,1,0,116343.09,0 +2030,15666043,Mackey,520,France,Male,33,4,156297.58,2,1,1,166102.61,0 +2031,15746190,Payton,624,Spain,Female,28,2,0,2,0,1,104353.26,0 +2032,15591357,Cowger,765,France,Male,51,3,123372.3,1,1,1,115429.32,0 +2033,15658716,Banks,667,Germany,Female,37,5,92171.35,3,1,0,178106.34,1 +2034,15679909,Pugliesi,665,Spain,Male,41,8,0,2,1,0,132152.32,0 +2035,15634262,Fantin,709,Germany,Male,34,4,148375.19,2,1,1,21521.38,0 +2036,15799825,Bentley,583,France,Female,44,8,0,2,1,1,27431.62,0 +2037,15756875,Freeman,782,Spain,Male,34,6,147422.44,1,0,1,42143.61,0 +2038,15678146,Wong,668,Spain,Female,24,7,173962.32,1,0,0,106457.11,1 +2039,15710743,Onwuamaeze,621,France,Male,47,0,0,1,1,1,133831.37,1 +2040,15595831,Shen,579,Germany,Female,64,6,145215.43,1,1,1,164083.72,0 +2041,15626684,Huang,547,France,Female,38,5,167539.97,1,0,1,159207.34,0 +2042,15709846,Yeh,840,France,Female,39,1,94968.97,1,1,0,84487.62,0 +2043,15635459,Shih,667,Germany,Female,27,3,106116.5,2,1,0,3674.71,0 +2044,15642544,Henderson,723,France,Male,34,5,0,2,0,1,12092.03,0 +2045,15566494,Fang,487,France,Male,45,2,0,2,1,0,77475.73,0 +2046,15655238,Dellucci,668,France,Female,31,9,0,2,0,0,41291.73,0 +2047,15733429,Chou,520,Germany,Male,34,8,120018.86,2,1,1,343.38,0 +2048,15814536,Conti,549,France,Male,37,2,112541.54,2,0,0,47432.43,0 +2049,15771702,Roberts,567,France,Female,35,5,166118.45,2,1,0,127827.18,0 +2050,15723008,Lo Duca,720,France,Female,45,1,102882.4,2,1,1,35633.15,1 +2051,15797160,Glover,492,France,Female,49,8,0,1,1,1,182865.09,1 +2052,15792222,Johnstone,712,France,Female,37,1,106881.5,2,0,0,169386.81,0 +2053,15644765,Ashton,689,Germany,Male,26,4,120727.97,1,0,1,149073.88,0 +2054,15610686,Melton,850,France,Male,63,8,169832.57,1,0,0,184107.26,1 +2055,15730868,Marshall,747,France,Male,41,5,0,2,1,1,22750.17,0 +2056,15705991,Kenenna,469,Germany,Male,38,9,113599.42,1,0,0,11950.29,0 +2057,15577078,Zakharov,539,Spain,Male,38,6,0,1,1,1,152880.07,1 +2058,15679550,Chukwualuka,743,France,Male,32,9,0,2,1,0,175252.78,0 +2059,15787655,Chu,707,France,Male,47,3,0,2,1,0,174303.29,0 +2060,15668081,Capon,581,Spain,Female,50,4,0,2,1,1,80701.72,0 +2061,15747980,Cattaneo,737,Spain,Male,38,6,146282.79,2,1,0,198516.2,0 +2062,15710295,Patrick,445,Germany,Female,38,6,119413.62,2,1,0,175756.36,0 +2063,15724443,Taylor,703,Germany,Female,29,3,122084.63,1,0,1,82824.08,0 +2064,15571305,Stephenson,588,Germany,Female,35,1,103060.63,1,1,0,179866.01,1 +2065,15569503,Yeh,765,France,Male,44,6,0,2,1,1,159899.97,0 +2066,15581840,DeRose,626,France,Male,33,8,0,2,1,0,138504.28,0 +2067,15772262,Vavilov,545,Germany,Male,37,9,110483.86,1,1,1,127394.67,0 +2068,15767794,Browne,744,France,Male,31,9,120718.28,1,1,1,58961.49,0 +2069,15629338,Collingridge de Tourcey,658,Spain,Female,31,2,36566.96,1,1,0,103644.98,1 +2070,15790379,Rowe,629,Germany,Male,28,8,108601,1,1,1,119647.7,0 +2071,15750684,Jibunoh,719,France,Female,42,4,0,1,1,0,28465.86,1 +2072,15697214,Korovin,686,Spain,Female,36,5,0,2,1,1,152979.14,0 +2073,15711015,Hammonds,743,France,Male,36,4,0,2,1,1,190911.02,0 +2074,15573309,Ward,626,Spain,Female,48,2,0,2,1,1,95794.98,0 +2075,15805303,Olisanugo,661,Germany,Male,44,1,141136.62,1,1,0,189742.78,1 +2076,15741385,Gallop,710,Germany,Male,45,9,108231.37,1,1,1,188574.08,0 +2077,15780254,Gartrell,654,France,Male,40,6,0,1,0,0,183872.88,1 +2078,15744843,K'ung,569,Spain,Female,34,6,144855.34,1,0,0,196555.32,0 +2079,15815626,Oluchi,640,France,Male,63,2,68432.45,2,1,1,112503.24,1 +2080,15784736,Jamieson,562,France,Male,45,6,136855.24,1,1,0,46864,0 +2081,15813412,Barlow,721,France,Female,55,3,44020.89,1,1,0,65864.4,1 +2082,15809143,White,456,Germany,Male,32,9,133060.63,1,1,1,125167.92,0 +2083,15617617,Stewart,811,Spain,Male,39,7,0,2,1,1,177519.39,0 +2084,15779738,Buccho,534,France,Male,24,1,0,1,1,1,169653.32,0 +2085,15668669,Benson,423,France,Female,36,5,97665.61,1,1,0,118372.55,1 +2086,15687477,Thompson,594,Germany,Male,28,5,185013.02,1,1,0,16481.12,0 +2087,15578908,Todd,725,Spain,Female,32,0,0,2,1,1,138525.19,0 +2088,15687658,Burgin,716,France,Female,52,7,65971.61,2,1,0,14608,1 +2089,15615020,Nnaife,595,Germany,Female,41,9,150463.11,2,0,1,81548.38,0 +2090,15608886,Okwudiliolisa,679,France,Female,33,1,0,2,0,0,69608.48,0 +2091,15602551,Johnson,667,Spain,Male,39,9,0,2,1,0,68873.8,0 +2092,15672945,Parkes,661,France,Female,37,5,136425.18,1,1,0,81102.81,0 +2093,15757408,Lo,655,Spain,Male,38,3,250898.09,3,0,1,81054,1 +2094,15806132,Martin,555,France,Male,55,4,146798.81,1,1,1,74149.77,0 +2095,15813022,Kapustina,531,Spain,Male,70,1,0,2,0,0,99503.19,0 +2096,15673578,Page,611,Germany,Female,40,7,128486.91,2,1,0,10109.47,0 +2097,15757916,Amaechi,600,France,Female,38,9,0,2,1,1,58855.85,0 +2098,15689168,Munro,531,Spain,Male,37,1,143407.29,2,0,1,84402.46,0 +2099,15769216,Panicucci,601,France,Female,43,2,0,1,1,0,49713.87,1 +2100,15593295,Greathouse,548,France,Male,57,6,76165.65,1,1,1,133537.53,0 +2101,15804814,Ts'ui,759,France,Male,40,4,0,2,1,0,124615.59,0 +2102,15778934,Napolitani,678,Spain,Female,49,8,0,2,0,1,98090.69,0 +2103,15802351,Beers,755,Germany,Female,33,6,90560.3,2,1,1,42607.69,0 +2104,15630241,Tretyakova,594,France,Male,61,3,62391.22,1,1,1,192434.11,0 +2105,15719561,Lin,768,France,Male,42,5,0,3,0,0,60686.4,0 +2106,15615096,Costa,492,France,Female,31,7,0,2,1,1,49463.44,0 +2107,15659931,Ibezimako,637,Germany,Female,55,1,123378.2,1,1,0,81431.99,1 +2108,15714586,Marcelo,646,Spain,Female,42,3,99836.47,1,0,1,22909.56,0 +2109,15634949,Hay,593,Germany,Male,74,5,161434.36,2,1,1,65532.17,0 +2110,15589224,Moore,596,Spain,Male,41,5,0,2,0,1,141053.85,0 +2111,15795990,Lumholtz,722,Germany,Female,48,10,138311.76,1,1,1,3472.63,1 +2112,15603216,Simpson,642,France,Male,25,7,0,2,1,0,102083.78,0 +2113,15631201,Hill,472,Spain,Female,28,4,0,2,1,0,1801.77,0 +2114,15686255,Mouzon,738,Germany,Male,35,6,101744.84,1,0,0,85185.44,0 +2115,15746594,Wu,732,Spain,Male,33,8,0,1,1,0,119882.7,0 +2116,15718893,Pirozzi,404,Germany,Female,54,4,125456.07,1,1,0,83715.66,1 +2117,15671609,Ibeabuchi,701,France,Male,44,7,0,2,1,0,23425.78,0 +2118,15652540,Garnsey,683,France,Male,31,2,0,2,0,1,77326.78,0 +2119,15774857,Synnot,460,France,Female,27,7,0,2,1,0,156150.08,1 +2120,15791836,Wildman,690,France,Male,29,5,0,2,1,0,108577.97,0 +2121,15651554,Anenechukwu,618,Germany,Female,54,4,118449.21,1,1,1,133573.29,1 +2122,15583576,Tai,671,France,Male,30,2,0,1,0,1,102057.86,0 +2123,15732740,Plant,765,Spain,Female,32,9,178095.55,1,0,0,47247.56,0 +2124,15723320,Azubuike,651,Germany,Female,25,2,109175.14,2,1,0,114566.47,0 +2125,15603851,Galkin,704,France,Male,32,7,127785.17,4,0,0,184464.7,1 +2126,15777923,Johnston,544,France,Female,45,6,0,2,0,1,151401.33,0 +2127,15735719,Babbage,790,France,Female,40,9,0,2,1,1,70607.1,0 +2128,15703482,Walker,710,Germany,Male,34,9,134260.36,2,1,0,147074.67,0 +2129,15605835,Rice,743,France,Male,37,8,69143.91,2,0,1,105780.18,0 +2130,15664881,Norton,702,France,Male,34,4,100054.77,1,1,0,109496.45,0 +2131,15757568,Bogolyubov,704,France,Female,45,6,0,1,1,1,137739.45,0 +2132,15792660,Gibbons,614,France,Male,38,2,116248.88,1,1,0,105140.92,0 +2133,15599722,Chia,609,Spain,Female,43,6,86053.52,2,1,1,113276.46,1 +2134,15726354,Smith,688,France,Female,32,6,123157.95,1,1,0,172531.23,0 +2135,15610355,Hunter,713,France,Male,44,1,63438.91,1,1,0,64375.4,0 +2136,15704284,Ekechukwu,736,Germany,Male,57,9,95295.39,1,1,0,28434.44,1 +2137,15621893,Bellucci,727,France,Male,18,4,133550.67,1,1,1,46941.41,0 +2138,15588219,Ford,850,France,Female,38,1,106871.81,2,1,0,29333.01,0 +2139,15688619,Scott,718,Spain,Male,45,3,105266.32,2,1,1,193724.51,0 +2140,15765518,Gregson,643,France,Female,51,2,105229.53,1,1,0,34967.75,1 +2141,15616931,Moore,653,France,Male,41,8,102768.42,1,1,0,55663.85,0 +2142,15758372,Wallace,674,France,Male,18,7,0,2,1,1,55753.12,1 +2143,15782591,Cook,690,France,Male,35,6,112689.95,1,1,0,176962.31,0 +2144,15612109,Speth,819,France,Male,38,9,122334.26,2,1,1,181507.44,0 +2145,15613712,Boag,634,Spain,Male,34,1,0,2,1,0,61995.57,0 +2146,15639322,Grave,633,Spain,Male,33,4,137847.41,2,1,0,98349.13,0 +2147,15594349,Streeten,850,France,Male,49,5,122486.47,1,0,1,59748.19,0 +2148,15574167,Fox,665,France,Male,33,2,101286.11,1,1,1,159840.51,0 +2149,15811842,Artemyeva,630,Spain,Male,26,7,0,2,1,1,6656.64,0 +2150,15648794,Giordano,836,Spain,Male,57,4,101247.06,1,1,0,37141.62,1 +2151,15771211,Perkins,668,France,Male,38,10,86977.96,1,0,1,37094.75,0 +2152,15588614,Walton,753,France,Male,57,7,0,1,1,0,159475.08,1 +2153,15630698,Hay,745,France,Female,55,9,110123.59,1,0,1,51548.14,1 +2154,15694200,Gardner,693,France,Male,36,8,178111.82,1,0,0,58719.63,1 +2155,15721426,Milne,606,Germany,Male,65,10,126306.64,3,0,0,7861.68,1 +2156,15725997,She,660,France,Female,35,6,100768.77,1,1,0,19199.61,0 +2157,15762138,Hu,608,France,Male,42,5,0,2,1,0,178504.29,0 +2158,15750649,Uwakwe,744,France,Female,44,3,0,2,1,1,189016.14,0 +2159,15685706,Bird,731,France,Female,40,7,118991.79,1,1,1,156048.64,0 +2160,15641835,Anderson,683,France,Male,72,3,140997.26,1,0,1,52876.41,0 +2161,15586821,Bellew,727,France,Male,28,5,0,2,0,1,19653.08,0 +2162,15569678,Cocci,561,Germany,Male,32,6,166824.59,1,1,0,139451.98,0 +2163,15793842,Krichauff,700,France,Female,34,2,76322.69,1,1,0,128136.29,0 +2164,15667554,Cameron,605,France,Male,35,6,0,2,1,1,45206.57,0 +2165,15794479,Becker,767,Spain,Male,77,8,149083.7,1,1,1,190146.83,0 +2166,15585041,Ainsworth,511,France,Male,33,7,0,2,0,1,158313.87,0 +2167,15780650,Biryukov,667,France,Male,40,9,0,1,1,1,96670.2,0 +2168,15780846,Redding,787,France,Male,33,1,126588.81,2,0,1,62163.53,0 +2169,15805260,Wood,705,Germany,Female,56,2,143249.67,1,1,0,88428.41,1 +2170,15621629,Scott,773,Germany,Male,43,8,81844.91,2,1,1,35908.46,0 +2171,15662151,Gould,554,France,Male,40,4,0,1,0,1,168780.04,0 +2172,15747174,Hao,526,Germany,Male,58,9,190298.89,2,1,1,191263.76,0 +2173,15651585,Power,661,Germany,Male,35,2,117212.18,1,1,1,83052.03,0 +2174,15649738,White,698,France,Female,46,0,0,2,1,1,125962.02,0 +2175,15633108,Thorpe,646,France,Male,26,4,139848.17,1,1,0,164696.27,0 +2176,15769254,Tuan,757,Germany,Female,34,9,101861.36,2,0,0,187011.96,0 +2177,15704746,Inman,699,Spain,Male,35,2,167455.66,2,1,1,55324.49,0 +2178,15637644,Hanson,667,France,Female,24,4,0,2,0,1,34335.55,0 +2179,15609562,MacDonald,774,Spain,Female,43,1,116360.07,1,1,0,17004.14,0 +2180,15787459,Parkes,745,Spain,Male,40,3,88466.82,1,0,0,116331.42,0 +2181,15762902,Stanley,649,France,Female,42,7,0,2,0,1,22974.01,0 +2182,15738605,Fischer,634,Germany,Female,46,5,123642.36,1,1,1,49725.16,1 +2183,15724889,Chinweuba,665,Spain,Male,38,9,0,1,0,1,87412.74,0 +2184,15730735,Henning,713,France,Male,38,9,72286.84,2,1,1,26136.89,0 +2185,15689147,Ogochukwu,652,France,Female,40,1,0,2,1,0,126554.96,0 +2186,15730397,Narelle,739,Spain,Male,40,1,109681.61,1,1,1,193321.3,0 +2187,15762169,Bergman,556,Germany,Male,37,9,145018.64,2,1,0,90928.02,1 +2188,15589320,Sagese,699,Spain,Male,34,8,0,1,1,1,76510.46,0 +2189,15799211,Anenechi,708,Spain,Female,32,8,187487.63,1,1,1,120115.5,0 +2190,15798310,Palerma,480,France,Male,35,2,165692.91,1,1,1,197984.58,0 +2191,15609998,Okwudilichukwu,700,Germany,Female,59,5,137648.41,1,1,0,142977.05,1 +2192,15583548,Harrison,525,Spain,Female,47,6,118560,1,1,0,82522.61,1 +2193,15761763,Jamieson,845,France,Male,33,8,164385.53,1,1,0,150664.97,0 +2194,15764409,Goodman,613,France,Male,37,9,108286.5,1,1,1,114153.44,0 +2195,15710161,Ko,850,France,Female,34,2,0,2,1,1,171706.66,0 +2196,15735246,Norman,798,Spain,Female,58,9,0,2,0,0,119071.56,1 +2197,15791700,Ugochukwutubelum,773,Germany,Male,47,2,118079.47,4,1,1,143007.49,1 +2198,15670753,Uvarova,614,Spain,Male,35,2,127283.78,1,1,1,31302.35,0 +2199,15573876,Chia,473,Spain,Male,48,8,0,2,1,0,71139.8,0 +2200,15770174,Piazza,762,France,Male,29,6,141389.06,1,1,0,54122.89,0 +2201,15641114,Power,701,France,Male,37,8,130091.5,1,1,1,120031.29,0 +2202,15682435,P'eng,600,France,Male,35,4,143744.77,2,1,0,104076.51,0 +2203,15751788,Johnson,850,Spain,Male,28,9,97408.03,1,1,1,175853.64,0 +2204,15672598,Walker,613,Spain,Male,30,9,111927.45,1,1,1,175795.87,0 +2205,15762803,Innes,509,France,Male,31,3,0,2,1,0,15360.91,0 +2206,15812982,Francis,509,Spain,Male,38,2,0,1,0,0,168460.12,0 +2207,15597901,Chidozie,609,France,Male,34,1,0,1,1,1,181177.9,0 +2208,15731507,Mackenzie,456,France,Female,33,1,188285.68,1,0,0,58363.94,0 +2209,15809826,Craigie,728,France,Female,46,2,109705.52,1,1,0,20276.87,1 +2210,15764237,Manfrin,663,Spain,Male,33,9,0,2,0,0,91514.62,0 +2211,15769917,Onyekachi,673,Germany,Female,34,1,127122.79,3,0,1,76703.1,0 +2212,15641850,Pethard,717,France,Male,40,0,98241.04,1,1,0,110887.14,0 +2213,15770974,Nwabugwu,741,Germany,Female,37,8,170840.08,2,0,0,109843.16,0 +2214,15803749,DeRose,498,Germany,Female,41,4,87541.06,2,1,1,12577.21,1 +2215,15684999,Ch'eng,850,France,Female,26,4,62610.96,2,0,1,179365.1,0 +2216,15770225,Padovesi,493,France,Male,36,9,0,2,1,1,65816.53,0 +2217,15627484,Obielumani,686,France,Female,47,5,113328.93,1,1,0,124170.9,0 +2218,15610337,Stephens,666,Spain,Male,35,2,104832.49,1,1,0,175015.12,0 +2219,15752488,Emery,733,Spain,Female,31,9,102289.85,1,1,1,115441.66,0 +2220,15610056,Dufresne,631,Germany,Female,34,6,125227.82,2,0,1,128247.03,0 +2221,15806049,Lee,714,Germany,Female,49,5,140510.89,1,1,0,141914.94,0 +2222,15736069,Hsing,767,Germany,Female,35,6,132253.22,1,1,0,115566.57,1 +2223,15763662,Longo,711,Germany,Male,43,2,39043.29,2,1,1,175423.69,0 +2224,15615575,Vial,722,France,Male,34,8,0,2,1,1,133447.49,0 +2225,15691723,Chukwudi,631,Spain,Male,55,9,99685.06,1,1,0,114474.98,0 +2226,15774098,Grant,701,Germany,Male,38,3,125385.49,2,0,1,52044.66,0 +2227,15750808,Ma,790,Spain,Male,46,2,131365.37,2,1,1,180290.68,0 +2228,15744368,Sun,633,Spain,Male,58,6,98308.51,1,1,1,132034.13,0 +2229,15610594,Moss,644,France,Female,37,8,0,2,1,0,20968.88,0 +2230,15756125,Booth,757,Spain,Male,44,5,140856.16,2,1,0,158735.1,0 +2231,15623277,Ross,696,France,Female,30,8,0,2,1,1,196134.44,0 +2232,15795954,Ndukaku,746,France,Male,35,2,172274.01,1,1,0,22374.97,0 +2233,15671969,Pruneda,649,Spain,Male,36,8,0,2,1,0,161668.15,0 +2234,15791268,Neumann,565,Spain,Male,38,0,122447.76,1,0,0,67339.34,0 +2235,15713655,Calabrese,720,France,Female,38,10,0,2,1,1,56229.72,1 +2236,15633930,Yobachukwu,648,Spain,Female,56,6,157559.59,2,1,0,140991.23,1 +2237,15712849,Tung,632,Germany,Male,41,3,126550.7,1,0,0,177644.52,1 +2238,15639077,Marchesi,622,France,Female,30,2,158584.82,3,1,0,142342.55,1 +2239,15808784,Hess,835,France,Male,28,2,163569.61,2,1,1,154559.28,0 +2240,15648577,Pickering,493,France,Female,31,3,0,1,1,1,176570.28,1 +2241,15670345,Mazzi,785,Germany,Female,33,6,127211.45,1,0,0,191961.83,0 +2242,15633112,Madukaego,681,Germany,Male,42,3,118199.97,2,1,0,9452.88,1 +2243,15714397,Trentino,621,Germany,Female,30,2,101014.08,2,1,1,165257.31,0 +2244,15780038,Paterson,756,Spain,Male,38,6,119208.85,1,1,0,169763.89,1 +2245,15756305,Marchesi,515,France,Female,66,6,0,2,1,1,160663.11,0 +2246,15578799,Anayolisa,625,France,Female,58,10,53772.73,1,1,1,192072.1,1 +2247,15800326,Poole,717,Spain,Female,39,6,0,2,1,0,93275.61,0 +2248,15785485,Zhou,595,Germany,Female,41,2,138878.81,1,0,1,112269.67,0 +2249,15783958,Bates,539,Spain,Female,37,1,130922.81,2,0,0,2186.83,0 +2250,15727546,Olejuru,762,France,Male,35,9,0,2,1,1,43075.7,0 +2251,15739576,Bustard,706,Spain,Male,20,8,0,2,1,1,12368.11,0 +2252,15631333,Wade,677,Spain,Female,25,8,130866.19,1,1,0,42410.21,0 +2253,15604782,Tan,733,Germany,Female,33,7,187257.94,1,0,1,190430.81,0 +2254,15589643,Ngozichukwuka,684,Spain,Female,41,7,0,1,1,1,138394.37,0 +2255,15585533,Calabrese,679,France,Male,36,6,147733.64,1,0,1,172501.38,0 +2256,15681506,Lane,478,Spain,Male,43,1,0,2,1,1,197916.43,0 +2257,15630551,Forbes,696,France,Male,33,2,163139.27,1,1,1,7035.36,0 +2258,15698349,Davy,686,Spain,Female,35,4,0,2,1,1,159676.55,0 +2259,15776631,Ma,466,France,Female,36,5,119540.15,1,0,1,80603.99,0 +2260,15762216,Barrera,686,France,Female,41,4,129553.76,2,1,0,187599.8,0 +2261,15623927,Alexander,576,France,Male,55,9,0,2,1,1,94450.97,0 +2262,15681402,Ngozichukwuka,763,Germany,Female,61,1,66101.89,1,1,1,143981.27,0 +2263,15586264,Murray,572,France,Male,43,2,140431.98,1,1,0,26450.57,1 +2264,15594685,Hall,757,France,Female,49,2,0,2,0,0,164482.92,0 +2265,15812945,Padovesi,582,France,Female,29,0,0,1,1,1,84012.81,0 +2266,15734628,Lysaght,623,France,Female,35,5,0,2,1,0,101192.08,0 +2267,15629323,Kelechi,617,Germany,Female,37,4,116471.43,2,1,0,175324.74,1 +2268,15666823,Nebechi,425,France,Male,39,4,0,2,1,0,197226.32,0 +2269,15777553,Hanson,659,France,Female,56,9,123785.24,1,1,0,99504.03,1 +2270,15613097,Kao,605,France,Female,33,4,0,2,0,1,83700.66,0 +2271,15622217,Tu,538,France,Female,38,8,88758.95,2,0,0,28226.15,1 +2272,15703588,Palerma,665,Germany,Male,25,5,153611.83,2,1,0,35321.65,0 +2273,15570835,Fallaci,491,Germany,Female,57,4,112044.72,1,1,1,41229.73,1 +2274,15679299,Shen,726,Spain,Female,27,7,123826.07,1,0,1,78970.58,0 +2275,15808044,Ts'ui,580,France,Female,65,9,106804.26,3,1,0,107890.69,1 +2276,15579208,Chikezie,550,France,Female,48,6,0,2,1,1,191870.28,0 +2277,15684951,He,542,France,Female,59,2,68892.77,2,1,0,7905.06,1 +2278,15667620,Dreyer,732,France,Female,43,6,0,2,1,0,65731.53,0 +2279,15582960,Short,473,France,Female,33,5,125827.43,1,0,1,145698.73,0 +2280,15590730,Hunt,745,Spain,Male,34,9,0,2,1,0,50046.25,0 +2281,15763747,Ricci,732,France,Male,36,7,0,2,1,1,60830.24,0 +2282,15778320,Teng,848,Germany,Female,40,5,148495.64,1,0,0,158853.98,0 +2283,15642787,Ijendu,572,France,Male,37,1,133043.66,1,0,0,111243.09,0 +2284,15624633,Kibby,702,France,Male,45,9,74989.58,1,1,1,171014.69,0 +2285,15766765,Obiuto,664,Germany,Male,39,7,60263.23,1,1,0,170835.32,0 +2286,15783615,Ramos,630,Germany,Male,50,3,129370.91,4,1,1,47775.34,1 +2287,15640161,Calabrese,618,Germany,Male,44,5,157955.83,2,0,0,139297.71,0 +2288,15619889,Vasin,556,France,Male,26,4,0,1,1,0,195167.38,0 +2289,15579166,Munro,619,France,Female,30,7,70729.17,1,1,1,160948.87,0 +2290,15789097,Keeley,644,France,Male,48,8,0,2,0,1,44965.54,1 +2291,15674880,Archer,658,Spain,Male,50,2,0,2,1,0,52137.73,0 +2292,15778157,Murray,598,Spain,Male,27,8,90721.52,2,1,0,109296.18,0 +2293,15779064,Chidiegwu,677,France,Male,27,2,0,2,1,1,20092.89,0 +2294,15801265,Tang,689,Spain,Female,45,0,57784.22,1,1,0,197804,1 +2295,15589204,Farrar,591,France,Male,33,9,131765.72,1,1,0,118782.06,0 +2296,15664543,Shaw,699,France,Male,40,7,0,1,0,1,152876.13,1 +2297,15582714,Napolitani,749,Germany,Male,47,9,110022.74,1,0,1,135655.29,1 +2298,15797595,Greenhalgh,709,France,Female,40,9,131569.63,1,1,1,103970.58,0 +2299,15614034,Martin,607,Germany,Male,61,2,164523.5,2,1,1,35786.76,0 +2300,15763171,Hu,650,Germany,Female,25,2,114330.95,1,1,1,25325.07,0 +2301,15647266,Y?an,651,Spain,Female,45,10,135923.16,1,1,0,18732.84,0 +2302,15757577,Odili,676,France,Female,61,8,0,2,1,1,118522.73,0 +2303,15736656,H?,723,France,Female,49,4,0,2,0,1,89972.25,0 +2304,15635078,Chiemela,714,Spain,Male,45,0,124693.48,1,0,1,187194.15,0 +2305,15680141,Yuan,759,Spain,Female,35,7,147936.42,1,1,1,106785.7,0 +2306,15576945,Clements,582,France,Male,29,0,0,1,1,0,142516.35,0 +2307,15602034,Kolesnikov,697,France,Female,34,2,126558.92,1,1,0,73334.43,0 +2308,15732020,Rutherford,610,Germany,Male,57,6,106938.11,2,0,1,186612.47,0 +2309,15611029,Hsiung,488,Germany,Female,33,4,140002.35,1,1,0,123613.81,0 +2310,15621210,Angelo,599,Germany,Male,46,9,123444.72,1,1,1,31368.08,1 +2311,15569222,Mendes,781,France,Male,32,6,147107.91,1,1,1,40066.95,0 +2312,15664639,McGregor,645,France,Male,19,9,128514.84,1,0,0,175969.19,0 +2313,15724223,Bronner,545,France,Female,55,5,0,1,0,0,10034.77,1 +2314,15644621,Mironova,597,Germany,Female,40,9,106756.01,2,1,0,151167.94,0 +2315,15756056,Ku,561,Spain,Female,28,3,0,2,1,0,191387.76,0 +2316,15700353,Evans,662,France,Female,37,6,0,2,1,0,51229.17,0 +2317,15624388,Henderson,649,Germany,Female,50,5,155393.32,1,1,1,87351.42,1 +2318,15627212,Smith,630,France,Female,36,2,110414.48,1,1,1,48984.95,0 +2319,15648005,Russell,672,Spain,Male,33,2,0,2,1,1,182738,0 +2320,15681446,Sun,636,Germany,Female,37,9,157098.52,1,1,1,153535.27,0 +2321,15775888,McDonald,593,Germany,Female,38,5,85626.6,1,1,1,125079.65,0 +2322,15749019,Wong,545,Germany,Male,45,6,93796.42,2,1,1,162321.26,0 +2323,15709928,Niu,567,Spain,Female,41,1,0,2,1,0,3414.72,0 +2324,15784676,Fanucci,583,France,Male,51,6,125268.03,2,1,0,165082.25,0 +2325,15748116,Zetticci,681,France,Female,29,2,148143.84,1,1,1,52021.39,0 +2326,15612193,Hsia,762,Spain,Male,29,10,115545.33,2,1,0,148256.43,0 +2327,15762984,McIntosh,648,Spain,Male,35,7,0,2,0,0,122899.01,0 +2328,15613713,Kozlova,644,France,Male,30,5,44928.88,1,1,1,10771.46,0 +2329,15664204,Meany,706,Spain,Male,29,2,0,2,1,1,18255.51,0 +2330,15639415,Thompson,850,France,Male,35,3,162442.35,1,1,0,183566.78,0 +2331,15806332,Le Gallienne,484,Spain,Female,39,5,0,2,1,1,175224.12,0 +2332,15614929,Cheng,508,Germany,Male,28,0,96213.82,2,1,0,147913.56,0 +2333,15695492,P'eng,439,France,Female,29,6,156569.43,1,1,0,180598.66,0 +2334,15635972,Lloyd,484,Spain,Male,36,8,0,2,1,0,186136.48,0 +2335,15616380,Wheeler,803,Spain,Female,37,1,0,2,0,0,7455.2,0 +2336,15581440,Christie,724,Germany,Female,48,6,110463.25,2,1,1,80552.11,1 +2337,15654390,He,640,France,Male,33,7,154575.76,1,1,0,25722.28,1 +2338,15660688,King,701,Spain,Female,35,9,0,2,0,0,170996.86,0 +2339,15806307,Favors,537,France,Male,37,3,0,2,1,1,20603.32,0 +2340,15647975,Vida,651,Germany,Male,26,5,147037.32,1,0,0,141763.26,0 +2341,15595728,Thomas,523,Germany,Male,41,0,119276.31,1,0,0,122284.38,1 +2342,15735388,Wayn,717,France,Female,25,7,108664.85,2,1,0,190011.85,0 +2343,15788535,Tan,593,Spain,Male,44,5,0,1,1,0,128046.98,0 +2344,15765902,Gibson,706,Germany,Male,38,5,163034.82,2,1,1,135662.17,0 +2345,15642345,Y?,714,Germany,Female,49,4,93059.34,1,1,0,7571.51,1 +2346,15641250,Calabresi,794,Spain,Male,38,9,179581.31,1,1,0,23596.24,0 +2347,15706163,Enyinnaya,518,Germany,Male,46,4,113625.93,1,0,0,92727.42,1 +2348,15746708,Ritchie,589,Germany,Male,55,7,119961.48,1,1,0,65156.83,1 +2349,15775203,Chia,824,France,Male,45,3,129209.48,1,0,0,60151.77,0 +2350,15787907,Wang,719,Germany,Female,42,5,137227.04,3,1,0,149097.38,1 +2351,15646764,Lorenzo,617,Germany,Female,58,3,119024.75,2,1,0,35199.24,1 +2352,15678284,Pai,651,France,Male,35,7,74623.5,3,1,0,129451.29,1 +2353,15726791,Nuttall,637,Spain,Female,45,2,157929.45,1,1,1,145134.49,1 +2354,15813144,Osborne,554,France,Female,26,7,92606.86,2,1,0,192709.69,0 +2355,15669342,Ferri,731,Germany,Male,35,2,127862.93,2,1,0,139083.7,0 +2356,15710366,Hamilton,569,Spain,Female,42,1,0,1,1,1,83629.6,1 +2357,15614934,McEwan,625,Germany,Female,37,4,142711.81,1,1,0,35625.41,0 +2358,15588701,Lai,592,France,Female,38,4,0,2,1,0,35338.96,0 +2359,15665438,Hs?,669,France,Male,43,1,163159.85,1,0,1,15602.8,0 +2360,15644896,Thompson,663,Germany,Male,32,3,108586.86,1,1,1,182355.21,0 +2361,15670205,Boyd,518,Germany,Female,41,5,110624.99,1,1,0,89327.67,0 +2362,15635776,Trevisani,686,Germany,Female,43,5,154846.24,2,1,1,151903.6,0 +2363,15791053,Lucciano,709,Germany,Male,45,4,122917.71,1,1,1,11.58,1 +2364,15644005,Holman,571,France,Female,33,9,0,2,0,1,77519.62,0 +2365,15796343,Bazhenov,707,France,Female,31,2,82787.93,2,0,0,91423.69,0 +2366,15751057,Douglas,701,Germany,Male,32,5,102500.34,1,0,0,106287.77,0 +2367,15623430,Hill,672,France,Male,34,9,0,2,1,0,161800.77,0 +2368,15682600,Lo,620,Germany,Male,39,9,159492.79,1,1,0,80582.34,1 +2369,15769312,Forbes,557,Spain,Male,48,10,0,2,1,1,185094.48,0 +2370,15708212,Lin,648,Spain,Female,54,7,118241.02,1,1,0,172586.89,1 +2371,15650258,Sinclair,479,France,Female,35,2,113090.4,1,1,0,195649.79,0 +2372,15604345,Kemp,730,France,Female,22,9,65763.57,1,1,1,145792.01,0 +2373,15578297,Ebelegbulam,737,Germany,Female,43,1,125537.38,1,1,0,138510.01,1 +2374,15671789,Woods,616,France,Male,31,3,94263.91,2,1,0,168895.06,0 +2375,15726186,Genovese,639,Spain,Male,29,4,133434.57,2,1,0,97983.44,0 +2376,15764618,Tseng,815,Spain,Female,39,6,0,1,1,1,85167.88,0 +2377,15730738,Chiang,786,Spain,Male,31,9,0,2,1,1,18210.36,0 +2378,15637650,Williams,549,France,Male,50,9,94748.76,2,0,1,13608.18,0 +2379,15606267,Wilson,622,France,Female,38,4,98640.74,1,1,1,110457.99,0 +2380,15625904,Wang,624,France,Male,26,9,74681.9,2,0,0,31231.35,0 +2381,15654463,Moore,841,France,Male,34,4,0,2,1,0,141582.66,0 +2382,15774151,Iadanza,614,Spain,Female,41,7,179915.85,1,0,0,14666.35,1 +2383,15693259,Wallace,676,France,Male,30,1,128207.23,1,1,1,55400.17,0 +2384,15642468,Clark,697,France,Male,42,9,132739.26,2,0,0,174667.65,0 +2385,15758531,Y?,732,France,Female,40,10,0,2,1,0,154189.08,0 +2386,15728352,Yermakov,623,France,Male,27,4,120509.81,1,0,0,142170.44,0 +2387,15637240,Wei,541,France,Male,46,4,124547.13,2,1,0,94499.06,0 +2388,15595588,Chukwunonso,773,Spain,Female,39,4,0,2,0,1,182081.45,0 +2389,15778395,McIntyre,762,Germany,Male,34,4,88815.56,2,1,0,68562.26,1 +2390,15711825,Ts'ai,655,Spain,Female,35,1,82231.51,2,1,0,88798.02,0 +2391,15599251,Chung,602,Germany,Male,32,7,184715.86,2,1,0,113781.99,0 +2392,15570004,Tsou,850,France,Male,31,3,0,2,1,0,121866.87,0 +2393,15656912,Aitken,649,Spain,Male,51,4,0,1,1,1,150390.57,0 +2394,15657342,Dawson,850,Germany,Male,28,4,147972.19,1,1,0,60708.72,1 +2395,15716284,Ward,543,France,Male,43,9,0,2,1,1,78858.07,0 +2396,15672374,Pai,672,France,Male,52,8,170008.84,1,0,0,56407.42,1 +2397,15732476,Ifeanyichukwu,600,France,Female,27,3,0,2,0,1,125698.97,0 +2398,15747724,Briggs,671,Spain,Female,34,10,0,1,1,0,23235.38,0 +2399,15633877,Morrison,706,Spain,Female,42,8,95386.82,1,1,1,75732.25,0 +2400,15672516,Wall,541,Germany,Male,51,7,90373.28,2,1,0,179861.79,0 +2401,15607827,Nebechukwu,711,Germany,Male,34,4,133467.77,2,1,1,42976.64,0 +2402,15751336,Yao,630,Spain,Male,30,3,0,2,0,1,10486.69,0 +2403,15646539,Liao,531,France,Male,31,3,96288.26,1,1,0,56794.73,0 +2404,15756901,Ch'ang,641,France,Female,26,4,91547.84,2,0,1,28157.34,0 +2405,15809286,Burke,631,Germany,Male,37,8,138292.64,2,0,0,152422.91,1 +2406,15759021,Kay,685,France,Male,35,9,0,1,1,0,167033.83,0 +2407,15725039,McIntyre,702,Spain,Male,32,8,71667.74,1,1,1,126082.18,0 +2408,15579130,Chidiegwu,708,Germany,Female,43,0,118994.84,1,1,0,181499.77,1 +2409,15754112,Musgrove,653,Spain,Male,55,7,0,2,1,1,41967.03,0 +2410,15735522,Boulger,654,Germany,Male,37,2,145610.07,2,0,0,186300.59,0 +2411,15613326,Gow,596,France,Female,33,1,138162.81,1,1,0,85412.54,0 +2412,15739502,Amaechi,549,Germany,Female,31,9,135020.21,2,1,1,23343.18,0 +2413,15670914,Robe,754,France,Male,38,2,0,2,1,0,180698.32,0 +2414,15604073,Bibi,815,Germany,Female,25,8,135161.67,1,1,1,136071.05,0 +2415,15806027,Niu,556,France,Female,52,9,0,1,1,0,175149.2,1 +2416,15574886,Palerma,706,France,Male,32,6,94486.47,1,1,1,146949.74,0 +2417,15707120,Cocci,850,France,Male,46,9,117640.39,1,1,0,88920.68,0 +2418,15800845,Artemieva,732,Spain,Female,33,8,111379.55,1,1,1,45098.62,0 +2419,15603914,Arcuri,614,France,Male,40,6,0,1,1,1,20339.79,1 +2420,15722765,Owen,580,Spain,Female,57,0,136820.99,1,0,1,108528.74,0 +2421,15783305,Franklin,593,France,Female,46,7,98752.51,1,1,0,145560.38,0 +2422,15574842,Lorenzo,653,Germany,Female,25,2,158266.42,3,1,1,199357.24,0 +2423,15607837,Muriel,746,France,Female,29,4,105599.67,1,1,1,43106.17,0 +2424,15714877,MacDevitt,662,France,Female,29,10,0,2,1,0,137508.31,0 +2425,15782941,Chijindum,573,France,Male,31,2,0,2,1,1,91957.39,0 +2426,15630167,Gibson,684,Spain,Female,39,4,139723.9,1,1,1,120612.11,0 +2427,15759038,Whitehead,793,France,Female,41,3,141806.46,1,1,0,102921.17,0 +2428,15661821,Johnstone,798,Germany,Female,49,5,132571.67,1,1,1,31686.33,1 +2429,15728006,Endrizzi,524,France,Male,40,2,180516.9,1,1,0,180002.42,0 +2430,15712176,Burke,816,France,Male,31,8,0,2,1,1,28407.4,0 +2431,15689351,Johnson,742,Germany,Female,41,4,92805.72,1,0,1,73743.95,1 +2432,15782247,Yeh,540,France,Male,22,4,0,3,1,1,186233.26,1 +2433,15769064,Marshall,537,Germany,Male,39,3,135309.36,1,1,0,31728.86,1 +2434,15718153,Kao,759,Spain,Female,74,6,128917.84,1,1,1,48244.64,0 +2435,15613189,Browne,774,France,Female,52,2,56580.93,1,1,0,113266.28,1 +2436,15661734,Taylor,608,Germany,Male,42,8,131390.75,2,1,0,71178.09,0 +2437,15592645,Gibbons,704,Spain,Male,37,4,0,2,0,0,25684.93,0 +2438,15768387,Nott,581,France,Male,41,8,0,2,0,0,29737.14,0 +2439,15792525,Lei,628,Germany,Female,61,1,97361.66,1,1,1,149922.38,1 +2440,15586976,Alexeeva,566,France,Female,42,6,0,1,1,0,180702.12,1 +2441,15790659,Sheets,701,Spain,Male,59,7,0,2,0,1,27597.59,0 +2442,15691446,Tokaryev,735,Spain,Male,29,10,0,2,1,1,95025.27,0 +2443,15772632,Ts'ui,680,France,Female,34,1,0,2,1,0,167035.07,0 +2444,15706587,Johnston,560,France,Male,57,0,0,2,0,1,116781.71,0 +2445,15572461,Kung,663,Germany,Female,29,4,102714.65,2,0,0,21170.81,0 +2446,15654409,Unwin,665,France,Female,34,5,67816.72,1,1,1,29641.58,0 +2447,15568025,Hsueh,758,France,Male,51,8,81710.46,1,1,1,116520.07,0 +2448,15715769,Hao,621,France,Male,26,2,75237.54,1,0,1,44220.4,0 +2449,15667458,L?,764,Germany,Male,28,10,124023.18,1,1,0,166188.28,0 +2450,15567980,Frater,537,Germany,Female,46,5,100727.5,1,0,1,140857.76,1 +2451,15679294,Brennan,589,France,Female,46,10,107238.85,2,1,0,37024.28,0 +2452,15606507,Pisani,555,France,Male,24,5,0,2,1,0,27513.47,0 +2453,15578825,Golubev,734,France,Female,29,0,139994.66,1,1,0,17744.72,0 +2454,15619935,Vanmeter,783,Spain,Female,59,9,126224.87,1,1,1,4423.63,0 +2455,15636089,Hs?,678,Germany,Female,51,1,145751.03,1,0,0,109718.44,1 +2456,15727490,Scott,661,France,Male,47,5,0,1,0,1,107243.31,1 +2457,15591766,Crawford,607,Spain,Female,25,4,121166.89,1,0,1,115288.24,0 +2458,15641629,P'eng,537,Spain,Female,38,1,0,2,0,1,41233.97,0 +2459,15813303,Rearick,513,Spain,Male,88,10,0,2,1,1,52952.24,0 +2460,15756920,Genovesi,576,France,Male,63,9,70655.48,1,0,0,78955.8,1 +2461,15726403,Glenny,660,Germany,Male,41,1,129901.21,1,1,0,26025.6,1 +2462,15592765,Marks,637,France,Male,40,8,125470.81,1,1,1,174536.17,0 +2463,15704442,Fleming,672,France,Female,53,9,169406.33,4,1,1,147311.47,1 +2464,15641136,Davison,629,France,Male,32,2,0,2,0,1,77965.44,0 +2465,15725818,Chibuzo,583,Germany,Male,40,4,107041.3,1,1,1,5635.63,0 +2466,15612071,Wilson,763,Spain,Female,32,10,95153.77,1,0,1,81310.1,0 +2467,15719809,Endrizzi,516,Germany,Male,32,3,145166.09,2,0,0,111421.45,0 +2468,15716518,Yuryeva,617,France,Female,27,4,0,2,0,0,190269.21,0 +2469,15742210,Ugochukwu,700,France,Male,38,9,65962.63,1,1,1,100950.48,0 +2470,15630617,Lo Duca,727,Germany,Male,36,6,140418.81,1,1,1,113033.73,1 +2471,15720838,Gallo,689,Spain,Female,31,3,139799.63,1,0,1,120663.57,0 +2472,15595537,Trout,626,Germany,Male,49,9,171787.84,2,1,0,187192.23,0 +2473,15623196,Morley,686,France,Male,38,6,149238.97,1,1,1,97825.23,0 +2474,15679249,Chou,351,Germany,Female,57,4,163146.46,1,1,0,169621.69,1 +2475,15693199,Shao,739,France,Female,37,8,0,2,1,0,191557.1,1 +2476,15661219,Trentino,627,France,Male,32,10,0,2,1,0,103287.62,0 +2477,15617136,Mazzanti,451,Germany,Female,38,9,61482.47,1,1,1,167538.66,0 +2478,15760294,Endrizzi,512,France,Female,41,8,145150.28,1,1,0,64869.32,1 +2479,15652808,Monaldo,774,France,Female,41,5,126670.37,1,1,0,102426.06,0 +2480,15657139,Otutodilinna,652,France,Female,40,8,84390.8,2,0,1,107876.2,0 +2481,15803790,Allen,638,Germany,Male,37,2,89728.86,2,1,1,37294.88,0 +2482,15764105,Milne,475,France,Female,57,1,0,2,1,0,89248.99,0 +2483,15672610,Somadina,567,Spain,Male,40,4,118628.8,1,0,0,91973.63,0 +2484,15766896,Chieloka,750,France,Male,37,3,0,2,1,0,16870.2,0 +2485,15587735,Chukwuebuka,850,France,Male,39,6,96863.13,1,1,1,121681.19,0 +2486,15659501,Chioke,753,France,Female,38,6,142263.45,1,0,1,33730.43,0 +2487,15745001,Kovalev,683,Spain,Female,36,7,0,2,1,0,104786.59,0 +2488,15651140,Doherty,710,France,Female,32,3,0,1,1,0,94790.34,0 +2489,15571148,Baranov,645,Spain,Female,21,1,0,2,0,0,28726.07,0 +2490,15776824,Rossi,714,France,Male,28,6,122724.37,1,1,1,67057.27,0 +2491,15633141,Robinson,696,Germany,Female,35,4,174902.26,1,1,0,69079.85,0 +2492,15764174,Bidencope,612,Spain,Female,26,4,0,2,1,1,179780.74,0 +2493,15778155,T'ien,520,Germany,Female,31,3,108914.17,1,1,1,183572.39,1 +2494,15715920,De Bernales,782,Spain,Male,23,10,98052.66,1,1,1,142587.32,0 +2495,15671917,Wade,666,France,Male,46,5,123873.19,1,1,1,177844.06,0 +2496,15666548,Chung,466,Germany,Female,56,2,111920.13,3,1,0,197634.11,1 +2497,15625623,Stevenson,567,France,Female,45,4,0,2,0,1,121053.19,0 +2498,15748123,Chienezie,613,France,Male,20,3,0,2,1,1,149613.77,0 +2499,15648735,Cashin,718,France,Male,37,8,0,2,1,1,142.81,0 +2500,15634974,Seppelt,614,France,Female,37,8,75150.34,4,0,1,131766.67,1 +2501,15713378,Brownless,711,France,Male,38,10,0,2,0,0,53311.78,0 +2502,15753370,McDonald,691,Germany,Female,38,5,114753.76,1,1,0,107665.02,0 +2503,15782659,Mamelu,527,France,Male,32,0,0,1,1,0,109523.88,0 +2504,15583364,McGregor,476,France,Female,32,6,111871.93,1,0,0,112132.86,0 +2505,15625942,McDonald,619,Spain,Female,45,0,0,2,0,0,113645.4,0 +2506,15720284,Crawford,607,Germany,Female,37,4,135927.06,1,0,0,180890.4,0 +2507,15679642,Feng,695,Spain,Male,44,8,0,2,1,1,70974.13,0 +2508,15628007,Genovese,653,France,Male,33,1,0,2,0,0,53379.52,0 +2509,15661974,Pirozzi,677,France,Male,46,2,57037.74,1,1,1,158531.01,0 +2510,15689341,Gibbs,655,France,Female,50,10,0,4,1,0,179267.94,1 +2511,15607993,Milne,625,France,Female,52,2,79468.96,1,1,1,84606.03,0 +2512,15693267,Dickson,679,Germany,Female,34,7,121063.85,1,1,0,56984.58,0 +2513,15769522,O'Connor,734,France,Male,51,1,118537.47,1,1,1,116912.45,0 +2514,15755825,McGuirk,666,France,Male,39,10,0,2,1,0,102999.33,0 +2515,15598175,Toscani,592,Germany,Female,26,4,105082.07,2,1,0,132801.57,0 +2516,15744327,Ruth,564,France,Male,40,4,0,1,1,0,85455.62,1 +2517,15798666,Hughes,814,France,Female,36,6,0,2,1,1,98657.01,0 +2518,15577064,Onyekaozulu,592,Germany,Male,36,2,104702.65,2,1,0,107948.72,0 +2519,15759436,Aksenov,758,France,Female,50,2,95813.76,3,1,1,67944.09,1 +2520,15690231,K'ung,612,Spain,Female,62,0,167026.61,2,1,1,192892.05,0 +2521,15751561,Meng,498,Germany,Male,61,7,102453.26,1,1,0,187247.56,1 +2522,15739068,Nwoye,638,Germany,Male,25,4,148045.45,2,1,1,114722.42,0 +2523,15758056,Calabresi,558,France,Male,35,1,0,2,0,0,111687.57,0 +2524,15742269,Milano,756,France,Female,24,1,0,2,1,0,184182.25,0 +2525,15726490,Kirby,782,Spain,Male,52,4,0,1,1,1,52759.82,1 +2526,15738411,Ho,505,France,Male,34,10,104498.79,1,0,1,126451.14,0 +2527,15727919,Chukwuemeka,671,Spain,Female,29,6,0,2,0,0,12048.67,0 +2528,15709396,Hale,801,France,Male,42,6,0,2,1,1,95804.33,0 +2529,15654106,K?,604,France,Male,26,8,149542.52,2,0,1,197911.52,0 +2530,15621653,Rice,716,France,Female,29,10,87946.39,1,1,1,182531.74,0 +2531,15598086,Brown,624,France,Female,45,3,68639.57,1,1,0,168002.31,1 +2532,15752300,Sagese,607,Germany,Male,47,4,148826.32,1,1,1,79450.61,0 +2533,15658693,Aksyonova,827,France,Female,60,2,0,2,0,1,60615.83,0 +2534,15631838,Findlay,606,France,Male,61,5,108166.09,2,0,1,8643.21,0 +2535,15803804,Walker,717,Germany,Female,35,5,103214.71,1,1,0,172172.7,0 +2536,15578809,Hao,651,Germany,Male,40,1,134760.21,2,0,0,174434.06,1 +2537,15752026,Hammer,691,France,Male,58,3,0,1,0,1,194930.3,1 +2538,15723706,Abbott,573,France,Female,33,0,90124.64,1,1,0,137476.71,0 +2539,15752838,Lucas,723,Spain,Male,38,6,0,2,1,1,94415.6,0 +2540,15569571,Davydova,584,Germany,Female,46,6,87361.02,2,1,0,120376.87,1 +2541,15769703,West,550,Germany,Female,45,8,111257.59,1,0,0,97623.42,1 +2542,15679770,Smith,611,France,Female,61,3,131583.59,4,0,1,66238.23,1 +2543,15791102,Mai,549,Germany,Male,41,9,95020.8,3,1,1,131710.59,1 +2544,15655192,Fiorentino,850,Spain,Female,24,1,0,2,0,1,69052.87,0 +2545,15709487,Freeman,668,Germany,Male,34,5,80242.37,2,0,0,56780.97,0 +2546,15687130,Nkemjika,686,France,Female,43,0,0,1,1,1,170072.9,0 +2547,15755178,Ramos,660,France,Male,50,1,0,3,1,1,191849.15,1 +2548,15634772,Mario,682,Spain,Female,59,0,122661.39,1,0,1,84803.76,0 +2549,15617197,Chien,524,France,Male,50,4,0,2,1,1,31840.59,1 +2550,15631240,Dubinina,645,France,Female,36,8,0,2,1,1,12096.61,1 +2551,15784301,Wang,850,France,Male,42,0,0,2,1,0,44165.84,0 +2552,15631310,Hsieh,537,France,Female,53,3,0,1,1,1,91406.62,0 +2553,15756560,Moran,599,Spain,Female,46,7,81742.84,2,1,0,83282.21,0 +2554,15732270,Hung,727,Spain,Male,71,8,0,1,1,1,198446.91,1 +2555,15739357,Moss,756,Spain,Male,30,2,145127.85,1,0,0,7554.68,0 +2556,15771540,Fedorova,755,France,Male,38,9,148912.44,1,1,0,80416.16,0 +2557,15567486,Li,634,Spain,Female,41,4,0,2,1,1,164549.74,0 +2558,15714634,Nebechi,837,France,Male,26,4,89900.24,2,1,0,175477.03,0 +2559,15727021,Obialo,727,Germany,Female,30,8,119027.28,2,1,1,137903.54,0 +2560,15650670,Bateson,567,Germany,Female,40,2,105222.86,2,1,0,93795.86,0 +2561,15711834,Long,650,Spain,Female,30,6,0,1,0,0,67997.13,1 +2562,15729763,Nelson,655,Spain,Male,34,1,116114.93,1,1,1,49492.15,0 +2563,15646566,Bell,763,France,Female,58,9,187911.55,1,0,1,35825.18,0 +2564,15645463,Udinese,843,France,Female,27,5,0,2,1,1,67494.23,0 +2565,15672144,Mao,667,France,Female,38,6,144432.04,1,1,1,73963.17,1 +2566,15596088,Fanucci,705,France,Female,50,4,77065.9,2,0,1,145159.26,0 +2567,15614878,Yeh,660,Germany,Female,29,6,180520.29,1,1,1,123850.58,0 +2568,15635240,Onuoha,553,France,Male,42,1,0,2,0,0,23822.04,0 +2569,15775905,Moore,612,Germany,Female,47,6,130024.87,1,1,1,45750.21,1 +2570,15700657,Thornton,641,Germany,Female,40,2,110086.69,1,1,0,159773.14,0 +2571,15611905,Warlow-Davies,513,Spain,Female,31,5,174853.46,1,1,0,84238.63,0 +2572,15652527,Champion,680,France,Male,44,7,108724.98,1,0,1,72330.46,0 +2573,15785865,Mazzanti,711,France,Male,58,9,91285.13,2,1,1,26767.85,0 +2574,15645942,Macleod,689,Spain,Male,40,2,0,2,1,1,164768.82,0 +2575,15688691,Lei,665,Germany,Female,51,9,110610.41,2,0,1,1112.76,1 +2576,15592736,Lucchese,551,Germany,Male,54,5,102994.04,1,1,0,176680.16,1 +2577,15673529,Lombardo,645,Spain,Male,36,4,59893.85,2,1,0,43999.64,0 +2578,15724145,William,616,Germany,Male,29,8,149318.55,1,1,0,140746.13,0 +2579,15704629,Wright,582,France,Female,32,1,116409.55,1,0,1,152790.92,0 +2580,15597896,Ozoemena,365,Germany,Male,30,0,127760.07,1,1,0,81537.85,1 +2581,15731790,Boyle,697,Germany,Female,38,6,132591.36,1,1,1,7387.8,1 +2582,15634719,Chinwendu,704,France,Male,31,0,0,2,1,0,183038.33,0 +2583,15703205,Uwaezuoke,656,France,Female,46,5,113402.14,2,1,1,138849.06,0 +2584,15567333,Archambault,712,France,Female,31,7,0,2,1,0,170333.38,0 +2585,15754537,Ko,748,France,Male,40,0,0,1,0,0,60416.76,0 +2586,15612030,Udegbulam,724,France,Male,28,9,0,2,1,1,100240.2,0 +2587,15573242,Greene,691,France,Male,50,6,136953.47,1,1,1,2704.98,0 +2588,15601892,Hunter,563,France,Male,33,8,0,2,0,1,68815.05,0 +2589,15663885,Blinova,741,France,Male,32,5,0,1,1,1,64839.23,0 +2590,15701096,De Garis,778,France,Male,44,8,123863.64,1,1,0,144494.94,0 +2591,15710450,Okwudiliolisa,848,Spain,Male,22,7,120811.89,1,1,1,185510.34,0 +2592,15790846,Ts'ai,634,Germany,Male,38,2,148430.55,1,1,1,56055.72,0 +2593,15658956,Tuan,505,Germany,Male,40,6,47869.69,2,1,1,155061.97,0 +2594,15755223,Tseng,692,Germany,Male,53,7,150926.99,2,0,0,119817.19,0 +2595,15787318,Holmwood,537,Germany,Female,47,6,103163.35,1,1,0,16259.64,1 +2596,15737310,Thompson,633,France,Male,29,10,130206.28,1,1,0,184654.87,0 +2597,15763665,Y?,833,France,Female,28,4,136674.51,2,0,0,5278.78,0 +2598,15668818,Chidubem,592,Spain,Female,40,2,200322.45,1,1,1,113244.73,0 +2599,15765812,Trevisani,587,Spain,Male,48,1,0,2,1,1,8908,0 +2600,15704844,Hsiung,550,Spain,Male,62,7,80927.56,1,0,1,64490.67,0 +2601,15744582,Randall,680,France,Female,24,10,0,3,1,0,154971.63,1 +2602,15616700,Leach,622,Spain,Female,41,9,0,2,1,1,155786.39,0 +2603,15683521,Godfrey,594,Germany,Male,28,0,142574.71,2,1,0,129084.82,0 +2604,15583049,Wallace,643,Germany,Female,34,7,160426.07,1,0,1,188533.11,0 +2605,15643752,Wei,540,France,Male,25,5,116160.23,1,1,0,13411.67,0 +2606,15620398,Mitchell,635,Spain,Female,34,5,98683.47,2,1,0,15733.19,0 +2607,15715707,Light,657,France,Male,32,3,118829.03,2,1,1,73127.61,0 +2608,15814209,Capon,814,France,Male,31,1,118870.92,1,1,0,101704.19,0 +2609,15733768,Hou,600,France,Male,32,1,0,1,1,1,101986.16,0 +2610,15755242,Rowe,682,France,Female,46,2,0,1,1,1,114442.66,0 +2611,15729412,Holloway,682,France,Male,38,4,107192.38,1,1,1,15669.17,0 +2612,15746564,O'Sullivan,566,France,Male,42,3,108010.78,1,1,1,157486.1,0 +2613,15588446,Udinesi,550,Spain,Male,34,3,0,2,0,0,131281.28,0 +2614,15665221,Nwebube,630,France,Male,26,7,129837.72,2,0,1,197001.15,0 +2615,15640846,Chibueze,546,Germany,Female,58,3,106458.31,4,1,0,128881.87,1 +2616,15700209,Walker,486,France,Male,63,9,97009.15,1,1,1,85101,0 +2617,15658360,Gregory,762,Spain,Male,35,9,122929.42,2,0,0,149822.04,0 +2618,15602735,Kuo,692,Germany,Male,45,6,152296.83,4,0,1,108040.86,1 +2619,15724834,Wilson,498,France,Female,30,1,0,2,0,0,135795.53,0 +2620,15800062,Lanford,850,Spain,Male,49,8,0,1,0,0,25867.67,1 +2621,15685300,Meng,603,France,Male,35,6,128993.76,2,1,0,130483.56,0 +2622,15760102,Yeh,551,France,Female,36,5,0,1,1,0,183479.12,0 +2623,15787026,Onwuatuegwu,627,Germany,Male,27,0,185267.45,2,1,1,77027.34,0 +2624,15653696,Goliwe,515,France,Female,28,9,0,2,0,0,94141.75,0 +2625,15788946,Anthony,605,Spain,Female,29,3,116805.82,1,0,0,4092.75,0 +2626,15600724,Scott,567,Germany,Male,29,5,129750.68,1,1,0,109257.59,0 +2627,15574324,Genovese,568,Germany,Female,29,2,129177.01,2,0,1,104617.99,0 +2628,15707144,Onyeorulu,571,Germany,Male,25,6,82506.72,2,1,0,167705.07,0 +2629,15775891,Myers,634,Germany,Male,48,2,107247.69,1,1,1,103712.05,1 +2630,15711789,Davey,768,Spain,Female,42,3,0,1,0,0,161242.99,1 +2631,15600879,Parsons,554,Germany,Female,36,3,157780.93,2,1,0,6089.13,0 +2632,15681196,Chikere,629,France,Male,35,1,172170.36,1,1,1,159777.37,0 +2633,15716000,Hs?eh,638,Spain,Male,48,2,0,2,1,1,7919.08,0 +2634,15766776,Sal,576,France,Male,41,1,0,1,1,1,188274.6,0 +2635,15680278,Ts'ai,661,Spain,Female,42,9,75361.44,1,1,0,27608.12,1 +2636,15688637,Witt,592,France,Female,27,4,0,2,1,1,183569.25,0 +2637,15591179,Skelton,702,Spain,Male,30,2,0,2,1,1,145537.32,0 +2638,15677435,Kazantseva,647,France,Female,29,0,98263.46,2,1,0,164717.95,0 +2639,15698619,Bowhay,593,France,Male,43,9,0,2,1,1,76357.43,0 +2640,15581036,Beyer,712,Germany,Female,40,3,109308.79,2,1,0,120158.72,1 +2641,15622117,Fries,625,Spain,Female,31,8,0,2,1,0,151843.54,0 +2642,15599301,Tao,538,Germany,Female,28,6,164365.44,1,0,1,5698.97,0 +2643,15581548,Kaodilinakachukwu,637,Spain,Female,22,5,98800,1,1,0,122865.55,0 +2644,15586870,Ni,632,France,Male,27,4,193125.85,1,1,1,152665.85,0 +2645,15735263,Hsueh,736,France,Male,27,5,51522.75,1,0,1,192131.77,0 +2646,15765322,Connely,755,France,Male,23,5,84284.48,2,1,1,62851.6,0 +2647,15582944,Becker,425,Spain,Female,39,5,0,2,1,0,140941.47,0 +2648,15687162,Clayton,461,France,Male,51,9,119889.84,1,0,0,56767.67,1 +2649,15644962,Connolly,745,France,Male,21,4,137910.45,1,1,1,177235.23,0 +2650,15612615,Graham,616,France,Female,37,6,0,2,1,0,86242.18,0 +2651,15813439,Ch'ien,587,France,Male,33,5,100116.82,1,1,0,34215.58,0 +2652,15604544,Manfrin,850,Germany,Male,40,4,166082.15,2,0,1,44406.17,0 +2653,15761348,Kuo,601,France,Female,38,0,0,2,1,0,165196.65,0 +2654,15785078,Fomin,730,Spain,Male,26,3,0,1,1,0,34542.41,0 +2655,15759874,Chamberlain,532,France,Male,44,3,148595.55,1,1,0,74838.64,1 +2656,15643658,Barber,850,Germany,Male,53,2,94078.97,2,1,0,36980.54,0 +2657,15713267,Zimmer,779,Spain,Female,34,5,0,2,0,1,111676.63,0 +2658,15737782,Brazenor,562,France,Male,29,9,0,1,1,1,25858.68,0 +2659,15815490,Cocci,670,Germany,Male,40,2,164948.98,3,0,0,177028,1 +2660,15679410,Caldwell,729,France,Female,62,4,140549.4,1,1,0,30990.16,1 +2661,15756241,Yirawala,767,France,Female,44,2,152509.25,1,1,1,136915.15,0 +2662,15688409,Donaldson,742,France,Female,28,2,191864.51,1,1,0,108457.99,1 +2663,15742272,Ozerova,669,France,Female,44,8,96418.09,1,0,0,131609.48,1 +2664,15717898,Bruce,542,Spain,Male,32,2,131945.94,1,0,1,159737.56,0 +2665,15769582,Kang,586,France,Male,29,3,0,2,1,1,142238.54,0 +2666,15635660,Rossi,612,Germany,Male,30,9,142910.15,1,1,0,105890.55,1 +2667,15576723,Ts'ai,740,France,Female,37,7,0,2,1,1,194270.91,0 +2668,15591577,Moran,584,France,Male,35,3,146311.58,1,1,1,105443.47,0 +2669,15582325,Jennings,524,France,Male,52,2,87894.26,1,1,0,173899.42,1 +2670,15693947,Tokareva,614,France,Female,19,5,97445.49,2,1,0,122823.34,0 +2671,15760446,Pagnotto,598,France,Female,64,9,0,1,0,1,13181.37,1 +2672,15611105,Castella,799,Spain,Male,35,7,0,2,0,1,140780.8,0 +2673,15630920,Du Cane,724,France,Male,34,2,154485.74,2,0,0,78560.64,0 +2674,15574910,Ferguson,601,France,Male,50,2,115625.07,1,1,0,185855.21,0 +2675,15756472,Odinakachukwu,804,France,Male,25,7,108396.67,1,1,0,128276.95,0 +2676,15682890,Woronoff,745,Germany,Male,38,5,65095.41,2,1,1,140197.42,0 +2677,15641994,Meng,667,Germany,Male,43,1,103018.45,1,1,0,32462.39,1 +2678,15733297,Sinclair,518,France,Female,38,10,84764.79,1,1,1,162253.9,0 +2679,15767793,Hsu,819,France,Female,38,10,0,2,1,0,30498.7,0 +2680,15725698,Panicucci,520,Spain,Female,35,4,115680.81,1,1,1,90280.7,0 +2681,15813532,Burns,625,France,Female,39,5,0,2,1,0,32615.21,0 +2682,15576760,Onodugoadiegbemma,673,Germany,Male,36,5,73088.06,2,0,0,196142.26,0 +2683,15732102,Darling,656,Germany,Female,27,3,150905.03,2,1,0,16998.72,0 +2684,15739046,Maggard,850,Spain,Female,23,9,143054.85,1,0,1,62980.96,0 +2685,15631927,Thomas,574,Spain,Female,28,7,0,2,0,0,185660.3,0 +2686,15672115,Lettiere,679,France,Male,60,6,0,2,1,1,77331.77,0 +2687,15618765,Ponomaryov,530,Germany,Female,42,0,99948.45,1,0,1,97338.62,0 +2688,15679148,Oliver,508,France,Male,44,3,115451.05,2,0,0,67234.33,0 +2689,15728474,Chienezie,558,Germany,Male,32,4,108235.91,1,1,1,143783.28,0 +2690,15636999,Mao,414,France,Male,38,8,0,1,0,1,77661.12,1 +2691,15754261,Ho,648,Spain,Male,42,2,98795.61,2,1,0,89123.99,0 +2692,15629150,Lucchese,721,France,Female,37,1,0,2,1,0,70810.8,0 +2693,15736274,Prokhorova,751,France,Male,31,8,0,2,0,0,17550.49,0 +2694,15627697,Alekseyeva,662,France,Male,34,2,0,2,0,1,21497.27,0 +2695,15721585,Blacklock,628,Germany,Male,29,3,113146.98,2,0,1,124749.08,0 +2696,15639946,Sazonova,597,Germany,Female,39,8,162532.14,3,1,0,36051.46,1 +2697,15792176,Henty,698,Spain,Female,40,0,92053.44,1,1,1,143681.83,0 +2698,15699450,Li,723,France,Male,48,7,0,2,1,1,150694.58,0 +2699,15729954,Azuka,586,France,Female,28,5,0,3,1,0,170487.4,1 +2700,15600103,Alexander,633,Germany,Female,29,8,104944.1,1,1,1,97684.46,0 +2701,15786200,Brock,564,France,Male,31,4,0,2,1,0,53520.03,0 +2702,15797010,Shen,649,France,Female,31,2,0,2,1,0,15200.61,0 +2703,15670172,Padovesi,622,France,Female,30,4,107879.04,1,0,1,196894.62,0 +2704,15627352,Bulgakov,459,Germany,Male,46,7,110356.42,1,1,0,4969.13,1 +2705,15622494,Mazzanti,718,France,Male,27,2,0,2,0,0,26229.24,0 +2706,15585835,Lord,655,Spain,Female,34,4,109783.69,2,1,0,134034.32,0 +2707,15595071,Ramos,696,France,Male,22,9,149777,1,1,1,198032.93,0 +2708,15628203,Pai,637,France,Female,38,3,104339.56,1,0,0,119882.86,0 +2709,15667190,Yuan,630,Spain,Female,21,1,85818.18,1,1,1,133102.3,0 +2710,15780212,Mao,592,France,Male,37,4,212692.97,1,0,0,176395.02,0 +2711,15766869,Uspenskaya,634,Germany,Male,37,1,89696.84,2,1,1,193179.88,0 +2712,15775741,Powell,608,France,Female,28,9,0,2,1,1,125062.02,0 +2713,15628170,Brown,565,Germany,Female,32,9,68067.24,1,1,0,143287.58,0 +2714,15701318,Poole,763,Spain,Male,67,9,148564.66,1,0,1,87236.4,0 +2715,15710928,McChesney,665,France,Female,55,8,136354.16,1,1,1,93769.89,0 +2716,15682547,Lucchese,649,France,Male,38,1,122214,1,0,1,88965.46,0 +2717,15631170,Clements,695,France,Male,45,3,0,2,1,1,30793.61,0 +2718,15648702,Yuriev,775,Germany,Male,70,6,119684.88,2,1,1,74532.02,0 +2719,15783444,Endrizzi,788,France,Female,39,3,135139.33,1,0,1,113086.08,0 +2720,15809178,Pan,569,Germany,Female,42,9,146100.75,1,1,0,32574.01,1 +2721,15806688,Manfrin,726,Spain,Female,56,8,123110.9,3,0,1,130113.78,1 +2722,15576824,Kennedy,564,Germany,Female,44,3,111760.4,3,1,1,104722.47,1 +2723,15675422,Conway,544,France,Female,32,9,110728.39,1,1,1,14559.62,0 +2724,15681550,Lablanc,614,France,Female,41,8,121558.46,1,1,1,598.8,0 +2725,15812628,Dodd,453,Germany,Female,38,8,120623.21,1,1,0,129697.99,0 +2726,15597951,Muir,471,France,Female,58,4,114713.57,1,1,1,36315.03,0 +2727,15807045,Milanesi,829,Germany,Female,37,3,103457.76,1,0,0,1114.12,0 +2728,15581748,Shen,754,Germany,Male,57,2,101134.87,2,1,1,70954.41,0 +2729,15770420,Dillon,749,Germany,Male,46,10,78136.36,2,1,1,73470.98,0 +2730,15608230,Hoelscher,667,France,Male,23,1,0,2,1,0,91573.19,0 +2731,15730339,Bell,670,Spain,Male,30,3,133446.34,1,0,0,3154.95,0 +2732,15712584,Liao,670,France,Female,33,7,0,2,1,1,88187.81,0 +2733,15592816,Udokamma,623,Germany,Female,48,1,108076.33,1,1,0,118855.26,1 +2734,15641480,Sinnett,571,France,Male,32,5,131354.25,1,1,0,125256.53,0 +2735,15708505,Palerma,641,Germany,Female,37,7,62974.64,2,0,1,39016.43,0 +2736,15791131,Chimaijem,551,Germany,Female,30,2,143340.44,1,1,0,145796.49,0 +2737,15618225,Porter,741,Germany,Male,36,8,116993.43,2,1,0,168816.22,0 +2738,15644724,Fan,472,France,Male,31,4,58662.92,2,0,1,73322,0 +2739,15662098,Palmer,650,Spain,Male,41,3,128808.65,3,0,0,113677.53,1 +2740,15723894,Younger,625,France,Male,45,7,137555.44,1,0,0,124607.7,0 +2741,15787699,Burke,650,Germany,Male,34,4,142393.11,1,1,1,11276.48,0 +2742,15687738,Nwagugheuzo,535,France,Female,38,8,0,2,1,0,136620.64,0 +2743,15576126,Young,649,France,Female,41,2,125785.23,1,1,1,70523.92,0 +2744,15658889,Watson,689,France,Male,22,4,136444.25,1,1,0,51980.25,1 +2745,15667046,Tseng,694,Spain,Male,38,7,121527.4,1,1,0,113481.02,0 +2746,15669957,Drake,655,Germany,Male,52,9,144696.75,1,1,1,49025.79,0 +2747,15655794,Hanna,620,France,Male,36,8,0,2,1,1,145937.99,0 +2748,15599829,Padovesi,577,France,Female,35,10,0,2,1,1,25161.61,0 +2749,15753332,Loftus,401,Germany,Male,48,8,128140.17,1,1,0,175753.55,1 +2750,15671124,Buccho,599,France,Male,25,6,120383.41,1,1,1,24903.09,0 +2751,15767474,Lorenzo,481,France,Female,57,9,0,3,1,1,169719.35,1 +2752,15720671,Ibezimako,704,France,Male,42,8,129735.3,2,1,1,179565.57,0 +2753,15626787,Wei,698,Spain,Female,31,8,185078.26,1,0,0,115337.74,1 +2754,15774491,Ross,480,France,Female,28,6,0,2,0,0,48131.92,0 +2755,15579647,Oluchukwu,682,France,Male,42,0,0,1,1,1,160828.98,0 +2756,15625522,Walker,700,Spain,Male,31,7,0,2,0,1,145151.96,0 +2757,15765806,Wu,492,France,Male,29,1,144591.96,1,1,1,196293.76,0 +2758,15566708,Chidalu,444,France,Female,45,4,0,2,1,0,161653.5,1 +2759,15668347,Ingram,624,France,Male,36,6,0,2,0,0,84635.64,0 +2760,15575214,Ch'en,709,France,Male,37,7,0,1,1,0,159486.76,0 +2761,15591123,Iredale,557,Germany,Male,68,2,100194.44,1,1,1,38596.34,0 +2762,15573280,Gallagher,646,Germany,Male,50,6,145295.31,2,1,1,27814.74,0 +2763,15589018,Padilla,719,Germany,Male,28,3,106070.29,2,1,1,183893.31,0 +2764,15654495,Potter,706,Germany,Female,47,6,120621.89,1,1,1,140803.7,0 +2765,15597265,Mao,660,France,Male,38,7,0,2,0,1,146585.53,0 +2766,15733876,Schneider,667,France,Male,36,9,0,2,1,1,40062.29,0 +2767,15677217,Ibragimova,705,France,Male,30,1,0,1,1,1,181300.32,0 +2768,15747265,Huang,598,Germany,Female,27,10,171283.91,1,1,1,84136.12,0 +2769,15713379,Anderson,669,France,Male,26,4,0,2,1,1,197594.34,0 +2770,15730433,Nakayama,580,Germany,Female,38,1,128218.47,1,1,0,125953.83,1 +2771,15693347,Gardener,676,France,Female,32,5,0,2,1,1,75465.41,0 +2772,15715465,Aksenova,714,Germany,Male,28,7,77776.39,1,1,0,177737.07,0 +2773,15680736,Milne,597,Germany,Female,72,6,124978.19,2,1,1,7144.46,0 +2774,15610765,Onwumelu,559,France,Male,29,1,0,2,0,0,155639.76,0 +2775,15650034,Kudryashova,564,France,Female,28,1,0,1,1,1,162428.05,0 +2776,15782468,Hart,850,Spain,Male,51,3,109799.55,2,1,1,12457.76,1 +2777,15685109,Teng,689,France,Male,39,7,0,2,0,0,14917.09,0 +2778,15776233,Kruglova,758,Germany,Female,61,8,125397.21,1,1,0,182184.09,1 +2779,15761141,Palerma,604,Spain,Female,71,10,0,2,1,1,129984.2,0 +2780,15781702,Brookes,733,Germany,Male,38,9,111347.37,2,0,1,194872.97,0 +2781,15790235,Hsing,778,Spain,Male,40,8,104291.41,2,1,1,117507.11,0 +2782,15641416,Shaffer,732,Germany,Female,61,9,94867.18,2,1,1,157527.6,1 +2783,15775234,Laurie,646,France,Male,24,8,0,2,0,0,92612.88,0 +2784,15659475,Chung,597,France,Female,33,6,135703.59,2,0,0,74850.84,0 +2785,15642202,Whitfield,821,Germany,Female,37,5,106453.53,2,0,1,127413,0 +2786,15771417,Thomas,640,France,Male,43,7,132412.38,1,0,0,69584.3,1 +2787,15585100,Rioux,511,Germany,Female,40,9,124401.6,1,1,0,198814.24,1 +2788,15700487,Osonduagwuike,805,France,Male,46,6,118022.06,3,1,0,162643.15,1 +2789,15726589,Matveyev,540,Germany,Male,39,1,82531.11,1,1,0,114092.52,0 +2790,15747503,Hayward,705,Spain,Male,44,0,184552.12,1,1,0,68860.3,1 +2791,15595883,Nkemdirim,540,Germany,Male,39,4,127278.31,1,1,1,16150.34,0 +2792,15663826,Brim,532,Spain,Female,66,3,0,1,1,1,115227.02,0 +2793,15742820,Trevisano,535,France,Female,45,2,0,2,0,1,170621.55,0 +2794,15624793,Soubeiran,627,Germany,Male,23,5,184244.86,1,1,0,103099.22,0 +2795,15597930,Wilson,646,France,Male,52,8,59669.43,1,0,0,172495.81,1 +2796,15665110,Helena,515,France,Female,25,7,79543.59,1,0,1,38772.82,0 +2797,15770719,Duncan,697,France,Female,39,6,151553.19,1,1,1,44946.29,0 +2798,15731327,Hale,652,Germany,Male,27,2,166527.88,2,0,1,146007.7,0 +2799,15576044,Macdonald,579,Germany,Male,28,6,150329.15,1,1,0,145558.42,0 +2800,15775662,McKay,760,France,Male,43,8,121911.59,1,1,0,193312.33,0 +2801,15646817,Chiekwugo,769,France,Male,51,9,156773.78,2,1,0,40257.79,0 +2802,15596060,Skinner,498,Spain,Male,29,8,127864.26,1,1,1,46677.9,0 +2803,15723299,Sorokina,774,France,Male,53,4,113709.28,1,1,1,153887.93,1 +2804,15636982,Weller,705,Germany,Female,43,7,79974.55,1,1,1,103108.33,0 +2805,15751175,Bess,648,France,Female,44,2,0,2,1,1,58652.23,0 +2806,15618936,MacDonald,688,France,Female,51,5,0,1,1,0,91624.11,1 +2807,15787529,Gray,592,Spain,Male,38,0,0,1,1,0,65986.48,1 +2808,15780128,Ogbonnaya,705,France,Male,33,3,144427.96,2,1,0,113845.19,0 +2809,15615991,Udegbulam,654,France,Male,42,7,99263.09,1,1,1,67607.9,0 +2810,15757001,Mai,624,France,Female,32,2,79368.87,2,1,1,145471.94,0 +2811,15595388,Yeh,594,France,Female,30,10,0,2,1,1,124071.71,0 +2812,15699550,Babbage,695,Spain,Female,34,9,0,2,1,1,67502.12,0 +2813,15581620,Franklin,597,France,Male,28,2,0,3,1,1,78707.97,0 +2814,15600934,Randell,758,France,Female,52,7,125095.94,1,1,0,171189.83,1 +2815,15738672,Paterson,737,Germany,Female,40,2,162485.8,2,1,0,149381.32,0 +2816,15721307,Pickering,694,Germany,Male,37,1,95668.82,2,1,0,100335.55,0 +2817,15619280,Uspensky,683,France,Male,25,4,0,2,1,0,152698.24,0 +2818,15768244,Macleod,538,Spain,Female,30,8,0,2,1,1,41192.95,0 +2819,15806837,Nnaife,669,France,Male,37,4,0,1,1,0,132540.33,0 +2820,15643496,Randolph,730,France,Female,34,5,74197.38,2,1,0,96875.52,0 +2821,15813916,Kudryashova,622,France,Female,31,1,89688.94,1,1,1,152305.47,0 +2822,15626385,George,714,Spain,Female,33,10,103121.33,2,1,1,49672.01,0 +2823,15603582,Robertson,569,Spain,Female,34,3,0,1,1,0,133997.53,0 +2824,15764351,Yuryeva,668,Germany,Female,59,5,120170.07,1,0,1,50454.8,0 +2825,15667938,Hurst,628,France,Male,32,9,149136.31,2,1,1,16402.11,0 +2826,15576360,Ch'iu,600,France,Male,40,1,141136.79,1,1,1,67803.83,0 +2827,15628813,King,693,France,Female,43,4,152341.55,1,1,0,9241.78,0 +2828,15584190,Esposito,704,France,Male,36,7,120026.98,2,0,1,100601.73,0 +2829,15716449,Fraser,527,Spain,Male,33,9,132168.28,1,0,0,98734.15,0 +2830,15759913,Trentini,553,Germany,Male,43,6,85200.82,2,1,1,160574.09,0 +2831,15701555,Nicholls,575,Spain,Male,53,1,84903.33,2,0,1,26015.8,0 +2832,15758482,Montalvo,626,France,Female,32,0,0,2,0,0,187172.54,0 +2833,15758171,Tien,582,France,Male,20,4,0,1,1,1,55763.66,0 +2834,15680346,Chuang,683,Spain,Male,40,8,0,1,1,0,75848.22,0 +2835,15649124,Fang,850,France,Male,30,9,121535.18,1,0,0,40313.47,0 +2836,15812917,Kosisochukwu,653,Spain,Male,35,6,116662.96,2,1,1,23864.21,0 +2837,15768455,Young,679,France,Male,60,8,0,2,1,1,51380.9,0 +2838,15703059,Scott,549,Germany,Female,49,6,124829.16,1,0,1,93551.36,0 +2839,15646196,Yeh,850,Spain,Female,36,2,155180.56,2,0,0,169415.54,0 +2840,15585451,Vigano,558,Germany,Female,32,1,108262.87,1,1,1,6935.31,0 +2841,15714057,Windradyne,528,Spain,Male,40,4,0,2,1,0,25399.7,0 +2842,15748473,Curnow,801,France,Male,38,5,0,2,1,0,66256.27,0 +2843,15785782,Ugonna,513,Spain,Male,48,2,0,1,1,1,114709.13,1 +2844,15693233,De Neeve,666,Germany,Male,38,6,99812.88,2,1,1,158357.97,0 +2845,15757521,Ricci,606,France,Male,35,2,132164.26,1,0,1,164815.59,0 +2846,15812513,Nnaife,599,Germany,Male,45,10,103583.05,1,1,0,132127.69,1 +2847,15674950,Ebelechukwu,544,Germany,Male,39,4,142406.43,2,1,0,146637.45,0 +2848,15678572,Keating,529,Spain,Male,38,7,99842.5,2,1,0,90256.06,1 +2849,15713608,Tuan,850,France,Female,41,5,0,2,1,1,34827.43,0 +2850,15579262,Shearston,497,France,Male,41,9,0,1,0,0,22074.48,0 +2851,15610426,Tien,764,France,Female,39,5,81042.42,1,0,1,109805.17,0 +2852,15776454,Hamilton,603,France,Female,48,5,0,1,1,0,100478.6,1 +2853,15771483,Arnold,609,France,Male,40,6,0,2,1,1,97416.34,0 +2854,15648489,Ting,487,France,Male,53,4,199689.49,1,1,1,24207.86,1 +2855,15646609,Chao,748,France,Male,33,1,142645.43,1,0,0,69132.66,0 +2856,15693203,Powell,710,Spain,Female,75,5,0,2,1,1,9376.89,0 +2857,15813067,Williams,432,Germany,Female,45,3,110219.14,1,1,0,43046.7,1 +2858,15769829,Cheng,534,Spain,Male,51,3,0,2,0,1,20856.31,0 +2859,15662434,Zhdanova,607,France,Male,25,3,0,2,0,0,187048.72,0 +2860,15773503,Tsai,551,Spain,Male,32,4,0,2,1,0,53420.53,0 +2861,15705890,Nebechukwu,674,France,Male,45,7,142072.02,1,1,0,37013.29,0 +2862,15711398,Fetherstonhaugh,525,France,Female,25,6,0,2,1,0,89566.64,0 +2863,15752375,Ojiofor,645,Germany,Male,33,8,149564.61,1,0,0,149913.84,0 +2864,15659175,Severson,755,France,Female,43,9,0,2,1,0,18066.69,0 +2865,15597033,Speight,708,Germany,Male,37,8,153366.13,1,1,1,26912.34,0 +2866,15590228,Greenwalt,715,France,Male,21,6,76467.16,1,1,1,173511.72,0 +2867,15631848,Grover,727,France,Female,26,9,121508.28,1,1,1,146785.44,0 +2868,15654211,Milani,559,Spain,Female,27,1,0,1,0,1,1050.33,0 +2869,15707968,Akobundu,545,Spain,Male,36,8,73211.12,2,1,0,89587.34,1 +2870,15594084,Anderson,524,France,Male,22,9,0,2,1,0,74405.34,0 +2871,15651093,Chien,707,France,Female,55,1,0,2,0,1,54409.48,0 +2872,15798824,Kennedy,671,Spain,Male,38,0,92674.94,2,1,0,3647.57,0 +2873,15671591,Castiglione,439,Spain,Male,52,3,96196.24,4,1,0,198874.52,1 +2874,15707189,Marshall,667,Germany,Female,36,1,114391.62,1,1,1,53412.54,0 +2875,15733581,Duncan,831,Germany,Male,32,9,80262.66,1,1,0,194867.78,0 +2876,15641640,Uspenskaya,545,Spain,Female,33,7,173331.52,1,1,0,150452.88,0 +2877,15585284,Thomson,604,Spain,Female,35,7,147285.52,1,1,1,57807.05,0 +2878,15617866,Calabrese,657,Spain,Male,67,5,119785.47,2,1,1,107534.32,0 +2879,15667751,Herrera,487,Spain,Female,36,1,140137.15,1,1,0,194073.33,0 +2880,15669411,Muse,750,Germany,Female,52,6,107467.56,1,1,0,126233.18,1 +2881,15789425,Marsden,694,Germany,Female,37,8,98218.04,2,1,0,182354.46,1 +2882,15570943,Artemyeva,711,Germany,Female,35,2,133607.75,1,1,1,120586.32,0 +2883,15685829,McKay,551,France,Male,37,3,0,2,1,1,50578.4,0 +2884,15721917,Chuang,559,France,Female,38,8,95139.41,1,1,1,86575.46,0 +2885,15776047,Nicholls,620,France,Female,29,3,0,2,0,1,153392.28,0 +2886,15716024,Dennis,660,Spain,Male,42,5,0,2,1,0,115509.59,0 +2887,15675328,Knight,449,France,Female,37,6,0,2,1,0,82176.48,0 +2888,15604314,Webb,703,Germany,Female,26,1,97331.19,1,1,0,63717.49,0 +2889,15658339,Pugliesi,795,Germany,Male,37,2,139265.63,2,1,1,198745.94,0 +2890,15630402,Nebechukwu,594,France,Female,31,9,0,1,0,1,5719.11,0 +2891,15689616,Ward,586,Spain,Male,34,5,168094.01,1,0,0,20058.61,0 +2892,15774224,Nixon,613,Germany,Female,30,5,131563.88,2,1,0,170638.98,0 +2893,15701291,Chidubem,601,France,Male,44,3,0,2,1,0,30607.11,0 +2894,15719606,Rivers,657,France,Male,50,9,0,2,0,0,37171.46,0 +2895,15644119,Sochima,531,France,Male,31,3,0,1,1,1,42589.33,0 +2896,15646859,Heydon,621,Germany,Male,47,7,107363.29,1,1,1,66799.28,0 +2897,15606836,Lombardo,782,France,Female,33,2,94493.03,1,0,1,101866.39,0 +2898,15664150,Holland,528,Germany,Female,29,9,170214.23,2,1,0,49284,0 +2899,15624510,Tien,696,France,Male,52,6,139781.06,1,1,0,27445.4,1 +2900,15810944,Bryant,586,France,Female,35,7,0,2,1,0,70760.69,0 +2901,15668575,Hao,626,Spain,Female,26,8,148610.41,3,0,1,104502.02,1 +2902,15603246,Genovesi,498,France,Male,73,2,170241.7,2,1,1,165407.96,0 +2903,15804002,Kovalev,691,France,Female,33,1,128306.83,1,1,1,113580.79,0 +2904,15728773,Hsieh,568,France,Female,47,7,0,2,1,1,45978.39,0 +2905,15598044,Debellis,715,France,Female,35,3,0,1,1,1,152012.36,0 +2906,15694829,Chibueze,680,Germany,Male,32,7,175454,1,0,1,77349.92,0 +2907,15600575,Padovano,802,Spain,Male,41,6,0,2,1,0,47322.05,0 +2908,15727311,Yen,539,France,Female,22,0,100885.93,2,1,1,38772.65,0 +2909,15570769,Kibble,494,France,Male,69,9,93320.8,1,1,1,24489.44,0 +2910,15606274,Lori,594,Germany,Male,38,6,63176.44,2,1,1,14466.08,0 +2911,15746139,Enemuo,596,France,Male,33,2,139451.67,1,0,0,63142.12,0 +2912,15704987,Lu,649,France,Female,52,8,49113.75,1,1,0,41858.43,0 +2913,15628972,Nebeolisa,699,Germany,Male,32,1,123906.22,3,1,1,127443.82,1 +2914,15697686,Stewart,787,France,Female,40,6,0,2,1,1,84151.98,0 +2915,15733883,Ward,604,France,Male,28,7,0,2,0,0,58595.64,0 +2916,15617482,Milanesi,489,Germany,Female,52,1,131441.51,1,1,0,37240.11,1 +2917,15704583,Chikwado,651,France,Male,56,2,0,1,1,0,114522.68,1 +2918,15621083,Douglas,698,France,Male,57,6,136325.48,2,1,1,72549.27,1 +2919,15649487,Sal,578,Germany,Female,38,4,113150.44,2,1,0,176712.59,1 +2920,15736760,Douglas,538,Spain,Female,42,9,0,1,0,0,152855.96,0 +2921,15714658,Yates,696,France,Female,33,4,0,2,1,1,73371.65,0 +2922,15599081,Watt,507,Germany,Female,46,8,102785.16,1,1,1,70323.68,0 +2923,15705113,P'an,685,Spain,Male,34,6,83264.28,1,0,0,9663.28,0 +2924,15631159,H?,705,Germany,Male,41,4,72252.64,2,1,1,142514.66,0 +2925,15792818,Perry,499,Germany,Female,29,6,148051.52,1,1,0,118623.94,0 +2926,15633531,Lavrov,717,France,Female,76,9,138489.66,1,1,1,68400.14,0 +2927,15744529,Chiekwugo,510,France,Male,63,8,0,2,1,1,115291.86,0 +2928,15669656,Macdonald,632,France,Male,32,6,111589.33,1,1,1,170382.99,0 +2929,15581198,Jenkins,668,Germany,Female,39,0,122104.79,1,1,0,112946.67,1 +2930,15729054,Korovina,744,Germany,Male,32,4,96106.83,1,1,1,79812.77,0 +2931,15573452,Manning,663,Germany,Male,42,7,115930.87,1,1,0,19862.78,0 +2932,15776733,Wilson,638,Germany,Female,37,7,124513.66,2,1,0,158610.89,0 +2933,15724858,Begum,688,France,Female,54,9,0,1,1,0,191212.63,1 +2934,15713144,Ingrassia,588,Spain,Male,46,8,0,1,1,0,61931.21,0 +2935,15690188,Maclean,631,France,Male,33,7,0,1,1,1,58043.02,1 +2936,15689425,Olejuru,687,Spain,Male,35,8,100988.39,2,1,0,22247.27,0 +2937,15671766,Enyinnaya,599,France,Male,44,10,118577.24,1,1,1,31448.52,0 +2938,15782806,Watson,718,Spain,Male,28,6,0,2,1,0,146875.86,0 +2939,15764419,Langdon,730,France,Male,27,5,0,2,1,1,116081.93,0 +2940,15591915,Frolov,533,France,Female,39,2,0,1,0,1,73669.94,1 +2941,15772798,Chikezie,711,Spain,Female,28,5,0,2,1,1,93959.96,0 +2942,15792008,Zetticci,555,Spain,Female,26,9,0,2,0,1,158918.03,0 +2943,15715541,Yang,850,France,Female,42,9,113311.11,1,1,1,198193.75,0 +2944,15639277,Lin,678,France,Female,41,9,0,1,0,0,13160.03,0 +2945,15798850,Goddard,576,France,Male,32,7,0,2,1,0,4660.91,0 +2946,15776348,Rogers,835,Germany,Male,20,4,124365.42,1,0,0,180197.74,1 +2947,15727696,Zubareva,592,France,Male,42,1,147249.29,2,1,1,63023.02,0 +2948,15793813,Onochie,774,France,Male,36,7,103688.19,1,0,1,118971.74,0 +2949,15694395,Ts'ui,620,France,Female,29,1,138740.24,2,0,0,154700.61,0 +2950,15764195,Newsom,519,Spain,Male,39,4,111900.14,1,1,1,97577.17,0 +2951,15744919,Genovese,734,Spain,Female,37,0,152760.24,1,1,1,48990.5,0 +2952,15671655,Thorpe,763,Germany,Male,31,7,143966.3,2,1,1,140262.96,1 +2953,15654901,Horton,733,France,Male,51,10,141556.96,1,1,0,130189.53,0 +2954,15649136,Williamson,650,France,Female,43,6,0,2,1,1,16301.91,0 +2955,15775562,Shoobridge,538,France,Female,33,5,0,2,1,0,126962.41,0 +2956,15807481,Peng,577,France,Female,46,1,0,1,1,1,158750.53,0 +2957,15642885,Gray,792,France,Male,30,8,0,2,1,0,199644.2,0 +2958,15789109,Watson,686,France,Female,41,10,0,1,1,1,144272.71,1 +2959,15814004,Fyodorova,589,France,Male,29,2,0,2,0,1,98320.27,0 +2960,15673619,Bazhenov,530,France,Male,25,9,162560.32,1,1,0,64129.03,0 +2961,15595135,Solomon,778,Germany,Female,29,7,123229.46,1,1,0,181221.09,0 +2962,15583681,Layh,616,Spain,Male,31,7,76665.71,2,1,1,163809.08,0 +2963,15605000,John,550,France,Male,38,9,140278.99,3,1,1,171457.06,1 +2964,15718071,Tuan,655,France,Female,51,3,0,2,0,1,15801.02,0 +2965,15679760,Slattery,721,France,Male,46,1,115764.32,2,0,0,102950.79,0 +2966,15654574,Onyekachi,499,Germany,Male,36,5,131142.53,2,1,0,174918.46,0 +2967,15577178,Genovese,511,France,Male,45,5,68375.27,1,1,0,193160.25,1 +2968,15595324,Daniels,579,Germany,Female,39,5,117833.3,3,0,0,5831,1 +2969,15756932,Caldwell,696,Spain,Female,36,7,0,2,1,1,82298.59,0 +2970,15726358,Chiemenam,681,France,Male,34,7,0,2,0,0,130686.59,0 +2971,15595228,Wanliss,815,France,Male,45,7,0,1,0,1,52885.23,1 +2972,15782530,Bruce,681,Spain,Male,30,2,111093.01,1,1,0,68985.99,0 +2973,15592877,Wright,641,Spain,Male,42,9,132657.55,1,1,0,35367.19,0 +2974,15651983,Fang,591,France,Female,56,9,128882.49,1,1,1,196241.94,1 +2975,15746737,Eames,565,Germany,Male,59,9,69129.59,1,1,1,170705.53,0 +2976,15774179,Sutherland,487,France,Male,37,6,0,2,1,1,126477.41,0 +2977,15667265,Cavenagh,729,France,Male,39,4,121404.64,1,1,1,159618.17,0 +2978,15655123,Dumetolisa,505,Spain,Female,45,9,131355.3,3,1,0,195395.33,1 +2979,15595917,Mackay,580,France,Female,35,1,102097.33,1,0,1,168285.85,0 +2980,15668385,Dellucci,642,France,Male,40,1,154863.15,1,1,1,138052.51,0 +2981,15709476,Kenyon,850,Spain,Female,41,3,99945.93,2,1,0,71179.31,0 +2982,15711218,Parry,616,Germany,Male,39,2,121704.32,2,1,0,55556.3,0 +2983,15798659,Kennedy,526,Spain,Female,43,3,0,2,1,0,31705.19,0 +2984,15663939,Arnott,523,Germany,Male,35,8,138782.76,1,1,1,186118.93,0 +2985,15694946,Hanson,663,France,Male,35,9,0,2,1,1,195580.28,0 +2986,15631912,T'ao,840,France,Male,30,8,136291.71,1,1,0,54113.38,0 +2987,15768816,Shen,570,Germany,Male,42,0,107856.57,2,1,0,127528.84,0 +2988,15682268,Steere,676,Germany,Female,26,1,108348.66,1,0,0,60231.74,1 +2989,15684801,Abbott,689,France,Male,47,1,93871.95,3,1,0,156878.42,1 +2990,15636428,Sutherland,703,Spain,Female,45,1,0,1,1,0,182784.11,1 +2991,15809823,Thurgood,491,Germany,Male,19,2,125860.2,1,0,0,129690.5,0 +2992,15699284,Johnson,584,France,Male,49,8,172713.44,1,1,0,113860.81,0 +2993,15786993,Lung,810,France,Female,51,5,0,2,0,1,184524.74,0 +2994,15709441,Cocci,745,Spain,Female,59,8,0,1,1,1,36124.98,0 +2995,15710257,Matveyeva,625,France,Female,39,3,130786.92,1,0,1,121316.07,0 +2996,15582492,Moore,535,France,Female,29,2,112367.34,1,1,0,185630.76,0 +2997,15575694,Yobachukwu,729,Spain,Female,45,7,91091.06,2,1,0,71133.12,0 +2998,15756820,Fleming,655,France,Female,26,7,106198.5,1,0,1,32020.42,0 +2999,15766289,Dickinson,751,France,Male,47,5,142669.93,2,1,0,162760.96,0 +3000,15593014,Evseyev,525,France,Male,33,1,112833.35,1,0,1,175178.56,0 +3001,15584545,Aksenov,532,France,Female,40,5,0,2,0,1,177099.71,0 +3002,15675949,Fleming,696,Spain,Female,43,4,0,2,1,1,66406.37,0 +3003,15672091,Ulyanov,786,Germany,Female,32,2,104336.43,2,0,0,59559.81,0 +3004,15801658,Summers,580,France,Male,55,6,104305.74,1,0,1,175750.21,0 +3005,15706185,Clements,596,Germany,Male,47,5,140187.1,2,1,1,174311.3,0 +3006,15789863,Kazakova,683,France,Male,39,4,0,2,1,0,171716.81,0 +3007,15720943,Pirozzi,747,France,Female,45,1,114959.12,1,1,0,189362.39,1 +3008,15697997,Jamieson,602,France,Male,33,5,164704.38,1,0,1,180716.1,1 +3009,15665416,Ferri,779,France,Male,62,10,119096.55,1,0,1,116977.89,0 +3010,15660200,Mai,551,France,Male,31,1,0,2,1,1,185105.44,0 +3011,15619653,Hannaford,666,France,Male,47,2,0,1,1,0,35046.97,1 +3012,15773447,Fomin,526,Spain,Male,30,8,0,1,1,0,36251,0 +3013,15739160,Mahon,849,France,Female,41,9,115465.28,1,1,0,103174.5,0 +3014,15689237,Shaw,471,France,Female,27,4,0,2,1,0,122642.09,0 +3015,15679297,Volkova,628,Spain,Male,43,3,184926.61,1,1,0,122937.57,0 +3016,15591433,Miles,674,Germany,Male,43,8,85957.88,2,1,0,8757.39,0 +3017,15642725,Madison,797,France,Male,32,10,114084.6,1,0,1,125782.29,0 +3018,15701962,Scott,590,Spain,Female,29,2,166930.76,2,1,0,122487.73,0 +3019,15811613,Voss,588,France,Female,27,8,0,1,1,0,20066.38,0 +3020,15741049,Colebatch,577,France,Male,29,7,0,2,1,1,55473.15,0 +3021,15724423,Wilson,571,France,Female,38,6,107193.82,2,0,0,38962.94,0 +3022,15574305,T'ang,680,France,Male,36,3,116275.12,1,1,1,63795.8,0 +3023,15678168,Gibson,648,Spain,Female,27,7,0,2,1,1,163060.43,0 +3024,15697020,Hs?eh,618,France,Male,39,2,91068.56,1,1,0,26578.69,0 +3025,15610801,Pan,648,Germany,Male,41,5,123049.21,1,0,1,5066.76,0 +3026,15745232,Chikelu,759,France,Female,39,6,0,2,1,1,140497.67,0 +3027,15722758,Allan,585,France,Male,40,7,0,2,0,0,146156.98,0 +3028,15792102,Yefremova,774,France,Female,42,3,137781.65,1,0,0,199316.19,0 +3029,15675185,Chuang,697,Germany,Female,48,2,108128.96,2,1,1,103944.37,0 +3030,15801247,Fan,605,Spain,Male,39,10,105317.73,2,1,0,138021.36,0 +3031,15725660,Dellucci,676,France,Male,20,1,80569.73,1,0,0,68621.98,0 +3032,15638963,Garran,678,France,Female,22,4,174852.89,1,1,1,28149.06,0 +3033,15800061,Moretti,495,Spain,Female,45,3,89158.94,3,1,0,135169.76,1 +3034,15578006,Yao,787,France,Female,85,10,0,2,1,1,116537.96,0 +3035,15668504,Lucchesi,770,France,Male,36,2,89800.14,1,1,1,105922.69,0 +3036,15687491,Nkemdilim,817,Germany,Male,45,9,101207.75,1,0,0,88211.12,1 +3037,15610403,Anderson,659,France,Male,43,1,106086.42,2,1,0,26900.63,0 +3038,15741094,Sagese,693,France,Male,21,1,0,2,1,1,3494.02,0 +3039,15807909,Rubensohn,744,France,Male,47,9,0,2,1,0,113163.17,0 +3040,15666141,Baldwin,829,Spain,Female,26,8,101440.36,2,1,1,19324.5,0 +3041,15617134,Iqbal,716,France,Male,38,4,0,2,1,0,189678.7,0 +3042,15783029,Monaldo,671,France,Male,34,7,106603.74,2,1,1,26387.71,0 +3043,15622833,Mahon,835,Germany,Female,29,10,130420.2,2,0,0,106276.55,0 +3044,15746422,Muir,636,France,Female,38,1,0,1,1,0,45015.38,0 +3045,15750839,Burns,649,Spain,Male,29,2,45022.23,1,1,1,173495.77,0 +3046,15749130,Dyer,621,Germany,Male,27,1,74298.43,1,1,1,52581.96,0 +3047,15779862,Lyons,658,Germany,Female,31,3,133003.03,1,0,1,146339.27,1 +3048,15767871,H?,784,Spain,Male,48,7,0,2,1,1,182609.97,0 +3049,15679651,Gardiner,783,Spain,Female,37,1,136689.66,1,1,0,197890.65,0 +3050,15576219,Cameron,615,France,Male,32,4,0,2,1,1,6225.63,0 +3051,15699247,Chapman,791,France,Female,44,5,0,2,1,1,123977.86,1 +3052,15619087,Taylor,762,France,Male,53,1,102520.37,1,1,1,170195.4,0 +3053,15605327,Namatjira,607,France,Male,35,2,0,2,1,1,114190.3,0 +3054,15610140,He,601,France,Female,34,5,0,2,1,0,27022.57,0 +3055,15791174,Leibius,540,Spain,Male,67,1,88382.01,1,0,1,59457,0 +3056,15602373,White,812,France,Male,44,4,115049.15,2,1,0,165038.41,0 +3057,15762605,Wall,685,France,Male,58,1,104796.54,1,1,1,154181.41,0 +3058,15598840,Moretti,680,France,Male,33,1,123082.08,1,1,0,134960.98,0 +3059,15744279,Patterson,680,Spain,Female,58,8,0,2,1,1,65708.5,0 +3060,15670619,Coppin,631,France,Female,33,8,0,2,0,0,117374.22,0 +3061,15599533,Tsao,569,France,Female,43,7,0,2,1,1,77703.19,0 +3062,15757837,Kao,584,Germany,Male,33,3,88311.48,2,1,1,177651.38,0 +3063,15697574,Stewart,582,France,Female,40,9,0,3,1,1,60954.45,0 +3064,15578738,Tuan,609,France,Male,32,7,71872.19,1,1,1,151924.9,0 +3065,15762228,Barnes,506,Spain,Male,35,6,110046.93,2,1,0,26318.73,0 +3066,15614827,Sun,503,France,Male,42,8,104430.08,1,1,1,147557.71,0 +3067,15789815,Fallaci,503,France,Female,28,5,0,2,1,0,125918.17,0 +3068,15579781,Buccho,806,Germany,Male,31,10,138653.51,1,1,0,190803.37,0 +3069,15587013,Tien,653,France,Female,31,7,102575.04,1,1,1,11043.54,0 +3070,15570932,Pirozzi,666,France,Male,43,7,137780.74,2,1,1,119100.05,1 +3071,15794661,Liu,674,Spain,Male,32,2,0,2,1,0,140579.17,0 +3072,15581654,Long,798,France,Male,32,7,0,2,0,1,37731.95,0 +3073,15644296,Scott,740,France,Female,30,8,105209.54,1,1,0,1852.58,0 +3074,15614420,Gerasimova,531,Germany,Female,32,0,109570.21,2,1,1,172049.84,0 +3075,15609653,Ifeatu,614,Germany,Female,44,6,118715.86,1,1,0,133591.11,1 +3076,15594577,De Luca,556,France,Male,35,10,0,2,1,1,192751.18,0 +3077,15584114,Ogbonnaya,678,Germany,Female,43,2,153393.18,2,1,1,193828.27,0 +3078,15673367,Humffray,587,Germany,Male,33,6,132603.36,1,1,0,55775.72,0 +3079,15685576,Degtyaryov,527,Spain,Female,36,6,0,2,1,1,102280.29,0 +3080,15774727,Monaldo,757,Germany,Female,34,1,129398.01,2,0,0,44965.44,0 +3081,15694288,Cawthorne,468,Spain,Male,28,3,0,2,1,0,170661.02,0 +3082,15603319,Graham,693,France,Male,29,2,151352.74,1,0,0,197145.89,0 +3083,15759066,Carpenter,483,France,Female,44,5,136836.49,1,1,0,192359.9,1 +3084,15814816,Kambinachi,466,France,Male,40,4,91592.06,1,1,0,141210.18,1 +3085,15724402,Tyler,770,France,Female,30,8,0,2,1,0,100557.03,0 +3086,15571059,Martin,734,France,Female,54,3,0,1,1,0,130805.54,1 +3087,15674206,Walker,716,France,Female,22,8,0,2,1,1,92606.98,0 +3088,15715160,Khan,439,France,Male,36,2,165536.28,2,1,1,123956.83,0 +3089,15730448,Iroawuchi,538,Germany,Male,25,5,62482.95,1,1,1,102758.43,0 +3090,15662067,Summers,743,France,Male,40,8,68155.59,1,1,0,94876.65,0 +3091,15779581,Bottrill,734,Spain,Female,43,3,55853.33,2,0,1,94811.85,1 +3092,15662901,Hu,656,France,Male,37,2,0,2,0,1,67840.81,0 +3093,15689751,Jones,666,France,Female,31,2,79589.43,1,0,0,4050.57,0 +3094,15667742,Vincent,627,Spain,Male,41,5,100880.76,1,0,1,134665.25,0 +3095,15738448,Sanford,480,Germany,Female,25,3,174330.35,2,0,0,181647.13,0 +3096,15680243,Brown,792,France,Male,19,7,143390.51,1,1,0,33282.84,0 +3097,15745083,Lei,613,Germany,Male,59,8,91415.76,1,0,0,27965,1 +3098,15708228,Toscani,476,Germany,Male,30,3,134366.42,1,1,0,68343.53,0 +3099,15628523,Chien,539,France,Female,24,3,0,2,1,1,198161.07,0 +3100,15708196,Uchenna,696,Spain,Male,60,8,88786.81,1,1,1,196858.4,0 +3101,15735549,Lori,810,Germany,Male,35,3,96814.46,2,1,1,120511.03,0 +3102,15809347,Fanucci,763,Germany,Male,32,9,160680.41,1,1,0,30886.35,0 +3103,15660866,Chimaobim,640,France,Female,29,3,0,2,1,0,2743.69,0 +3104,15766609,Jowers,655,France,Female,47,10,0,2,1,0,167778.62,0 +3105,15654230,Miller,526,Germany,Male,31,5,145537.21,1,1,0,132404.64,0 +3106,15794566,Kirsova,678,France,Female,28,4,0,2,1,1,144423.17,1 +3107,15800890,T'ien,554,France,Female,45,6,0,2,1,1,181204.5,0 +3108,15697424,Ku,597,Spain,Female,30,2,119370.11,1,1,1,182726.22,1 +3109,15724536,Chin,560,Spain,Female,28,1,0,2,1,1,120880.72,0 +3110,15735878,Law,850,Germany,Female,47,10,134381.52,1,0,0,26812.89,1 +3111,15707596,Chung,546,Germany,Female,74,8,114888.74,2,1,1,66732.63,1 +3112,15657163,Cockrum,623,Germany,Male,42,1,149332.48,2,1,0,100834.22,0 +3113,15622478,Greaves,698,France,Female,40,7,105061.74,3,1,0,107815.31,1 +3114,15779529,Grant,620,France,Male,32,7,0,2,1,1,34665.79,0 +3115,15636023,O'Donnell,619,France,Female,40,10,0,1,1,1,147093.84,1 +3116,15582066,Maclean,561,France,Male,21,4,0,1,1,1,36942.35,0 +3117,15666675,Hsieh,753,France,Female,39,7,155062.8,1,1,1,16460.77,0 +3118,15732987,Hs?,721,Spain,Male,43,3,88798.34,1,0,0,45610.63,0 +3119,15789432,Mazzanti,451,France,Male,33,6,0,2,1,0,184954.11,0 +3120,15663161,Chiu,680,Germany,Female,51,5,143139.87,1,0,0,47795.43,1 +3121,15694879,Reeves,590,Spain,Female,23,7,0,2,1,0,196789.9,0 +3122,15593715,Castiglione,634,Germany,Male,27,3,107027.52,1,1,0,173425.68,0 +3123,15575002,Ferguson,676,France,Male,29,4,140720.93,1,1,0,36221.18,0 +3124,15622171,Nnamdi,642,France,Male,30,8,80964.57,2,1,0,174738.2,0 +3125,15795224,Wu,760,France,Male,39,6,178585.46,1,1,0,67131.3,1 +3126,15685346,Chu,736,Spain,Female,26,4,135889.13,1,1,1,165692.03,0 +3127,15691808,King,656,France,Male,43,7,134919.85,1,1,0,194691.95,0 +3128,15721007,Charlton,776,Germany,Male,33,8,115130.34,1,0,0,129525.5,1 +3129,15794253,Marsh,832,Spain,Female,34,6,138190.13,2,0,1,146511.2,0 +3130,15694453,Walker,631,Germany,Male,37,9,131519.49,2,1,1,51752.18,0 +3131,15813113,Chang,795,Spain,Female,56,5,0,1,1,0,35418.69,1 +3132,15614187,Pottinger,648,Germany,Female,39,3,126935.98,2,0,1,57995.74,0 +3133,15619407,Buckley,615,France,Male,39,4,133707.09,1,1,1,108152.75,0 +3134,15646227,Folliero,682,France,Female,27,1,97893.2,1,1,0,166144.98,0 +3135,15660541,Olisanugo,694,France,Male,34,5,127900.03,1,1,0,101737.8,0 +3136,15753874,Kent,694,France,Male,37,10,143835.47,1,0,1,33326.71,0 +3137,15617877,Jessop,607,France,Male,44,0,0,2,1,1,81140.09,0 +3138,15772073,Hodge,664,France,Male,48,10,0,1,1,0,140173.17,1 +3139,15701537,Ignatiev,756,France,Male,60,2,0,1,1,1,166513.49,1 +3140,15736228,Chambers,645,France,Female,40,3,129596.77,1,1,1,103232.6,0 +3141,15780572,Mansom,653,Spain,Male,30,4,0,2,1,0,120736.04,0 +3142,15769596,Yen,710,Germany,Female,24,2,110407.44,2,0,0,15832.43,1 +3143,15586996,Azikiwe,697,France,Female,76,7,0,2,0,1,188772.45,0 +3144,15722061,Allen,619,Germany,Female,41,8,142015.76,2,1,0,114323.66,0 +3145,15638003,Komarova,648,Spain,Male,55,1,81370.07,1,0,1,181534.04,0 +3146,15775590,Mackay,482,Germany,Female,48,2,69329.47,1,0,0,102640.52,1 +3147,15730688,Yu,548,France,Female,28,8,116755.5,2,1,1,158585.17,1 +3148,15753102,Curtis,752,Spain,Male,44,6,83870.33,1,1,0,178722.24,0 +3149,15810075,Fang,648,France,Female,39,6,130694.89,2,1,1,153955.38,1 +3150,15723373,Page,643,Spain,Female,34,8,117451.47,1,1,0,65374.86,0 +3151,15795298,Olisaemeka,573,Germany,Female,35,9,206868.78,2,0,1,102986.15,0 +3152,15584320,Brennan,686,France,Female,39,3,111695.62,1,0,0,136643.84,0 +3153,15724161,Sutton,644,France,Female,40,9,137285.26,4,1,0,77063.63,1 +3154,15750056,Hyde,702,France,Female,29,6,149218.39,1,1,1,9633.01,0 +3155,15609637,Nkemakolam,652,France,Male,51,7,0,2,0,1,43496.36,0 +3156,15794493,Chimaijem,641,Spain,Male,32,7,0,2,1,1,24267.28,0 +3157,15569641,Sung,692,Germany,Female,41,8,130701.29,1,1,0,59354.24,1 +3158,15815236,Chiganu,574,Spain,Male,34,5,0,2,0,0,28269.86,0 +3159,15811177,Beneventi,643,France,Female,31,3,167949.48,1,1,0,143162.34,0 +3160,15680587,Esposito,834,France,Male,23,4,131254.81,1,1,0,20199.3,0 +3161,15672821,Owen,591,France,Male,28,5,0,2,1,1,48606.92,0 +3162,15767681,Smalley,470,Spain,Male,34,9,0,2,0,1,89013.67,0 +3163,15600379,Hsiung,608,Spain,Male,34,7,86656.13,1,0,1,59890.29,0 +3164,15801336,Ch'ang,649,Germany,Female,37,8,114737.26,1,1,1,106655.88,1 +3165,15721592,Barton,665,France,Female,38,5,0,2,1,0,156439.56,0 +3166,15581282,Lucchese,651,France,Female,39,6,0,1,1,0,24176.44,0 +3167,15746203,Hsia,555,Germany,Male,62,4,119817.33,1,0,1,43507.1,1 +3168,15583137,Pope,637,France,Female,48,7,130806.99,2,1,1,132005.85,1 +3169,15680752,Horrocks,675,France,Female,49,0,0,1,1,1,80496.71,1 +3170,15688172,Tai,677,Spain,Male,40,5,0,2,1,0,88947.56,0 +3171,15791373,Chikezie,850,Germany,Female,35,2,80931.75,1,0,0,12639.67,1 +3172,15589449,Frye,815,France,Female,56,3,0,3,1,1,94248.16,1 +3173,15692819,Toscani,665,Germany,Male,32,1,132178.67,1,0,0,11865.76,0 +3174,15727467,Mellor,485,France,Female,27,3,0,2,1,0,141449.86,0 +3175,15734312,Kang,577,Spain,Male,43,6,0,2,1,1,149457.81,0 +3176,15764604,Sutherland,586,France,Female,35,7,164769.02,3,1,0,119814.25,1 +3177,15613014,Hs?,722,Germany,Male,29,1,107233.85,2,1,0,24924.92,0 +3178,15759684,Ting,528,France,Female,27,7,176227.07,2,0,1,139481.53,0 +3179,15609669,Chuang,542,France,Female,39,4,109949.39,2,1,1,41268.65,0 +3180,15685536,Chu,552,France,Female,34,5,0,2,1,1,1351.41,0 +3181,15750447,Ozoemena,678,France,Female,60,10,117738.81,1,1,0,147489.76,1 +3182,15663249,Howells,575,Spain,Female,37,9,133292.45,1,1,0,111175.09,0 +3183,15638646,Lucchese,669,France,Female,43,1,160474.59,1,1,1,95963.14,0 +3184,15734161,Nnonso,636,France,Male,43,6,0,2,1,0,43128.95,0 +3185,15631070,Gerasimova,667,Germany,Male,55,9,154393.43,1,1,1,137674.96,1 +3186,15761950,Woronoff,652,Germany,Female,45,9,110827.49,1,1,1,153383.54,1 +3187,15649668,Wilhelm,637,Germany,Female,36,10,145750.45,2,1,1,96660.76,0 +3188,15713912,Nebechukwu,516,Spain,Female,45,8,109044.3,1,0,1,115818.16,0 +3189,15586757,Anenechukwu,801,France,Female,32,4,75170.54,1,1,1,37898.5,0 +3190,15596522,Meredith,692,France,Female,42,2,0,2,1,0,145222.93,0 +3191,15625395,Chinomso,585,France,Female,28,6,105795.9,1,1,1,41219.09,0 +3192,15760570,Stephenson,590,France,Male,32,5,0,2,1,0,59249.83,0 +3193,15566689,Chimaoke,554,Spain,Male,66,8,0,2,1,1,116747.62,0 +3194,15725794,Winters,659,France,Female,49,1,0,1,1,0,116249.72,1 +3195,15673539,Napolitani,690,France,Female,26,3,118097.87,1,1,0,61257.83,0 +3196,15705298,L?,697,Germany,Male,29,0,172693.54,1,0,0,141798.98,0 +3197,15675791,Williams,610,France,Male,36,4,129440.3,2,1,0,102638.35,0 +3198,15747043,Giles,599,Spain,Male,36,4,0,2,0,0,13210.56,0 +3199,15736397,Wang,544,France,Male,23,1,96471.2,1,1,0,35550.97,0 +3200,15678201,Robertson,548,France,Female,46,1,0,1,1,1,104469.06,1 +3201,15720745,Murray,635,Spain,Male,24,4,140197.18,1,1,1,142935.83,0 +3202,15637593,Greco,722,France,Male,20,6,0,2,1,0,195486.28,0 +3203,15598070,Marchesi,564,France,Female,33,4,135946.26,1,1,0,63170,0 +3204,15787550,Chao,719,France,Male,69,3,0,2,1,1,58320.06,0 +3205,15603942,Hawthorn,547,Germany,Male,50,3,81290.02,3,0,1,177747.03,1 +3206,15733973,Bibi,850,France,Female,42,8,0,1,1,0,19632.64,1 +3207,15596761,Hawdon,515,Germany,Male,60,9,113715.36,1,1,0,18424.24,1 +3208,15652400,Moss,667,Spain,Male,56,2,168883.08,1,0,1,18897.78,0 +3209,15717893,Briggs,607,Germany,Male,36,8,143421.74,1,1,0,97879.02,0 +3210,15622585,McIntyre,525,France,Male,26,7,153644.39,1,1,1,63197.88,0 +3211,15733964,Russo,606,Spain,Female,53,1,109330.06,1,1,1,75860.01,0 +3212,15753861,Ballard,686,Germany,Female,27,1,115095.88,2,0,0,78622.46,0 +3213,15747097,Hs?,611,France,Male,35,10,0,1,1,1,23598.23,1 +3214,15594762,Pisani,827,Spain,Male,46,1,183276.32,1,1,1,13460.27,0 +3215,15667417,Tao,572,France,Male,33,9,68193.72,1,1,0,19998.31,0 +3216,15684861,Thomson,726,France,Female,32,8,0,2,0,0,185075.63,0 +3217,15742204,Hsu,579,Germany,Male,31,6,139729.54,1,0,1,135815.38,0 +3218,15623502,Morrison,598,Spain,Female,56,4,98365.33,1,1,1,44251.33,0 +3219,15774872,Joslin,663,France,Male,36,10,0,2,1,0,136349.55,0 +3220,15611191,Scott,505,Germany,Female,37,10,122453.97,2,1,1,52693.99,0 +3221,15674331,Bidwill,576,Germany,Male,30,7,132174.41,2,0,0,93767.03,0 +3222,15619465,Cameron,555,Spain,Female,24,2,0,2,0,1,197866.55,0 +3223,15575247,Cartwright,524,France,Male,30,1,0,2,1,0,126812.85,0 +3224,15695679,Yao,776,Spain,Male,39,2,104349.45,1,0,0,79503.05,0 +3225,15713463,Tate,645,Germany,Female,41,2,138881.04,1,1,0,129936.53,1 +3226,15785170,Neal,850,Germany,Female,32,0,116968.91,1,0,0,175094.62,0 +3227,15796351,Yao,603,Germany,Male,35,1,105346.03,2,1,1,130379.5,0 +3228,15639576,Burns,691,France,Male,26,9,136623.19,1,1,0,153228,0 +3229,15693264,Onyinyechukwuka,583,France,Female,29,10,0,2,1,1,111285.85,0 +3230,15589715,Fulks,584,France,Female,66,5,0,1,1,0,49553.38,1 +3231,15769902,Christie,679,France,Female,33,6,0,2,1,1,98015.85,0 +3232,15587177,Lloyd,646,France,Male,36,6,124445.52,1,1,0,88481.32,0 +3233,15814553,Ball,559,France,Female,34,5,68999.66,2,1,1,66879.27,0 +3234,15601550,Genovesi,595,Spain,Male,36,6,85768.42,1,1,1,24802.77,0 +3235,15664907,Alexander,527,France,Male,47,1,0,1,1,0,21312.16,1 +3236,15612465,Siciliano,684,Spain,Male,34,9,100628,2,1,1,190263.78,0 +3237,15810800,Ositadimma,673,Spain,Female,32,0,0,1,1,1,72873.33,0 +3238,15665760,Kazantsev,802,Spain,Male,38,7,0,2,0,1,57764.65,0 +3239,15588080,Giles,675,France,Male,54,6,0,1,1,0,110273.84,1 +3240,15776844,Hao,762,Spain,Female,19,6,0,2,1,0,55500.17,0 +3241,15717560,Martin,580,France,Male,50,0,125647.36,1,1,0,57541.08,1 +3242,15629739,Hartley,621,Germany,Female,31,8,100375.39,1,1,1,90384.26,0 +3243,15729908,Allan,411,France,Female,36,10,0,1,0,0,120694.35,0 +3244,15716781,Dolgorukova,815,France,Male,24,7,171922.72,1,0,1,178028.96,0 +3245,15646936,Nnamdi,631,Germany,Female,32,2,146810.99,2,1,1,180990.29,0 +3246,15768151,Romano,514,Germany,Female,45,3,109032.23,1,0,1,155407.21,1 +3247,15579212,Chuang,638,France,Male,57,6,0,1,1,0,33676.48,1 +3248,15721835,Owen,791,Spain,Male,25,7,0,1,1,0,89666.28,0 +3249,15800515,Singh,516,France,Male,35,5,128653.59,1,1,0,127558.26,0 +3250,15591279,Nwagugheuzo,734,France,Male,37,3,80387.81,1,0,1,77272.62,0 +3251,15587419,Shipton,611,France,Male,58,8,0,2,0,1,107665.68,1 +3252,15750335,Paterson,850,Germany,Male,43,0,108508.82,3,1,0,184044.8,1 +3253,15699619,Rivas,641,France,Male,31,10,155978.17,1,1,0,91510.71,0 +3254,15606472,Lung,585,France,Female,38,5,0,1,1,1,87363.56,0 +3255,15778368,Allan,552,Germany,Male,50,4,121175.56,1,1,0,117505.07,1 +3256,15671387,Fetherstonhaugh,507,France,Female,29,4,89349.47,2,0,0,180626.68,0 +3257,15573926,Lung,735,Spain,Male,38,7,86131.71,2,0,0,93478.96,0 +3258,15709183,Davidson,707,France,Female,58,3,102346.86,1,1,1,114672.64,0 +3259,15577514,Mai,698,Germany,Female,36,7,121263.62,1,1,1,13387.88,0 +3260,15778830,Dellucci,841,France,Male,31,2,0,2,1,0,173240.52,0 +3261,15768072,Mitchell,688,Spain,Female,33,2,0,1,0,0,27557.18,1 +3262,15768293,Sun,614,France,Male,51,3,0,2,1,1,5552.37,0 +3263,15654456,Napolitano,511,Germany,Male,48,6,149726.08,1,0,0,88307.87,1 +3264,15807525,Bailey,447,France,Male,43,2,0,2,1,0,33879.26,1 +3265,15574372,Hoolan,738,France,Male,35,5,161274.05,2,1,0,181429.87,0 +3266,15671249,Kent,422,France,Female,33,2,0,2,1,0,102655.31,0 +3267,15779744,Chou,537,Spain,Male,30,1,103138.17,1,1,1,96555.42,0 +3268,15624755,Pepper,707,Germany,Female,40,3,109628.44,1,1,0,189366.03,0 +3269,15611430,Abramowitz,690,France,Male,54,5,0,1,1,0,12847.61,1 +3270,15774744,Lord,664,Germany,Male,33,7,97286.16,2,1,0,143433.33,0 +3271,15629885,Wilson,850,France,Female,33,7,118004.26,1,1,0,183983.82,0 +3272,15708791,Abazu,584,Spain,Male,32,9,85534.83,1,0,0,169137.24,0 +3273,15793890,Harriman,728,France,Female,59,4,0,1,1,1,163365.85,1 +3274,15646091,Frankland,560,Spain,Female,43,4,95140.44,2,1,0,123181.44,1 +3275,15596984,Pinto,629,France,Female,31,6,0,1,1,1,16447.6,1 +3276,15800215,Kwemtochukwu,658,France,Male,25,3,0,2,0,1,173948.4,0 +3277,15577806,Chiu,794,Germany,Female,54,1,75900.84,1,1,1,192154.66,0 +3278,15749381,Yu,790,France,Female,41,2,126619.27,1,1,0,198224.38,0 +3279,15683758,Onyekachukwu,640,France,Male,44,7,111833.47,1,1,0,67202.74,0 +3280,15670615,Castiglione,652,Spain,Male,37,7,0,2,1,0,68789.93,0 +3281,15715622,To Rot,583,France,Female,57,3,238387.56,1,0,1,147964.99,1 +3282,15707634,Anenechukwu,775,France,Female,32,2,108698.96,2,1,1,161069.73,0 +3283,15806901,Henderson,584,France,Female,39,2,112687.69,1,1,1,127749.61,0 +3284,15775335,Ellis,635,Germany,Female,48,4,81556.89,2,1,0,191914.37,0 +3285,15724150,Nkemdirim,814,France,Male,48,9,136596.85,1,1,1,185791.9,0 +3286,15627220,Kang,735,Germany,Female,43,9,98807.45,1,0,0,184570.04,1 +3287,15672330,Lear,678,France,Female,31,1,0,2,0,1,130446.65,0 +3288,15668521,Jamieson,693,France,Male,37,1,0,2,1,1,82867.55,0 +3289,15807837,Mazzanti,640,France,Female,30,6,107499.7,1,1,1,187632.22,0 +3290,15592570,Marino,773,Spain,Female,23,8,0,2,1,0,56759.79,0 +3291,15748589,Winter,736,France,Female,30,9,0,2,1,0,34180.33,0 +3292,15635893,T'ien,693,France,Female,28,8,0,2,1,1,158545.25,0 +3293,15757632,Hughes-Jones,496,France,Female,41,1,176024.05,2,1,0,182337.98,0 +3294,15691863,Cody,751,France,Female,39,3,0,2,1,1,84175.34,0 +3295,15706071,Hunt,528,Germany,Male,39,0,127631.62,1,0,1,22197.8,1 +3296,15654296,Estrada,754,Spain,Female,19,9,0,1,1,0,189641.11,0 +3297,15755018,Dickinson,568,Germany,Female,26,10,109819.16,2,1,0,154491.39,0 +3298,15594041,Fanucci,592,Spain,Female,41,2,138734.94,1,1,0,90020.74,0 +3299,15670587,Yang,558,Germany,Male,25,10,111363.1,2,1,0,197264.35,0 +3300,15724527,Forbes,825,France,Male,34,9,0,2,1,1,31933.06,0 +3301,15801904,Heard,677,Germany,Male,28,0,143988,2,1,0,8755.69,1 +3302,15658195,Efremova,653,France,Male,34,5,118838.75,1,1,1,52820.13,0 +3303,15630113,Morphett,593,Spain,Male,35,4,161637.75,1,1,1,20008.46,0 +3304,15784320,Lenhardt,632,France,Female,44,3,133793.89,1,1,1,34607.14,1 +3305,15676513,Burns,601,Germany,Male,35,8,71553.83,1,1,0,177384.45,0 +3306,15574072,Ch'ien,786,France,Female,62,8,0,1,1,1,165702.64,0 +3307,15633854,Sun,654,France,Female,40,3,0,2,1,0,167889.1,0 +3308,15618566,Jamieson,572,France,Female,38,7,0,2,1,1,133122.62,0 +3309,15733014,Nolan,813,France,Female,62,10,64667.95,2,0,1,140454.14,0 +3310,15753343,Barry,523,France,Female,28,2,121164.11,1,1,1,59938.81,0 +3311,15746076,Saunders,506,Spain,Male,50,3,0,2,1,0,12016.79,0 +3312,15608226,McMorran,513,Spain,Male,72,3,98903.06,1,1,1,81251.24,0 +3313,15605684,Phelan,664,France,Female,31,7,104158.84,1,1,0,134169.85,0 +3314,15638988,Fu,684,France,Male,54,6,0,2,1,1,94888.6,0 +3315,15628767,Hotchin,608,Spain,Female,63,3,139529.93,2,1,1,175696.16,1 +3316,15737977,Aksyonov,527,France,Female,25,6,0,2,0,1,96758.58,0 +3317,15758116,Rossi,666,France,Male,53,5,64646.7,1,1,0,128019.48,1 +3318,15575119,Hughes,779,France,Male,71,3,0,2,1,1,146895.36,1 +3319,15625126,Duncan,629,France,Female,40,6,0,2,1,1,139356.3,0 +3320,15567114,McGarry,430,France,Male,35,1,118894.22,1,0,0,2923.61,0 +3321,15672242,Aksenov,712,France,Male,24,2,0,1,0,1,121232.51,0 +3322,15681327,Akhtar,682,France,Male,30,9,0,2,1,1,2053.42,0 +3323,15802585,Pisani,634,France,Female,41,8,68213.99,1,1,1,6382.46,0 +3324,15740630,Pisano,487,Spain,Female,31,1,0,2,1,0,158750.13,0 +3325,15815420,McDaniels,808,Spain,Male,47,8,139196,1,0,1,74028.36,0 +3326,15711468,Tennant,527,France,Female,32,7,0,2,1,1,44099.75,0 +3327,15799626,Donaghy,637,Germany,Male,50,4,126345.55,1,0,1,17323,1 +3328,15659325,Todd,802,Spain,Male,40,5,0,2,1,1,175043.69,0 +3329,15651352,Tobenna,529,France,Female,38,2,0,1,1,0,146388.85,1 +3330,15684925,Vicars,850,France,Female,43,3,0,2,0,0,2465.8,0 +3331,15657439,Chao,738,France,Male,18,4,0,2,1,1,47799.15,0 +3332,15574122,Tien,817,France,Male,34,5,129278.43,1,0,0,165562.84,0 +3333,15720508,Hsing,735,France,Male,31,3,119558.35,1,0,0,72927.68,0 +3334,15599078,Yang,619,Germany,Female,41,5,92467.58,1,1,0,38270.47,0 +3335,15702300,Walker,671,France,Male,27,5,0,2,0,0,120893.07,0 +3336,15660735,T'ang,581,Spain,Female,31,6,0,2,1,0,188377.21,0 +3337,15671390,Chukwukere,690,Spain,Male,36,10,0,2,1,0,55902.93,0 +3338,15647385,Ch'iu,579,Spain,Male,56,4,99340.83,1,0,0,4523.74,1 +3339,15739223,Pai,688,Spain,Female,24,3,0,2,1,1,102195.16,0 +3340,15631305,Franklin,599,Spain,Female,28,4,126833.79,2,1,0,60843.09,1 +3341,15809263,Y?,729,Germany,Male,29,5,109676.52,1,1,1,25548.47,0 +3342,15640866,Peng,718,France,Female,29,3,0,1,0,1,134462.29,0 +3343,15775663,Otitodilichukwu,712,Germany,Male,53,6,134729.99,2,1,1,132702.64,0 +3344,15631800,Pagnotto,474,France,Male,37,3,98431.37,1,0,0,75698.44,0 +3345,15654292,Vessels,565,Germany,Male,33,8,130368.31,2,1,0,105642.43,0 +3346,15648320,Heller,658,France,Female,31,7,123974.96,1,1,0,102153.75,0 +3347,15726747,Donaldson,714,France,Male,63,4,138082.16,1,0,1,166677.54,0 +3348,15694510,Ifeanyichukwu,725,France,Male,45,1,129855.32,1,0,0,24218.65,0 +3349,15572291,Kao,825,France,Male,40,6,132308.22,1,0,0,117122.5,0 +3350,15603465,Dunn,665,Germany,Female,45,5,155447.65,2,1,0,51871.95,1 +3351,15685628,Calabresi,670,Spain,Male,35,2,124268.64,2,0,1,84321.03,0 +3352,15792729,Holland,474,Germany,Female,34,9,176311.36,1,1,0,160213.27,0 +3353,15767414,Calabresi,591,France,Male,40,2,99886.42,2,1,1,88695.19,0 +3354,15568044,Butusov,508,France,Female,31,7,0,2,1,1,6123.15,0 +3355,15751333,Atkinson,695,France,Female,36,2,0,2,0,1,167749.54,0 +3356,15623062,Vasilyeva,660,Germany,Male,24,5,85089.3,1,1,1,71638,0 +3357,15713621,Mollison,687,Germany,Male,41,10,134318.21,2,1,1,198064.52,0 +3358,15670668,Webb,658,Germany,Male,29,5,75395.53,2,0,1,54914.92,0 +3359,15750638,Obiajulu,705,Germany,Female,33,5,116765.7,1,0,0,190659.17,1 +3360,15747878,Aiken,739,Spain,Male,60,4,0,1,1,1,51637.67,0 +3361,15726796,Brabyn,844,France,Male,38,7,111501.66,1,1,1,119333.38,0 +3362,15754952,Su,602,Germany,Female,48,7,76595.08,2,0,0,127095.14,0 +3363,15652192,Traeger,759,France,Female,33,9,160541.36,2,0,0,93541.14,0 +3364,15681924,Ekwueme,747,Germany,Male,38,2,129728.6,1,1,0,89289.54,0 +3365,15763544,Thompson,673,France,Male,47,1,0,2,0,0,108762.16,0 +3366,15764431,Chinwenma,671,Spain,Female,34,5,130929.02,4,1,1,28238.25,1 +3367,15684010,Tuan,640,Germany,Female,74,2,116800.25,1,1,1,34130.43,0 +3368,15648881,Tsai,581,Germany,Male,40,0,101016.53,1,0,1,7926.35,1 +3369,15733303,Liu,630,France,Male,67,5,0,2,1,1,27330.27,0 +3370,15643294,Robinson,703,France,Female,33,8,190566.65,1,1,1,79997.14,0 +3371,15749905,Carr,698,Spain,Female,47,6,0,1,1,0,50213.81,1 +3372,15625175,Palerma,742,Germany,Female,43,6,97067.69,1,0,1,60920.03,1 +3373,15643967,Chineze,652,France,Female,37,4,92208.54,1,0,1,197699.8,1 +3374,15578251,Fang,644,France,Male,37,2,186347.97,2,1,0,92809.73,0 +3375,15772573,Simpson,735,Spain,Male,55,2,103176.62,1,0,1,163516.16,0 +3376,15733234,Moretti,777,France,Female,58,4,0,1,1,1,62449.07,1 +3377,15721582,Hale,644,Germany,Female,40,4,77270.08,2,1,1,115800.1,1 +3378,15628219,Benson,665,Germany,Female,37,3,111911.63,1,1,1,110359.68,1 +3379,15571302,Estep,529,Germany,Male,72,5,94216.05,1,1,1,78695.68,0 +3380,15637178,Mishina,803,Spain,Female,45,7,0,2,1,1,128378.04,0 +3381,15601184,Abramovich,604,Spain,Female,26,3,0,2,1,0,155248.62,0 +3382,15629511,Lavrentiev,738,France,Male,49,6,106770.82,1,1,0,123499.27,0 +3383,15570629,Alexeyeva,655,Germany,Female,72,5,138089.97,2,1,1,99920.41,0 +3384,15665766,T'ang,698,Germany,Male,39,9,133191.19,2,0,1,53289.49,0 +3385,15693732,Kilgour,775,France,Female,66,9,0,2,1,1,67622.34,0 +3386,15765982,Chin,735,France,Male,41,7,74135.85,1,1,1,11783.1,1 +3387,15582016,Fiorentini,766,Spain,Male,41,6,99208.46,2,1,0,62402.38,0 +3388,15798024,Lori,537,Germany,Male,84,8,92242.34,1,1,1,186235.98,0 +3389,15588622,Marchesi,599,Germany,Male,25,7,108380.72,1,1,1,79005.95,0 +3390,15724863,Sheppard,420,Spain,Female,55,4,91893.32,1,1,0,144870.28,1 +3391,15618213,Nnanna,674,France,Female,32,7,85757.93,1,1,1,95481,0 +3392,15780411,Norris,570,France,Female,46,3,0,2,0,0,820.46,0 +3393,15725429,Vincent,623,Germany,Male,33,8,96759.42,1,1,1,174777.98,0 +3394,15600626,Bradley,710,France,Male,30,6,0,2,1,1,8991.17,0 +3395,15668460,Bellucci,466,France,Male,29,6,0,2,1,1,2797.27,0 +3396,15576263,Clements,759,France,Female,22,5,0,1,1,0,22303.17,0 +3397,15720354,Knowles,581,France,Male,71,4,0,2,1,1,197562.08,0 +3398,15691624,Chidiebere,820,France,Male,33,2,132150.26,2,1,0,23067.97,0 +3399,15793196,Kelly,759,France,Male,41,9,0,2,0,1,190294.12,0 +3400,15633352,Okwukwe,628,France,Female,31,6,175443.75,1,1,0,113167.17,1 +3401,15750874,Onyemere,676,France,Male,31,3,78990.15,1,1,1,124777.14,0 +3402,15588923,Murphy,591,France,Female,33,4,113743.37,1,1,0,124625.08,0 +3403,15715745,Elliott,690,France,Female,26,5,157624.84,1,1,1,49599.27,0 +3404,15611800,Loggia,624,France,Female,62,7,125163.62,2,1,1,151411.5,0 +3405,15576928,Walsh,573,France,Female,23,2,0,1,1,0,122964.18,0 +3406,15793693,Mahomed,694,France,Male,60,9,0,1,1,1,57088.97,0 +3407,15581252,Dolgorukova,632,Spain,Female,29,7,80922.75,1,1,0,7820.78,0 +3408,15797760,Bogdanov,632,France,Male,40,3,193354.86,2,1,0,149188.41,0 +3409,15790564,She,832,Germany,Female,40,9,107648.94,2,1,1,134638.97,0 +3410,15593736,Cook,598,Germany,Female,46,7,131769.04,1,0,0,184980.23,1 +3411,15595937,Bruno,430,Germany,Male,36,1,138992.48,2,0,0,122373.42,0 +3412,15815628,Moysey,711,France,Female,37,8,113899.92,1,0,0,80215.2,0 +3413,15782802,Beneventi,582,Germany,Male,26,6,114450.32,1,1,1,14081.64,0 +3414,15627412,Ferri,605,France,Male,39,3,0,2,1,0,199390.45,0 +3415,15734609,Skinner,657,France,Female,37,2,0,2,1,1,7667.48,0 +3416,15710689,Angel,578,Spain,Male,40,6,63609.92,1,0,0,74965.61,1 +3417,15565806,Toosey,532,France,Male,38,9,0,2,0,0,30583.95,0 +3418,15815530,Chin,612,France,Female,42,10,75497.51,1,0,0,149682.78,0 +3419,15632272,Lung,792,France,Female,42,2,0,2,1,0,92664.09,0 +3420,15684103,Mellor,674,France,Female,26,10,0,2,1,1,138423.1,0 +3421,15654519,Hassall,680,France,Male,31,1,0,2,1,1,3148.2,0 +3422,15767722,Richardson,593,France,Female,39,0,117704.73,1,1,0,197933.5,0 +3423,15654346,Poninski,679,Germany,Male,35,1,130463.55,2,1,1,37341.17,0 +3424,15660147,Dore,493,Spain,Male,32,8,46161.18,1,1,1,79577.4,0 +3425,15814998,Bonham,688,Spain,Male,42,5,0,2,0,0,197602.29,0 +3426,15802207,Ibezimako,769,Germany,Male,43,4,110182.54,2,1,1,87537.32,0 +3427,15658668,Hunter,581,Spain,Male,49,10,0,2,0,0,41623.59,0 +3428,15715079,Bold,465,France,Male,41,9,117221.15,1,1,0,168280.95,0 +3429,15570360,Wan,641,France,Female,35,4,0,2,0,0,125986.18,0 +3430,15674678,Bradley,731,Germany,Female,43,9,79120.27,1,0,0,548.52,1 +3431,15780925,Tretyakova,625,France,Male,37,1,177069.24,2,1,1,96088.54,0 +3432,15688193,Graham,468,France,Male,36,3,61636.97,1,0,0,107787.42,0 +3433,15778219,Izmailov,790,France,Male,26,5,0,1,1,0,20510.79,0 +3434,15696514,Calabrese,587,Germany,Female,37,6,104414.03,1,1,0,192026.02,0 +3435,15712303,Valentin,692,France,Male,66,4,159732.02,1,1,1,118188.15,0 +3436,15719090,Osonduagwuike,676,Germany,Female,34,4,89437.03,1,1,1,189540.95,0 +3437,15735632,Williamson,571,France,Male,41,8,0,1,1,1,63736.17,0 +3438,15619436,Pan,700,France,Female,32,3,0,1,0,0,95740.37,0 +3439,15722404,Carpenter,445,France,Female,30,3,0,2,1,1,127939.19,0 +3440,15662063,McIver,746,France,Male,36,7,142400.77,1,1,1,193438.69,0 +3441,15745605,Trevisan,722,France,Female,47,2,88011.4,1,1,1,90655.94,1 +3442,15636658,Rozhkova,596,France,Male,36,2,0,2,1,1,12067.39,0 +3443,15784130,He,850,Germany,Female,30,8,154870.28,1,1,1,54191.38,0 +3444,15606755,Moretti,597,Spain,Female,46,4,0,2,1,0,58667.16,1 +3445,15801699,Fishbourne,436,Spain,Male,43,5,0,2,1,1,35687.43,0 +3446,15784097,Gibson,660,Germany,Male,28,1,118402.25,2,1,0,14288.93,0 +3447,15764654,Zikoranachidimma,649,France,Male,37,9,87374.88,2,1,1,247.36,0 +3448,15612092,Palmer,646,Germany,Male,32,8,105397.8,1,1,0,78111.84,1 +3449,15610903,Chukwueloka,560,Spain,Female,31,5,125341.69,1,1,0,79547.39,0 +3450,15705777,Real,710,Germany,Male,49,10,129164.88,1,1,1,193266.72,0 +3451,15661936,Chikelu,513,France,Male,40,3,141004.46,1,1,0,105028.46,0 +3452,15700864,Fiorentini,607,France,Female,21,0,0,2,1,0,116106.52,0 +3453,15722965,Yefimova,757,France,Male,57,3,89079.41,1,1,1,53179.21,1 +3454,15737521,Ball,619,Germany,Male,40,9,103604.31,2,0,0,140947.05,0 +3455,15814465,Ch'in,612,France,Male,24,1,182705.05,1,1,1,171837.06,0 +3456,15580988,Odell,842,France,Male,29,8,0,2,1,1,123437.05,0 +3457,15789974,Enemuo,713,France,Male,33,6,94598.48,1,0,0,197519.66,1 +3458,15713370,Hunter,657,Spain,Male,36,8,188241.05,2,0,0,183058.51,1 +3459,15748673,Nepean,770,France,Female,37,9,0,2,0,0,22710.72,0 +3460,15754919,Nwebube,773,France,Female,40,10,0,2,0,1,69303.15,0 +3461,15641662,Enticknap,470,Germany,Male,39,5,117469.91,2,0,0,63705.9,0 +3462,15813422,Lu,781,Spain,Male,35,4,80790.74,1,1,0,116429.51,0 +3463,15713596,Ugochukwu,428,France,Female,62,1,107735.93,1,0,1,58381.77,0 +3464,15791216,Mann,600,Germany,Male,43,8,133379.41,1,1,0,177378.66,1 +3465,15689031,Murphy,697,Spain,Female,37,7,168066.87,1,1,0,35450.53,0 +3466,15763704,Docherty,692,Germany,Female,43,2,69014.49,2,0,0,164621.43,0 +3467,15631339,Adams,791,France,Male,28,4,0,1,1,0,174435.48,0 +3468,15771509,Hirst,538,Germany,Female,42,1,98548.62,2,0,1,94047.75,0 +3469,15769586,Horan,820,France,Female,49,1,0,2,1,1,119087.25,0 +3470,15656096,Cumbrae-Stewart,679,Spain,Female,26,3,76554.06,1,1,1,184800.27,0 +3471,15585280,Kinney,649,France,Female,36,2,0,2,0,1,75035.48,0 +3472,15743582,T'ang,632,France,Female,27,3,107375.82,1,1,1,62703.38,0 +3473,15761692,Muir,594,France,Male,40,9,122417.17,2,0,1,190882.69,0 +3474,15627840,Toscano,682,France,Female,42,0,0,1,0,1,91981.85,1 +3475,15778861,Wallace,720,Spain,Male,33,6,97188.62,1,0,0,91881.29,0 +3476,15770554,Fraser,769,France,Male,31,4,61297.05,2,1,1,7118.02,0 +3477,15806956,Iqbal,746,Spain,Male,30,1,112666.67,1,0,0,11710.4,1 +3478,15701908,Nina,623,Spain,Female,40,7,0,1,1,1,25904.12,0 +3479,15736990,Chuang,537,France,Male,28,3,157842.07,1,1,0,86911.49,0 +3480,15743714,Ch'ien,468,France,Male,46,7,91443.75,1,1,0,10958.18,0 +3481,15807993,Bruno,588,Germany,Female,30,0,110148.49,1,1,0,5790.9,1 +3482,15644686,Kennedy,729,Spain,Female,34,9,53299.96,2,1,1,42855.97,0 +3483,15677377,Lawrence,543,Spain,Male,37,3,0,2,1,1,78915.68,0 +3484,15626412,Mort,499,Spain,Male,39,6,0,2,1,1,81409,0 +3485,15643679,Goliwe,784,Germany,Male,28,2,70233.74,2,1,1,179252.73,0 +3486,15728456,Martinez,604,France,Male,33,3,0,1,1,0,42171.13,1 +3487,15630661,Vasilyev,614,Spain,Female,25,10,75212.28,1,1,0,58965.04,0 +3488,15734044,Black,671,France,Female,31,7,41299.03,1,0,1,102681.32,0 +3489,15705001,Napolitani,587,Spain,Female,35,3,83286.56,1,1,0,125553.52,0 +3490,15809817,Ch'en,593,Spain,Male,43,10,0,2,0,0,53478.02,0 +3491,15809137,Sagese,453,France,Male,29,6,0,1,0,0,198376.02,1 +3492,15751593,Fraser,570,Germany,Male,35,6,85668.59,1,1,0,105525.36,0 +3493,15626491,Hughes,655,France,Female,45,7,57327.04,1,0,1,47349,0 +3494,15765461,Giles,632,Spain,Male,47,3,0,2,1,0,178822.32,0 +3495,15568120,Lacross,681,France,Female,37,7,69609.85,1,1,1,72127.83,0 +3496,15787161,Pisani,591,Germany,Male,46,4,129269.27,1,1,0,163504.33,0 +3497,15812324,King,779,France,Male,27,1,0,2,1,1,190623.02,0 +3498,15588944,Maughan,456,France,Female,63,1,165350.61,2,0,0,140758.07,1 +3499,15694253,Palerma,686,France,Female,41,7,152105.57,2,0,1,132374.41,0 +3500,15759566,Tochukwu,617,France,Male,74,10,0,2,1,1,53949.98,0 +3501,15675675,Slate,850,France,Female,32,5,106290.64,1,1,0,121982.73,0 +3502,15802060,Ch'ang,646,Germany,Female,30,10,100548.67,2,0,0,136983.77,0 +3503,15660505,Romani,735,Germany,Male,46,2,106344.95,1,1,0,114371.33,1 +3504,15782630,Genovese,543,France,Male,35,5,137482.19,1,0,0,62389.35,0 +3505,15700710,Chiebuka,490,France,Female,37,3,116465.53,1,0,1,24435.77,0 +3506,15742834,Liao,640,France,Male,45,1,0,1,1,1,10908.33,0 +3507,15806511,Berry,445,Spain,Male,45,10,0,2,0,1,90977.48,0 +3508,15608166,Fallaci,761,France,Male,36,9,127637.92,1,1,1,81062.93,0 +3509,15614230,T'an,426,France,Female,34,3,0,2,1,1,61230.83,0 +3510,15729958,Wilkinson,777,France,Male,37,1,0,1,1,1,126837.72,0 +3511,15800814,Palerma,534,France,Male,35,2,81951.74,2,1,0,115668.53,0 +3512,15674727,Lazarev,777,France,Female,42,5,147531.82,1,1,1,38819.45,0 +3513,15657779,Boylan,806,Spain,Male,18,3,0,2,1,1,86994.54,0 +3514,15801395,Warren,790,France,Female,33,10,135120.72,1,0,0,195204.99,0 +3515,15757911,Trevisani,643,Spain,Female,32,2,0,1,0,0,131301.74,0 +3516,15665340,Trevisano,584,Spain,Female,37,8,0,2,0,1,100835.19,0 +3517,15787151,Liao,638,France,Female,34,7,0,2,1,1,198969.78,0 +3518,15757821,Burgess,771,Spain,Male,18,1,0,2,0,0,41542.95,0 +3519,15600688,Liston,600,France,Female,39,5,0,2,0,0,118272.07,0 +3520,15594878,Thompson,661,Spain,Female,41,5,28082.95,1,1,0,69586.27,1 +3521,15569248,Milanesi,554,France,Female,43,10,0,2,1,0,149629.13,1 +3522,15812706,Mazure,627,Spain,Male,49,4,111087.5,1,0,1,146680.25,0 +3523,15645045,Rudduck,659,France,Female,38,9,0,2,1,1,132809.18,0 +3524,15766746,Darwin,835,France,Male,35,6,127120.07,1,1,0,28707.69,0 +3525,15700383,Uvarova,763,France,Female,35,7,115651.6,2,1,1,104706.29,0 +3526,15632551,Buccho,625,Germany,Male,31,4,77743.01,2,1,0,75335.68,0 +3527,15795129,Gallo,799,France,Female,30,9,0,2,1,0,136827.96,0 +3528,15650545,Tomlinson,849,France,Male,69,7,71996.09,1,1,1,139065.94,0 +3529,15612769,Carr,692,France,Male,28,5,61581.97,1,1,1,70179.91,0 +3530,15710853,Ts'ui,623,France,Female,24,5,0,2,1,0,116160.04,0 +3531,15623712,Coates,453,Spain,Female,42,5,0,3,1,0,83008.49,1 +3532,15653251,Hickey,408,France,Female,84,8,87873.39,1,0,0,188484.52,1 +3533,15755077,Norton,778,Germany,Female,37,0,105617.73,2,1,1,133699.82,1 +3534,15808557,Mancini,695,France,Female,42,5,0,1,0,1,72172.13,1 +3535,15614687,Tien,677,Germany,Female,44,4,148770.61,2,1,1,191057.76,0 +3536,15626882,Stobie,662,Spain,Male,37,5,94901.09,1,1,1,48233.75,0 +3537,15748034,Drakeford,534,France,Male,29,7,174851.9,1,1,1,79178.31,0 +3538,15632324,Pisani,602,France,Male,59,7,0,2,1,1,162347.05,0 +3539,15761023,Murphy,554,Germany,Female,43,2,120847.11,1,1,0,7611.61,1 +3540,15761453,Kovalev,667,France,Male,42,6,0,1,1,0,88890.05,0 +3541,15646726,Crawford,672,France,Male,43,5,0,1,0,0,63833.09,0 +3542,15637169,Maclean,838,Spain,Female,67,4,103267.8,1,1,1,78310.04,0 +3543,15636024,Blackburn,692,Spain,Female,34,4,109699.08,1,1,1,37898.91,0 +3544,15801218,Bermudez,675,France,Male,49,8,135133.39,1,0,1,179521.24,1 +3545,15642655,Savage,731,Spain,Male,33,1,0,1,1,0,130726.96,0 +3546,15690130,Wyatt,468,France,Female,32,8,137649.47,1,0,0,198714.29,0 +3547,15653753,Chiemenam,542,Spain,Male,43,6,113567.94,1,1,0,89543.25,0 +3548,15641359,Shao,662,Spain,Female,35,6,0,2,0,0,2423.9,1 +3549,15776827,Langdon,770,Germany,Male,37,5,141547.26,2,0,1,180326.83,0 +3550,15647725,Napolitano,675,France,Female,61,5,62055.17,3,1,0,166305.16,1 +3551,15648455,Kung,647,Germany,Male,51,4,131156.76,1,1,0,29883.63,0 +3552,15580629,Blackwood,604,France,Male,31,6,134837.58,1,1,0,192029.19,0 +3553,15730161,Marcelo,833,France,Female,39,3,0,2,1,0,1710.89,0 +3554,15626612,Yin,741,Spain,Male,40,4,104784.23,1,1,0,135163.76,1 +3555,15662865,Storey,658,Spain,Male,36,1,0,2,0,1,84927.42,0 +3556,15629094,Fomin,528,France,Female,36,1,156948.41,1,1,1,149912.28,1 +3557,15651823,Nkemjika,590,France,Female,60,6,147751.75,1,1,0,88206.04,1 +3558,15594827,Glasgow,675,France,Male,34,1,124619.33,2,0,1,163667.56,0 +3559,15786392,Chen,765,France,Male,41,4,124182.21,1,0,0,100153.43,0 +3560,15727353,Ch'ang,650,France,Female,64,7,142028.36,1,1,0,32275.09,1 +3561,15733777,Evans,817,France,Male,44,8,0,1,0,0,65501.91,1 +3562,15614302,Crotty,699,Germany,Female,31,10,125837.86,2,1,0,189392.66,0 +3563,15723263,Cocci,495,Germany,Female,34,9,117160.32,1,1,1,116069.24,1 +3564,15687270,Iroawuchi,491,Spain,Female,61,8,0,2,0,1,139861.53,0 +3565,15803121,Chia,847,France,Male,51,5,97565.74,1,0,0,144184.06,1 +3566,15598700,Hysell,676,Spain,Female,30,5,0,2,0,1,157888.5,0 +3567,15741875,Williamson,746,Spain,Female,25,3,104833.79,1,0,0,71911.3,0 +3568,15631709,Ginikanwa,470,Spain,Female,31,2,101675.22,2,1,0,45033.75,0 +3569,15672970,Chigolum,714,Spain,Male,20,3,0,2,0,1,150465.93,0 +3570,15761670,Morley,695,France,Female,50,8,0,1,1,0,126381.6,1 +3571,15706005,Roberts,674,France,Male,46,2,174701.05,1,1,0,90189.72,1 +3572,15790336,Tokareva,664,Germany,Male,36,6,71142.77,2,1,0,122433.09,0 +3573,15754267,Fleming,697,Germany,Male,31,3,108805.42,2,0,1,123825.83,0 +3574,15791988,Chinomso,670,France,Male,68,4,0,2,1,1,11426.7,0 +3575,15683375,Compton,541,France,Female,32,4,0,1,1,1,114951.42,0 +3576,15625151,Wan,640,France,Female,66,9,116037.76,1,0,1,184636.05,0 +3577,15635285,Taylor,647,France,Male,28,8,0,2,1,1,91055.27,0 +3578,15574296,Kambinachi,757,France,Male,23,2,80673.96,2,1,0,93991.65,0 +3579,15711618,Chang,704,Germany,Female,39,1,124640.51,1,1,0,116511.12,1 +3580,15670943,See,778,Germany,Male,31,9,182275.23,2,1,0,190631.23,0 +3581,15634359,Dyer,639,Germany,Female,41,5,98635.77,1,1,0,199970.74,0 +3582,15586629,Campbell,637,France,Male,33,5,0,2,1,0,139947.17,0 +3583,15588461,Cremonesi,686,France,Male,35,4,0,1,1,0,8816.37,0 +3584,15773221,Harris,577,Spain,Male,43,8,79757.21,1,1,0,135650.72,1 +3585,15664227,Threatt,506,Germany,Male,28,8,53053.76,1,0,1,24577.34,0 +3586,15741745,Lane,757,France,Male,28,7,120911.75,2,1,1,131249.46,0 +3587,15652626,Grave,826,France,Male,55,4,115285.85,1,1,0,140126.17,0 +3588,15599410,Stanley,721,France,Male,41,2,0,2,1,0,168219.75,0 +3589,15571958,McIntosh,489,Spain,Male,40,3,221532.8,1,1,0,171867.08,0 +3590,15785406,Watts,446,France,Female,51,4,105056.13,1,0,0,70613.52,0 +3591,15687884,Alekseyeva,677,France,Male,37,3,88363.03,1,0,1,117946.3,0 +3592,15621685,Davies,769,France,Male,29,2,123757.52,2,1,0,84872.66,0 +3593,15628886,Matlock,677,Spain,Male,56,5,123959.97,1,1,1,60590.72,1 +3594,15699325,Fedorova,555,Germany,Female,62,10,114822.64,1,0,1,8444.5,0 +3595,15578369,Chiedozie,652,Germany,Female,37,9,145219.3,1,1,0,159132.83,0 +3596,15654156,Marcelo,722,Germany,Female,32,5,106807.64,1,1,1,76998.69,0 +3597,15707199,Cooper,643,France,Male,36,0,148159.71,1,0,0,55835.66,0 +3598,15671630,McMillan,796,Germany,Female,40,1,99745.95,1,1,0,177524.19,0 +3599,15632079,Hardy,720,Germany,Female,37,8,156282.79,1,1,0,45985.52,0 +3600,15767921,Madukwe,613,France,Male,41,7,0,2,1,0,60297.72,0 +3601,15573599,Adamson,506,France,Female,57,6,0,2,0,1,194421.12,1 +3602,15747208,Watt,608,France,Male,50,6,0,1,1,0,93568.77,1 +3603,15582762,Mazzanti,667,Spain,Male,77,2,0,1,1,1,34702.92,0 +3604,15772528,Mishin,750,France,Female,47,7,121376.15,2,1,0,54473.6,1 +3605,15755798,Feng,610,France,Male,33,4,111582.11,1,0,0,113943.17,0 +3606,15788683,Kang,588,Germany,Female,34,10,129417.82,1,1,0,153727.32,0 +3607,15616922,Kelly,479,France,Female,26,1,0,2,1,1,19116.97,0 +3608,15771855,Yu,682,France,Male,37,5,0,2,0,1,112554.68,0 +3609,15601873,Bull,677,France,Female,36,7,0,1,1,0,47318.75,0 +3610,15657868,Serra,850,Germany,Male,40,6,94607.08,1,1,0,36690.49,0 +3611,15711716,Ferguson,580,France,Female,56,1,131368.3,1,1,0,106918.67,1 +3612,15734246,She,746,France,Female,21,8,166883.07,2,0,1,194563.65,0 +3613,15792151,Hamilton,635,Spain,Female,37,3,0,2,1,0,91086.73,0 +3614,15770159,Nnanna,664,Germany,Male,25,6,172812.72,2,1,1,108008.65,0 +3615,15747649,Summerville,558,Germany,Female,36,0,126606.63,2,1,1,172363.52,0 +3616,15639357,Allan,415,France,Male,46,9,134950.19,3,0,0,178587.36,1 +3617,15738907,Tobenna,798,France,Female,60,6,96956.1,1,1,0,31907.44,1 +3618,15663446,Volkova,792,Germany,Female,29,4,107601.79,1,1,0,18922.18,1 +3619,15750867,Nucci,489,Germany,Female,46,8,92060.06,1,1,0,147222.95,1 +3620,15715939,Wright,730,France,Male,33,0,0,2,1,0,1474.79,0 +3621,15763806,Astorga,773,France,Male,41,4,0,2,1,1,24924.92,0 +3622,15637993,Pokrovsky,711,France,Male,36,9,137688.71,1,1,1,46884.1,0 +3623,15720338,Mazzanti,592,Spain,Male,55,8,85845.43,2,1,1,128918.42,0 +3624,15627162,Blesing,695,Germany,Male,27,6,125552.96,1,1,0,105291.26,0 +3625,15596710,Ku,640,France,Female,33,1,167298.42,1,0,1,145381.65,0 +3626,15781678,Pisani,470,Spain,Male,31,4,55732.92,2,1,1,103792.53,0 +3627,15634968,Hsueh,789,Germany,Female,37,6,110689.07,1,1,1,71121.04,1 +3628,15609475,Ricci,604,Spain,Female,39,7,98544.11,1,1,1,52327.57,0 +3629,15573319,Azubuike,493,Germany,Female,35,8,178317.6,1,0,0,197428.64,0 +3630,15738291,Nevzorova,671,France,Female,48,8,115713.84,2,0,0,83210.84,0 +3631,15782456,Odili,656,France,Male,46,9,143267.14,2,0,0,193099.43,0 +3632,15794841,Kung,739,Spain,Male,19,5,89750.21,1,1,0,193008.52,0 +3633,15684696,Lei,560,Spain,Female,26,3,116576.45,1,1,0,157567.37,0 +3634,15629846,Sheehan,827,Germany,Female,47,8,143001.5,2,1,0,108977.5,0 +3635,15674442,Kung,681,France,Male,23,7,157761.56,1,0,0,147759.84,0 +3636,15571689,Kelechi,740,France,Female,37,5,0,2,1,1,27528.4,0 +3637,15730469,Anenechi,663,Spain,Male,31,4,103430.11,2,0,1,36479.27,0 +3638,15809320,McElhone,845,Spain,Female,52,0,0,1,1,0,31726.76,1 +3639,15684367,Chigbogu,555,Spain,Male,27,5,0,2,0,0,96398.51,0 +3640,15793049,Atkins,680,Germany,Female,48,8,115115.38,1,1,0,139558.6,1 +3641,15603665,Colombo,638,Germany,Female,39,0,122501.28,2,1,1,95007.8,0 +3642,15613623,Tilley,640,Spain,Male,62,3,0,1,1,1,101663.47,0 +3643,15569572,Sopuluchi,778,France,Male,42,6,0,2,1,1,106197.44,0 +3644,15698791,Udinesi,679,France,Male,45,3,146758.24,1,1,0,48466.89,0 +3645,15626233,Onyekachi,593,France,Female,32,3,0,2,1,1,151978.36,0 +3646,15607263,McCartney,788,France,Male,55,3,0,1,0,1,13288.46,1 +3647,15610900,Thompson,770,France,Female,70,9,110738.89,1,1,0,22666.77,1 +3648,15624775,Onyeoruru,729,France,Male,67,2,94203.8,1,0,1,102391.06,0 +3649,15691703,Shih,545,France,Male,47,8,105792.49,1,0,1,67830.2,1 +3650,15745355,Golibe,597,France,Male,41,4,153198.23,1,1,1,92090.36,0 +3651,15724955,Lucchesi,537,France,Male,38,3,0,2,0,0,141023.01,0 +3652,15628999,Townsend,732,France,Male,79,10,61811.23,1,1,1,104222.8,0 +3653,15654341,Chao,542,France,Male,34,8,101116.06,1,1,0,196395.05,0 +3654,15744240,Shen,688,Germany,Female,46,0,74458.25,1,0,1,6866.31,0 +3655,15632365,Booth,542,Germany,Male,33,8,142871.27,2,0,0,77737.86,0 +3656,15729689,Chan,754,Germany,Male,35,6,98585.94,2,0,1,106116.84,0 +3657,15759284,Yeh,750,France,Female,37,6,0,1,1,1,117948,1 +3658,15602124,Badgery,731,France,Male,30,7,0,2,1,1,184581.68,0 +3659,15661903,Hsia,699,France,Female,43,3,80764.03,1,1,0,199378.58,1 +3660,15664668,Zarate,534,France,Female,42,9,144801.97,1,0,1,12483.39,1 +3661,15736431,Congreve,494,Spain,Male,27,2,0,2,1,0,22404.64,0 +3662,15748639,Hayslett,497,Germany,Male,35,7,110053.62,2,1,1,92887.06,0 +3663,15628123,Robinson,632,France,Female,28,5,118890.81,1,0,1,145157.97,0 +3664,15602731,Wong,724,France,Male,31,5,0,1,1,0,134889.95,1 +3665,15794137,Nevzorova,751,Germany,Female,37,0,151218.98,1,1,1,109309.29,0 +3666,15748696,Page,733,France,Male,42,9,150507.21,1,0,1,169964.12,0 +3667,15725068,Quinn,701,Spain,Female,21,9,0,2,1,1,26327.42,0 +3668,15807340,O'Donnell,525,Germany,Male,33,4,131023.76,2,0,0,55072.93,0 +3669,15586133,Pisano,666,Germany,Female,44,2,122314.5,1,0,0,68574.88,1 +3670,15576185,Sinclair,653,France,Male,29,2,0,2,1,1,41671.81,0 +3671,15660809,Loving,850,France,Male,28,4,0,2,1,1,12409.01,0 +3672,15616666,Artemova,646,Germany,Female,52,6,111739.4,2,0,1,68367.18,0 +3673,15706904,Robertson,750,France,Male,43,6,113882.31,1,1,1,74564.41,0 +3674,15606915,Genovese,764,France,Male,24,7,98148.61,1,1,0,26843.76,0 +3675,15749693,Ugonnatubelum,658,France,Female,32,9,0,2,1,0,156774.75,0 +3676,15791743,Corbett,727,France,Male,32,1,59271.82,1,1,1,46019.43,0 +3677,15796480,Reilly,687,France,Female,31,2,0,2,0,1,145411.39,0 +3678,15790442,Wright,631,Spain,Male,33,2,0,2,1,1,158268.84,0 +3679,15609458,Vincent,797,France,Male,30,10,69413.44,1,1,1,74637.57,0 +3680,15593897,Carr,650,Spain,Male,25,7,160599.06,2,1,1,28391.52,0 +3681,15604576,Eiland,850,Spain,Male,22,3,0,1,1,1,144385.54,0 +3682,15666270,Omeokachie,676,France,Female,40,2,147803.48,1,1,0,95181.06,1 +3683,15572626,Mackenzie,620,Spain,Male,44,8,0,2,1,1,15627.51,0 +3684,15727197,Pinto,576,France,Female,52,9,170228.59,2,0,0,148477.57,1 +3685,15714006,Gardener,482,France,Female,35,2,133111.73,1,0,1,79957.95,0 +3686,15642137,Fang,695,Spain,Female,39,5,0,2,0,0,102763.69,0 +3687,15665327,Cattaneo,706,France,Male,18,2,176139.5,2,1,0,129654.22,0 +3688,15626806,Labrador,668,France,Female,32,2,0,2,1,1,40652.33,0 +3689,15662578,Dettmann,679,Germany,Male,35,1,110245.13,1,1,1,178291.09,0 +3690,15790829,Gibson,703,France,Female,45,5,0,2,1,0,131906.44,0 +3691,15654959,Hope,670,Spain,Male,67,6,158719.57,1,1,1,118607.4,0 +3692,15760244,Ives,590,France,Female,76,5,160979.68,1,0,1,13848.58,0 +3693,15715394,Greece,613,Spain,Male,35,4,123557.65,2,0,1,170903.4,0 +3694,15722246,Omeokachie,742,France,Female,60,4,0,1,1,1,13161.66,1 +3695,15609704,Mao,608,France,Female,33,4,0,1,1,0,79304.38,1 +3696,15757628,Savage,571,France,Male,40,10,112896.86,1,1,1,121402.53,0 +3697,15633586,Brierly,595,France,Female,39,7,120962.13,1,0,0,23305.01,0 +3698,15565796,Docherty,745,Germany,Male,48,10,96048.55,1,1,0,74510.65,0 +3699,15717935,McDonald,589,France,Female,21,3,0,2,0,1,55601.44,0 +3700,15577700,Rapuokwu,749,France,Male,37,10,185063.7,2,1,1,134526.87,0 +3701,15747345,Bergamaschi,678,France,Female,22,6,118064.93,2,1,1,195424.01,0 +3702,15678317,Manfrin,603,France,Male,46,2,0,2,1,1,59563.49,0 +3703,15698335,Bergamaschi,504,France,Female,73,8,0,1,1,1,34595.58,0 +3704,15768451,MacDonald,739,Germany,Male,40,5,149131.03,3,1,1,60036.99,1 +3705,15753213,Lees,604,France,Female,34,7,0,2,1,0,193021.49,0 +3706,15769645,Senior,612,France,Female,35,3,0,1,1,1,48108.72,0 +3707,15657565,Nwokezuike,629,Spain,Female,44,6,125512.98,2,0,0,79082.76,0 +3708,15620323,Ekwueme,652,Spain,Female,42,3,83492.07,2,1,0,37914.12,0 +3709,15679983,Garmon,565,France,Male,34,7,0,1,0,0,74593.84,0 +3710,15812616,Enyinnaya,707,France,Female,49,10,0,1,1,0,82967.97,1 +3711,15601796,Chizuoke,645,France,Male,30,1,125739.26,1,1,1,193441.23,0 +3712,15729489,Hyde,762,Germany,Female,34,8,98592.88,1,0,1,191790.29,1 +3713,15613216,Cameron,639,Spain,Female,39,1,141789.15,1,1,0,92455.96,0 +3714,15657937,Lord,709,Germany,Male,22,0,112949.71,1,0,0,155231.55,0 +3715,15815428,Biryukova,823,France,Male,34,3,105057.33,1,1,0,9217.92,0 +3716,15640409,Carpenter,817,Germany,Female,46,0,89087.89,1,0,1,87941.85,1 +3717,15699492,Lorenzo,665,Germany,Female,27,2,147435.96,1,0,0,187508.06,0 +3718,15623536,Madukwe,646,Germany,Male,39,0,154439.86,1,1,0,171519.06,0 +3719,15707551,Hutcheon,568,France,Male,30,8,73054.37,2,1,1,27012,0 +3720,15577999,Sleeman,850,France,Female,62,1,124678.35,1,1,0,70916,1 +3721,15788775,Milne,473,Germany,Male,40,8,152576.25,2,1,0,73073.68,0 +3722,15758362,Williamson,731,France,Female,41,9,152243.57,1,1,1,88783.59,0 +3723,15807961,Bruno,619,France,Male,25,4,0,1,1,0,145524.36,0 +3724,15710978,Palerma,715,Germany,Male,42,2,88120.97,2,1,1,21333.22,0 +3725,15703541,Wang,772,Germany,Female,51,9,143930.92,1,0,1,46675.51,1 +3726,15626474,Onyemere,686,France,Female,31,1,0,2,1,0,4802.25,0 +3727,15608344,Dawson,749,Germany,Female,29,7,137059.05,3,1,0,102975.72,1 +3728,15768367,Nebechukwu,781,France,Female,27,7,186558.55,1,1,1,175071.29,1 +3729,15806210,Bateman,675,Spain,Male,66,5,115654.47,2,1,1,131970.86,0 +3730,15697702,Lord,730,Spain,Male,29,2,0,2,1,0,14174.09,0 +3731,15689152,Loggia,683,Spain,Male,38,3,126152.84,1,0,0,15378.75,0 +3732,15568573,Graham,554,Germany,Female,51,7,105701.91,1,0,1,179797.79,1 +3733,15689598,Dean,722,France,Male,46,6,0,1,1,1,93917.68,1 +3734,15713374,Jarvis,689,Germany,Male,67,9,157094.78,1,1,1,99490.01,0 +3735,15679733,Haugh,796,Germany,Male,40,2,113228.38,2,1,1,46415.09,0 +3736,15759274,Micklem,447,France,Female,32,10,0,1,1,1,151815.76,0 +3737,15607748,Bennett,498,Germany,Male,37,8,108432.88,2,1,1,14865.05,0 +3738,15607577,Roberts,663,Spain,Male,27,8,0,1,1,1,188007.99,0 +3739,15813697,Onyekaozulu,498,Germany,Female,44,2,120702.67,2,1,1,98175.74,0 +3740,15801125,Kegley,627,France,Female,32,1,0,1,1,0,106851.7,0 +3741,15777855,Manna,649,France,Male,45,7,0,2,0,1,75204.21,0 +3742,15635396,Thompson,738,Germany,Female,29,9,139106.19,1,1,0,141872.05,1 +3743,15698031,Romano,587,Germany,Female,39,6,101851.8,2,1,0,7103.71,0 +3744,15678944,Brown,655,Germany,Female,32,6,130935.56,1,1,0,9241.83,1 +3745,15718507,Su,647,Germany,Male,37,3,116509.99,1,1,1,149517.71,1 +3746,15808334,Mackay,776,Germany,Female,37,1,93124.04,2,1,1,196079.32,0 +3747,15804709,Watt,688,Germany,Male,35,5,111578.18,1,0,0,166165.93,1 +3748,15645835,Milani,605,France,Male,32,9,0,2,1,1,55724.24,0 +3749,15738166,Hsu,596,France,Female,39,10,86546.29,1,0,1,131768.98,0 +3750,15675360,Valenzuela,427,France,Male,33,8,0,1,1,1,13858.95,0 +3751,15793042,Sung,629,France,Male,39,2,129669.32,2,1,0,82774.07,0 +3752,15630106,Lo,496,Spain,Male,29,2,0,2,1,0,55389.59,0 +3753,15810385,Giordano,717,Spain,Female,36,2,164557.95,1,0,1,82336.73,0 +3754,15578211,Connolly,777,France,Male,23,6,0,2,1,1,163225.48,0 +3755,15572792,Bellucci,535,Spain,Male,35,8,118989.92,1,1,1,135536.72,0 +3756,15620030,Jamieson,744,France,Male,29,1,0,1,0,0,82422.97,0 +3757,15783541,Fomina,755,France,Male,31,5,0,2,0,1,194660.78,0 +3758,15679284,Aksenov,593,Spain,Female,45,6,79259.75,1,1,0,55347.28,0 +3759,15582910,Turnbull,514,France,Male,38,4,112230.38,1,1,0,16717.11,1 +3760,15688337,Dixon,721,France,Male,40,9,118129.87,1,1,1,160277.65,0 +3761,15734970,White,835,Spain,Male,38,7,86824.09,1,0,0,175905.97,0 +3762,15759140,Long,682,France,Female,64,10,128306.7,1,0,1,66040.83,0 +3763,15643042,Han,590,Germany,Female,40,2,117641.43,2,0,0,92198.05,0 +3764,15773868,Belov,653,Germany,Female,37,3,125734.2,2,1,0,134625.09,1 +3765,15615820,MacDonald,837,France,Male,49,8,103302.37,1,1,1,50974.57,0 +3766,15730273,Parsons,841,France,Male,27,8,0,1,1,0,171922.72,0 +3767,15724890,Cross,584,Spain,Male,36,4,82696.09,2,0,0,83058.14,0 +3768,15765952,Milanesi,769,France,Male,29,4,145471.37,1,1,0,188382.77,0 +3769,15685920,Lombardo,599,Spain,Male,34,2,101506.66,1,0,0,198030.24,0 +3770,15663263,Collins,698,France,Male,47,5,156265.31,2,0,0,1055.66,0 +3771,15568953,Alexeieva,477,France,Male,27,1,128554.98,1,1,1,133173.19,0 +3772,15643361,Cullen,477,Germany,Male,34,8,139959.55,2,1,1,189875.83,0 +3773,15699486,Johnson,745,Spain,Male,34,7,132944.53,1,1,1,31802.92,0 +3774,15747854,Rudd,749,France,Female,35,3,0,3,1,1,132649.85,0 +3775,15691785,Findlay,850,France,Male,61,1,0,1,1,0,53067.83,1 +3776,15709004,Mai,528,Germany,Male,22,5,93547.23,2,0,1,961.57,0 +3777,15652218,Morrison,750,France,Male,33,2,152302.72,1,1,0,71333.44,0 +3778,15697127,Monaldo,543,France,Female,31,2,147674.26,1,1,1,16658.76,0 +3779,15658486,Gidney,579,Spain,Female,59,3,148021.12,1,1,1,74878.22,0 +3780,15694160,Sagese,624,France,Male,37,0,0,2,0,0,112104.55,0 +3781,15685290,Wall,595,Germany,Male,46,5,142360.62,2,1,0,48421.4,1 +3782,15701042,Dalton,596,Germany,Female,27,2,151027.56,1,1,0,170320.58,0 +3783,15680449,Hsing,431,Germany,Female,44,2,138843.7,1,1,0,37688.31,1 +3784,15599860,Warner,647,Spain,Female,26,8,109958.15,1,1,1,136592.24,1 +3785,15723169,Williams,640,France,Female,31,9,138857.59,1,1,0,48640.77,0 +3786,15803842,Dunn,752,Germany,Female,45,3,105426.5,2,0,1,89773.45,0 +3787,15728224,Kerr,710,Germany,Female,41,9,149155.53,2,1,0,42131.26,1 +3788,15644174,Marchesi,638,Germany,Male,27,4,135096.05,1,1,1,186523.72,1 +3789,15707110,Endrizzi,660,Germany,Male,28,2,170890.05,2,1,0,41758.9,0 +3790,15765415,King,609,Spain,Female,45,4,89122.3,1,1,1,199256.98,0 +3791,15756751,Griffiths,596,Spain,Female,54,0,78126.28,1,1,1,153482.91,1 +3792,15795151,Hartzler,705,France,Female,38,3,123894.43,1,1,0,21177.1,0 +3793,15632859,Chukwudi,444,France,Male,36,7,0,2,0,1,138743.86,0 +3794,15584037,Denisov,727,Germany,Male,58,5,106913.43,1,1,0,25881,1 +3795,15621409,Endrizzi,496,France,Male,32,4,127845.83,1,1,0,66469.2,0 +3796,15581102,Baresi,554,France,Female,22,8,0,2,0,1,142670.61,0 +3797,15578096,Nnachetam,537,France,Male,26,7,106397.75,1,0,0,103563.23,0 +3798,15669887,Lambert,839,France,Female,51,3,0,1,1,1,69101.23,1 +3799,15621834,Game,700,Spain,Female,43,0,0,2,1,0,59475.35,0 +3800,15655341,Chinagorom,458,Spain,Female,35,5,166492.48,1,1,0,135287.74,0 +3801,15685314,Noble,850,France,Female,28,2,0,2,1,1,38773.74,0 +3802,15653997,Haynes,699,Spain,Male,31,6,114493.68,1,0,0,138396.32,0 +3803,15629551,Cattaneo,615,Germany,Female,44,9,126104.98,2,0,1,110718.02,0 +3804,15651264,Yobanna,850,Germany,Male,51,4,124425.99,1,0,0,118545.49,1 +3805,15760825,Fraser,604,France,Female,40,1,0,2,1,0,123207.17,0 +3806,15597394,Rhodes,668,Spain,Male,34,0,0,1,0,0,99984.86,0 +3807,15740383,Jimenez,594,Spain,Female,38,10,0,2,1,0,58332.91,0 +3808,15670562,Pharr,470,France,Male,30,3,101140.76,1,1,1,50906.65,0 +3809,15698117,Jerger,701,Germany,Male,41,0,150844.94,1,0,1,127623.36,0 +3810,15694805,McIntyre,664,Spain,Male,35,1,115024.5,1,0,1,169665.79,0 +3811,15746802,Onio,477,France,Female,30,6,131286.46,1,1,0,194144.45,0 +3812,15589428,Tomlinson,756,France,Female,42,9,0,2,1,0,35673.42,0 +3813,15790267,Onuoha,625,France,Female,40,7,141267.67,1,0,1,177397.49,0 +3814,15665402,Panicucci,703,Spain,Male,73,5,137761.55,1,1,1,159677.46,0 +3815,15642093,Piccio,646,France,Male,30,7,0,2,1,0,153566.97,0 +3816,15666181,Ramsden,650,France,Male,33,0,98064.97,1,1,0,52411.99,0 +3817,15602554,Vorobyova,664,France,Female,31,9,114519.57,2,0,1,79222.02,0 +3818,15724251,Todd,682,Germany,Female,29,6,101012.77,1,0,0,32589.89,1 +3819,15740147,Cremonesi,725,France,Female,44,10,0,1,0,1,93777.61,0 +3820,15718289,Bradley,553,Germany,Male,46,3,82291.1,1,1,0,112549.99,1 +3821,15763148,Stanley,576,France,Male,39,9,84719.98,1,0,0,191063.36,0 +3822,15685245,Jowett,608,Spain,Female,56,5,0,2,0,1,153810.41,0 +3823,15626985,Yefremova,850,France,Female,39,0,104386.53,1,1,0,105886.77,0 +3824,15585823,Wilson,627,France,Male,31,8,128131.73,1,1,0,96131.47,0 +3825,15728167,Abramovich,667,France,Male,44,2,122806.95,1,0,0,15120.86,0 +3826,15762928,Venables,548,Spain,Male,44,8,0,1,1,0,16989.77,0 +3827,15751774,Monnier,774,France,Male,76,4,112510.89,1,1,1,143133.18,0 +3828,15654733,Hsieh,794,Germany,Male,57,3,117056.46,1,1,0,93336.93,1 +3829,15809777,Gadsden,497,Germany,Female,55,7,131778.66,1,1,1,9972.64,0 +3830,15744200,Ni,587,France,Female,36,1,70784.27,1,1,0,30579.82,0 +3831,15720713,Chibueze,850,France,Female,29,10,0,2,1,1,199775.67,0 +3832,15695356,Chinwemma,722,France,Male,46,5,0,2,1,0,179908.71,0 +3833,15653315,Kang,555,Spain,Female,35,1,0,2,1,0,101667,0 +3834,15604792,Kuo,609,Germany,Male,38,6,140752.06,2,0,1,171430.16,0 +3835,15704819,Ositadimma,734,Spain,Female,39,6,92126.26,2,0,0,112973.34,0 +3836,15670859,Smith,718,Germany,Female,39,7,93148.74,2,1,1,190746.38,0 +3837,15602797,Okwudilichukwu,645,Spain,Female,49,5,110132.55,3,0,1,187689.91,1 +3838,15662533,Porter,598,Spain,Female,23,6,0,2,1,0,153229.19,0 +3839,15778154,Kung,628,Germany,Male,50,4,122227.71,1,0,1,14217.77,1 +3840,15806230,Trevisano,629,Germany,Male,40,2,121647.54,2,1,1,64849.74,1 +3841,15662884,Naylor,739,Germany,Male,58,1,110597.76,1,0,1,160122.66,1 +3842,15750778,Ponomarev,653,France,Female,60,2,120731.39,4,1,1,138160.11,1 +3843,15717185,Udinese,711,France,Male,28,8,0,2,1,1,64286.39,0 +3844,15677804,Aliyeva,783,Spain,Male,38,1,0,3,1,1,80178.54,1 +3845,15568915,Bailey,681,France,Male,38,6,153722.47,1,1,0,101319.76,0 +3846,15736495,Jackson,712,France,Male,34,8,114088.32,1,1,0,92794.61,0 +3847,15737354,Yin,554,France,Female,48,7,0,2,1,1,63708.07,0 +3848,15667889,Akobundu,611,France,Female,37,6,0,2,1,0,110782.88,0 +3849,15577831,Byrne,560,Germany,Male,41,4,152532.3,1,0,0,10779.69,0 +3850,15729836,Robinson,646,Spain,Male,32,1,0,2,1,0,183289.22,0 +3851,15775293,Stephenson,680,France,Male,34,3,143292.95,1,1,0,66526.01,0 +3852,15697597,Chiemenam,631,France,Male,26,1,149144.61,1,0,1,123697.95,0 +3853,15639669,Forbes,746,France,Male,36,9,127157.04,1,1,1,155700.15,0 +3854,15631392,Douglas,654,Germany,Male,43,9,84673.17,2,0,1,82081.35,0 +3855,15580935,Okechukwu,687,Germany,Male,33,9,135962.4,2,1,0,121747.96,0 +3856,15590344,Russell,708,Germany,Male,32,3,151691.44,2,1,1,172810.51,0 +3857,15653306,Ermakova,679,Germany,Female,32,0,88335.05,1,0,0,159584.81,0 +3858,15805025,Oster,636,France,Female,45,7,139859.23,1,1,1,108402.54,0 +3859,15658449,Chizoba,695,France,Male,45,9,43134.65,1,0,1,77330.35,0 +3860,15694450,Bianchi,677,France,Male,42,5,99580.13,1,1,0,21007.96,0 +3861,15605666,Peyser,720,France,Female,34,6,110717.38,1,1,1,9398.45,0 +3862,15615126,Cocci,780,France,Female,37,3,0,2,0,0,182156.81,1 +3863,15726588,Seleznev,653,Spain,Female,36,3,0,2,0,0,110525.6,0 +3864,15645095,Huang,674,France,Female,28,3,0,1,1,0,51536.99,0 +3865,15808960,Alleyne,620,Germany,Male,40,5,108197.11,2,1,0,49722.34,0 +3866,15729435,McKenzie,623,France,Male,40,6,0,2,1,1,66119.07,0 +3867,15656840,Zikoranachukwudimma,547,France,Female,29,6,104450.86,1,1,1,37160.28,0 +3868,15659149,King,530,France,Male,39,2,0,2,1,0,197923.05,0 +3869,15585490,Nkemdilim,746,France,Female,34,4,0,1,0,1,65166.6,0 +3870,15674929,Anderson,512,France,Female,31,7,0,2,0,0,49326.07,0 +3871,15746341,Ejikemeifeuwa,630,France,Male,40,8,0,2,1,1,42495.81,0 +3872,15662091,Adams,570,Spain,Male,21,7,116099.82,1,1,1,148087.62,0 +3873,15620123,Christie,605,France,Male,39,6,111169.91,1,0,0,9641.4,0 +3874,15616240,Yeh,530,Spain,Male,37,4,0,2,1,1,164844.37,0 +3875,15624186,McGregor,813,Germany,Female,25,5,123616.43,1,0,1,132959.33,0 +3876,15605036,Pisano,704,Spain,Female,37,9,155619.58,1,1,1,135088.58,0 +3877,15805151,Ginikanwa,565,Germany,Male,31,2,89558.39,2,1,1,4441.54,0 +3878,15753847,Hawkins,645,Spain,Male,45,4,0,1,0,1,174916.85,1 +3879,15653222,Otutodilichukwu,526,Germany,Female,32,6,131938.92,2,1,1,1795.93,0 +3880,15757541,Rickard,778,France,Female,33,9,151772.63,2,0,0,180249.94,1 +3881,15726945,Andreev,677,France,Female,72,8,0,2,1,1,153604.44,0 +3882,15794276,Steele,588,France,Female,64,3,0,1,1,1,189703.65,0 +3883,15568328,Black,488,France,Female,22,6,0,2,1,1,66393.89,0 +3884,15604355,Shand,519,France,Male,39,1,97700.02,1,1,1,30709.03,0 +3885,15735788,Chiagoziem,709,France,Male,31,6,0,2,1,1,71009.84,0 +3886,15618255,Fedorov,642,Germany,Female,56,6,103244.86,2,1,0,143049.72,1 +3887,15720941,Tien,710,Germany,Male,34,8,147833.3,2,0,1,1561.58,0 +3888,15769110,Stehle,653,France,Female,46,5,0,2,1,0,49707.85,0 +3889,15576094,Sung,743,France,Male,71,0,0,2,0,1,29837.65,0 +3890,15756150,Alexander,418,France,Female,39,2,0,2,0,0,9041.71,0 +3891,15719579,McIntosh,670,Germany,Female,33,9,84521.48,2,0,1,198017.05,0 +3892,15748854,Sung,723,Germany,Female,28,5,91938.31,1,1,0,143481.85,0 +3893,15612455,Yao,549,Germany,Male,45,6,124240.93,1,1,1,146372.51,0 +3894,15664802,Chinweuba,543,France,Female,42,5,0,2,0,0,101905.34,0 +3895,15735687,Chinweuba,595,Spain,Male,37,2,157084.99,1,1,0,134767.13,0 +3896,15664734,T'ao,673,Germany,Female,25,3,108244.82,2,1,1,103573.96,0 +3897,15767894,Ch'ien,741,France,Female,21,9,0,2,0,1,139259.54,0 +3898,15666884,Su,508,Germany,Female,41,5,82161.7,2,1,0,187776.49,0 +3899,15750156,Yu,662,Germany,Male,59,2,104568.41,1,1,0,8059.44,1 +3900,15751120,Loyau,752,France,Female,36,2,119912.46,1,1,0,124354.92,0 +3901,15575748,Conti,809,France,Male,36,9,68881.59,2,0,1,109135.11,0 +3902,15714610,Alexeeva,575,Spain,Male,30,2,0,2,1,1,82222.86,0 +3903,15720305,Power,591,Spain,Female,40,1,86376.29,1,0,1,136767.16,1 +3904,15678129,Hill,643,Spain,Female,45,9,150840.03,2,1,0,155516.35,0 +3905,15566633,Freeman,698,Germany,Male,55,8,155059.1,2,1,1,144584.29,0 +3906,15680436,Hsing,496,France,Female,29,4,0,2,1,0,164806.89,0 +3907,15674343,Esposito,597,France,Male,44,8,78128.13,2,0,1,109153.04,0 +3908,15658890,Belonwu,603,Germany,Male,46,4,98899.76,2,1,1,86190.34,0 +3909,15599004,Tsao,655,Spain,Male,37,1,0,1,1,1,106040.97,0 +3910,15726487,P'eng,431,France,Male,63,6,160982.89,1,1,1,168008.17,0 +3911,15698716,Baker,620,France,Female,70,3,87926.24,2,1,0,33350.26,1 +3912,15710527,Matthews,782,France,Female,35,4,0,1,1,1,119565.34,0 +3913,15655590,Garcia,581,Spain,Male,46,2,79385.21,2,0,0,188492.82,0 +3914,15732266,Field,553,Germany,Male,53,5,127997.83,1,1,0,165378.66,1 +3915,15669326,Gordon,658,France,Male,44,2,168396.34,1,1,1,14178.73,0 +3916,15672246,Jefferies,686,Germany,Male,43,2,134896.03,1,1,1,97847.05,0 +3917,15620276,Palermo,539,Spain,Male,36,6,0,3,1,1,118959.64,0 +3918,15640258,Chou,685,France,Female,50,6,94238.75,2,1,1,50664.07,1 +3919,15740283,Ewing,850,France,Male,29,1,0,2,0,0,152996.89,0 +3920,15759717,Mazzi,763,Spain,Female,39,7,0,2,1,0,19458.75,0 +3921,15620268,Thomson,634,Germany,Male,43,3,212696.32,1,1,0,115268.86,0 +3922,15743871,Nkemdirim,567,France,Male,59,3,0,2,1,0,25843.7,1 +3923,15614491,Lockyer,539,France,Male,39,3,139153.68,2,1,0,147662.33,0 +3924,15595047,Murray,764,France,Male,41,7,0,2,0,0,134878.34,0 +3925,15732334,Black,653,France,Female,40,0,0,2,1,0,35795.85,0 +3926,15701206,Torreggiani,566,Spain,Male,44,5,0,2,1,0,66462.79,0 +3927,15581280,Atkinson,714,Germany,Male,29,6,92887.13,1,1,1,69578.49,0 +3928,15651943,Richards,580,Spain,Female,65,1,0,2,0,1,103182.46,0 +3929,15609545,Azubuike,548,France,Male,29,5,83442.98,1,0,1,177017.39,0 +3930,15658548,Ignatiev,646,Germany,Female,36,6,144773.29,2,1,0,53217.3,0 +3931,15626008,Miller,622,Germany,Female,52,9,111973.97,1,1,1,162756.29,1 +3932,15774133,Cox,706,France,Female,35,8,178032.53,1,0,1,42181.68,0 +3933,15763798,McMillan,680,France,Male,23,5,140007.19,1,0,1,31714.08,0 +3934,15758013,Napolitano,698,France,Male,37,5,98400.61,2,0,0,25017.28,0 +3935,15705765,Lane,581,Spain,Female,46,1,0,2,1,0,104272.04,0 +3936,15648362,Kennedy,728,Germany,Male,45,3,108924.33,2,1,0,84300.4,1 +3937,15761102,T'ao,707,Spain,Female,32,4,132835.56,1,0,0,136877.24,0 +3938,15610165,Hsiung,761,France,Female,26,1,0,2,1,1,199409.19,0 +3939,15723717,Heath,483,Germany,Male,41,1,118334.44,1,0,0,163147.99,1 +3940,15654611,Parry,736,Germany,Female,25,9,81732.88,2,1,0,136497.28,0 +3941,15659736,Herbert,716,Germany,Male,66,5,121411.9,1,0,0,10070.4,1 +3942,15603170,Kang,654,France,Male,32,9,121455.65,1,1,0,190068.53,1 +3943,15786167,Andreyeva,649,Spain,Male,20,5,0,2,1,1,58309.54,0 +3944,15671915,Bowen,649,France,Male,46,5,0,2,1,1,76946.6,0 +3945,15794792,Golubev,612,France,Female,31,8,117989.76,1,1,1,54129.86,0 +3946,15652789,Hancock,657,Spain,Male,40,10,0,2,1,1,52990.7,0 +3947,15739168,Fowler,511,France,Female,31,5,137411.29,1,0,1,161854.98,0 +3948,15719950,Sutherland,682,France,Male,61,10,73688.2,1,1,1,172141.33,0 +3949,15743818,Rowley,748,Spain,Male,58,9,122330.7,2,0,1,124429.19,0 +3950,15717937,Gibbons,554,Germany,Male,43,5,99906.89,1,0,0,24983.39,0 +3951,15602841,Lockett,794,Spain,Female,28,5,0,2,0,1,86699.98,0 +3952,15619972,Akabueze,807,France,Female,47,9,167664.83,1,0,0,125440.11,1 +3953,15796114,Phelps,594,France,Female,34,7,141525.55,1,0,0,9443.15,0 +3954,15633546,Frederick,652,Spain,Female,33,3,124832.51,1,1,0,195877.06,0 +3955,15758755,Beneventi,729,France,Female,34,9,132121.71,1,0,1,105409.31,0 +3956,15695168,Bruce,625,France,Male,39,2,0,2,1,0,100403.05,0 +3957,15754342,Green,597,Germany,Female,60,0,78539.84,1,0,1,48502.88,0 +3958,15756610,Carlson,657,Germany,Female,38,5,123770.46,1,0,0,47019.66,1 +3959,15640917,Tang,633,France,Male,43,5,0,2,1,1,48249.88,0 +3960,15663164,Yudin,663,Germany,Male,49,7,116150.65,3,1,1,84358.71,1 +3961,15616811,MacDonald,535,France,Male,47,0,160729.1,1,0,1,145986.35,0 +3962,15610781,Watt,702,France,Female,29,10,88378.6,1,1,0,88550.28,0 +3963,15600911,Mbadiwe,712,France,Male,33,2,182888.08,1,1,0,3061,0 +3964,15629603,Chuang,607,France,Male,31,8,0,2,1,1,43196.5,0 +3965,15714981,Sabbatini,476,France,Male,37,4,0,1,1,1,55775.84,1 +3966,15775892,Caldwell,748,Spain,Female,23,8,85600.08,1,0,0,134077.71,0 +3967,15782778,Ewers,815,France,Male,35,4,0,2,0,1,198490.33,0 +3968,15786643,Tsao,602,France,Male,32,10,0,2,1,1,116052.92,0 +3969,15595657,Hannam,649,Germany,Male,40,4,95001.33,1,0,1,123202.99,0 +3970,15743673,Wood,551,Spain,Male,27,2,113873.22,1,1,1,85129.77,1 +3971,15634310,Ko,509,France,Male,30,6,0,2,1,0,180598.86,0 +3972,15790809,Lo Duca,685,Spain,Male,40,7,74896.92,1,1,0,198694.2,0 +3973,15668695,Endrizzi,536,France,Female,22,5,89492.62,1,0,0,42934.43,0 +3974,15669281,Ch'iu,711,Spain,Male,38,3,128718.78,1,0,0,114793.45,0 +3975,15621031,Mofflin,761,Spain,Male,27,8,0,2,1,0,63297.7,0 +3976,15720071,Fiorentini,535,France,Female,49,3,0,1,0,0,61820.41,1 +3977,15792180,Chiekwugo,566,Germany,Male,22,7,144954.75,2,1,0,102246,0 +3978,15813894,Bogle,620,Spain,Male,21,9,0,2,0,0,154882.79,0 +3979,15669490,Ifeanacho,837,Germany,Male,37,6,94001.61,2,1,0,140723.05,0 +3980,15783030,Owens,685,France,Female,40,7,0,1,1,0,72852.74,1 +3981,15695792,Ch'ien,673,France,Male,65,0,0,1,1,1,85733.33,0 +3982,15575676,Chung,638,France,Male,24,1,0,2,0,1,162597.15,0 +3983,15627665,Sung,614,France,Male,46,4,0,1,1,0,74379.57,1 +3984,15814092,Wang,626,France,Female,44,2,0,1,0,1,173117.22,1 +3985,15695225,Sun,834,Spain,Male,38,8,0,2,1,1,66485.26,0 +3986,15615091,Maitland,691,France,Male,24,6,0,2,1,1,92811.2,0 +3987,15794345,Ma,706,Spain,Male,38,8,0,2,0,1,46635.11,0 +3988,15726484,Pollard,633,France,Male,37,7,141546.35,1,1,1,124830.11,0 +3989,15650442,Hsieh,644,Germany,Female,32,8,141528.88,1,1,1,167087.34,1 +3990,15714256,Gerasimov,666,France,Male,30,7,109805.3,1,0,1,163625.56,0 +3991,15778752,Johnson,708,France,Male,32,10,86614.06,2,1,1,172129.26,0 +3992,15601659,Fiorentino,496,Germany,Female,59,7,91680.1,2,1,0,163141.18,1 +3993,15602811,Chioke,730,Germany,Male,38,0,38848.19,2,0,0,94003.11,0 +3994,15779414,Rossi,696,Spain,Male,40,3,153639.11,1,1,1,138351.68,0 +3995,15763097,Siciliano,809,Spain,Male,80,8,0,2,0,1,34164.05,0 +3996,15633666,Efremov,701,Spain,Female,33,7,123870.07,1,1,0,97794.71,0 +3997,15718789,Brigstocke,604,France,Male,30,5,0,2,1,0,75786.55,0 +3998,15690620,Olisaemeka,665,France,Male,39,10,46323.57,1,1,0,136812.02,0 +3999,15737071,Tang,639,France,Female,60,5,162039.78,1,1,1,84361.72,1 +4000,15665062,Lucchese,696,France,Male,19,1,110928.51,1,1,1,2766.63,0 +4001,15600692,West,520,France,Male,38,5,0,2,1,0,163185.76,0 +4002,15792064,Pai,545,Germany,Male,53,5,114421.55,1,1,0,180598.28,1 +4003,15811486,Tang,634,Germany,Female,29,8,130036.21,2,0,1,69849.55,0 +4004,15626141,Fedorov,750,France,Female,26,1,151510.17,2,1,1,19921.72,0 +4005,15738546,Gboliwe,530,Spain,Female,41,4,0,2,0,1,147606.71,0 +4006,15677052,Ko,589,France,Female,59,2,0,2,1,1,126160.24,1 +4007,15656454,Le Gallienne,654,France,Male,37,6,83568.55,1,1,0,47046.72,0 +4008,15645496,Seleznyova,648,France,Female,43,7,139972.18,1,1,0,143668.58,0 +4009,15612505,Joseph,835,Spain,Male,45,3,100212.13,1,1,0,152577.62,0 +4010,15708513,Bevan,446,France,Female,39,1,90217.07,1,1,0,191350.48,0 +4011,15685654,Allan,514,Spain,Male,66,9,0,2,1,1,14234.31,0 +4012,15732307,Lavrentiev,694,Germany,Male,33,4,124067.32,1,1,1,77906.87,0 +4013,15726814,Walton,554,Spain,Male,46,4,0,2,0,1,57320.92,0 +4014,15653776,Salier,720,Germany,Female,57,1,162082.31,4,0,0,27145.73,1 +4015,15597914,Evdokimov,641,Germany,Female,51,2,117306.69,4,1,1,26912.72,1 +4016,15631603,Ponomaryova,813,France,Male,32,1,122889.88,1,1,1,26476.18,0 +4017,15789753,Millar,480,France,Male,40,6,148790.61,1,0,1,79329.7,0 +4018,15678034,Grosse,811,France,Male,46,9,180226.24,1,1,0,13464.64,1 +4019,15690209,Hsiao,715,Germany,Female,32,3,104857.19,2,1,0,114149.8,0 +4020,15592091,Belbin,620,Spain,Male,31,2,166833.86,2,1,1,135171.6,0 +4021,15647453,Ifeajuna,721,France,Male,42,4,102936.72,1,0,0,1187.88,0 +4022,15697100,Wright,772,Germany,Female,48,6,108736.52,1,1,0,184564.67,1 +4023,15811290,Komarova,680,Germany,Male,44,0,129974.79,2,1,1,33391.38,0 +4024,15629187,Titheradge,535,France,Male,38,8,85982.07,1,1,0,9238.35,0 +4025,15758073,Dellucci,655,France,Female,20,7,134397.61,1,0,0,28029.54,0 +4026,15640769,Hobbs,660,France,Male,63,8,137841.53,1,1,1,42790.29,0 +4027,15606641,Beggs,762,Germany,Male,56,10,100260.88,3,1,1,77142.42,1 +4028,15718280,Luffman,662,Germany,Male,39,5,139822.11,2,1,1,146219.9,0 +4029,15764335,Caldwell,463,Germany,Female,41,8,123151.51,2,1,0,70127.93,0 +4030,15634218,Mancini,501,Germany,Male,27,4,95331.83,2,1,0,132104.76,0 +4031,15808760,Evseev,603,Spain,Female,42,6,0,1,1,1,90437.87,0 +4032,15648461,Hs?eh,688,Spain,Male,37,7,138162.41,2,1,1,113926.31,0 +4033,15593555,Chinedum,430,France,Male,38,9,0,2,1,1,12050.77,0 +4034,15569079,Hagins,632,Germany,Male,48,6,126066.26,1,1,0,64345.61,1 +4035,15800736,Kirwan,601,Spain,Female,42,4,96763.89,1,1,1,199242.65,0 +4036,15792607,Little,769,France,Female,38,2,0,2,0,0,75578.67,0 +4037,15640034,Milligan,551,France,Male,42,2,139561.46,1,1,0,43435.43,1 +4038,15807563,Ch'iu,841,France,Female,52,5,0,1,0,0,183239.71,1 +4039,15684461,McKay,469,Spain,Female,31,6,0,1,1,0,146213.75,1 +4040,15580134,Crawford,479,Spain,Male,27,2,172463.45,1,1,1,40315.27,0 +4041,15679075,Onyemere,701,France,Male,37,8,107798.85,1,1,0,16966.73,0 +4042,15742504,Azuka,593,France,Male,36,2,70181.48,2,1,0,80608.12,0 +4043,15567328,Ch'en,738,Spain,Male,38,5,177997.07,1,0,1,19233.41,0 +4044,15698294,Royster,635,Spain,Male,31,1,0,2,1,0,135382.23,0 +4045,15607142,Parkin,658,France,Male,32,8,0,1,1,1,80410.68,0 +4046,15738516,Kozlova,687,Spain,Female,36,5,0,1,1,0,17696.22,0 +4047,15806403,Hu,650,France,Male,37,9,0,2,1,0,17974.08,0 +4048,15656707,Ma,720,Spain,Male,21,2,123200.78,1,1,1,180712.28,0 +4049,15653715,Coates,602,France,Female,63,7,0,2,1,1,56323.21,0 +4050,15806184,Burns,618,Spain,Male,33,4,0,2,1,1,77550.18,0 +4051,15585734,Gouger,803,Germany,Male,41,9,137742.9,2,1,1,166957.82,0 +4052,15725639,Ignatyev,793,France,Female,63,9,116270.72,1,1,1,184243.25,0 +4053,15618401,Douglas,616,Germany,Male,41,10,113220.2,2,1,1,114072.91,0 +4054,15785385,Fiorentino,550,Spain,Male,51,5,0,2,1,0,153917.41,0 +4055,15734762,Ignatiev,602,France,Female,56,3,115895.22,3,1,0,4176.17,1 +4056,15767129,Munz,452,France,Female,60,6,121730.49,1,1,1,142963.29,0 +4057,15797204,Paling,655,Spain,Female,28,3,113811.85,2,0,1,76844.23,0 +4058,15769272,Clark,510,France,Female,26,6,136214.08,1,0,0,159742.33,0 +4059,15771966,Akobundu,557,France,Male,39,8,146200.01,1,1,0,177944.64,0 +4060,15691952,Fanucci,676,France,Male,37,10,106242.67,1,1,1,166678.28,0 +4061,15593250,Hsiao,640,France,Female,29,4,0,2,1,0,44904.26,0 +4062,15605333,Clancy,529,Spain,Male,31,6,0,1,1,0,10625.91,0 +4063,15800083,Macdonald,559,France,Male,45,8,24043.45,1,0,1,169781.45,1 +4064,15575691,Palerma,689,France,Female,58,5,0,2,0,1,49848.86,0 +4065,15689886,Holden,626,Germany,Male,39,10,132287.92,3,1,1,51467.92,1 +4066,15809838,Moore,697,Spain,Male,30,1,0,2,0,0,735.79,0 +4067,15736154,Gallo,823,France,Female,44,1,0,2,0,1,182495.7,0 +4068,15767391,Otutodilinna,565,Germany,Female,32,4,90322.99,2,0,1,118740.37,0 +4069,15704910,Rios,631,Spain,Male,23,3,0,2,1,0,13813.24,0 +4070,15656613,McGregor,646,France,Female,34,3,131283.11,1,0,0,130500.65,0 +4071,15611551,Hill,676,Spain,Male,48,1,131659.59,2,0,1,14152.15,0 +4072,15732430,H?,850,Spain,Female,54,4,120952.74,1,1,0,66963.15,0 +4073,15741865,Ferrari,810,France,Female,38,9,153166.17,1,1,1,93261.69,0 +4074,15634143,Onyemauchechi,581,Spain,Male,30,0,53291.86,1,0,0,196582.28,0 +4075,15609676,Nkemakonam,718,France,Female,35,2,167924.95,1,1,0,43024.64,0 +4076,15761600,White,713,France,Male,43,5,86394.14,1,1,1,130001.13,0 +4077,15676404,Kirillov,672,France,Female,50,1,0,1,1,0,12106.82,1 +4078,15659236,Iadanza,781,Spain,Male,33,3,0,2,1,1,42556.33,0 +4079,15690440,Stiles,656,Spain,Male,47,1,0,2,1,1,197961.93,0 +4080,15694601,Ankudinov,583,France,Female,31,4,158978.79,1,1,0,12538.92,0 +4081,15812262,Gaffney,808,Germany,Female,37,2,100431.84,1,1,0,35140.49,1 +4082,15762821,Udinese,721,Spain,Male,33,5,0,2,0,1,117626.9,0 +4083,15669301,Romani,778,Germany,Female,29,6,150358.97,1,1,0,62454.01,1 +4084,15672640,Kambinachi,850,Spain,Female,45,4,114347.85,2,1,1,109089.04,0 +4085,15750458,Hawkins,693,France,Female,39,4,0,2,0,1,142331.39,0 +4086,15627251,Tsui,520,France,Male,34,4,134007.9,1,1,1,193209.11,0 +4087,15764294,Ifeatu,759,Germany,Male,31,4,98899.91,1,1,1,47832.82,0 +4088,15659962,McIntosh,637,France,Male,60,3,0,2,1,1,70174.03,0 +4089,15788536,Armit,755,Germany,Male,40,2,137430.82,2,0,0,176768.59,0 +4090,15596979,Fang,662,France,Female,47,6,0,2,1,1,129392.75,0 +4091,15681220,Chou,503,France,Female,37,8,0,2,1,1,97893.32,0 +4092,15635097,Okeke,599,Germany,Male,39,2,188976.89,2,0,1,176142.09,0 +4093,15780779,Ramsbotham,583,Spain,Female,40,4,0,2,1,0,114093.73,0 +4094,15798470,Scannell,764,Spain,Female,48,1,75990.97,1,1,0,158323.81,1 +4095,15760880,Edman,513,France,Male,29,10,0,2,0,1,25514.77,0 +4096,15616929,De Luca,730,Spain,Male,62,5,112181.08,1,0,1,61513.87,0 +4097,15758775,Vasilyeva,820,Spain,Male,34,10,97208.46,1,1,1,59553.34,0 +4098,15663386,Tuan,597,Spain,Female,26,7,0,2,1,0,110253.2,0 +4099,15621267,Ejimofor,637,France,Male,32,5,0,1,0,0,148769.08,0 +4100,15720509,Hs?,696,France,Male,34,9,150856.79,1,0,1,8236.78,0 +4101,15693322,Shaver,635,Germany,Female,37,9,146748.07,1,0,1,11407.58,0 +4102,15589544,Wallis,673,Spain,Female,57,4,0,2,1,1,49684.09,0 +4103,15772030,Coupp,662,Spain,Male,33,3,0,2,0,1,68064.83,0 +4104,15693337,Perry,683,Spain,Male,41,0,148863.17,1,1,1,163911.32,0 +4105,15676571,Bezrukova,850,France,Male,55,6,0,1,1,0,944.41,1 +4106,15701392,Lucciano,815,Spain,Male,28,6,0,2,0,1,185547.71,0 +4107,15741092,Ingram,671,Spain,Male,34,10,153360.02,1,1,0,140509.86,0 +4108,15643865,Lo Duca,601,France,Female,40,3,92055.36,1,0,1,164652.02,1 +4109,15769389,Wan,709,Germany,Female,39,9,124723.92,1,1,0,73641.86,0 +4110,15807768,Cohn,702,Germany,Male,28,1,103033.83,1,1,1,40321.87,0 +4111,15801630,Yen,558,France,Male,40,6,0,2,1,0,173844.89,0 +4112,15705034,Peng,691,Spain,Male,40,1,0,2,1,1,145613.17,0 +4113,15763107,Little,700,France,Female,30,9,0,1,1,1,174971.64,0 +4114,15667085,Meng,667,France,Male,33,4,0,2,1,1,131834.75,0 +4115,15647008,Adams,624,Germany,Male,54,3,116726.22,1,1,0,110498.1,1 +4116,15584505,Hill,580,France,Female,23,5,113923.81,2,0,0,196241.43,0 +4117,15748068,Boyle,571,Spain,Female,31,3,0,2,1,1,194667.92,0 +4118,15663964,Pagnotto,561,France,Male,37,5,0,2,1,0,83093.25,0 +4119,15782311,Feng,529,France,Male,28,9,0,2,1,1,52545.24,0 +4120,15588197,Endrizzi,670,France,Male,36,7,0,2,0,0,59571.5,0 +4121,15610105,Shen,666,Germany,Female,21,1,121827.43,2,1,1,99818.31,0 +4122,15606133,Lay,628,Spain,Male,42,7,0,2,0,1,172967.87,0 +4123,15599403,Wu,577,France,Male,60,10,125389.7,2,1,1,178616.73,0 +4124,15648225,Shephard,652,Spain,Female,38,1,103895.31,1,0,1,159649.44,0 +4125,15608406,Schmidt,678,France,Male,26,5,111128.04,1,1,0,60941.27,1 +4126,15633378,Davidson,692,Spain,Female,49,9,0,2,1,0,178342.63,0 +4127,15664759,Lamb,675,Spain,Male,32,10,0,2,1,0,191545.65,0 +4128,15625545,Hussey,712,Spain,Male,52,9,0,1,1,1,117977.45,1 +4129,15772148,Ferrari,639,Germany,Female,37,5,151242.48,1,0,1,49637.65,0 +4130,15810829,Macfarlan,618,France,Male,48,7,0,1,1,0,13921.82,1 +4131,15731669,Szabados,554,France,Male,39,2,129709.62,1,1,0,173197.12,0 +4132,15738634,Yuan,533,France,Male,47,9,83347.25,1,1,1,137696.25,0 +4133,15737571,Matveyev,540,Spain,Female,28,6,84121.04,1,0,1,80698.54,0 +4134,15667602,Cheng,704,Spain,Male,33,3,0,2,1,0,73018.74,0 +4135,15684147,Palerma,678,France,Male,43,5,102338.19,1,1,1,79649.62,0 +4136,15789874,Wang,712,France,Female,29,3,87375.78,2,0,0,166194.53,0 +4137,15757952,Teng,651,France,Male,44,2,0,3,1,0,102530.35,1 +4138,15698732,K'ung,789,Germany,Male,51,3,104677.09,1,1,0,74265.38,0 +4139,15714355,Sinclair,775,Germany,Male,32,8,121669.23,1,0,1,125898.39,0 +4140,15599090,McKelvey,564,Germany,Male,40,7,108407.34,1,1,1,83681.2,0 +4141,15762048,Yuan,841,Germany,Female,33,7,154969.79,2,1,1,99505.75,0 +4142,15790596,Moran,850,Spain,Male,39,0,141829.67,1,1,1,92748.16,0 +4143,15609623,McConnell,637,France,Female,63,5,0,1,1,0,28092.77,1 +4144,15711901,Iheatu,500,France,Male,45,2,109162.82,1,1,1,126145.08,0 +4145,15779809,Giordano,655,France,Male,44,8,87471.63,1,0,1,188593.98,0 +4146,15729018,Alexander,666,France,Female,33,2,147229.65,1,1,1,56410.17,0 +4147,15698246,Gordon,658,France,Female,24,2,0,2,1,1,84694.49,0 +4148,15712409,Tang,749,Germany,Male,66,6,182532.23,2,1,1,195429.92,0 +4149,15758306,T'an,654,France,Male,32,6,0,2,1,1,137898.57,0 +4150,15621435,Davies,623,France,Female,39,1,160903.2,1,0,0,78774.36,0 +4151,15566295,Sanders,761,France,Female,33,6,138053.79,2,1,0,148779.41,0 +4152,15569098,Winifred,627,France,Male,44,6,153548.12,1,0,0,35300.08,1 +4153,15662532,Holmes,757,Germany,Male,31,8,149085.9,2,1,1,197077.36,0 +4154,15664001,Riddle,695,Germany,Female,53,8,95231.91,1,0,0,70140.8,1 +4155,15703437,Chinedum,726,France,Male,34,3,0,2,1,0,196288.46,0 +4156,15708003,Aleksandrova,587,Spain,Male,41,8,85109.21,1,1,0,1557.82,0 +4157,15599452,Conti,605,Germany,Female,43,8,125338.8,2,1,0,23970.13,0 +4158,15719793,Watson,850,Spain,Male,62,5,0,2,1,1,180243.56,0 +4159,15771580,Davison,850,France,Female,38,0,106831.69,1,0,1,148977.72,0 +4160,15732268,Cook,751,France,Male,29,3,159597.45,1,1,0,39934.41,0 +4161,15722350,Udinesi,627,Germany,Female,37,7,147361.57,1,1,1,133031.96,0 +4162,15611371,Siciliani,736,France,Male,43,4,176134.54,1,1,1,52856.88,0 +4163,15673584,Bell,652,France,Female,74,5,0,2,1,1,937.15,0 +4164,15636396,Jackson,627,France,Female,35,7,0,2,0,1,193022.44,0 +4165,15706170,Onyemere,636,France,Male,34,1,84055.43,1,0,0,37490.84,0 +4166,15725478,McClemans,775,France,Male,60,7,0,2,1,1,111558.7,0 +4167,15654562,Ma,850,Spain,Female,45,5,174088.3,4,1,0,5669.31,1 +4168,15737509,Morrison,850,Spain,Male,34,8,199229.14,1,0,0,68106.29,0 +4169,15690796,Chambers,516,France,Male,37,8,0,1,1,0,101834.58,0 +4170,15716728,Basedow,513,Spain,Female,42,10,0,2,0,1,73151.25,0 +4171,15605665,Nwora,673,Germany,Female,69,3,78833.15,2,1,1,37196.15,0 +4172,15748481,Howey,564,France,Female,27,6,0,1,0,0,7819.76,0 +4173,15757777,Pai,636,France,Female,35,2,0,2,1,1,23129.46,0 +4174,15747808,Ni,712,France,Male,29,3,102540.61,1,1,1,189680.79,0 +4175,15810593,Forbes,568,France,Male,51,4,0,3,1,1,66586.56,0 +4176,15693376,Baryshnikov,741,Spain,Male,43,0,0,2,1,1,2920.63,1 +4177,15579808,Kramer,754,Germany,Female,39,8,129401.87,1,1,1,87684.93,0 +4178,15598275,Sochima,709,France,Female,32,7,0,2,1,1,199418.02,0 +4179,15737080,Marchesi,510,France,Female,32,1,0,2,0,1,28515.17,0 +4180,15668580,Todd,716,Spain,Male,33,2,0,2,1,1,92916.53,0 +4181,15569438,Mai,607,Germany,Male,36,10,106702.94,2,0,0,198313.69,0 +4182,15675842,Pinto,656,Spain,Male,26,4,139584.57,1,1,0,36308.93,0 +4183,15577587,Reynolds,550,Germany,Male,52,5,121016.23,1,1,1,41730.37,1 +4184,15625592,Sal,486,France,Male,26,2,0,2,1,1,31399.4,0 +4185,15635141,Miller,598,Germany,Male,59,8,118210.42,2,0,0,60192.14,1 +4186,15642570,Scott,675,Spain,Male,35,8,0,2,1,0,29062.25,0 +4187,15702175,Herrin,755,France,Female,29,4,148654.84,2,1,1,28805.09,0 +4188,15677785,Stevenson,656,Spain,Male,32,5,136963.12,1,1,0,133814.28,0 +4189,15786153,McKenzie,644,Germany,Male,47,9,137774.11,2,1,0,151902.78,0 +4190,15759499,Gardiner,598,France,Female,32,4,111156.52,1,1,1,167376.26,0 +4191,15659568,Atkinson,850,Spain,Female,31,3,121237.65,1,1,1,31022.56,0 +4192,15715597,Onyemauchechi,679,France,Male,36,1,97234.58,1,1,0,188997.08,0 +4193,15610147,Ross,632,France,Male,60,2,0,2,0,1,2085.32,0 +4194,15802362,Newland,550,Spain,Male,45,0,0,2,0,1,70399.71,0 +4195,15660524,Hu,572,Germany,Female,54,9,97382.53,1,1,1,195771.95,0 +4196,15747168,Sanders,626,Germany,Female,47,2,103108.8,1,0,1,166475.44,1 +4197,15796910,Tsui,625,Spain,Female,57,7,0,1,0,0,84106.17,1 +4198,15707674,Marino,515,France,Female,58,2,131852.81,1,1,0,81436.68,1 +4199,15565706,Akobundu,612,Spain,Male,35,1,0,1,1,1,83256.26,1 +4200,15587596,Morrison,628,Spain,Female,39,8,107553.33,1,1,0,117523.41,0 +4201,15751943,Mai,529,Spain,Female,43,5,0,2,0,0,79476.63,0 +4202,15621227,Hs?eh,668,Germany,Female,46,7,161806.09,1,1,1,173052.19,0 +4203,15757588,Wright,526,France,Male,30,9,0,2,0,0,100995.68,0 +4204,15640922,Demaine,791,France,Female,52,7,0,1,1,1,122782.5,0 +4205,15567557,Chien,573,France,Male,27,2,128243.03,1,1,1,11631.34,0 +4206,15670103,Dickinson,565,France,Female,38,5,126645.13,1,1,1,168303.55,0 +4207,15720929,Kazantseva,604,France,Female,47,8,62094.71,3,0,0,9308.1,1 +4208,15732774,Marchesi,656,France,Male,37,7,112291.34,1,1,0,153157.97,0 +4209,15628558,Pan,447,France,Female,44,5,89188.83,1,1,1,75408.24,0 +4210,15729201,Harewood,682,France,Male,55,9,0,1,1,0,153356.8,1 +4211,15731117,Kao,437,Spain,Male,28,2,109161.25,1,1,0,152987.42,0 +4212,15615207,Yeh,792,Spain,Male,47,0,0,1,1,1,5557.88,1 +4213,15773512,Bischof,627,Spain,Female,25,4,0,1,1,1,194313.93,0 +4214,15572145,Ashton,767,France,Female,34,8,0,2,1,0,94767.77,0 +4215,15642710,Napolitani,686,France,Male,26,7,0,2,1,0,1540.89,0 +4216,15574213,Wilson,789,France,Female,53,1,158271.74,1,1,1,5036.39,1 +4217,15718852,Uren,794,France,Male,56,9,96951.21,1,1,1,71776.76,0 +4218,15583840,Okechukwu,587,Germany,Male,35,5,121863.61,1,1,1,23481.69,1 +4219,15782418,Ku,589,Germany,Female,19,9,83495.11,1,1,1,143022.31,1 +4220,15813504,Onyemachukwu,543,Germany,Female,25,1,146566.01,1,0,1,161407.48,0 +4221,15711314,Kao,589,Spain,Female,45,1,0,1,0,0,125939.22,1 +4222,15621064,Russell,701,Germany,Male,23,5,186101.18,2,1,1,76611.33,0 +4223,15627847,Woronoff,850,France,Male,40,6,0,1,1,0,136985.08,1 +4224,15588090,Ferri,726,Germany,Female,51,8,107494.86,2,1,0,140937.91,1 +4225,15735270,Ruggiero,767,Spain,Male,47,2,0,1,1,0,48161.18,1 +4226,15671804,Wilding,648,Spain,Male,36,8,146943.38,2,1,1,130041.45,0 +4227,15753215,Yashina,651,Spain,Female,36,8,0,2,1,0,91652.43,0 +4228,15789941,Yevseyev,633,France,Female,36,6,125130.28,1,0,0,125961.48,0 +4229,15691061,Rapuokwu,740,France,Female,37,9,0,2,1,1,73225.31,0 +4230,15808326,Maslov,592,France,Female,34,9,0,2,1,1,20460.2,0 +4231,15566660,Cole,670,France,Female,41,10,0,3,1,0,81602.02,0 +4232,15778947,Sullivan,628,France,Male,36,3,0,2,1,1,8742.91,0 +4233,15632977,Hsiao,745,France,Male,47,5,0,2,0,0,145789.71,0 +4234,15591747,Rossi,705,France,Male,32,3,0,2,0,0,129576.99,0 +4235,15567335,Allsop,559,France,Female,42,7,0,2,1,1,190040.29,0 +4236,15609299,Chamberlain,595,France,Male,29,6,150685.79,1,1,0,87771.06,0 +4237,15669945,Jackson,492,France,Male,35,4,141359.37,2,1,0,39519.53,0 +4238,15736271,Dumetochukwu,498,France,Female,29,9,0,1,1,0,190035.83,0 +4239,15710390,Uspensky,655,France,Female,39,6,94631.26,2,1,1,148948.52,0 +4240,15756481,Garcia,636,France,Female,39,3,118336.14,1,1,0,184691.77,0 +4241,15736730,Soto,634,France,Female,45,2,0,1,1,1,143458.31,0 +4242,15626040,McDonald,793,Spain,Male,63,0,0,2,0,1,27166.75,0 +4243,15746553,Castles,526,Germany,Male,50,5,124233.24,1,0,1,159456.87,1 +4244,15622518,Stephenson,768,France,Female,26,5,51116.26,1,1,1,70454.79,1 +4245,15684908,Davidson,540,Germany,Male,64,1,91869.69,1,0,1,95421,0 +4246,15569446,Tu,732,France,Female,34,8,122338.43,2,1,0,187985.85,0 +4247,15777504,Colbert,617,France,Female,30,8,0,1,1,1,92621.9,0 +4248,15677906,Owens,637,Spain,Female,54,5,0,1,0,1,150836.98,0 +4249,15703292,Chimezie,573,France,Male,26,8,86270.93,2,1,1,90177.3,0 +4250,15712938,Genovese,531,France,Male,44,3,0,2,1,1,34416.79,0 +4251,15631359,Daluchi,489,France,Female,38,5,117289.92,1,0,0,85231.88,0 +4252,15720847,Sheffield,601,France,Male,35,2,0,2,1,1,118983.18,0 +4253,15787830,Bailey,452,Germany,Male,33,7,153663.27,1,1,0,111868.23,0 +4254,15599869,Dyson,728,Spain,Female,29,1,0,1,1,1,83056.22,0 +4255,15592078,Davide,590,Germany,Female,27,8,123599.49,2,1,0,1676.92,0 +4256,15596228,Uwaezuoke,490,France,Male,29,4,0,2,1,0,32089.57,0 +4257,15578462,Hs?,596,Spain,Female,76,9,134208.25,1,1,1,13455.43,0 +4258,15756894,Onwuka,635,France,Male,29,1,0,1,0,1,24865.54,0 +4259,15796167,Flores,782,Germany,Male,35,7,98556.89,2,1,0,117644.36,0 +4260,15664808,Nicoll,790,Spain,Female,37,3,0,3,0,0,98897.32,0 +4261,15664555,Hughes,587,France,Male,40,2,0,4,0,1,106174.7,1 +4262,15607278,Romano,794,Spain,Female,46,8,134593.79,1,1,1,46386.37,0 +4263,15585222,Norman,515,France,Male,41,8,0,2,1,1,185054.14,0 +4264,15750299,Davison,746,Spain,Male,24,10,68781.82,1,0,1,47997.39,0 +4265,15761294,Manna,667,Germany,Female,56,8,137464.04,1,1,0,130846.79,1 +4266,15810454,Reed,709,France,Male,32,4,147307.91,1,0,1,40861.55,0 +4267,15673984,Daniels,536,France,Female,35,8,0,1,1,0,171840.24,1 +4268,15609319,Hunt,711,France,Female,41,3,145754.91,1,1,1,101455.07,0 +4269,15709941,Feng,753,France,Male,46,8,0,3,1,0,90747.94,1 +4270,15580252,Waters,748,France,Male,44,4,112610.77,1,0,1,2048.55,0 +4271,15741275,Yuan,623,France,Female,57,7,71481.79,2,1,1,84421.34,0 +4272,15707132,Yudin,465,France,Male,33,5,0,2,0,1,78698.09,0 +4273,15600708,Calabresi,640,Spain,Female,34,3,77826.8,1,1,1,168544.85,0 +4274,15804787,Onyemauchechukwu,562,France,Male,75,5,87140.85,1,1,1,39351.64,0 +4275,15690021,Martin,502,Germany,Female,42,0,132002.7,1,0,1,28204.98,1 +4276,15763895,Hung,536,France,Male,32,7,178011.5,2,1,0,22375.14,0 +4277,15623478,Maslova,670,Germany,Female,32,4,102954.68,2,0,1,134942.45,0 +4278,15797910,Zetticci,775,Germany,Male,51,2,123783.25,1,1,1,134901.57,0 +4279,15577751,Pisano,759,Germany,Male,30,4,101802.67,1,0,0,8693.8,0 +4280,15781777,Sutherland,604,France,Male,33,3,148659.48,1,0,0,42437.75,0 +4281,15740527,Lai,766,Germany,Female,62,7,142724.48,1,0,1,5893.23,1 +4282,15721251,Watson,554,Spain,Female,41,4,112152.89,1,0,1,36242.19,0 +4283,15602994,Gorbunov,487,France,Female,53,10,89550.85,1,0,1,90076.85,0 +4284,15750769,Padovano,725,France,Male,35,7,75915.75,1,1,0,150507.43,0 +4285,15740175,Raynor,732,Germany,Female,42,2,118889.66,2,0,0,87422.15,0 +4286,15679968,Ting,623,France,Male,40,5,118788.57,1,1,0,192867.4,0 +4287,15694404,Eberegbulam,781,France,Female,42,3,156555.54,1,1,1,175674.01,0 +4288,15657529,Chin,714,Germany,Male,53,1,99141.86,1,1,1,72496.05,1 +4289,15762882,Manna,577,Germany,Female,31,4,61211.18,1,1,1,145250.43,0 +4290,15642579,Chang,731,Spain,Female,37,1,128932.4,1,1,1,180712.52,0 +4291,15598884,Kent,650,Spain,Female,23,5,0,1,1,1,180622.43,0 +4292,15770185,Buckley,779,France,Male,32,10,80728.15,1,1,0,86306.75,0 +4293,15800287,Micco,706,Spain,Female,46,2,127660.46,2,1,0,150156.82,1 +4294,15665861,Avdeev,733,Spain,Male,44,3,106070.89,1,0,1,101617.43,0 +4295,15662203,Bremer,579,Germany,Female,42,3,137560.38,2,1,1,85424.34,0 +4296,15616454,Davidson,476,Germany,Female,34,8,111905.43,1,0,1,197221.81,1 +4297,15702788,Gadsdon,775,France,Male,40,9,126212.64,1,1,0,70196.57,0 +4298,15778149,Connolly,538,Spain,Male,68,9,0,2,1,0,110440.5,1 +4299,15680001,McDonald,602,France,Male,38,7,111835.94,2,1,0,124389.61,0 +4300,15711991,Chiawuotu,615,France,Male,30,8,0,2,0,0,3183.15,0 +4301,15633834,Milne,700,Germany,Female,28,3,99705.69,2,0,0,146723.72,0 +4302,15765266,Fleming,615,France,Male,32,1,0,2,0,0,2139.25,0 +4303,15791867,Hicks,544,Germany,Male,44,2,108895.93,1,0,0,69228.2,1 +4304,15675380,Logan,573,Spain,Male,56,3,154669.77,1,0,1,115462.27,1 +4305,15770576,Hammond,555,Spain,Male,50,7,128061,2,1,1,62375.1,0 +4306,15775294,Weber,692,France,Female,31,2,0,2,1,0,91829.17,1 +4307,15727059,Lettiere,476,France,Female,40,4,0,2,0,0,182547.04,0 +4308,15702499,Schnaars,770,Spain,Male,46,9,190678.02,1,1,1,14725.36,0 +4309,15611699,Tao,641,France,Female,40,7,0,1,1,0,126996.67,0 +4310,15654000,Algarin,705,France,Female,35,5,0,1,1,0,133991.11,1 +4311,15657881,Onyemere,784,France,Male,38,5,136712.91,1,0,1,169920.92,0 +4312,15719991,Korovina,727,Spain,Female,52,1,154733.97,1,1,0,80259.67,1 +4313,15720687,Chidubem,576,France,Female,41,4,112609.91,1,0,0,191035.18,1 +4314,15687079,King,646,Spain,Male,69,10,115462.44,1,1,0,40421.87,0 +4315,15582276,Greco,638,France,Male,34,5,133501.36,1,0,1,155643.04,0 +4316,15763980,Beneventi,632,Germany,Male,30,1,58668.02,1,1,1,78670.52,0 +4317,15720774,P'eng,850,Spain,Male,44,7,89118.26,1,1,0,104240.77,1 +4318,15592194,Metcalf,492,France,Female,28,9,0,2,1,0,95957.09,0 +4319,15803685,Greco,673,Germany,Female,77,10,76510.52,2,0,1,59595.66,0 +4320,15759456,Lupton,609,Spain,Male,34,7,140694.78,2,1,0,46266.63,0 +4321,15611544,Ibeamaka,701,Germany,Male,36,7,95448.32,2,1,0,189085.07,0 +4322,15794257,Hsiung,651,France,Male,34,4,91562.99,1,1,1,123954.15,0 +4323,15681697,Rueda,508,France,Male,31,8,72541.48,1,1,0,129803.08,0 +4324,15579566,Li Fonti,616,Spain,Female,43,3,120867.18,1,1,0,18761.92,1 +4325,15577970,Alexeeva,489,France,Male,34,5,0,1,0,0,43540.59,0 +4326,15727489,Madueke,567,Spain,Female,45,1,157320.51,1,1,0,62193.92,0 +4327,15764284,Torres,714,Spain,Male,27,3,0,3,1,1,129130.09,0 +4328,15581811,Chukwubuikem,678,Germany,Female,30,1,139676.95,2,0,1,16146,0 +4329,15622527,Holloway,581,France,Female,55,6,0,1,1,1,22442.13,0 +4330,15753362,Evdokimov,748,Spain,Male,60,3,0,2,1,1,78194.37,0 +4331,15666652,Anayolisa,781,France,Female,19,3,0,2,1,1,124297.32,0 +4332,15789714,Semmens,691,Spain,Male,21,3,103000.94,1,1,1,104648.58,0 +4333,15771543,Tu,507,Germany,Male,31,2,134237.07,1,1,1,166423.66,1 +4334,15748327,Anderson,724,Germany,Male,34,6,118235.7,2,0,0,157137.23,0 +4335,15754649,Fang,705,Spain,Female,57,3,0,2,1,1,34134.14,0 +4336,15810460,Fanucci,708,Spain,Female,64,5,0,3,0,1,112520.07,1 +4337,15771742,Boyle,580,Germany,Male,38,9,115442.19,2,1,0,128481.5,1 +4338,15642160,Milanesi,850,France,Male,38,5,0,2,1,0,16491.64,0 +4339,15798439,Davidson,714,Spain,Male,25,2,0,1,1,1,132979.43,0 +4340,15605293,McKay,559,France,Female,43,1,0,2,1,1,196645.87,0 +4341,15692631,Bogdanova,577,Spain,Female,44,8,115557,1,0,1,127506.76,0 +4342,15665376,Lavrentiev,647,Germany,Female,35,3,166518.63,2,1,0,147930.46,0 +4343,15772412,Corser,554,Spain,Male,30,6,135370.12,1,1,1,179689.05,1 +4344,15654577,Alexeeva,549,Germany,Male,54,5,92877.33,1,1,0,2619.64,1 +4345,15585427,Madueke,528,France,Female,26,10,102073.67,2,0,0,166799.93,0 +4346,15584536,Barber,720,Germany,Male,46,3,97042.6,1,1,1,133516.51,1 +4347,15585853,McCardle,743,Spain,Male,41,7,0,1,1,0,163736.09,1 +4348,15645271,Radcliffe-Brown,615,Germany,Male,24,8,108528.07,2,0,0,179488.41,1 +4349,15579387,Ni,635,Germany,Female,44,2,79064.85,2,0,1,113291.75,0 +4350,15623107,Chukwumaobim,686,Spain,Male,45,3,74274.87,3,1,0,64907.48,1 +4351,15754072,Dennis,840,Spain,Female,36,6,0,2,1,0,141364.27,0 +4352,15666163,Hayward,695,France,Male,43,1,100421.1,1,1,1,101141.28,0 +4353,15765192,Jones,564,France,Male,26,7,84006.88,2,0,0,183490.99,0 +4354,15804822,L?,805,France,Female,31,4,0,2,1,0,4798.12,0 +4355,15612893,Nelson,558,Spain,Male,45,4,0,1,1,0,131807.14,0 +4356,15593636,Cardus,657,France,Female,39,4,80293.81,1,1,0,97192.76,0 +4357,15693326,Whitehouse,641,France,Female,42,7,125437.14,2,0,0,164128.58,0 +4358,15809901,Johnstone,755,France,Male,36,8,0,2,1,0,176809.87,0 +4359,15759751,Tsui,483,France,Male,48,1,0,2,1,1,110059.38,0 +4360,15605425,Chia,545,Germany,Female,44,2,127536.44,1,1,0,108398.63,0 +4361,15801934,Su,678,France,Male,66,8,0,2,1,1,47117.03,0 +4362,15592000,Calabresi,781,Germany,Female,48,9,82794.18,1,1,0,124720.68,1 +4363,15618695,Ts'ui,571,Spain,Female,22,3,108117.1,1,0,1,53328.7,0 +4364,15637110,McCulloch,634,Spain,Female,35,10,0,1,1,0,82634.41,0 +4365,15727408,Koo,523,Germany,Male,27,8,61688.61,2,1,0,147059.16,0 +4366,15716328,Miller,501,France,Female,40,2,0,2,0,0,141946.92,0 +4367,15669060,Woolnough,662,France,Male,74,6,0,2,1,0,123583.85,0 +4368,15675854,Douglas,573,Spain,Male,50,0,159304.07,1,0,1,155915.24,1 +4369,15621116,Fang,648,Germany,Male,33,5,138664.24,1,1,0,29076.27,0 +4370,15781495,Munro,662,France,Female,22,2,126362.57,2,1,1,97382.8,0 +4371,15740470,Vinogradov,725,France,Male,39,4,160652.45,2,1,0,57643.55,0 +4372,15714391,Lai,563,France,Female,35,2,183572.84,1,1,1,66006.75,1 +4373,15730137,Udegbulam,628,France,Male,31,0,88421.81,1,0,0,72350.47,0 +4374,15596455,Mao,546,Spain,Female,45,2,0,1,0,0,197789.83,1 +4375,15717290,Onyekaozulu,688,Germany,Male,41,2,112871.19,2,0,1,65520.74,0 +4376,15616555,Fu,850,Germany,Male,41,8,60880.68,1,1,0,31825.84,0 +4377,15659820,Cross,614,France,Female,34,5,0,2,1,0,185561.89,0 +4378,15696301,Snider,719,France,Female,37,9,101455.7,1,1,0,25803.59,1 +4379,15771087,Harrison,757,France,Female,71,0,88084.13,2,1,1,154337.47,0 +4380,15808831,Dale,669,France,Male,29,7,0,2,1,1,138145.62,0 +4381,15812241,Udinese,438,Germany,Male,59,7,127197.14,1,1,0,51565.98,1 +4382,15680370,DeRose,492,France,Male,39,7,0,2,0,1,71323.23,0 +4383,15780561,Hay,622,France,Female,39,9,83456.79,2,0,0,38882.34,0 +4384,15800784,Bruce,645,France,Male,42,4,98298.18,1,1,1,676.06,0 +4385,15715796,Romani,728,France,Male,37,0,0,2,1,1,72203.8,0 +4386,15605375,Tseng,651,France,Male,35,2,86911.8,1,1,0,174094.24,0 +4387,15621520,Tang,783,Germany,Female,42,2,139707.28,1,1,0,2150.22,0 +4388,15665460,Isayeva,732,Spain,Female,67,1,0,2,1,1,177783.04,0 +4389,15801152,Hill,553,Spain,Female,39,1,142876.98,2,1,0,44363.42,0 +4390,15756425,Barnes,660,France,Male,30,7,146301.31,1,0,0,96847.91,0 +4391,15674328,Moreno,670,France,Female,40,3,47364.45,1,1,1,148579.43,1 +4392,15742404,McGregor,718,France,Male,38,7,0,2,1,0,38308.34,0 +4393,15757140,Genovese,787,France,Male,51,0,58137.08,1,0,1,142538.31,0 +4394,15570051,Gill,775,Germany,Female,38,6,179886.41,2,0,0,153122.58,0 +4395,15669175,Ts'ai,479,Germany,Male,24,6,107637.97,2,0,1,169505.83,0 +4396,15790324,Green,660,France,Female,20,6,167685.56,1,1,0,57929.9,0 +4397,15691119,Martin,721,Germany,Male,68,4,136525.99,1,0,0,175399.14,0 +4398,15743478,Johnson,659,Germany,Male,39,8,52106.33,2,1,1,107964.36,0 +4399,15707007,Onio,743,France,Female,39,8,0,1,1,0,94263.44,0 +4400,15572547,Vaguine,670,France,Female,45,9,104930.38,1,1,0,155921.81,1 +4401,15567063,Manna,766,Germany,Female,34,6,106434.94,1,0,1,137995.66,1 +4402,15689633,Toomey,845,Spain,Female,38,2,112803.92,1,1,0,179631.85,0 +4403,15720637,Bell,710,Germany,Female,46,10,120530.34,1,1,0,166586.99,1 +4404,15616859,Bonwick,602,Germany,Female,43,2,113641.49,4,1,0,115116.35,1 +4405,15766166,Folliero,604,Spain,Male,43,2,145081.72,1,1,1,23881.62,0 +4406,15617655,Holt,564,Spain,Female,35,9,0,2,1,1,105837.38,0 +4407,15623450,Brown,637,Germany,Female,27,7,135842.89,1,1,1,101418.05,0 +4408,15796612,Ch'ang,527,France,Female,31,1,112203.25,1,1,0,182266.01,0 +4409,15795963,Fiorentini,687,France,Male,34,7,129895.19,1,0,1,28698.17,0 +4410,15781598,Middleton,756,Germany,Male,41,6,149049.92,1,0,1,50422.36,1 +4411,15691871,Millar,503,Germany,Male,42,9,153279.39,1,1,1,151336.96,0 +4412,15740345,Osborne,657,Spain,Male,42,5,41473.33,1,1,0,112979.6,1 +4413,15662626,Feng,666,France,Female,40,2,0,2,0,0,36371.27,0 +4414,15596575,Vale,615,Germany,Male,39,5,113193.51,2,1,1,52166.25,0 +4415,15657321,Arkwookerum,712,Germany,Male,27,8,113174.21,2,1,0,147261.58,0 +4416,15575955,Lujan,764,France,Female,24,0,0,2,1,0,88724.49,0 +4417,15743893,Alexeyeva,471,France,Male,42,3,164951.56,1,1,0,190531.77,0 +4418,15697270,Gannon,608,Spain,Male,27,4,153325.1,1,1,1,199953.33,0 +4419,15644356,Prokhorova,682,Spain,Female,47,10,134032.01,1,1,0,144290.97,0 +4420,15677586,Romero,587,Germany,Female,32,3,125445.04,2,1,1,130514.78,0 +4421,15571261,Toscani,714,Germany,Female,35,6,126077.43,2,1,1,53954.24,0 +4422,15698758,Onwuamaegbu,630,Spain,Female,31,1,0,2,1,1,169802.73,0 +4423,15787014,King,648,Germany,Female,28,8,90371.09,1,1,1,146851.73,0 +4424,15739857,Trentino,785,France,Female,40,3,0,2,1,1,96832.82,0 +4425,15774630,Peacock,601,Germany,Female,47,1,142802.02,1,1,1,57553.02,0 +4426,15805523,Nnaife,717,France,Female,28,1,90537.16,1,0,1,74800.99,0 +4427,15749557,Chao,707,France,Female,44,6,0,2,1,1,192542.17,0 +4428,15681180,Barese,771,France,Female,23,7,156123.73,1,1,0,72990.62,0 +4429,15742028,Udegbulam,602,France,Female,35,5,0,2,1,0,31050.02,0 +4430,15686463,Fu,626,France,Male,38,7,141074.59,1,1,0,52795.56,1 +4431,15654379,Onwuatuegwu,588,Spain,Male,59,4,0,2,1,1,27435.41,0 +4432,15783629,Degtyaryov,616,Germany,Female,42,6,117899.95,2,0,0,150266.81,0 +4433,15751193,Nnaemeka,621,Spain,Male,33,4,0,2,1,1,40299.23,0 +4434,15724099,Udinese,674,France,Male,26,6,166257.96,1,1,1,149369.41,0 +4435,15568429,Mitchell,633,Spain,Female,46,3,0,2,1,0,120250.58,0 +4436,15648967,Ch'en,698,Germany,Female,64,1,169362.43,1,1,0,84760.32,1 +4437,15664498,Golovanov,508,France,Male,26,7,205962,1,1,0,156424.4,0 +4438,15779522,Efimov,736,France,Female,24,0,0,2,1,0,109355.73,1 +4439,15583850,Davidson,672,Germany,Male,68,0,126061.51,2,1,1,184936.77,0 +4440,15696539,Wade,613,France,Female,21,7,105627.95,1,1,1,36560.51,0 +4441,15760121,Maynard,712,France,Male,32,9,100606.02,1,1,0,165693.06,0 +4442,15628279,Murphy,624,France,Female,38,3,0,2,1,1,163666.85,0 +4443,15766163,Zotova,676,France,Male,38,1,0,2,0,1,35644.79,0 +4444,15566467,Hannah,683,Germany,Female,32,0,138171.1,2,1,1,188203.58,0 +4445,15639049,Cartagena,489,France,Female,31,7,139395.08,1,0,1,6120.84,0 +4446,15736413,Hall,739,France,Male,29,1,0,2,1,1,164484.78,0 +4447,15634815,Hunt,701,France,Female,37,3,0,2,1,1,164268.28,0 +4448,15716381,Greece,666,Germany,Female,50,7,109062.28,1,1,1,140136.1,1 +4449,15708162,Thomson,565,Germany,Female,40,1,89994.71,2,0,1,121084.27,0 +4450,15569364,Victor,666,France,Male,36,3,0,2,1,0,35156.54,0 +4451,15791191,Mitchell,633,France,Male,59,2,103996.74,1,1,1,103159.11,0 +4452,15621205,Olisaemeka,578,France,Male,34,4,175111.11,1,1,1,74858.3,0 +4453,15704788,Krawczyk,812,Spain,Female,49,8,66079.45,2,0,0,91556.57,1 +4454,15775756,Alexandrova,809,Germany,Male,33,8,148055.74,1,0,0,199203.21,0 +4455,15641312,Paterson,615,France,Male,36,6,0,1,1,1,27011.8,1 +4456,15782531,Chou,684,Spain,Female,31,8,0,2,1,0,188637.05,0 +4457,15724428,Abel,544,France,Male,40,8,0,2,1,0,61581.2,0 +4458,15743617,Chesnokova,713,Germany,Male,47,1,95994.98,1,1,0,197529.23,0 +4459,15585839,Niu,633,France,Male,37,2,0,2,1,0,182258.17,0 +4460,15658158,Sullivan,672,Germany,Female,23,10,110741.56,1,1,0,80778.5,0 +4461,15637678,Ma,661,France,Male,35,5,0,1,1,0,155394.52,0 +4462,15701809,Cavill,749,Spain,Female,28,3,0,1,1,0,3408.7,0 +4463,15676937,Nicholls,635,Spain,Female,32,8,0,2,1,1,19367.98,1 +4464,15778975,Nnonso,850,Germany,Female,70,1,96947.58,3,1,0,62282.99,1 +4465,15710375,Gibson,641,France,Male,41,6,0,2,1,0,65396.79,0 +4466,15579914,Garcia,633,Germany,Male,30,2,109786.82,2,1,1,139712.81,0 +4467,15595160,Renwick,413,Spain,Male,35,2,0,2,1,1,60972.84,0 +4468,15595391,Norris,538,France,Male,31,1,0,2,1,0,1375.46,0 +4469,15630363,Nkemakonam,437,France,Female,39,0,102721.49,1,0,0,22191.82,0 +4470,15692443,Piccio,612,Spain,Male,33,5,69478.57,1,1,0,8973.67,1 +4471,15593795,Linton,516,Germany,Female,53,1,156674.2,1,1,0,118502.34,1 +4472,15642824,Onyekaozulu,826,Spain,Female,56,8,174506.1,2,0,1,161802.82,1 +4473,15683524,Tobenna,660,Germany,Female,23,6,166070.48,2,0,0,90494.72,0 +4474,15713532,Wang,646,Germany,Female,29,4,105957.44,1,1,0,15470.91,0 +4475,15719827,O'Donnell,767,France,Male,36,3,0,1,0,0,65147.27,0 +4476,15578435,Langlands,640,France,Male,40,8,110340.68,1,1,1,157886.6,0 +4477,15723028,Smith,778,France,Male,33,1,0,2,1,0,85439.73,0 +4478,15595609,Sykes,679,Germany,Male,52,9,135870.01,2,0,0,54038.62,0 +4479,15622443,Marshall,549,France,Male,31,4,0,2,0,1,25684.85,0 +4480,15579112,Gibson,598,France,Male,47,2,0,2,1,1,186116.54,0 +4481,15648479,Stephenson,655,France,Female,45,0,0,2,1,0,166830.71,0 +4482,15659234,Y?,494,France,Male,30,3,85704.95,1,0,1,27886.06,0 +4483,15811970,Kang,653,France,Female,42,1,0,2,1,1,5768.32,0 +4484,15774192,Miller,539,Germany,Female,38,8,105435.74,1,0,0,80575.44,1 +4485,15595136,Kryukov,645,France,Female,37,1,0,2,1,1,68987.55,0 +4486,15630580,Y?,751,Germany,Male,34,9,108513.25,2,1,1,27097.82,0 +4487,15660646,Fanucci,528,France,Male,35,3,156687.1,1,1,0,199320.77,0 +4488,15614365,Lombardi,696,Germany,Male,31,3,150604.52,1,0,0,5566.6,0 +4489,15776128,Hs?,716,France,Female,44,6,155114.9,1,0,0,133871.83,0 +4490,15787035,Anderson,602,France,Female,35,8,0,2,1,1,152843.53,0 +4491,15792646,Trentino,647,Spain,Female,64,1,91216,1,1,1,41800.18,0 +4492,15726832,Donnelly,850,Germany,Male,61,3,141784.02,1,1,1,92053.75,0 +4493,15773260,Tsou,590,France,Female,32,0,127763.24,1,1,0,100717.54,0 +4494,15624437,Johnson,825,Spain,Female,32,1,0,2,1,1,42935.15,0 +4495,15717138,Watson,850,Spain,Male,31,6,82613.56,2,1,0,149170.92,0 +4496,15657317,Allan,789,France,Female,32,7,69423.52,1,1,0,107499.39,0 +4497,15626948,Butcher,701,France,Female,42,6,86167.82,1,1,0,153342.38,0 +4498,15758901,Henderson,713,Spain,Female,47,1,0,1,1,0,107825.08,1 +4499,15777759,Boucaut,570,France,Male,30,2,131406.56,1,1,1,47952.45,0 +4500,15773322,Obiajulu,536,Germany,Female,44,4,121898.82,1,0,0,131007.18,0 +4501,15697318,Ifeatu,771,Germany,Male,32,9,77487.2,1,0,0,33143.04,0 +4502,15678916,Kelly,512,France,Female,75,2,0,1,1,0,123304.62,0 +4503,15632118,Pirozzi,698,Spain,Male,45,5,164450.94,1,1,0,141970.02,1 +4504,15788118,Siciliano,656,France,Male,33,7,138705.02,2,1,0,37136.15,0 +4505,15788930,Silva,761,Spain,Male,37,7,132730.17,1,1,0,199293.01,0 +4506,15628583,Iweobiegbunam,709,France,Female,30,5,0,2,0,1,161388.22,0 +4507,15635177,Williamson,597,Spain,Female,66,3,0,1,1,1,70532.53,0 +4508,15587690,Madueke,592,France,Male,28,2,116498.22,1,1,0,144290.25,0 +4509,15627630,Chiagoziem,599,France,Female,41,1,0,2,1,0,96069.82,0 +4510,15610930,Kwemto,572,Germany,Female,35,1,139979.07,1,1,0,185662.84,0 +4511,15657747,Zito,611,Germany,Female,43,9,127216.31,2,0,1,17913.25,0 +4512,15568006,Ukaegbunam,634,France,Female,45,2,0,4,1,0,101039.53,1 +4513,15751748,Trevisani,666,France,Male,51,2,148222.65,1,0,0,156953.54,1 +4514,15722212,Edmondstone,696,France,Female,41,8,0,2,0,0,28276.83,0 +4515,15658670,Chien,669,France,Female,38,8,0,2,1,0,84049.16,0 +4516,15761654,Boni,726,Spain,Male,30,8,134152.29,1,1,1,147822.44,0 +4517,15812210,Yashina,497,Germany,Female,32,8,111537.23,4,1,1,9497.99,1 +4518,15787051,Georg,750,Spain,Female,39,7,119565.92,1,1,0,87067.73,0 +4519,15642991,Tung,850,Spain,Female,29,7,0,2,1,0,23237.25,0 +4520,15713769,Michelides,617,Spain,Male,38,7,0,1,1,1,27239.28,0 +4521,15605826,Korovina,652,Germany,Male,46,10,121063.8,3,1,0,151481.86,1 +4522,15648898,Chuang,560,Spain,Female,27,7,124995.98,1,1,1,114669.79,0 +4523,15705309,Yuriev,629,Spain,Male,39,5,0,2,0,0,116748.14,0 +4524,15734202,Chidimma,660,Germany,Female,52,4,86891.84,1,1,0,90877.76,0 +4525,15658852,Stevens,676,France,Male,38,8,0,2,1,1,133692.88,0 +4526,15612633,Kao,581,Spain,Male,43,9,78022.61,1,0,1,30662.91,0 +4527,15604818,Edmund la Touche,798,France,Male,34,9,154495.79,1,1,0,191395.88,0 +4528,15593900,Belousov,705,France,Male,38,1,189443.72,1,0,1,106648.58,0 +4529,15624995,McCane,714,Spain,Female,31,6,152926.6,1,1,1,50899.91,0 +4530,15570087,Parry-Okeden,664,France,Female,44,8,142989.69,1,1,1,115452.51,1 +4531,15802617,Hudson,697,Germany,Male,43,7,115371.94,2,1,0,64139.1,0 +4532,15656029,Marsden,609,France,Male,37,6,0,2,0,1,22030.72,0 +4533,15739194,Manfrin,548,Spain,Male,38,0,178056.54,2,1,0,38434.73,0 +4534,15607275,Ch'ang,850,Spain,Male,39,6,206014.94,2,0,1,42774.84,1 +4535,15629475,Clark,656,France,Male,41,2,0,2,1,0,158973.77,0 +4536,15635034,Aldrich,727,Germany,Male,37,9,101191.83,1,1,1,34551.35,1 +4537,15756333,Khan,642,France,Female,55,7,0,2,1,1,101515.76,0 +4538,15777436,Murray,710,Spain,Female,31,5,0,2,1,0,9561.73,0 +4539,15676835,Anayolisa,710,Spain,Male,33,1,0,2,1,0,168313.17,0 +4540,15574206,Shillito,718,France,Female,37,7,0,2,1,1,55100.09,0 +4541,15613017,McMillan,586,Germany,Male,32,1,149814.54,1,1,0,31830.06,0 +4542,15815131,Howells,617,Spain,Female,36,7,115617.24,1,1,1,71519.4,0 +4543,15585455,Stewart,630,France,Male,28,9,0,2,0,0,32599.35,0 +4544,15692929,Ikechukwu,791,Germany,Female,42,10,113657.41,2,0,1,139946.68,1 +4545,15758081,Repina,673,Spain,Male,39,8,138160,1,1,1,110468.51,0 +4546,15667476,Cox,477,Germany,Female,36,3,117700.86,1,0,0,74042,0 +4547,15738248,Lo,662,France,Female,37,5,0,2,1,0,151871.84,0 +4548,15672152,Grant,850,Germany,Male,37,9,122506.38,1,0,1,199693.84,1 +4549,15673372,Stevenson,635,France,Female,58,1,0,1,1,1,58907.08,1 +4550,15587611,Kauffmann,537,France,Male,59,9,0,2,0,0,103799.77,1 +4551,15803415,Samsonova,579,France,Female,39,3,166501.17,2,1,0,93835.64,0 +4552,15715673,Niu,651,Spain,Female,46,4,89743.05,1,1,0,156425.57,1 +4553,15655648,Bock,610,France,Female,25,2,0,2,1,0,123723.83,0 +4554,15763613,Barlow,581,France,Male,30,1,0,2,1,0,199464.08,0 +4555,15660385,Stevenson,592,France,Male,39,7,0,2,1,0,83084.33,0 +4556,15733261,Kung,688,Spain,Female,35,6,0,1,1,0,25488.43,1 +4557,15796231,Nwankwo,681,France,Female,18,1,98894.39,1,1,1,9596.4,0 +4558,15624866,Brewer,658,Germany,Male,37,3,168735.74,2,0,0,70370.24,0 +4559,15623730,Ch'iu,792,France,Male,34,1,0,1,0,1,86330.32,0 +4560,15668248,Quinn,528,Germany,Female,62,7,133201.17,1,0,0,168507.68,1 +4561,15694518,Kodilinyechukwu,624,Spain,Female,36,0,0,2,1,0,111605.9,0 +4562,15638028,Ifeanyichukwu,562,Germany,Male,31,4,127237.25,2,0,1,143317.42,0 +4563,15795895,Yermakova,678,Germany,Male,36,1,117864.85,2,1,0,27619.06,0 +4564,15694376,Sullivan,705,Germany,Female,64,3,153469.26,3,0,0,146573.66,1 +4565,15669204,Grant,650,Germany,Male,23,4,93911.3,2,1,0,69055.45,0 +4566,15773779,Jacka,593,Spain,Female,46,2,76597.79,1,1,1,54453.72,0 +4567,15580682,Tsai,652,France,Female,40,4,79927.36,2,1,1,33524.6,0 +4568,15768530,Emery,554,Spain,Female,27,4,0,2,1,1,135083.73,0 +4569,15672875,Piccio,584,Germany,Male,32,8,40172.91,1,1,1,137439.34,0 +4570,15617082,Sanders,516,France,Male,33,7,115195.58,1,1,1,11205.5,0 +4571,15760514,Sharp,789,Germany,Female,43,9,116644.29,2,1,1,60176.1,0 +4572,15761775,Myers,598,Germany,Male,20,8,180293.84,2,1,1,29552.7,0 +4573,15799964,Campbell,669,Germany,Female,30,7,139872.81,1,1,0,188795.85,0 +4574,15693906,Abbott,645,France,Female,24,3,34547.82,1,1,1,11638.17,0 +4575,15739514,Preston,659,France,Female,32,9,0,2,1,1,93155.75,0 +4576,15756926,Atherton,833,Germany,Male,29,1,96462.25,2,0,1,48986.18,0 +4577,15770984,Fanucci,697,Spain,Female,40,7,130334.35,2,0,1,116951.1,0 +4578,15703979,Evans,580,Germany,Male,39,3,119688.81,1,1,0,137041.26,0 +4579,15801821,Cookson,691,France,Male,38,1,0,2,0,0,44653.5,0 +4580,15711028,Nnachetam,534,France,Male,52,1,0,3,1,1,104035.41,1 +4581,15791842,Johnstone,478,France,Female,32,6,71187.24,1,1,1,110593.62,0 +4582,15746127,Hort,572,France,Female,47,2,0,2,1,0,36099.7,0 +4583,15663625,Johnson,501,France,Male,37,4,0,2,0,0,12470.3,0 +4584,15604891,Zaytseva,624,Spain,Female,38,8,0,2,1,0,95403.41,0 +4585,15589666,Sorokina,595,France,Female,39,9,136422.41,1,1,1,151757.81,0 +4586,15627881,Diehl,603,France,Male,30,8,0,2,1,1,47536.46,0 +4587,15664895,Onuchukwu,602,France,Female,25,0,0,2,1,1,101274.17,0 +4588,15676094,Osonduagwuike,500,France,Female,34,6,0,1,1,1,140268.45,0 +4589,15761720,Mead,422,France,Male,41,6,153238.88,1,1,0,11663.09,0 +4590,15611961,Stewart,615,France,Male,35,7,0,2,1,0,150784.29,0 +4591,15680167,Thomson,635,France,Female,78,6,47536.4,1,1,1,119400.08,0 +4592,15762543,Goliwe,711,France,Female,32,1,0,2,1,0,126188.42,0 +4593,15658475,Lori,834,France,Male,36,8,142882.49,1,1,0,89983.02,1 +4594,15779743,Onwuamaeze,633,France,Female,44,7,0,2,1,0,29761.29,0 +4595,15661532,Butusov,650,France,Female,31,1,160566.11,2,0,0,27073.81,0 +4596,15782360,Rogers,743,Germany,Male,65,2,131935.51,1,1,1,96399.67,1 +4597,15767908,Nicholson,567,France,Male,38,6,127678.8,2,0,0,45422.89,0 +4598,15677105,Rossi,706,Germany,Female,46,4,105214.58,1,1,0,108699.59,1 +4599,15641474,Hall,638,France,Male,46,9,139859.54,1,1,0,38967.29,0 +4600,15624451,Huddart,641,France,Female,38,3,0,2,1,0,116466.19,0 +4601,15577985,Chinomso,574,France,Female,34,5,112324.45,2,1,1,17993.43,0 +4602,15571666,Shaw,642,Germany,Male,30,8,134497.27,1,0,0,43250.54,0 +4603,15783691,Hargreaves,722,Spain,Female,35,1,120171.58,1,1,0,125240.8,0 +4604,15671172,Swain,623,France,Male,23,1,106012.2,2,0,1,191415.94,0 +4605,15731760,Butcher,681,France,Male,25,5,0,1,0,1,90860.97,0 +4606,15585599,Stone,530,France,Female,34,8,0,2,0,1,141872.52,0 +4607,15784958,Allan,797,France,Female,55,10,0,4,1,1,49418.87,1 +4608,15734524,Wang,653,France,Male,51,3,0,1,1,0,170426.65,1 +4609,15614103,Colombo,850,Germany,Male,42,8,119839.69,1,0,1,51016.02,1 +4610,15794895,McKay,581,Spain,Male,34,1,0,2,0,1,81175.25,0 +4611,15772381,Brient,589,Germany,Male,38,8,92219.21,1,1,0,99106.97,0 +4612,15710553,Yin,555,Germany,Male,48,3,142055.41,2,0,1,79134.78,0 +4613,15649292,Bellucci,748,France,Female,49,7,29602.08,1,0,0,163550.58,1 +4614,15792565,Duncan,745,France,Female,46,7,0,2,1,1,67769.94,0 +4615,15718245,Pirozzi,730,France,Male,34,1,0,2,1,1,126592.01,0 +4616,15703117,Findlay,565,France,Female,44,1,0,2,0,1,89602.81,0 +4617,15758136,King,778,France,Male,37,3,141803.77,1,0,1,179421.84,0 +4618,15799932,Iweobiegbunam,812,France,Male,24,10,0,2,1,1,156906.15,0 +4619,15633516,Tucker,526,France,Male,42,1,0,1,0,1,168486.02,0 +4620,15622532,Izmailova,708,France,Female,47,0,126589.12,2,0,1,132730.07,1 +4621,15798960,Meng,680,France,Male,33,2,108393.35,1,0,1,39057.67,0 +4622,15698664,Liang,567,Spain,Male,43,2,115643.58,2,0,0,174606.35,0 +4623,15703614,Hutchinson,564,Spain,Male,48,5,132876.23,1,1,0,79259.77,0 +4624,15699195,Shen,709,France,Female,24,3,110949.41,1,1,1,168515.61,0 +4625,15710543,Okwuoma,629,France,Male,46,1,130666.2,1,1,1,161125.67,1 +4626,15695499,Chinwemma,510,France,Female,45,10,103821.47,2,0,1,77878.62,0 +4627,15622321,Golubova,506,France,Female,32,3,0,1,1,1,80823.02,0 +4628,15715744,Schiavone,605,France,Male,39,7,0,1,0,1,119348.28,0 +4629,15788151,Moore,650,Spain,Male,32,1,132187.73,2,1,1,178331.36,0 +4630,15687153,Graham,850,Germany,Male,49,8,98649.55,1,1,0,119174.88,1 +4631,15684958,Amadi,489,Germany,Male,38,2,126444.08,2,1,1,82662.73,0 +4632,15706116,McKay,659,Germany,Female,30,8,154159.51,1,1,0,40441.1,0 +4633,15740557,Fedorova,753,France,Female,43,5,0,2,1,0,109881.71,0 +4634,15707291,Percy,477,Germany,Male,48,8,129250,2,1,1,157937.35,0 +4635,15583353,Floyd,610,Spain,Female,45,3,0,1,1,0,38276.84,1 +4636,15761024,Long,619,France,Female,33,2,167733.51,2,1,1,65222.48,0 +4637,15630709,Castiglione,619,Germany,Female,31,2,56116.3,2,0,0,2181.94,0 +4638,15639590,Melendez,758,France,Female,30,3,141581.08,1,1,0,156249.06,0 +4639,15659399,Mazzi,516,Germany,Male,50,7,139675.07,2,1,0,45591.23,0 +4640,15567078,Kovaleva,789,France,Female,27,8,66201.96,1,1,1,79458.12,0 +4641,15696373,Gill,687,France,Female,44,9,0,2,0,0,103042.2,1 +4642,15786617,Arcuri,485,Germany,Male,34,3,133658.24,1,1,0,70209.83,0 +4643,15657449,Chukwuma,446,Germany,Male,25,3,136202.78,1,1,0,176743.51,0 +4644,15672594,Stevenson,597,France,Female,60,0,131778.08,1,0,0,10703.53,1 +4645,15714240,Ponomarev,712,Spain,Male,74,5,0,2,0,0,151425.82,0 +4646,15782144,Gilroy,522,France,Female,34,3,0,2,1,1,3894.34,0 +4647,15665008,Sidorov,805,Germany,Female,26,8,42712.87,2,1,1,28861.69,0 +4648,15581733,Bates,781,France,Female,28,4,0,2,1,0,177703.15,0 +4649,15751392,Fanucci,689,Spain,Female,57,4,0,2,1,0,136649.8,1 +4650,15785815,Toscano,670,Germany,Male,31,1,142631.54,2,1,1,175894.24,0 +4651,15664214,Hearn,670,France,Male,33,2,141204.65,2,1,0,76257.46,0 +4652,15579996,Iroawuchi,524,Germany,Female,25,7,131402.21,1,0,0,193668.49,0 +4653,15675252,Martin,734,Spain,Female,39,3,92636.96,2,1,1,125671.29,0 +4654,15579617,Sinclair,489,France,Female,51,3,0,2,0,1,174098.28,1 +4655,15593976,Swanson,578,Germany,Female,31,5,102088.68,4,0,0,187866.21,1 +4656,15716041,Chinomso,622,Spain,Male,39,9,0,2,0,1,100862.36,0 +4657,15654489,Fomin,843,France,Female,38,8,134887.53,1,1,1,10804.04,0 +4658,15736302,McKay,687,France,Male,48,4,0,2,1,1,170893.85,0 +4659,15805909,Bergamaschi,700,Spain,Male,28,8,159900.38,1,0,0,22698.56,0 +4660,15572762,Matveyeva,410,Germany,Female,50,2,102278.79,2,1,0,89822.48,0 +4661,15724632,Madukaego,537,France,Female,41,0,0,2,0,1,175262.49,0 +4662,15670416,Ferri,780,France,Female,43,0,0,1,0,1,15705.27,0 +4663,15749528,Achebe,652,Spain,Male,58,6,0,2,0,1,170025.43,0 +4664,15578783,Mai,620,Germany,Male,35,0,76989.97,1,1,1,17242.79,0 +4665,15580719,Davis,697,France,Female,23,10,0,2,1,1,79734.23,0 +4666,15656293,Davey,786,France,Male,35,3,0,2,1,0,92712.97,0 +4667,15691875,Tsou,850,Germany,Female,39,5,114491.82,1,1,0,99689.48,0 +4668,15596870,Marino,749,Germany,Male,54,3,144768.94,1,1,0,93336.3,1 +4669,15780770,Kerr,445,France,Male,31,7,145056.59,1,1,1,175893.53,0 +4670,15751491,Hsiao,443,Germany,Male,50,3,117206.3,1,1,0,42840.18,1 +4671,15706200,Graham,637,Germany,Male,41,2,138014.4,2,1,0,140298.24,0 +4672,15808674,Ejikemeifeuwa,616,Germany,Female,45,6,128352.59,3,1,1,144000.59,1 +4673,15641411,Volkova,756,France,Female,23,1,112568.31,1,1,1,113408.11,0 +4674,15764661,Wang,644,France,Male,33,2,0,1,1,0,96420.58,0 +4675,15689492,Benjamin,850,Germany,Male,41,1,176958.46,2,0,1,125806.3,0 +4676,15602405,Ryrie,703,Germany,Female,38,9,99167.54,1,1,0,65720.92,0 +4677,15610271,Andreev,684,Spain,Female,42,3,103210.27,1,1,0,31002.03,0 +4678,15791780,Ts'ao,706,Germany,Female,48,10,104478.12,3,0,1,158248.71,1 +4679,15589147,Frolov,580,Spain,Male,61,8,125921.37,1,1,1,94677.83,0 +4680,15756975,Montemayor,777,Spain,Female,35,3,0,2,1,1,17257.72,0 +4681,15729582,Fu,676,Germany,Male,48,3,80697.44,1,0,0,101397.86,0 +4682,15742971,Whitehead,708,France,Female,44,2,161887.81,2,1,0,84870.23,0 +4683,15568046,Izuchukwu,809,France,Male,24,7,109558.36,1,1,0,183515.13,0 +4684,15694890,Lai,588,France,Male,38,1,124271.26,1,1,0,75969.19,0 +4685,15736963,Herring,623,France,Male,43,1,0,2,1,1,146379.3,0 +4686,15646490,Duffy,537,Spain,Male,42,1,190569.23,1,0,1,127154.8,0 +4687,15607314,Chiefo,536,Spain,Male,53,2,143923.96,1,1,0,2019.78,1 +4688,15576745,Fyodorov,769,France,Male,48,2,96542.16,2,0,1,197885.72,0 +4689,15669606,Chu,690,France,Male,33,5,0,2,1,0,138017.68,0 +4690,15737832,Robertson,771,Spain,Male,45,0,139825.56,1,0,0,170984.97,1 +4691,15681990,Palmerston,497,Germany,Male,24,6,111769.14,2,1,0,55859.27,0 +4692,15758050,Madukwe,622,Spain,Male,37,4,0,2,1,0,4459.5,0 +4693,15787848,Chinedum,602,Spain,Male,30,9,113672.18,2,0,0,102135.92,0 +4694,15713594,French,543,France,Female,32,7,147256.86,1,1,0,112771.95,0 +4695,15588186,Polyakov,520,Spain,Male,45,7,107023.03,1,1,0,32903.93,0 +4696,15786739,Clements,669,France,Male,37,1,125529.55,1,1,1,162260.93,0 +4697,15699467,Connor,631,Spain,Female,41,0,0,1,0,0,87959.83,0 +4698,15680706,Balashov,537,Germany,Male,48,4,131834.8,1,1,0,166476.95,1 +4699,15645717,Avdeeva,732,France,Male,62,2,0,2,1,1,25438.87,0 +4700,15748597,Chester,844,Spain,Male,56,5,99529.7,1,0,1,157230.06,1 +4701,15773709,Hung,838,Spain,Male,35,0,0,2,0,1,197305.91,0 +4702,15629787,Tu,652,France,Male,27,10,107303.72,2,0,0,44435.76,0 +4703,15661007,Thompson,660,France,Male,33,0,72783.42,1,0,0,181051.99,0 +4704,15686812,Jones,692,Spain,Female,44,8,0,1,0,1,159069.37,0 +4705,15754113,Li,588,France,Female,35,0,0,2,1,1,155485.24,0 +4706,15749489,Denisova,533,Germany,Female,22,10,115743.6,1,0,0,43852.05,0 +4707,15574352,Clogstoun,850,France,Male,43,4,161256.53,1,1,1,140071.57,0 +4708,15701281,Tan,511,France,Male,27,8,0,2,1,1,49089.36,0 +4709,15811985,Power,530,Spain,Male,44,6,0,2,0,0,55893.37,0 +4710,15713505,Harriman,554,France,Male,31,1,0,2,0,1,192660.55,0 +4711,15685653,Benson,585,Germany,Female,40,3,162261.01,2,1,0,137028.51,0 +4712,15758831,Thornton,754,France,Male,39,3,74896.33,1,0,0,34430.16,0 +4713,15618774,White,474,France,Male,54,3,0,1,1,0,108409.17,1 +4714,15764448,Mackenzie,837,Germany,Male,35,0,144037.6,1,1,0,145325.32,0 +4715,15611024,Kalinina,567,France,Female,23,9,93522.2,1,0,1,81425.61,0 +4716,15738220,Bennet,800,Spain,Male,38,1,0,2,1,0,51553.43,0 +4717,15805764,Hallahan,646,France,Male,18,10,0,2,0,1,52795.15,0 +4718,15580487,Martin,627,Germany,Male,38,8,106922.92,2,0,1,84270.09,0 +4719,15675787,Rivera,505,France,Male,26,8,112972.57,1,1,0,145011.62,0 +4720,15583580,Chiawuotu,566,Germany,Female,35,1,123042,1,1,0,66245.44,1 +4721,15780654,Sergeyev,619,Germany,Female,33,3,100488.92,2,0,1,36446.74,0 +4722,15695034,Christie,757,France,Female,44,4,123322.15,1,1,0,137136.29,0 +4723,15805671,Louis,648,France,Male,32,0,0,1,0,1,117323.31,0 +4724,15790658,Iqbal,621,Spain,Male,42,8,68683.68,1,1,1,74157.71,0 +4725,15578648,Marino,543,Germany,Male,49,6,59532.18,1,1,0,104253.56,0 +4726,15734987,Robertson,658,France,Female,43,7,140260.36,2,1,0,2748.72,0 +4727,15721740,Pai,633,Germany,Male,50,7,88302.65,1,1,1,195937.16,0 +4728,15641822,Barese,648,France,Female,19,1,0,2,0,1,22101.86,0 +4729,15765650,Chigolum,501,Germany,Male,40,5,114655.58,1,0,0,126535.92,0 +4730,15788556,Trouette,683,France,Female,42,4,148283.94,1,1,1,44692.63,1 +4731,15576550,Ugochukwu,619,Spain,Female,38,1,0,1,1,0,112442.63,1 +4732,15622230,Cribb,705,France,Female,35,3,0,2,0,1,66331.01,0 +4733,15653937,McIntyre,638,Germany,Female,53,1,123916.67,1,1,0,16657.68,1 +4734,15743538,Pickering,710,France,Female,31,1,0,2,1,0,20081.3,0 +4735,15591740,Fletcher,590,France,Female,54,4,0,2,1,1,93820.49,1 +4736,15650086,Uchenna,725,France,Male,43,2,165896,2,1,0,130795.52,0 +4737,15718773,Pisano,638,France,Female,32,0,0,2,1,0,160129.99,0 +4738,15615140,Corson,791,France,Male,36,6,111168.97,1,1,1,189969.91,0 +4739,15644361,Hooper,702,France,Female,40,1,103549.24,1,0,0,9712.52,1 +4740,15774536,He,607,France,Female,32,6,0,2,0,0,196062.01,0 +4741,15618661,Chidubem,535,France,Male,30,6,103804.97,1,1,1,125710.53,0 +4742,15605020,Schofield,651,France,Male,45,2,165901.59,2,1,0,23054.51,1 +4743,15762134,Liang,506,Germany,Male,59,8,119152.1,2,1,1,170679.74,0 +4744,15685279,Somadina,511,Spain,Female,57,8,122950.31,1,1,1,181258.76,0 +4745,15582849,McIntosh,757,France,Female,51,1,0,1,1,1,22835.13,1 +4746,15655410,Hinton,768,Germany,Male,49,1,133384.66,1,1,0,102397.22,1 +4747,15649129,Sal,757,France,Male,32,9,0,2,1,0,115950.96,0 +4748,15702380,De Luca,663,Spain,Male,64,6,0,2,0,1,15876.52,0 +4749,15759067,Bromby,537,Germany,Female,37,7,158411.95,4,1,1,117690.58,1 +4750,15683027,Chang,570,Germany,Male,29,4,122028.65,2,1,1,173792.77,0 +4751,15597487,Hunter,850,France,Female,35,5,0,1,1,1,80992.8,0 +4752,15763256,Sheppard,661,Germany,Female,64,8,128751.65,2,1,0,189398.18,1 +4753,15620111,Fan,659,France,Male,54,8,133436.52,1,1,0,56787.8,0 +4754,15623053,Muir,454,Spain,Male,40,2,123177.01,1,1,0,148309.98,0 +4755,15595592,Lai,708,France,Female,59,2,0,1,1,0,179673.11,1 +4756,15740072,Padovesi,720,France,Female,37,2,120328.88,2,1,1,138470.21,0 +4757,15778005,Kemp,785,France,Female,39,1,130147.98,1,1,0,163798.41,1 +4758,15583278,Greece,743,Spain,Female,36,8,92716.96,1,1,1,33693.78,0 +4759,15601263,Young,493,Spain,Female,48,7,0,2,1,0,48545.1,0 +4760,15709222,Chukwueloka,557,Spain,Male,34,3,0,1,0,1,123427.98,0 +4761,15713949,Woods,850,France,Male,40,1,76914.21,1,1,0,174183.44,0 +4762,15717706,Forbes,799,France,Female,32,3,106045.92,2,1,1,17938,0 +4763,15756071,Kang,756,France,Male,34,1,103133.26,1,1,1,90059.04,0 +4764,15696564,Nweke,752,France,Male,38,0,145974.79,2,1,1,137694.23,0 +4765,15657637,Ts'ui,696,Spain,Female,36,3,0,3,1,0,65039.9,0 +4766,15755863,Milano,630,Spain,Female,49,1,0,2,0,1,162858.29,0 +4767,15719858,Chao,659,Spain,Female,38,9,0,2,1,1,35701.06,0 +4768,15688876,Wan,685,Spain,Male,39,9,0,2,1,1,18826.06,0 +4769,15698528,Napolitani,599,Spain,Female,31,3,0,1,1,1,130086.47,1 +4770,15770345,Kovaleva,559,Spain,Female,31,1,139183.06,1,0,1,143360.56,0 +4771,15761506,Russell,615,Spain,Male,19,5,0,2,1,0,159920.92,0 +4772,15716619,Chiebuka,580,Germany,Female,36,3,74974.89,1,1,1,12099.67,0 +4773,15788367,Ellis,487,Spain,Male,44,6,61691.45,1,1,1,53087.98,0 +4774,15709451,Gordon,646,Germany,Female,35,1,121952.75,2,1,1,142839.82,0 +4775,15640421,Conway,811,France,Female,35,7,0,1,1,1,178.19,0 +4776,15580068,Buccho,526,Spain,Male,35,5,0,2,1,1,105618.14,0 +4777,15677123,Aksyonova,767,Spain,Male,37,7,0,2,1,1,24734.25,0 +4778,15619801,Batty,548,France,Female,33,1,80107.83,2,0,1,82245.67,0 +4779,15582246,Rowe,737,Spain,Female,45,2,0,2,0,1,177695.67,0 +4780,15711843,Pisani,613,Germany,Male,40,1,147856.82,3,0,0,107961.11,1 +4781,15680046,Onochie,711,Spain,Male,36,8,0,2,1,0,55207.41,0 +4782,15804131,Farmer,850,Spain,Female,53,7,65407.16,2,0,0,182633.63,1 +4783,15722611,Cameron,752,France,Female,53,8,114233.18,1,1,1,51587.04,0 +4784,15729224,Jennings,710,France,Female,37,5,0,2,1,0,115403.31,0 +4785,15811588,Eluemuno,664,Spain,Female,53,7,187602.18,1,1,0,186392.99,1 +4786,15702138,Swift,510,France,Female,22,3,156834.34,1,0,0,44374.44,0 +4787,15749799,Pisani,577,France,Female,34,2,0,2,1,1,84033.35,0 +4788,15752885,Nnonso,529,France,Male,42,1,157498.9,1,1,1,82276.62,0 +4789,15674932,Cameron,757,Spain,Female,44,9,0,2,1,0,177528.92,0 +4790,15743828,Stevens,691,France,Male,41,2,0,1,1,1,56850.92,1 +4791,15642022,Zito,621,Spain,Male,34,8,0,1,0,0,47972.65,0 +4792,15746461,Taylor,709,Spain,Male,35,2,0,2,1,0,104982.39,0 +4793,15809991,Ferrari,756,Spain,Male,19,4,130274.22,1,1,1,133535.29,0 +4794,15787322,Yeh,788,France,Female,41,6,0,1,1,1,25571.37,0 +4795,15575498,Gould,705,France,Female,39,5,149379.66,2,1,0,96075.55,0 +4796,15691387,Agafonova,483,France,Male,29,9,0,1,1,1,81634.45,0 +4797,15765457,Fowler,719,Spain,Male,35,1,100829.94,1,1,1,165008.97,0 +4798,15666173,Chidumaga,793,Germany,Female,32,1,96408.98,1,1,1,138191.81,0 +4799,15627377,Sabbatini,593,France,Male,41,6,0,2,1,1,99136.49,0 +4800,15656683,Johnson,551,France,Male,52,1,0,1,0,0,63584.55,1 +4801,15679810,Chapman,690,France,Male,39,6,0,2,1,0,160532.88,0 +4802,15606310,Birk,823,France,Male,71,5,149105.08,1,0,1,162683.06,0 +4803,15756871,Capon,512,Spain,Male,39,3,0,1,1,0,134878.19,0 +4804,15610002,Chidubem,802,Spain,Male,41,5,0,2,1,1,134626.3,0 +4805,15567802,Childs,450,Spain,Female,34,2,0,2,1,0,175480.93,0 +4806,15745452,Sun,651,Germany,Male,41,1,90218.11,1,1,0,174337.68,0 +4807,15617252,Lung,697,France,Female,33,1,87347.7,1,1,0,172524.51,0 +4808,15753248,Tao,611,France,Male,28,2,0,2,0,0,25395.83,0 +4809,15610755,Napolitano,643,France,Female,33,0,137811.75,1,1,1,184856.89,0 +4810,15662238,Davis,822,France,Male,37,3,105563,1,1,0,182624.93,0 +4811,15799186,Sagese,632,France,Male,38,4,0,2,0,0,192505.62,0 +4812,15686941,Hutchinson,575,Spain,Female,26,7,0,2,1,0,112507.63,0 +4813,15601172,Nelson,672,France,Male,31,6,91125.75,1,1,0,177295.92,0 +4814,15723858,Schiavone,517,Spain,Male,39,3,0,2,0,1,12465.51,0 +4815,15615896,Chienezie,621,Spain,Male,39,8,0,2,1,0,36122.96,0 +4816,15737647,Obioma,775,Germany,Female,77,6,135120.56,1,1,0,37836.64,0 +4817,15582841,Butusov,600,France,Male,29,8,0,2,0,1,34747.43,0 +4818,15760090,Pisano,640,France,Male,28,7,0,2,1,1,131097.9,0 +4819,15588587,Stetson,752,France,Female,36,1,86837.95,1,1,1,105280.55,0 +4820,15683157,Waring,613,France,Male,26,4,100446.57,1,0,1,149653.81,0 +4821,15694209,Fanucci,484,France,Female,32,3,0,2,1,1,139390.99,0 +4822,15655875,Thao,511,France,Female,33,3,0,2,1,0,132436.71,0 +4823,15805704,Murphy,745,France,Female,32,2,0,4,0,1,179705.13,1 +4824,15744789,McConnell,786,Spain,Female,32,6,114512.59,1,1,0,15796.66,0 +4825,15799357,Armfield,727,France,Male,35,5,136364.46,1,0,0,142754.71,0 +4826,15726153,Fanucci,622,France,Male,31,5,106260.67,1,1,1,2578.43,0 +4827,15713346,Panina,794,France,Male,24,10,146126.75,1,1,1,88992.05,0 +4828,15665053,Nixon,636,Spain,Male,52,4,111284.53,1,0,1,32936.44,1 +4829,15592379,Walker,741,Spain,Female,42,9,121056.63,2,1,0,39122.58,0 +4830,15692599,Chiemela,687,France,Male,34,5,128270.56,1,1,0,191092.62,0 +4831,15620758,Martel,660,Spain,Male,30,4,0,2,1,0,129149.06,0 +4832,15637428,Briggs,660,France,Male,35,7,0,2,1,0,13218.6,0 +4833,15808389,Iheatu,617,France,Female,79,7,0,1,1,1,160589.18,0 +4834,15807003,Jennings,762,France,Male,32,10,191775.65,1,1,0,179657.83,0 +4835,15702912,Ch'en,752,Spain,Female,35,2,0,1,1,0,44335.54,1 +4836,15590623,Kovalyov,561,Spain,Male,34,4,85141.79,2,1,1,29217.37,0 +4837,15728078,Yeh,609,France,Male,26,10,126392.18,1,0,1,43651.49,0 +4838,15708256,Chien,803,France,Male,28,3,0,2,1,0,159654,0 +4839,15582335,Brown,556,France,Female,40,9,129860.37,1,0,0,17992.94,0 +4840,15649150,Buddicom,531,France,Female,53,5,127642.44,1,1,0,141501.45,1 +4841,15691647,McGregor,411,France,Female,35,2,0,2,1,1,93825.78,0 +4842,15668270,Thompson,587,Germany,Female,44,5,125584.17,2,1,1,41852.24,1 +4843,15624820,Ross,683,Spain,Male,56,7,50911.21,3,0,0,97629.31,1 +4844,15736254,Ch'ang,654,France,Male,29,2,91955.61,1,1,0,37065.66,0 +4845,15720814,Warren,670,Germany,Female,36,2,84266.44,2,0,0,38614.69,0 +4846,15642997,Uspenskaya,655,France,Female,36,2,147149.59,1,1,1,87816.86,0 +4847,15693200,King,752,France,Female,36,7,0,2,1,0,184866.86,0 +4848,15624596,Trentini,534,France,Female,23,5,104822.45,1,0,1,160176.47,0 +4849,15807167,Konovalova,635,France,Male,42,1,146766.72,2,0,1,164357.1,0 +4850,15660301,Dellucci,491,Germany,Male,70,6,148745.92,2,1,1,17818.33,0 +4851,15593094,Goddard,516,France,Male,27,9,0,1,1,0,142680.64,1 +4852,15618239,Neumann,530,France,Female,48,0,0,1,1,0,85081.09,0 +4853,15574137,Ch'in,687,Spain,Male,35,3,0,2,1,1,176450.19,0 +4854,15614740,Walters,684,France,Female,41,6,135203.81,2,1,1,121967.88,0 +4855,15574071,Muravyova,706,Germany,Male,23,2,93301.97,2,0,1,127187.04,0 +4856,15671148,Barry,490,Germany,Male,33,5,96341,2,0,0,108313.34,0 +4857,15721921,Woolnough,796,France,Male,44,8,165326.2,1,1,1,57205.55,0 +4858,15717995,Keen,849,France,Male,27,0,0,2,0,1,157891.86,0 +4859,15632050,Liebe,779,France,Female,41,10,99786.2,1,1,0,86927.53,0 +4860,15647111,White,794,Spain,Female,22,4,114440.24,1,1,1,107753.07,0 +4861,15759991,Hunter,748,Spain,Male,36,4,141573.55,1,1,0,82158.14,0 +4862,15790204,Myers,663,Spain,Female,22,9,0,1,1,0,29135.89,1 +4863,15686780,Rogova,645,Spain,Female,55,1,133676.65,1,0,1,17095.49,0 +4864,15640491,Raff,464,France,Female,33,10,147493.7,2,1,0,100447.53,0 +4865,15783225,Cocci,737,France,Male,54,9,0,1,1,0,83470.4,1 +4866,15734438,Kanayochukwu,590,France,Female,29,4,0,2,1,0,121846.81,0 +4867,15688760,Obialo,522,Germany,Female,37,3,95022.57,1,1,1,129107.59,0 +4868,15768124,Liu,648,France,Female,34,3,0,1,1,0,54726.43,0 +4869,15661330,Gilbert,754,France,Male,37,6,0,1,1,1,116141.72,0 +4870,15781272,Coles,669,France,Male,50,4,149713.61,3,1,1,124872.42,1 +4871,15573888,Ponomaryov,648,Germany,Female,43,1,107963.38,1,0,0,186438.86,1 +4872,15575858,Bergamaschi,763,France,Male,40,3,0,2,1,0,134281.11,0 +4873,15645937,Guerin,790,Spain,Male,32,3,0,1,1,0,91044.47,0 +4874,15702337,Sinclair,581,France,Male,37,7,0,2,1,1,74320.75,0 +4875,15764537,Dominguez,703,France,Male,43,8,0,2,1,0,9704.66,0 +4876,15619616,Costa,571,France,Female,33,9,102017.25,2,0,0,128600.49,0 +4877,15585133,Wei,657,Spain,Female,27,8,0,2,0,0,6468.24,0 +4878,15573971,Mills,737,France,Male,44,7,0,2,0,0,57898.58,0 +4879,15579433,Pugh,793,Spain,Male,29,8,96674.55,2,0,0,192120.66,0 +4880,15777045,Price,783,Spain,Female,44,3,81811.71,1,1,0,164213.53,1 +4881,15611580,Wood,751,Spain,Male,33,4,79281.61,1,1,0,117547.76,0 +4882,15614778,Robertson,579,France,Male,31,6,0,2,1,0,26149.25,0 +4883,15771750,Sawtell,655,Germany,Female,36,10,122314.39,1,1,0,9181.66,0 +4884,15593280,Yuryeva,614,Germany,Male,43,8,140733.74,1,1,1,166588.76,0 +4885,15569274,Pisano,678,Germany,Male,49,2,116933.11,1,1,0,195053.58,1 +4886,15654408,Kharitonova,562,Spain,Male,41,5,165445.04,2,1,0,85787.31,0 +4887,15657468,Simmons,711,Germany,Female,53,5,123805.03,1,1,0,102428.51,0 +4888,15614213,Muramats,620,France,Male,37,0,107548.94,1,1,0,71175.94,0 +4889,15589869,Tang,437,France,Male,49,9,111634.29,2,0,1,166440.32,0 +4890,15693205,Peng,691,Germany,Female,41,8,109153.96,3,1,1,148848.76,1 +4891,15797113,Bevan,552,Spain,Female,34,4,0,2,1,0,140286.69,0 +4892,15676958,Zito,765,Germany,Male,34,5,86055.17,2,1,1,104220.5,0 +4893,15739592,Sokolov,707,Germany,Female,51,10,98438.23,1,0,0,70778.63,1 +4894,15656263,Teng,764,Spain,Male,29,5,0,2,1,0,65868.28,0 +4895,15636872,Amadi,585,France,Female,32,8,144705.87,2,0,0,171482.56,0 +4896,15589435,Davide,784,France,Male,31,7,0,2,1,1,143204.41,0 +4897,15640464,Parkes,605,France,Male,41,5,91612.91,1,1,1,28427.84,0 +4898,15723851,Mazzanti,699,Spain,Male,40,2,0,1,1,0,78387.32,0 +4899,15722122,Findlay,544,France,Female,40,7,0,1,0,1,161076.92,0 +4900,15696852,Hsu,803,France,Female,32,9,192122.84,1,1,1,54277.45,1 +4901,15634936,Chukwukadibia,735,France,Male,41,7,179904,1,1,1,137180.95,0 +4902,15575935,Baxter,673,France,Male,59,0,178058.06,2,0,1,21063.71,1 +4903,15634491,Kung,652,France,Male,30,2,176166.56,2,1,1,152210.81,0 +4904,15628530,Booth,694,France,Male,42,3,156864.2,2,0,0,88890.75,0 +4905,15678720,Evans,741,France,Female,44,7,0,2,1,1,190534.76,0 +4906,15627999,Kung,590,Spain,Male,30,3,0,2,1,0,83090.35,0 +4907,15571244,Tung,809,Spain,Female,33,3,0,2,0,1,141426.78,0 +4908,15739931,Yuan,523,France,Male,34,2,161588.89,1,1,1,51358.66,0 +4909,15806256,Jackson,540,France,Male,48,2,109349.29,1,1,0,88703.04,1 +4910,15787258,Ross,596,Spain,Female,29,6,0,2,1,0,116696.77,0 +4911,15706463,Yang,597,France,Female,36,9,0,2,1,1,7156.09,0 +4912,15691004,Yu,407,Spain,Male,37,1,0,1,1,1,49161.12,1 +4913,15792228,Onwumelu,748,France,Male,60,0,152335.7,1,1,0,126743.33,1 +4914,15733447,Gay,562,France,Female,51,1,124662.54,1,1,1,65390.46,1 +4915,15679062,Morrison,734,Germany,Female,47,10,91522.04,2,1,1,138835.91,0 +4916,15594409,Belov,710,France,Male,45,1,0,2,1,1,36154.66,0 +4917,15613816,Mao,539,Spain,Female,39,6,62052.28,1,0,1,59755.14,0 +4918,15681991,Walsh,542,France,Male,32,7,107871.72,1,1,0,125302.64,0 +4919,15796074,Bruno,717,France,Female,36,2,99472.76,2,1,0,94274.72,1 +4920,15625941,Gray,682,Spain,Female,50,10,128039.01,1,1,1,102260.16,0 +4921,15615016,Maurer,515,France,Male,33,2,0,2,1,1,136028.97,0 +4922,15748414,Chiang,526,Spain,Female,33,8,114634.63,2,1,0,110114.38,1 +4923,15751203,Cattaneo,702,France,Male,26,5,56738.47,2,1,1,100442.22,1 +4924,15662658,Grieve,651,Germany,Male,34,2,90355.12,2,0,0,193597.94,0 +4925,15574868,Lowell,792,Germany,Male,36,5,115725.24,2,0,0,1871.25,0 +4926,15790282,Trentino,817,Germany,Male,58,3,114327.59,2,1,1,42831.11,0 +4927,15762927,Sung,674,Germany,Female,36,6,100762.64,1,1,0,182156.86,0 +4928,15803456,Yen,641,France,Female,40,9,0,1,0,0,151648.66,1 +4929,15771857,Philipp,513,Spain,Male,39,7,89039.9,2,1,1,146738.83,0 +4930,15700601,Dynon,561,France,Male,34,1,78829.53,1,1,1,12148.2,0 +4931,15569670,Alexeyeva,627,Germany,Male,30,6,112372.96,1,1,1,118029.09,0 +4932,15772341,Hs?eh,682,Germany,Male,81,6,122029.15,1,1,1,50783.88,0 +4933,15661548,Ferri,683,France,Female,29,0,157829.12,1,0,0,129891.66,0 +4934,15787597,Hsu,420,Germany,Female,31,1,108377.75,2,1,1,9904.63,0 +4935,15806913,Bishop,670,France,Female,54,2,95507.12,1,1,1,63213.31,0 +4936,15804862,Toscani,505,Germany,Male,43,6,127146.68,1,0,0,137565.87,0 +4937,15792986,T'ao,580,Germany,Male,24,1,133811.78,1,1,0,17185.95,1 +4938,15625632,Philip,577,France,Male,36,3,121092.47,2,0,1,143783.46,0 +4939,15727703,Li Fonti,773,Germany,Male,34,10,126979.75,1,0,0,36823.28,0 +4940,15606273,Rene,616,France,Male,37,5,144235.73,2,0,0,154957.66,1 +4941,15799652,Daigle,763,France,Female,38,0,152582.2,2,0,0,31892.82,0 +4942,15715047,Joshua,640,Spain,Male,43,9,172478.15,1,1,0,191084.4,1 +4943,15784687,Simmons,592,France,Male,36,1,126477.42,1,0,0,179718.17,0 +4944,15615322,Jamieson,528,Spain,Male,43,7,97473.87,2,1,1,159823.16,0 +4945,15722072,Hou,630,France,Male,53,5,138053.67,1,0,1,114110.97,0 +4946,15646784,Cochran,529,France,Female,31,2,164003.05,2,1,1,60993.23,0 +4947,15644692,Bibb,546,France,Female,47,8,0,1,1,1,66408.01,1 +4948,15670354,Jen,753,France,Female,62,6,0,2,1,1,136398.9,0 +4949,15716357,Corran,772,Spain,Female,39,4,122486.11,2,1,1,140709.25,0 +4950,15786717,He,567,France,Male,36,1,0,2,0,0,8555.73,0 +4951,15771383,Loggia,628,Germany,Female,45,6,53667.44,1,1,0,115022.94,0 +4952,15649793,Lovely,658,France,Male,20,7,0,2,0,0,187638.34,0 +4953,15731543,Becker,679,Spain,Male,58,9,109327.65,1,1,1,3829.13,0 +4954,15684516,Plascencia,629,Spain,Male,34,1,121151.05,1,0,0,119357.93,0 +4955,15677249,Somadina,731,Spain,Male,42,9,101043.63,1,1,1,192175.52,0 +4956,15581525,Walker,775,Germany,Male,33,3,83501.66,2,1,0,128841.31,0 +4957,15628420,Alekseeva,660,Spain,Male,33,2,80462.24,1,0,0,150422.35,0 +4958,15600478,Watson,752,France,Male,39,3,0,1,1,0,188187.05,0 +4959,15594502,Zotov,655,France,Male,37,6,109093.41,2,1,0,1775.52,0 +4960,15784361,Williamson,543,Spain,Female,46,5,140355.6,1,1,1,85086.78,0 +4961,15767626,Carpenter,811,France,Male,42,10,0,2,1,1,3797.79,0 +4962,15632521,Cattaneo,689,Germany,Male,45,0,130170.82,2,1,0,150856.38,0 +4963,15665088,Gordon,531,France,Female,42,2,0,2,0,1,90537.47,0 +4964,15652084,Boni,515,France,Male,40,0,109542.29,1,1,1,166370.81,0 +4965,15574761,Lynch,466,France,Female,41,3,33563.95,2,1,0,178994.13,1 +4966,15729515,McCarthy,782,France,Male,36,1,148795.17,2,1,1,195681.43,0 +4967,15682070,Davies,611,France,Male,64,9,0,2,1,1,53277.15,0 +4968,15743817,Hargreaves,621,Germany,Male,40,8,174126.75,3,1,0,172490.78,1 +4969,15572158,Blackburn,604,Spain,Male,41,3,0,1,0,0,11819.84,0 +4970,15584477,K?,655,Spain,Female,35,1,106405.03,1,1,1,82900.25,0 +4971,15614893,Meng,689,Spain,Male,38,2,0,1,1,1,82709.8,0 +4972,15665963,Cattaneo,681,Spain,Male,30,2,128393.29,1,1,1,180593.45,0 +4973,15612524,Hunt,643,Germany,Male,41,2,127841.52,1,1,0,172363.41,0 +4974,15596962,Owens,617,France,Female,24,4,137295.19,2,1,1,91195.12,0 +4975,15744942,Steele,638,Spain,Female,55,2,155828.22,1,0,1,108987.25,1 +4976,15573278,Kennedy,743,France,Male,39,6,0,2,1,0,44265.28,0 +4977,15717056,Pan,828,Germany,Female,25,7,144351.86,1,1,0,116613.26,0 +4978,15795881,Alexander,776,Spain,Male,35,8,106365.29,1,1,1,148527.56,0 +4979,15758939,Bray,540,Germany,Male,35,7,127801.88,1,0,1,84239.46,0 +4980,15792250,Nnabuife,616,Germany,Female,45,4,122793.96,1,1,1,62002.04,0 +4981,15740406,Padovesi,628,Germany,Male,38,10,113525.84,1,1,0,46044.48,1 +4982,15768137,Bray,667,Spain,Female,23,6,136100.69,2,0,0,169669.33,1 +4983,15569120,Lucas,615,France,Male,30,7,0,2,1,1,156346.84,0 +4984,15723721,Tinline,543,France,Male,30,4,140916.81,1,1,0,157711.18,0 +4985,15777122,Esomchi,553,France,Female,31,4,0,2,1,1,89087.4,0 +4986,15742681,Liao,554,Germany,Male,26,4,121365.39,1,1,1,8742.36,0 +4987,15582090,Iroawuchi,684,Spain,Female,36,4,0,1,1,0,117038.96,0 +4988,15711254,Retana,452,France,Female,35,7,0,2,1,0,164241.67,0 +4989,15775067,Fang,606,France,Male,47,3,93578.68,2,0,1,137720.56,1 +4990,15602851,Ozioma,629,France,Male,40,9,0,1,1,0,106.67,0 +4991,15802857,Robson,659,Spain,Female,33,8,115409.6,1,0,1,1539.21,0 +4992,15701175,Bruno,493,France,Female,33,8,90791.69,1,1,1,59659.53,0 +4993,15783019,Price,794,France,Female,62,9,123681.32,3,1,0,173586.63,1 +4994,15728912,Swanson,554,France,Female,44,6,92436.86,1,1,0,126033.9,0 +4995,15585580,Chang,796,Germany,Female,52,9,167194.36,1,1,1,62808.93,1 +4996,15583480,Morgan,807,France,Female,36,4,0,2,0,1,147007.33,0 +4997,15620341,Nwebube,500,Germany,Male,44,9,160838.13,2,1,0,196261.64,0 +4998,15613886,Trevisan,722,Spain,Male,43,1,0,1,1,0,44560.17,1 +4999,15792916,Ositadimma,559,Spain,Female,40,7,144470.77,1,1,1,18917.95,0 +5000,15710408,Cunningham,584,Spain,Female,38,3,0,2,1,1,4525.4,0 +5001,15598695,Fields,834,Germany,Female,68,9,130169.27,2,0,1,93112.2,0 +5002,15649354,Johnston,754,Spain,Male,35,4,0,2,1,1,9658.41,0 +5003,15737556,Vasilyev,590,France,Male,43,7,81076.8,2,1,1,182627.25,1 +5004,15671610,Hooper,740,France,Male,36,7,0,1,1,1,13177.4,0 +5005,15625092,Colombo,502,Germany,Female,57,3,101465.31,1,1,0,43568.31,1 +5006,15741032,Tsao,733,France,Male,48,5,0,1,0,1,117830.57,0 +5007,15750014,Chikere,755,Germany,Female,37,0,113865.23,2,1,1,117396.25,0 +5008,15784761,Ballard,554,Spain,Female,46,7,87603.35,3,0,1,96929.24,1 +5009,15768359,Akhtar,534,France,Male,36,4,120037.96,1,1,0,36275.94,0 +5010,15805769,O'Loughlin,656,Spain,Male,33,4,0,2,1,0,116706,0 +5011,15719508,Davis,575,Germany,Male,49,7,121205.15,4,1,1,168080.53,1 +5012,15609011,Barry,480,Spain,Male,47,8,75408.33,1,1,0,25887.89,1 +5013,15703106,K'ung,575,France,Male,40,5,0,2,1,1,122488.59,0 +5014,15626795,Gorman,672,France,Female,40,3,0,1,1,0,113171.61,1 +5015,15773731,John,758,Spain,Female,35,5,0,2,0,0,100365.51,0 +5016,15756196,Tsou,682,France,Male,50,6,121818.84,2,0,1,124151.37,0 +5017,15687903,Okonkwo,501,France,Female,29,8,0,2,1,0,112664.24,0 +5018,15777599,Esposito,746,Germany,Male,34,6,141806,2,1,1,183494.87,0 +5019,15754577,Boni,556,France,Female,51,8,61354.14,1,1,0,198810.65,1 +5020,15584113,Pratt,823,Germany,Female,53,4,124954.94,1,0,1,131259.6,1 +5021,15669589,Page,491,Germany,Female,68,1,95039.12,1,0,1,116471.14,1 +5022,15632793,Wilkinson,638,France,Female,29,9,103417.74,1,1,1,15336.4,0 +5023,15711130,Tseng,734,France,Male,45,2,0,2,1,0,99593.28,0 +5024,15615254,Clark,555,France,Male,40,10,43028.77,1,1,0,170514.21,0 +5025,15720583,Finch,745,Germany,Female,44,0,119638.21,1,1,1,34265.08,1 +5026,15780432,Shen,728,France,Male,37,3,122689.51,2,0,0,106977.53,1 +5027,15673223,Hou,626,France,Male,44,10,0,2,0,0,164287.86,0 +5028,15807989,Wall,681,Germany,Male,37,8,73179.34,2,1,1,25292.53,0 +5029,15761168,Manna,478,France,Female,38,4,171913.87,1,1,0,51820.87,1 +5030,15651272,Reyes,709,France,Male,38,5,0,2,1,1,81452.29,0 +5031,15812832,Jideofor,562,Germany,Male,33,8,92659.2,2,1,0,1354.25,0 +5032,15680517,Sal,769,Germany,Female,34,7,137239.17,1,1,1,71379.92,1 +5033,15750569,Iweobiegbunam,684,Germany,Female,46,3,102955.14,2,1,0,154137.33,0 +5034,15690743,Shao,536,France,Female,61,8,65190.29,1,1,1,64308.49,1 +5035,15627741,Heath,631,Germany,Female,29,2,96863.52,2,1,1,31613.35,0 +5036,15712121,Chidimma,657,Spain,Male,34,5,154983.98,1,1,0,27738.01,0 +5037,15805429,Murray,699,Germany,Male,59,3,106819.65,1,0,1,163570.25,0 +5038,15814923,Sullivan,606,Spain,Male,38,7,128578.52,1,1,1,193878.51,0 +5039,15589230,Wu,612,France,Female,63,2,126473.33,1,0,1,147545.65,0 +5040,15775490,Downie,660,France,Female,38,5,110570.78,2,1,0,195906.59,0 +5041,15749727,Chukwufumnanya,829,Spain,Male,50,7,0,2,0,1,178458.86,0 +5042,15619238,Allan,567,Spain,Male,29,8,0,2,1,0,156125.72,0 +5043,15593468,Findlay,850,France,Female,33,3,0,2,1,1,11159.19,0 +5044,15718454,Ch'eng,712,Spain,Female,44,2,0,2,0,0,45738.94,0 +5045,15789498,Miller,562,France,Male,30,3,111099.79,2,0,0,140650.19,0 +5046,15744691,Tsai,755,France,Female,29,3,0,3,1,0,4733.94,0 +5047,15708289,Graham,793,Spain,Male,25,3,100913.57,1,0,0,10579.72,0 +5048,15790412,Norton,471,Spain,Male,26,8,0,2,1,1,179655.87,0 +5049,15741416,Yegorov,707,France,Male,42,2,16893.59,1,1,1,77502.56,0 +5050,15598894,Holt,784,Spain,Male,38,10,122267.85,1,0,0,145759.93,0 +5051,15663294,Kao,703,France,Male,32,1,125685.79,1,1,1,56246.72,0 +5052,15572728,Ross,704,Spain,Male,36,8,127397.34,1,1,0,151335.24,0 +5053,15706729,Hsiao,662,France,Male,38,0,105271.56,1,0,1,179833.45,0 +5054,15674433,Allan,636,Germany,Female,28,2,115265.14,1,0,0,191627.85,0 +5055,15641170,Liang,640,Spain,Male,36,4,0,1,0,0,173016.46,0 +5056,15806284,Briggs,739,Spain,Male,31,1,0,2,1,1,58469.75,0 +5057,15690958,Cantrell,767,Germany,Male,23,2,139542.82,1,0,1,28038.28,0 +5058,15606386,Wang,753,Germany,Female,46,3,111512.75,3,1,0,159576.75,1 +5059,15682322,Aksenov,714,France,Male,37,9,148466.93,2,0,1,151280.96,0 +5060,15579915,Glennon,707,France,Male,29,4,0,2,1,0,139953.94,0 +5061,15681928,Yancy,577,France,Female,35,4,108155.49,1,1,0,105407.79,0 +5062,15734005,Mazzi,633,France,Female,42,1,0,2,1,0,56865.62,0 +5063,15650432,Liu,849,Germany,Male,41,10,84622.13,1,1,1,198072.16,0 +5064,15592578,Nucci,614,Spain,Female,41,7,146997.64,2,0,0,137791.18,0 +5065,15671243,Y?,558,France,Female,47,9,0,2,1,0,103787.28,0 +5066,15775709,Nucci,832,France,Female,27,10,98590.25,1,1,0,30912.89,0 +5067,15702631,Tang,567,France,Female,26,2,0,2,1,1,78651.55,0 +5068,15602282,Kao,587,Germany,Female,45,8,134980.74,1,1,1,123309.57,1 +5069,15717879,Chen,712,Spain,Female,79,5,108078.56,1,1,1,174118.93,0 +5070,15740878,Yao,655,Spain,Female,29,9,0,2,0,1,85736.26,0 +5071,15794468,Tsou,641,France,Female,42,6,0,2,0,0,121138.77,0 +5072,15773277,Barnes,676,France,Male,35,5,106836.67,2,1,0,84199.78,0 +5073,15572657,H?,472,France,Male,29,8,102490.27,1,0,1,181224.56,0 +5074,15800295,Cruz,644,Germany,Male,34,9,112746.54,2,0,0,141230.07,0 +5075,15672397,Smith,598,France,Male,38,0,125487.89,1,0,0,158111.71,0 +5076,15684921,Onuchukwu,792,Spain,Male,25,8,142862.21,1,1,1,130639.01,0 +5077,15720676,Bukowski,700,France,Female,37,7,0,2,1,0,17040.82,0 +5078,15731829,Simmons,616,France,Male,34,10,0,2,1,0,25662.27,0 +5079,15732672,Stewart,743,Spain,Male,35,6,79388.33,1,1,1,193360.69,0 +5080,15692406,Gow,427,France,Male,37,5,0,2,1,1,121485.1,0 +5081,15764405,Williams,731,France,Male,29,10,0,2,1,1,162452.65,0 +5082,15757537,Francis,610,France,Female,31,6,107784.65,1,1,1,141137.53,0 +5083,15793307,Calabresi,724,Spain,Female,41,4,142880.28,3,0,0,185541.2,1 +5084,15660679,Chimaobim,653,Spain,Female,38,9,149571.94,1,1,0,118383.18,0 +5085,15666856,Chikwendu,774,France,Male,49,1,142767.39,1,1,1,8214.41,0 +5086,15687372,Padovesi,547,Germany,Male,49,8,121537.71,2,1,0,46521.45,1 +5087,15667289,Henderson,719,Spain,Male,50,2,0,2,0,0,10772.13,0 +5088,15624641,Kharlamova,740,Spain,Male,43,9,0,1,1,0,199290.68,1 +5089,15734610,Onio,543,France,Male,42,4,89838.71,3,1,0,85983.54,1 +5090,15631882,Yeh,688,Germany,Male,45,9,103399.87,1,0,0,129870.93,0 +5091,15642709,Feng,474,France,Female,30,9,0,2,0,0,63158.22,0 +5092,15811026,Norman,505,Germany,Male,43,5,136855.94,2,1,0,171070.52,0 +5093,15596303,White,688,France,Female,39,0,0,2,1,0,53222.15,1 +5094,15787255,Manfrin,650,Germany,Female,55,2,140891.46,3,1,1,179834.45,1 +5095,15617166,Ritchie,610,France,Male,37,0,0,1,1,0,114514.64,0 +5096,15742442,Udegbulam,705,Spain,Female,46,5,89364.91,1,0,1,139162.15,0 +5097,15758692,Kao,669,France,Female,29,7,146011.4,1,0,0,50249.16,0 +5098,15568238,Diaz,650,Spain,Male,20,8,0,2,1,1,113469.65,0 +5099,15730353,Olisaemeka,550,Germany,Male,29,9,145294.08,2,1,0,147484.13,0 +5100,15731555,Ross-Watt,595,Germany,Female,45,9,106000.12,1,0,0,191448.96,1 +5101,15582404,Miller,572,Spain,Female,26,5,0,2,1,0,119381.41,0 +5102,15721462,Shubin,622,Spain,Female,58,2,0,2,1,1,33277.31,0 +5103,15632899,Nwankwo,662,Spain,Male,20,9,104508.77,2,0,0,73107.53,0 +5104,15808526,Cartwright,783,Germany,Female,58,3,127539.3,1,1,1,96590.39,1 +5105,15694349,Ngozichukwuka,714,Spain,Male,44,7,0,1,0,1,6923.11,0 +5106,15718465,Sadler,671,Germany,Male,51,3,96891.46,1,1,0,176403.33,1 +5107,15682995,Azuka,600,France,Female,32,1,78535.25,1,1,0,64349.6,0 +5108,15584776,Shen,847,Spain,Female,37,9,112712.17,1,1,0,116097.26,0 +5109,15777772,Whittaker,650,Spain,Male,55,9,119618.42,1,1,1,29861.13,0 +5110,15576156,Abazu,710,Spain,Female,28,6,0,1,1,0,48426.98,0 +5111,15646756,Murphy,682,France,Female,33,8,74963.5,1,1,1,32770.56,0 +5112,15742886,Ford,642,France,Male,26,1,138023.79,2,0,1,117060.2,0 +5113,15586135,Gratwick,536,Spain,Female,28,4,0,1,1,1,136197.65,0 +5114,15616152,Pai,754,France,Female,47,1,185513.67,1,1,0,27438.83,0 +5115,15721460,Lorenzo,678,France,Male,60,8,185648.56,1,0,0,192156.54,1 +5116,15727317,Brady,533,Germany,Female,49,1,102286.6,3,1,0,69409.37,1 +5117,15649536,Wong,741,Germany,Male,38,4,128015.83,1,1,0,58440.43,0 +5118,15754929,Douglas,757,France,Male,31,10,39539.39,2,0,0,192519.39,0 +5119,15572051,Kennedy,721,France,Male,40,3,0,1,1,1,144874.67,0 +5120,15668142,Chang,700,France,Male,37,3,77608.46,2,1,1,175373.46,0 +5121,15701176,Brown,663,France,Male,26,5,141462.13,1,1,0,440.2,0 +5122,15708422,Hsiung,677,Spain,Female,35,0,0,2,0,0,76637.38,0 +5123,15655632,MacDonald,655,France,Male,27,2,131691.33,1,1,0,49480.66,0 +5124,15744606,Davidson,832,Spain,Male,29,8,93833.86,1,0,1,10417.87,0 +5125,15612140,Milano,721,Spain,Female,46,7,137933.39,1,1,1,67976.57,0 +5126,15656086,Bovee,542,Spain,Male,54,8,105770.14,1,0,1,140929.98,1 +5127,15655298,Lewis,654,Spain,Female,54,5,0,2,0,1,47139.06,0 +5128,15644796,Dyer,821,Spain,Female,38,8,0,2,0,1,126241.4,1 +5129,15726250,Hsia,508,France,Female,38,3,166328.65,2,0,1,22614.19,0 +5130,15764432,Hicks,588,Germany,Female,42,2,164307.77,1,1,0,48498.19,0 +5131,15631721,Millar,691,Germany,Male,38,9,163965.69,2,0,1,103511.26,0 +5132,15707479,Fan,664,France,Male,40,7,125608.72,1,1,0,122073.48,0 +5133,15579826,Young,439,France,Female,66,9,0,1,1,0,65535.56,0 +5134,15668104,Kerr,479,Spain,Male,37,6,118433.94,1,0,1,160060.9,0 +5135,15641604,Frolova,850,France,Female,55,10,98488.08,1,1,0,155879.57,1 +5136,15587240,Vasilyev,518,France,Male,40,4,0,2,0,1,194416.58,0 +5137,15680767,Sabbatini,717,Germany,Female,64,10,98362.35,2,1,1,21630.21,0 +5138,15601594,Ifeanacho,698,France,Female,51,6,144237.91,4,1,0,157143.61,1 +5139,15589969,Capon,850,France,Male,34,6,0,1,0,1,52796.31,0 +5140,15703728,Chieloka,700,Spain,Male,47,4,0,1,1,0,121798.52,1 +5141,15617790,Hanson,626,France,Female,29,4,105767.28,2,0,0,41104.82,0 +5142,15662500,Ts'ao,774,Spain,Male,32,9,0,2,1,0,10604.48,0 +5143,15778526,Bradshaw,719,Spain,Female,48,5,0,2,0,0,78563.66,0 +5144,15670584,Nkemakolam,646,Spain,Male,31,2,0,1,1,1,170821.43,1 +5145,15748069,Clunie,485,France,Female,25,3,134467.26,1,1,1,113266.09,0 +5146,15680597,Cover,784,Germany,Male,38,1,138515.02,1,1,1,171768.76,0 +5147,15628992,Esposito,850,Germany,Male,32,2,128647.98,2,0,0,54416.18,0 +5148,15719624,Hodgson,669,France,Female,38,9,121858.98,1,1,0,130755.34,0 +5149,15812767,Harvey,731,Spain,Male,70,3,0,2,1,1,141180.66,0 +5150,15689201,Dobie,721,France,Female,49,1,120108.56,1,0,1,183421.76,0 +5151,15614716,Okwudilichukwu,515,France,Female,37,0,196853.62,1,1,1,132770.11,0 +5152,15683618,Dyer,774,France,Female,35,3,121418.62,1,1,1,24400.37,0 +5153,15799631,Chase,585,Spain,Male,36,10,0,2,1,1,180318.6,0 +5154,15692259,Baresi,695,France,Female,29,9,0,2,1,0,111565.45,0 +5155,15590966,Lo,729,Germany,Female,42,4,97495.8,2,0,0,2002.5,0 +5156,15656426,Tyler,713,France,Female,42,3,0,2,0,0,82565.01,0 +5157,15675256,Ts'ui,555,Spain,Male,33,5,127343.4,1,0,1,121789.3,0 +5158,15751185,Aparicio,699,Spain,Female,50,0,158633.61,1,1,0,193785.87,0 +5159,15789582,Macleod,587,France,Male,55,9,0,1,1,0,64593.07,0 +5160,15651103,Sal,762,Spain,Female,69,9,183744.98,1,1,1,196993.69,0 +5161,15672299,Yeh,510,France,Male,44,6,0,2,1,1,175518.31,0 +5162,15772250,Udegbunam,842,Spain,Male,46,9,0,1,0,0,17268.02,0 +5163,15763922,Alexandrov,608,France,Male,31,7,79962.92,2,1,0,60901.72,0 +5164,15633870,Ozioma,850,France,Female,36,10,0,2,1,1,100750.03,0 +5165,15624323,Atkins,642,France,Male,36,4,0,2,1,1,195224.91,0 +5166,15688612,Campos,850,France,Male,33,7,140956.99,1,0,0,3510.18,0 +5167,15694644,Wood,455,Spain,Female,43,6,0,1,1,1,81250.79,0 +5168,15587174,Kerr,726,France,Male,29,7,0,2,1,1,91844.14,1 +5169,15579559,Chienezie,544,Spain,Male,30,8,145241.63,1,1,1,80676.83,0 +5170,15775430,Tsou,651,Germany,Male,31,7,138008.06,2,1,0,129912.74,0 +5171,15623695,McKinnon,814,France,Female,31,4,0,2,1,1,142029.17,0 +5172,15760849,Nwachukwu,537,France,Male,39,2,0,2,1,1,137651.6,0 +5173,15813095,Nwebube,553,France,Male,37,2,0,2,1,0,33877.29,0 +5174,15705281,Burt,800,Spain,Male,38,9,0,1,1,0,78744.39,0 +5175,15812594,Ross,791,France,Male,34,7,0,2,1,0,96734.46,0 +5176,15626322,Lees,699,Spain,Female,29,9,127570.93,2,1,0,164756.81,0 +5177,15723105,Feetham,756,France,Female,28,6,0,1,1,1,164394.65,0 +5178,15588449,Chuang,591,Spain,Female,27,5,107812.67,1,0,1,162501.83,1 +5179,15794849,Aitken,850,Germany,Male,22,7,91560.58,2,0,0,10541.38,0 +5180,15620000,Chambers,760,Germany,Male,34,6,121303.77,2,1,1,59325.21,0 +5181,15799720,Coburn,569,Spain,Male,43,8,161546.68,2,0,1,178187.28,0 +5182,15711287,Ahmed,661,Spain,Female,35,5,128415.45,1,1,0,142626.49,0 +5183,15613102,Ogochukwu,670,France,Female,31,2,57530.06,1,1,1,181893.31,1 +5184,15621440,Soto,694,France,Male,38,1,0,2,0,1,156858.2,0 +5185,15677146,Obiajulu,728,France,Female,28,4,142243.54,2,1,0,33074.51,0 +5186,15801169,Yegorova,764,Germany,Female,39,9,138341.51,1,1,0,50072.94,1 +5187,15722425,Lucchese,639,France,Male,32,9,0,2,1,0,111340.36,0 +5188,15682421,Talbot,683,France,Female,30,2,0,2,0,1,100496.84,1 +5189,15691910,Lu,663,Spain,Male,30,4,0,3,1,0,101371.05,0 +5190,15721779,Arnold,826,Spain,Male,41,5,146466.46,2,0,0,180934.67,0 +5191,15579548,Nicholson,735,Spain,Male,36,5,0,2,1,0,105152.17,0 +5192,15681075,Chukwualuka,682,France,Female,58,1,0,1,1,1,706.5,0 +5193,15607884,Wallace,663,France,Female,39,8,0,2,1,1,101168.9,0 +5194,15767757,Pisano,562,Spain,Female,29,9,120307.58,1,1,1,6795.61,0 +5195,15791550,Kelly,696,France,Male,27,4,87637.26,2,0,0,196111.35,0 +5196,15658589,Brady,850,Spain,Male,38,2,94652.04,1,1,1,171960.76,0 +5197,15670822,Palmer,719,France,Female,22,7,114415.84,1,1,1,177497.4,0 +5198,15629744,Tan,804,France,Female,71,8,0,2,0,1,147995.96,0 +5199,15660768,L?,604,France,Male,40,1,84315.02,1,0,0,36209.1,0 +5200,15726310,Mordvinova,782,Spain,Female,27,3,0,2,1,0,143614.01,0 +5201,15641298,Corones,512,Germany,Male,42,9,93955.83,2,1,0,14828.54,0 +5202,15625675,Clements,569,France,Male,36,1,67087.69,1,1,0,154775.7,0 +5203,15713354,Morrice,597,Germany,Female,22,6,101528.61,1,1,0,70529,1 +5204,15633866,Hsiung,753,Germany,Male,30,1,110824.52,1,1,1,57896.27,0 +5205,15704231,Barrett,430,France,Female,33,8,0,1,1,1,69759.91,0 +5206,15735400,Kanayochukwu,756,France,Male,28,8,179960.2,1,1,0,89938.08,0 +5207,15632826,Tardent,493,France,Male,38,3,134006.77,1,1,0,89578.32,0 +5208,15751022,Bowhay,777,Germany,Female,37,10,121532.17,2,1,1,73464.88,0 +5209,15664737,Lei,779,Spain,Female,38,7,0,2,1,1,138542.87,0 +5210,15681126,Baker,702,Spain,Female,38,2,0,1,1,1,161888.63,0 +5211,15738954,Pisano,551,France,Male,35,7,129717.3,2,0,0,86937.2,0 +5212,15662263,Castillo,749,Germany,Male,22,4,94762.16,2,1,1,42241.54,0 +5213,15621611,Gibson,742,Germany,Male,55,5,155196.17,1,0,1,121207.66,1 +5214,15783752,Lindsay,752,Germany,Male,29,4,129514.99,1,1,1,102930.46,0 +5215,15709474,Macnamara,740,Germany,Female,57,3,113386.36,2,1,1,65121.63,1 +5216,15701280,Romano,576,France,Male,24,3,0,1,0,1,78498.04,1 +5217,15671104,Aksakova,637,Spain,Male,43,3,172196.23,1,1,1,104769.96,0 +5218,15796434,Farnsworth,724,France,Male,28,5,97612.12,1,1,1,96498.14,0 +5219,15781505,Giordano,685,France,Male,20,4,104719.94,2,1,0,38691.34,0 +5220,15625819,Arnold,625,France,Female,38,7,0,1,1,0,164804.02,0 +5221,15753174,Thompson,571,Germany,Male,37,9,139592.98,3,1,0,104152.65,1 +5222,15654067,Koch,584,Spain,Female,29,4,0,2,1,0,88866.92,0 +5223,15724719,Jones,550,France,Female,22,7,139096.85,1,1,0,129890.94,0 +5224,15624695,Otitodilinna,662,Spain,Female,72,7,140301.72,1,0,1,179258.67,0 +5225,15718216,Fleetwood-Smith,803,Spain,Male,43,3,0,1,1,0,72051.44,0 +5226,15586300,Chinonyelum,615,France,Male,66,7,0,2,1,1,74580.8,0 +5227,15783349,Montague,481,Spain,Male,39,1,111233.09,1,1,1,123995.15,0 +5228,15725767,Milani,701,France,Male,23,3,0,2,1,0,38960.59,0 +5229,15791925,Palermo,751,France,Male,29,10,147737.63,1,0,1,94951.27,0 +5230,15793585,Anderson,675,France,Male,35,8,0,2,1,1,56642.97,0 +5231,15576641,Crawford,733,Germany,Male,40,5,125725.02,2,1,1,50783.1,0 +5232,15749519,Lin,822,France,Male,38,6,128289.7,3,1,0,9149.96,1 +5233,15684960,Yewen,559,France,Female,46,5,0,1,1,0,21006.1,1 +5234,15591286,Simmons,731,Germany,Female,49,4,88826.07,1,1,1,33759.41,1 +5235,15668323,Mbadiwe,678,France,Female,41,1,143443.61,1,1,0,196622.28,1 +5236,15608528,Munro,645,France,Female,68,9,0,4,1,1,176353.87,1 +5237,15645184,Graham,701,France,Male,29,2,0,2,1,0,176943.59,0 +5238,15702566,Lombardo,554,Spain,Male,26,8,149134.46,1,1,1,177966.24,0 +5239,15660840,Kalinin,723,France,Male,30,3,124119.54,1,1,0,162198.32,0 +5240,15750811,Woodward,766,Germany,Male,44,3,116822.7,1,0,0,197643.24,0 +5241,15733842,Pirozzi,597,France,Female,24,1,103219.47,1,1,0,60420.07,0 +5242,15581526,Iweobiegbulam,574,France,Male,41,1,0,2,0,0,70550,0 +5243,15662751,Piazza,655,Germany,Female,40,0,81954.6,1,1,1,198798.44,1 +5244,15684319,Baranova,780,Germany,Female,37,10,95196.26,1,1,0,126310.39,1 +5245,15702190,Fan,672,Spain,Male,43,5,0,2,1,1,64515.5,0 +5246,15588517,Sun,717,France,Male,38,7,0,2,1,1,158580.05,0 +5247,15801863,Marino,521,France,Female,32,2,136555.01,2,1,1,129353.21,0 +5248,15584271,Donaldson,633,France,Male,59,5,0,1,1,1,137273.97,0 +5249,15700366,Burton,669,France,Male,39,3,119452.03,1,1,1,171575.54,0 +5250,15804038,Quinn,740,France,Male,44,9,0,1,0,1,96528,1 +5251,15720820,Sabbatini,462,Germany,Female,24,9,69881.09,2,0,1,64421.02,0 +5252,15743759,Brooks,619,France,Male,39,5,0,2,1,1,158444.61,0 +5253,15749947,Black,665,France,Female,44,7,0,2,1,1,66548.58,0 +5254,15670496,Schwartz,655,Spain,Female,27,9,0,2,0,0,108008.05,0 +5255,15746664,Ts'ui,463,Spain,Male,20,8,204223.03,1,1,0,128268.39,0 +5256,15745533,Sargent,799,France,Female,63,1,110314.21,2,1,0,37464,1 +5257,15761497,Udinesi,713,Spain,Female,48,1,163760.82,1,0,0,157381.14,1 +5258,15628600,Lee,807,Germany,Female,31,1,141069.18,3,1,1,194257.11,0 +5259,15627002,Taylor,728,France,Male,38,1,115934.74,1,1,1,139059.05,0 +5260,15614635,Kepley,582,France,Male,52,2,151457.88,1,0,1,40893.61,0 +5261,15731281,Ozuluonye,704,Germany,Female,35,3,154206.07,2,1,1,40261.49,0 +5262,15814022,Lassetter,714,France,Female,26,9,89928.99,1,1,0,46203.31,0 +5263,15659194,Mishina,628,France,Male,30,8,89182.09,1,1,1,13126.9,0 +5264,15745030,Trevisano,809,Germany,Male,41,1,79706.25,2,1,0,165675.01,0 +5265,15691817,Iloerika,547,Spain,Female,44,5,0,3,0,0,5459.07,1 +5266,15707488,Tan,560,France,Female,27,5,0,2,1,0,131919.48,0 +5267,15784700,Chikelu,811,France,Male,31,7,117799.28,1,1,1,182372.35,0 +5268,15710397,Lin,584,France,Male,26,4,0,2,1,0,147600.54,0 +5269,15687648,Nicholson,691,France,Male,28,1,0,2,0,0,92865.41,0 +5270,15732281,Ugoji,680,Germany,Male,34,6,146422.22,1,1,0,67142.97,1 +5271,15607230,Michel,588,Germany,Male,33,9,150186.22,2,1,1,65611.01,0 +5272,15567630,Bruce,721,Germany,Male,40,6,100275.88,1,1,0,138564.48,1 +5273,15587507,Feng,850,France,Male,47,6,0,1,1,0,187391.02,1 +5274,15733904,McDonald,529,France,Male,32,9,147493.89,1,1,0,33656.35,0 +5275,15709511,Watt,622,France,Male,43,8,0,2,1,0,100618.17,0 +5276,15579616,Goodwin,683,France,Female,42,8,0,2,0,1,198134.9,0 +5277,15694852,Arcuri,575,France,Male,29,4,121823.4,2,1,1,50368.87,0 +5278,15589924,Rapuluolisa,577,Spain,Female,40,1,0,2,1,1,108787,0 +5279,15799300,Kao,510,Germany,Male,31,0,113688.63,1,1,0,33099.41,1 +5280,15731330,Tsui,652,Spain,Female,40,7,100471.34,1,1,1,124550.88,0 +5281,15694129,Summers,569,Germany,Female,28,3,100032.52,1,1,0,5159.21,1 +5282,15620372,Cross,687,Spain,Male,31,3,0,2,0,0,48228.1,0 +5283,15744622,Osorio,822,France,Male,32,8,116358,1,1,0,108798.36,0 +5284,15799815,Bobrov,656,Germany,Female,23,4,163549.63,1,0,1,21085.12,0 +5285,15759250,Barnett,745,Germany,Male,51,3,99183.9,1,1,1,28922.25,0 +5286,15732643,Pike,386,Spain,Female,53,1,131955.07,1,1,1,62514.65,1 +5287,15690540,Gearheart,684,Spain,Female,41,1,134177.06,1,0,0,177506.66,0 +5288,15803078,Bruno,635,Spain,Female,38,1,0,2,1,0,90605.05,0 +5289,15652180,Egobudike,582,France,Male,30,2,0,2,1,1,132029.95,0 +5290,15741195,Okechukwu,613,Spain,Male,19,5,0,1,1,1,176903.35,0 +5291,15743490,Zikoranachidimma,795,Germany,Female,56,9,94348.94,1,1,0,29239.29,1 +5292,15575510,Milanesi,659,France,Female,32,2,155584.21,1,0,1,153662.88,0 +5293,15732610,Ahern,745,France,Female,28,6,0,2,1,0,154389.18,0 +5294,15602909,Dickson,604,Spain,Female,41,10,0,2,1,1,166224.39,0 +5295,15734058,Anayochukwu,509,Germany,Male,32,9,170661.47,1,1,1,21646.2,0 +5296,15801788,McDonald,706,Germany,Female,29,6,185544.36,1,1,0,171037.63,0 +5297,15702462,Fiorentini,619,Spain,Female,44,6,52831.13,1,1,1,112649.22,1 +5298,15683416,Russo,572,Germany,Male,51,8,97750.07,3,1,1,193014.26,1 +5299,15794187,Young,695,France,Male,36,6,114007.5,2,1,0,118120.88,0 +5300,15792989,Bianchi,543,France,Female,71,1,104308.77,1,1,1,25650.04,0 +5301,15613734,Fallaci,640,France,Female,33,6,84719.13,2,1,1,113048.79,0 +5302,15606177,Crawford,672,France,Male,39,2,0,2,1,0,87372.49,0 +5303,15636700,Marsh,701,France,Male,39,9,140236.98,1,0,1,146651.99,0 +5304,15645766,Kosisochukwu,634,Spain,Male,25,9,0,2,1,1,8227.91,0 +5305,15671345,Piccio,531,Spain,Female,42,6,75302.85,2,0,0,57034.35,0 +5306,15652469,Nevels,699,France,Male,27,1,0,2,1,0,93003.21,0 +5307,15749638,Kaodilinakachukwu,605,France,Female,51,9,104760.82,1,1,1,165574.54,1 +5308,15728706,Amaechi,534,France,Female,49,7,0,1,1,0,13566.48,1 +5309,15735439,P'an,449,Spain,Female,31,1,113693,1,0,0,82796.29,0 +5310,15778696,Ikemefuna,684,Spain,Female,36,5,174180.39,1,1,0,119830.08,0 +5311,15624744,Tai,622,Germany,Male,42,9,115766.26,1,0,0,72155.85,1 +5312,15584338,Winn,714,France,Female,40,0,0,2,1,0,62762.12,0 +5313,15726178,Hardy,712,Spain,Female,48,8,0,2,1,0,183235.33,0 +5314,15794939,Chiu,783,France,Female,72,5,121215.9,2,1,1,105206.48,0 +5315,15788068,Lopez,743,Germany,Male,45,10,144677.19,3,1,0,22512.44,1 +5316,15572956,Steen,683,France,Male,36,5,115350.63,1,1,1,122305.91,0 +5317,15780386,Ferri,654,Spain,Male,40,5,105683.63,1,1,0,173617.09,0 +5318,15791114,Yegorova,700,France,Male,37,1,135179.49,1,1,0,160670.37,0 +5319,15708046,Knowles,744,Spain,Male,31,0,117551.23,1,1,0,158958.9,0 +5320,15719779,May,645,Germany,Male,25,1,157404.02,2,1,0,93073.04,0 +5321,15591550,Bianchi,525,Spain,Male,36,3,77910.23,1,1,0,67238.01,0 +5322,15639368,Pipes,732,France,Male,25,0,110942.9,1,0,0,172576.56,0 +5323,15699830,Doherty,721,France,Female,40,7,0,2,1,1,122580.48,0 +5324,15569264,Yobanna,622,France,Male,32,5,179305.09,1,1,1,149043.78,0 +5325,15595158,Hsu,654,Germany,Male,31,5,150593.59,2,1,1,105218.45,0 +5326,15599126,Russell,529,France,Female,43,0,123815.86,1,1,1,78463.99,1 +5327,15650575,Payne,720,Spain,Female,59,6,0,2,1,1,160849.43,1 +5328,15641490,Windsor,850,Germany,Female,25,8,69385.17,2,1,0,87834.24,0 +5329,15680234,Bray,667,Germany,Male,27,2,138032.15,1,1,0,166317.71,0 +5330,15592230,Seleznyov,620,France,Male,41,3,0,2,1,1,137309.06,0 +5331,15626212,Wark,616,France,Male,29,9,0,1,1,1,166984.44,0 +5332,15700627,Y?,637,Germany,Female,46,2,143500.82,1,1,0,166996.46,1 +5333,15782641,Brown,710,Spain,Female,29,3,119670.18,1,1,0,188022.44,0 +5334,15784445,Huang,717,Spain,Male,33,1,99106.73,1,0,0,194467.23,0 +5335,15813681,Zito,786,Germany,Male,24,2,120135.55,2,1,1,125449.47,0 +5336,15596649,Bailey,651,France,Female,39,8,0,1,1,0,137452.57,0 +5337,15700460,Allnutt,530,France,Female,55,4,120905.03,1,0,1,123475.88,1 +5338,15724076,Christie,815,Spain,Female,57,5,0,3,0,0,38941.44,1 +5339,15784000,Pope,715,Germany,Female,34,9,102277.52,1,0,0,177852.57,1 +5340,15733966,Johnstone,496,Germany,Female,55,4,125292.53,1,1,1,31532.96,1 +5341,15612667,Bird,680,Spain,Male,42,0,0,1,1,0,136377.21,0 +5342,15654025,Jones,646,France,Female,51,4,101629.3,1,0,0,130541.1,0 +5343,15589431,Pedder,807,Germany,Male,47,1,171937.27,1,1,1,65636.92,0 +5344,15578238,Calabrese,727,France,Male,47,7,0,2,1,0,193305.35,0 +5345,15566269,Chialuka,787,France,Male,25,5,0,2,1,0,47307.9,0 +5346,15639217,McKenzie,806,France,Male,34,6,0,2,0,0,100809.99,0 +5347,15688644,Holloway,603,France,Male,31,1,129743.75,1,1,0,109145.2,0 +5348,15662426,Tang,649,Spain,Male,32,1,0,1,0,1,91167.19,1 +5349,15720511,Byrne,547,Germany,Male,41,3,151191.31,1,1,0,175295.89,1 +5350,15567246,Selwyn,684,Germany,Male,32,3,102630.13,2,1,1,127433.47,0 +5351,15647965,Genovese,477,France,Female,57,9,114023.64,2,1,1,71167.17,1 +5352,15679048,Koger,558,Germany,Male,41,2,124227.14,1,1,1,111184.67,0 +5353,15675749,Baranov,695,France,Female,23,1,0,2,1,1,141756.32,0 +5354,15782181,Greco,592,Spain,Male,35,6,80285.16,1,1,0,72678.75,1 +5355,15795738,Owens,789,France,Male,31,4,175477.15,1,1,1,172832.9,0 +5356,15773751,Y?,597,France,Female,29,1,132144.35,1,1,0,158086.33,0 +5357,15655436,Kendall,839,Germany,Male,47,2,136911.07,1,1,1,168184.62,1 +5358,15691396,Ko,405,Germany,Male,31,5,133299.67,2,1,1,72950.14,0 +5359,15796958,Tang,658,France,Male,39,7,0,2,1,0,48378.4,0 +5360,15801832,Lombardo,684,Germany,Male,42,1,117691,1,1,1,23135.65,1 +5361,15661349,Perkins,633,France,Male,35,10,0,2,1,0,65675.47,0 +5362,15719265,Feng,589,France,Male,46,9,0,2,1,0,170676.67,0 +5363,15779985,Lo,750,Germany,Female,37,1,133199.71,2,1,1,27366.77,0 +5364,15663410,Piccio,771,Spain,Male,51,5,135506.58,3,1,1,152479.64,1 +5365,15704144,Mazzanti,812,Germany,Male,33,2,127154.14,2,0,1,105383.49,0 +5366,15774104,Chukwualuka,539,Spain,Male,39,2,0,2,1,1,48189.94,0 +5367,15812230,Elliot,670,Germany,Female,42,5,49508.79,3,1,1,100324.01,0 +5368,15742848,Gratton,673,France,Male,41,5,0,1,1,1,65657.29,0 +5369,15745326,Carandini,538,France,Female,62,3,75051.49,1,0,0,17682.02,1 +5370,15674541,Robinson,575,Spain,Male,52,8,123925.23,1,0,0,111342.66,1 +5371,15728564,Lo,682,France,Male,41,6,0,2,0,1,134158.09,1 +5372,15580701,Ma,712,France,Male,33,3,153819.58,1,1,0,79176.09,1 +5373,15688973,Vinogradova,598,Spain,Female,39,5,0,2,1,1,83103.46,0 +5374,15709412,H?,776,Spain,Male,30,6,0,2,0,1,63908.86,0 +5375,15607753,Alexandrova,606,Spain,Female,23,10,70417.79,1,0,1,90896.04,0 +5376,15705352,Yang,686,Spain,Male,38,7,111484.88,1,1,1,76076.2,0 +5377,15602500,Maslova,850,Spain,Male,38,1,146343.98,1,0,1,103902.11,0 +5378,15672437,Buccho,642,France,Male,72,1,160541,2,1,1,142223.94,0 +5379,15720968,Young,606,Germany,Male,27,2,130274.26,2,1,0,147533.09,0 +5380,15730796,Barker,627,France,Female,21,7,98993.02,1,1,1,169156.64,0 +5381,15768219,Sung,850,Spain,Male,36,0,0,2,1,0,141242.57,0 +5382,15663883,Hansen,850,Germany,Male,32,9,141827.33,2,1,1,149458.73,0 +5383,15589296,Brown,724,France,Female,40,6,110054.45,1,1,1,86950.72,0 +5384,15586425,Lo Duca,579,France,Male,28,4,0,2,1,1,176925.69,0 +5385,15679813,Ellis,727,Spain,Male,28,1,0,1,1,0,40357.39,0 +5386,15681410,Korff,813,Germany,Female,36,6,98088.09,1,0,1,26687.22,1 +5387,15668283,Gardiner,642,France,Male,48,9,118317.27,4,0,0,78702.98,1 +5388,15624072,Kiernan,669,Spain,Male,22,10,0,2,1,0,176163.74,0 +5389,15669664,Thompson,574,Germany,Male,54,1,99774.5,1,0,0,4896.11,1 +5390,15682728,Mathews,774,France,Female,32,4,0,2,0,0,114899.13,0 +5391,15573851,Macrossan,735,France,Female,38,1,0,3,0,0,92220.12,1 +5392,15733661,Illingworth,639,Spain,Female,27,8,133806.54,2,1,0,6251.3,0 +5393,15710012,Bowen,738,Spain,Male,44,2,0,2,1,0,43018.82,1 +5394,15763327,Craig,835,France,Male,32,8,124993.29,2,1,1,27548.06,0 +5395,15668853,Menhennitt,637,Spain,Female,44,0,157622.58,1,1,1,120454.2,0 +5396,15639303,Moore,589,Germany,Male,48,5,126111.61,1,0,1,133961.19,0 +5397,15691011,Shoebridge,591,France,Male,42,9,161651.37,2,1,1,131753.97,0 +5398,15638513,Palermo,723,France,Female,40,7,142856.95,2,0,0,38019.74,0 +5399,15648933,Reilly,831,Germany,Male,44,3,111100.98,1,1,1,28144.07,1 +5400,15628904,Bowen,733,Spain,Male,35,8,102918.38,1,1,1,45959.86,0 +5401,15644788,Fyodorov,731,France,Female,30,5,0,2,1,0,189528.72,0 +5402,15598161,Clements,654,France,Male,47,10,0,2,1,0,170481.98,0 +5403,15745624,McKenzie,828,France,Male,37,4,0,2,1,0,94845.45,0 +5404,15733169,Craig,590,Spain,Male,22,7,125265.61,1,1,1,161253.08,0 +5405,15801417,Iloerika,657,France,Male,37,4,82500.28,1,1,1,115260.72,0 +5406,15592707,Dolgorukova,531,Germany,Female,64,2,175754.87,2,1,1,60721.4,0 +5407,15593954,Eva,516,France,Female,47,6,109387.33,1,0,0,121365.45,0 +5408,15714431,Yeh,561,France,Male,37,1,100443.36,2,0,1,101693.73,0 +5409,15638257,P'an,682,Spain,Female,54,0,83102.72,2,1,1,54132.93,0 +5410,15690939,Howe,575,Spain,Male,28,7,0,1,1,1,10666.05,0 +5411,15723613,Jenkins,623,France,Female,28,4,0,2,1,0,41227.67,0 +5412,15813640,Shih,642,France,Female,40,7,0,2,1,0,10712.82,0 +5413,15707322,Nnamdi,779,France,Female,48,2,115290.27,1,0,0,98912.69,1 +5414,15588918,Mitchell,671,France,Female,42,6,0,2,1,0,197202.48,0 +5415,15600357,Findlay,495,France,Female,40,1,140197.71,2,1,0,150720.39,0 +5416,15747014,Pisani,850,France,Female,28,1,105245.34,1,0,1,74780.13,0 +5417,15809830,Belisario,630,France,Male,50,8,0,2,0,1,79377.45,0 +5418,15662245,Pomeroy,588,France,Male,32,1,0,2,1,1,8763.87,0 +5419,15651075,Ibrahimova,562,Germany,Male,35,3,142296.13,1,0,1,177112.7,0 +5420,15594456,K?,740,Spain,Female,56,4,99097.33,1,1,1,85016.64,1 +5421,15583462,Graham,695,France,Male,28,5,171069.39,2,1,1,88689.4,0 +5422,15757661,Trevisano,589,France,Female,39,7,0,2,0,0,95985.64,0 +5423,15729117,Trevisano,607,France,Female,31,1,102523.88,1,1,1,166792.71,0 +5424,15749671,K?,794,France,Male,35,6,0,2,1,1,68730.91,0 +5425,15566253,Manning,580,Germany,Male,44,9,143391.07,1,0,0,146891.07,1 +5426,15595153,Tucker,644,Germany,Female,44,8,106022.73,2,0,0,148727.42,0 +5427,15698572,Schaffer,636,Spain,Female,36,1,0,1,1,0,43134.58,0 +5428,15674149,Esomchi,599,Germany,Male,36,3,128960.21,2,1,1,40318.33,0 +5429,15623082,Ch'ang,507,France,Female,35,2,0,2,1,0,97633.93,0 +5430,15797905,Walker,682,France,Female,48,7,0,2,1,0,65069.03,0 +5431,15746028,Chu,714,France,Female,24,7,0,2,1,0,166335,0 +5432,15582951,Crawford,696,France,Female,25,8,126442.59,1,1,0,121904.44,0 +5433,15616471,Milne,599,Spain,Male,51,0,0,1,1,1,175235.99,0 +5434,15641575,Anenechukwu,577,France,Male,37,2,127261.35,1,1,0,56185.05,0 +5435,15638803,Donaldson,733,Spain,Female,32,5,0,2,1,0,131625.14,0 +5436,15808283,Kelly,647,France,Female,33,4,0,1,1,0,152323.04,0 +5437,15811200,Ts'ao,831,France,Female,34,2,0,2,0,0,165840.94,0 +5438,15733476,Gonzalez,543,Germany,Male,30,6,73481.05,1,1,1,176692.65,0 +5439,15633274,Tai,679,France,Male,34,7,160515.37,1,1,0,121904.14,0 +5440,15582168,Muravyova,713,Germany,Female,61,4,149525.34,2,1,0,123663.63,0 +5441,15807269,Milanesi,690,Germany,Male,43,2,166522.78,1,0,0,119644.59,1 +5442,15602979,Lin,751,France,Male,29,1,135536.5,1,1,0,66825.33,0 +5443,15660417,Lambert,613,Germany,Female,43,10,120481.69,1,0,0,94875.03,1 +5444,15590199,Temple,701,Spain,Male,28,1,103421.32,1,0,1,76304.73,0 +5445,15641794,Ridley,698,France,Male,33,5,135658.73,2,0,1,39755,0 +5446,15779174,Young,451,France,Female,36,2,0,2,1,1,180142.42,0 +5447,15785547,Slye,665,France,Male,28,8,191402.82,2,1,0,83238.4,0 +5448,15795124,Pan,726,Germany,Male,50,9,94504.35,1,0,1,5078.9,0 +5449,15718912,Hsueh,608,Germany,Female,44,5,126147.84,1,0,1,132424.69,1 +5450,15592028,Roberts,549,France,Female,46,7,0,1,1,1,109057.56,0 +5451,15580227,Moss,803,France,Male,33,6,0,2,1,0,115676.61,0 +5452,15657830,Andrews,663,France,Male,43,4,87624.03,2,1,0,149401.33,0 +5453,15798256,Takasuka,558,France,Female,45,1,153697.53,2,0,0,89891.4,1 +5454,15643819,Dawson,714,France,Female,25,4,0,2,0,0,82500.84,0 +5455,15754301,Bruche,704,France,Male,39,5,0,1,1,0,6416.92,0 +5456,15726855,Oliver,805,Germany,Female,45,9,116585.97,1,1,0,189428.75,1 +5457,15755225,Ryan,659,Germany,Male,34,9,134464.58,2,1,0,178833.34,0 +5458,15725221,Sabbatini,738,Germany,Male,62,10,83008.31,1,1,1,42766.03,0 +5459,15789055,Watt,635,Spain,Male,35,2,113635.16,1,1,0,90883.12,0 +5460,15617507,Wilson,530,Spain,Female,36,7,0,2,1,0,80619.09,0 +5461,15668894,Abramova,661,Germany,Male,41,5,122552.48,2,0,1,120646.4,0 +5462,15589563,Purdy,531,Spain,Male,31,2,118899.45,2,0,0,41409.36,0 +5463,15693162,Higgins,694,France,Female,29,5,99713.87,1,0,0,112317.89,0 +5464,15750099,Marshall,731,France,Female,36,6,0,1,0,0,152128.36,0 +5465,15795540,Reye,556,France,Female,36,2,134208.22,1,0,1,177670.57,0 +5466,15794941,Chibueze,647,Germany,Female,41,1,85906.65,3,1,0,189159.97,0 +5467,15611848,Kwemtochukwu,850,Germany,Male,32,3,137714.25,1,0,1,159403.68,0 +5468,15581237,Biryukova,573,Spain,Male,33,1,160777.9,1,1,1,149536.15,0 +5469,15738150,Chidozie,591,France,Male,45,5,0,2,1,1,155492.87,0 +5470,15678571,Barber,723,France,Male,21,4,0,2,0,0,24847.02,0 +5471,15736124,Thompson,617,France,Male,25,1,102585.88,2,1,1,115387.4,0 +5472,15623202,Maslov,704,Germany,Female,39,10,102556.18,2,1,0,171971.25,1 +5473,15804201,Jones,457,Germany,Male,42,4,126772.57,1,0,1,126106.4,0 +5474,15596863,Chidumaga,787,Germany,Female,38,3,158373.23,1,1,1,28228.35,0 +5475,15696277,Hs?,651,France,Female,34,9,0,2,1,0,138113.71,0 +5476,15748608,Trentini,612,Germany,Male,42,5,141927.1,1,1,1,43018.98,0 +5477,15723864,Lucas,828,Spain,Male,47,1,109876.82,2,1,0,83611.45,1 +5478,15802390,Willoughby,724,France,Female,34,2,0,2,1,1,118863.38,0 +5479,15774336,Jamieson,648,Germany,Male,44,9,111369.79,2,1,1,91947.74,0 +5480,15648766,Robertson,569,Spain,Male,35,3,116969.35,1,0,0,94488.82,0 +5481,15659094,Ojiofor,765,Germany,Female,34,8,136729.51,2,0,0,47058.21,0 +5482,15606397,Cameron,577,Germany,Female,44,1,152086.15,1,0,1,44719.5,1 +5483,15642619,Mayne,603,Spain,Male,46,2,0,2,1,0,174478.54,0 +5484,15666032,Mancini,568,Spain,Male,28,1,127289.28,1,0,0,45611.51,0 +5485,15595842,Paramor,748,Germany,Male,45,2,119852.01,1,0,0,73853.94,1 +5486,15753837,Young,573,Spain,Male,38,4,0,2,1,1,196517.43,0 +5487,15783882,Daly,771,Spain,Female,41,5,0,2,0,1,92914.67,0 +5488,15799790,Carter,763,France,Male,35,9,0,1,1,1,31372.91,0 +5489,15628155,Dike,410,France,Female,35,7,117183.74,1,1,1,109733.73,0 +5490,15703778,Hughes,728,France,Male,33,8,129907.63,1,0,1,36083.96,0 +5491,15722322,Green,655,Spain,Female,78,2,0,2,0,1,188435.38,0 +5492,15639278,Chinomso,580,Germany,Female,36,6,145387.32,2,1,1,169963.2,1 +5493,15568487,Gorshkov,712,France,Male,35,7,124616.23,1,1,1,69320.97,0 +5494,15682084,Chinomso,680,France,Male,31,9,0,2,1,0,36145.53,0 +5495,15642821,Ijendu,383,Spain,Female,48,8,95808.19,1,0,0,137702.01,1 +5496,15601387,Yen,721,France,Male,35,10,0,2,1,0,71594.26,0 +5497,15642515,Arcuri,620,France,Female,42,1,0,2,0,1,65565.92,0 +5498,15710421,Baresi,774,Spain,Female,36,8,117152.3,1,0,0,101828.39,0 +5499,15726774,Field,563,France,Male,35,3,106250.72,1,0,0,39546.32,0 +5500,15649078,Christian,850,Germany,Female,27,8,111837.78,2,1,1,110805.79,0 +5501,15641877,Ross,681,France,Male,47,9,97023.21,1,1,1,2168.13,0 +5502,15796496,Trevisani,631,France,Female,31,8,137687.72,1,1,0,190067.12,0 +5503,15815690,Akabueze,614,Spain,Female,40,3,113348.5,1,1,1,77789.01,0 +5504,15631739,Dunn,704,Spain,Male,24,10,122109.78,1,1,1,127654.37,0 +5505,15625584,Martin,786,France,Male,32,2,120452.4,2,0,0,79602.86,0 +5506,15802466,Donaldson,534,France,Female,53,7,0,2,1,1,80619.17,0 +5507,15697028,McClinton,590,Spain,Male,34,0,65812.35,2,0,1,160346.3,0 +5508,15575759,Bentley,583,Spain,Female,40,3,54428.37,1,1,0,109638.78,1 +5509,15567442,Ibezimako,656,France,Female,75,3,0,2,1,1,1276.87,0 +5510,15746805,Thomson,597,France,Male,33,9,0,2,1,0,49374.82,0 +5511,15636330,Ch'in,588,Germany,Female,48,1,143279.58,2,1,0,31580.8,1 +5512,15714970,Holbrook,667,Germany,Male,32,0,103846.65,1,1,0,20560.69,0 +5513,15653784,Solomina,627,France,Male,37,2,125190.86,1,0,1,84584.69,0 +5514,15693543,McDonald,708,France,Female,33,8,0,2,0,1,15246.83,0 +5515,15773283,Dennis,641,France,Male,65,6,38340.02,1,1,0,32607.77,1 +5516,15742534,Faulk,527,Germany,Female,28,2,123802.98,2,1,1,155846.69,0 +5517,15569878,Dale,592,France,Male,37,3,96651.03,1,1,1,3232.82,0 +5518,15729454,Gorbunov,465,France,Male,33,8,0,2,1,0,177668.55,0 +5519,15578375,Farrell,628,France,Male,39,6,0,2,0,0,134441.6,0 +5520,15785559,De Luca,678,France,Male,43,1,133237.21,1,1,0,111032.79,1 +5521,15649414,Walker,570,France,Female,61,6,142105.35,1,1,1,45214.04,0 +5522,15701605,Forster,815,France,Male,37,1,166115.42,1,1,0,67208.3,0 +5523,15686696,Brown,817,France,Female,37,6,81070.34,2,1,0,80985.88,0 +5524,15625586,Monaldo,717,France,Male,35,4,0,1,1,1,167573.06,0 +5525,15654975,Wu,641,France,Female,53,0,123835.52,2,0,1,160110.65,0 +5526,15782993,Pan,624,France,Male,51,10,123401.43,2,1,1,127825.25,0 +5527,15774382,Longo,579,Germany,Male,49,4,169377.31,1,1,1,123535.05,0 +5528,15689602,Findlay,698,France,Male,38,2,130015.24,1,1,1,41595.3,0 +5529,15756155,Fu,645,France,Male,32,4,0,2,0,1,97628.08,0 +5530,15812647,Yin,691,France,Male,34,8,133936.04,2,1,0,91359.79,0 +5531,15736043,Hamilton,638,France,Male,34,6,114543.27,1,1,1,97755.29,0 +5532,15696744,Miller,705,France,Female,31,3,119794.67,1,0,0,182528.44,0 +5533,15602572,Hsing,720,France,Male,33,9,0,2,1,1,142956.48,0 +5534,15674765,Mitchell,553,Spain,Male,44,4,0,1,1,0,10789.3,0 +5535,15678725,Chamberlin,658,France,Female,29,8,0,2,0,1,130461.09,0 +5536,15694444,Buttenshaw,648,Germany,Female,32,8,157138.99,3,1,0,190994.48,1 +5537,15795878,Anayochukwu,636,Spain,Male,45,3,0,2,1,1,159463.8,0 +5538,15735346,Wallace,527,Germany,Female,41,10,136733.24,1,1,1,57589.29,0 +5539,15687094,Calabresi,717,Germany,Female,28,9,82498.14,2,0,0,40437.67,0 +5540,15790067,Sun,614,Spain,Male,39,3,151914.93,1,0,0,56459.45,0 +5541,15605742,Tuan,737,France,Male,43,0,80090.93,1,1,0,39920,1 +5542,15566740,Nazarova,587,Spain,Male,51,3,83739.32,1,0,1,148798.45,0 +5543,15664897,Bryant,682,France,Female,35,2,181166.44,1,1,1,63737.19,1 +5544,15585777,Pai,710,France,Male,38,3,130588.82,1,1,1,154997.64,0 +5545,15650864,Power,507,France,Male,42,6,0,2,1,0,34777.23,0 +5546,15806709,Hao,609,Germany,Male,33,6,94126.67,1,0,0,93718.16,0 +5547,15633818,McMillan,786,France,Male,32,9,0,2,1,0,133112.41,0 +5548,15713845,Merrett,688,France,Male,38,7,148045.68,1,1,0,175479.92,1 +5549,15639662,Phillips,710,France,Male,38,2,0,2,1,0,96.27,0 +5550,15567013,De Luca,779,Spain,Male,33,3,0,2,1,0,30804.68,0 +5551,15777784,Tu,733,France,Female,44,6,168165.84,1,0,1,197193.49,0 +5552,15800251,Elder,583,Germany,Female,26,10,72835.56,2,1,0,96792.15,0 +5553,15651315,Dilke,627,France,Male,41,3,0,2,1,0,132719.8,0 +5554,15651450,Panicucci,666,Germany,Male,31,3,123212.08,2,1,1,112157.31,0 +5555,15784218,Mason,620,Spain,Male,38,0,0,2,1,1,38015.34,0 +5556,15572398,Townsend,614,Spain,Female,39,6,0,2,1,1,164018.98,0 +5557,15707962,Gunson,606,France,Male,40,6,119501.88,2,1,0,46774.94,0 +5558,15705663,Milano,700,Germany,Female,39,5,144550.83,2,1,1,189664.43,0 +5559,15645355,Macleod,677,Germany,Male,34,3,126729.41,1,1,1,26106.39,1 +5560,15729557,Olisaemeka,850,Germany,Male,36,5,119984.07,1,1,0,191535.11,1 +5561,15631436,Gleeson,564,France,Male,35,4,0,1,1,0,158937.55,0 +5562,15583073,Martin,771,Spain,Female,56,2,0,1,1,1,25222.6,1 +5563,15614361,Liao,620,Spain,Male,42,9,121490.05,1,1,1,29296.74,0 +5564,15724684,Sung,610,Spain,Male,46,5,91897.8,1,1,0,54394.28,0 +5565,15700083,Lai,609,Spain,Male,39,2,139443.75,2,1,0,9234.06,0 +5566,15636541,Cartwright,683,Germany,Male,35,5,144961.97,1,0,1,26796.73,0 +5567,15796015,Wu,633,Germany,Male,42,3,126041.02,1,0,1,11796.89,0 +5568,15787222,Ch'in,676,Germany,Male,28,1,69459.05,2,1,1,128461.29,0 +5569,15594270,Biryukov,693,France,Male,38,7,198338.77,2,1,1,14278.18,0 +5570,15701524,Ting,709,France,Male,36,0,0,2,1,0,46811.77,0 +5571,15645847,P'eng,569,Germany,Male,35,2,109196.66,3,1,0,109393.19,1 +5572,15708867,Niu,684,Spain,Female,38,3,134168.5,3,1,0,3966.5,1 +5573,15613140,Mellor,565,France,Male,34,6,0,1,1,1,63173.64,0 +5574,15628893,Power,681,France,Male,29,8,0,1,1,0,66367.33,0 +5575,15764073,Arcuri,503,Spain,Female,36,9,0,2,1,1,16274.67,0 +5576,15782879,Lang,656,France,Male,40,2,0,2,1,1,180553.48,0 +5577,15635964,Eve,566,Germany,Male,65,4,120100.41,1,1,0,107563.16,1 +5578,15726087,Ch'in,592,France,Female,62,5,0,1,1,1,100941.57,0 +5579,15726313,Napolitani,687,Spain,Female,50,5,0,2,1,0,110230.4,0 +5580,15578073,Barker,686,Spain,Male,22,8,0,2,0,0,142331.85,0 +5581,15786249,Whitfield,616,Spain,Male,30,2,0,2,1,0,199099.51,0 +5582,15812850,Stradford,494,Spain,Male,67,5,0,2,1,1,85890.16,0 +5583,15596972,Brownlow,534,France,Male,38,3,0,1,0,0,143938.27,0 +5584,15620579,Dunn,695,Spain,Female,31,8,0,2,0,1,131644.41,0 +5585,15768270,DeRose,579,Spain,Female,31,9,0,2,1,0,112395.98,0 +5586,15656597,Wang,432,Germany,Male,38,2,135559.8,2,1,1,71856.3,0 +5587,15699446,Hobbs,816,Germany,Female,25,2,150355.35,2,1,1,35770.84,0 +5588,15615004,Anderson,730,France,Female,37,1,0,2,1,1,124364.63,0 +5589,15704771,Ugochukwu,593,France,Female,35,6,133489.12,2,1,1,78101.29,0 +5590,15588372,Kirsova,715,Germany,Female,37,9,105489.31,1,0,0,143096.49,1 +5591,15681439,Tsou,775,Germany,Male,25,10,60205.2,2,1,0,14073.11,0 +5592,15607509,Ozerova,539,France,Male,38,5,0,2,1,0,47388.41,0 +5593,15670343,Li,576,Spain,Male,19,6,0,2,0,0,72306.07,0 +5594,15597968,Fyans,617,Spain,Male,50,7,0,1,1,0,184839.7,1 +5595,15658432,Freeman,688,France,Male,40,6,0,1,1,1,47886.44,0 +5596,15616431,Chiu,608,France,Male,33,4,0,1,0,1,130474.03,0 +5597,15796957,Iadanza,597,Spain,Male,35,9,0,3,0,1,73181.39,1 +5598,15815552,Ferguson,670,France,Female,42,6,112333.63,1,1,1,65706.86,0 +5599,15631871,Kelly,616,Germany,Female,57,7,116936.81,1,1,1,104379.36,0 +5600,15635870,She,579,Germany,Female,50,5,117721.02,1,0,1,192146.63,1 +5601,15596713,Christie,786,France,Male,37,7,165896.22,2,1,1,66977.68,0 +5602,15684211,Creel,704,Spain,Female,44,9,153656.85,1,1,0,158742.81,0 +5603,15760521,Thompson,796,France,Female,50,1,94164,1,1,1,189414.74,0 +5604,15608408,Lazareva,598,Spain,Male,39,1,0,2,1,0,159130.32,0 +5605,15804721,Boni,602,France,Male,49,0,191808.73,1,0,0,97640.2,0 +5606,15730272,Evseev,619,France,Male,58,5,152199.33,1,1,1,86022.09,0 +5607,15741988,Marino,492,Germany,Female,52,8,125396.24,1,1,0,10014.72,1 +5608,15771728,Mackenzie,641,Germany,Male,41,7,104405.54,3,1,0,17384.21,0 +5609,15605113,Sutherland,518,France,Female,27,1,133801.49,1,1,1,143315.57,0 +5610,15661945,Nicolay,623,Spain,Female,40,4,0,3,1,0,31669.18,0 +5611,15783816,Lori,733,France,Female,28,5,0,2,0,0,12761.16,0 +5612,15721207,Piazza,625,Germany,Male,42,6,100047.33,1,1,0,93429.95,0 +5613,15764072,Somerville,759,France,Female,31,1,109848.6,1,1,1,42012.55,0 +5614,15689412,Christie,604,France,Female,32,7,127849.38,1,1,0,15798.7,0 +5615,15798385,Grave,512,Spain,Female,46,3,0,2,1,1,56408.14,0 +5616,15775339,Lori,520,France,Female,29,8,95947.76,1,1,0,4696.44,0 +5617,15585256,Iloerika,805,Spain,Male,26,2,0,2,1,1,25042.1,0 +5618,15797329,Muir,626,France,Male,43,4,137638.69,1,1,0,130442.08,1 +5619,15780220,Pauley,656,France,Male,38,10,0,1,1,1,136521.82,0 +5620,15648951,Kao,785,Spain,Male,41,7,0,2,1,1,199108.88,0 +5621,15752409,Grant,553,France,Male,31,6,0,2,0,0,124596.63,0 +5622,15807524,Chukwuma,569,France,Female,44,4,0,2,0,0,134394.78,0 +5623,15766649,Vincent,670,France,Male,38,10,89416.99,1,0,0,144275.39,0 +5624,15696812,Lazareva,586,Spain,Male,42,6,0,2,1,1,123410.23,0 +5625,15581295,Ch'ien,617,Spain,Female,45,1,0,1,1,0,143298.06,0 +5626,15663234,Bishop,508,France,Female,60,7,143262.04,1,1,1,129562.74,0 +5627,15741417,Chibuzo,624,Spain,Female,35,7,119656.45,2,1,1,4595.05,0 +5628,15695174,Chang,654,France,Male,29,4,132954.64,1,1,1,146715.07,0 +5629,15665168,Calabrese,681,Germany,Female,44,3,105206.7,2,1,1,163558.36,0 +5630,15601503,Tokaryev,578,Spain,Male,28,4,0,2,0,0,6947.09,0 +5631,15706131,Logan,621,Spain,Female,37,9,83061.26,2,1,0,9170.54,0 +5632,15782758,Ozerova,632,France,Male,40,5,147650.68,1,1,1,199674.83,0 +5633,15591091,Goering,644,France,Male,44,5,73348.56,1,1,0,157166.79,1 +5634,15715877,Lo,821,France,Male,28,2,0,2,1,0,46072.52,0 +5635,15756918,Simmons,754,France,Female,38,2,0,2,0,0,3524.69,0 +5636,15746662,Maduabuchim,568,Spain,Female,27,1,116320.68,1,0,1,45563.94,0 +5637,15626679,Linger,584,France,Male,33,3,0,2,0,1,59103.13,0 +5638,15793343,Yeh,549,France,Female,29,8,0,2,1,1,189558.44,0 +5639,15576774,Stevenson,729,France,Female,38,7,0,2,0,0,45779.9,0 +5640,15801316,Ifeatu,523,France,Male,61,8,66250.71,1,1,1,21859.06,0 +5641,15800514,Kenechukwu,477,Germany,Female,24,2,95675.62,2,0,0,162699.7,1 +5642,15662232,Learmonth,675,Germany,Male,42,2,92616.64,2,1,0,8567.18,0 +5643,15737778,Dickson,782,Spain,Female,41,4,0,1,1,0,132943.88,0 +5644,15782096,Volkova,616,Spain,Female,36,6,0,1,1,1,12916.32,1 +5645,15783522,Mitchell,738,Spain,Female,37,8,100565.94,1,1,1,128799.86,0 +5646,15785373,Wong,717,Spain,Female,42,5,190305.78,1,1,0,99347.8,1 +5647,15756272,James,526,Germany,Female,35,9,118536.4,1,1,0,40980.87,1 +5648,15615245,Shao,660,France,Male,19,5,127649.64,1,1,1,40368.65,0 +5649,15600174,Walton,525,France,Male,35,7,165358.77,1,0,1,94738.54,0 +5650,15752956,Stanley,629,Spain,Male,29,6,0,2,1,1,88842.8,0 +5651,15644882,Watson,616,Germany,Female,36,10,78249.53,1,1,0,136934.91,0 +5652,15766272,Folliero,521,Germany,Female,61,0,125193.96,1,1,1,109356.53,0 +5653,15800620,Fitzgerald,691,France,Female,29,9,0,2,0,0,199635.93,0 +5654,15569764,Garner,687,Germany,Female,41,2,154007.21,1,1,0,158408.23,0 +5655,15747458,Folliero,677,Spain,Female,43,3,133214.88,2,1,1,95936.84,0 +5656,15573171,Liao,695,Spain,Male,63,1,146202.93,1,1,1,126688.83,1 +5657,15736769,Lucchesi,663,France,Female,27,9,0,2,1,0,150850.29,0 +5658,15763381,Chan,496,France,Male,30,0,90963.49,1,0,1,27802,0 +5659,15814430,Ma,747,Spain,Male,41,9,0,1,1,0,32430.94,1 +5660,15638607,Nwabugwu,546,France,Female,52,2,0,1,1,0,137332.37,1 +5661,15737133,P'eng,706,Spain,Male,68,4,114386.85,1,1,1,28601.68,0 +5662,15613945,Andrews,472,France,Female,26,5,0,2,1,0,108411.66,0 +5663,15659937,Otutodilinna,703,France,Female,40,7,0,2,0,1,122518.5,0 +5664,15765287,Grant,850,France,Female,38,2,0,2,1,0,9015.07,0 +5665,15661723,Abramovich,667,Spain,Male,71,4,137260.78,1,0,1,94433.08,1 +5666,15766064,Komarova,559,France,Male,33,9,111060.05,2,1,0,110371.84,0 +5667,15649616,Otutodilichukwu,636,Spain,Male,60,7,124447.73,1,1,1,141364.62,1 +5668,15719017,Donaldson,672,France,Female,34,8,0,2,1,1,16245.25,0 +5669,15720919,Duggan,667,France,Male,42,7,0,1,0,1,108348.94,1 +5670,15706706,Chinwendu,648,Germany,Male,33,7,135310.41,2,0,1,171668.2,0 +5671,15709653,Hamilton,497,France,Male,32,8,0,2,1,0,67364.42,0 +5672,15805104,Smith,743,France,Female,73,6,0,2,0,1,107867.38,0 +5673,15622442,Mazzi,619,France,Male,29,5,0,2,1,0,194310.1,0 +5674,15572801,Krischock,639,Spain,Male,34,5,139393.19,2,0,0,33950.08,0 +5675,15767598,Kent,540,Spain,Male,28,8,0,2,0,0,197588.32,0 +5676,15757897,Binder,766,France,Female,26,3,104258.8,1,1,1,428.23,0 +5677,15568104,Zubarev,749,France,Female,26,6,0,2,0,1,34948.77,0 +5678,15763414,Degtyarev,655,Germany,Male,32,9,113447.01,1,1,0,82084.3,0 +5679,15732265,Obialo,630,France,Male,33,9,0,2,1,0,64804.59,0 +5680,15621974,Davydova,778,Germany,Female,33,4,111063.73,2,1,0,83556.65,0 +5681,15803947,Teng,757,Germany,Female,30,6,161378.02,1,0,0,71926.28,1 +5682,15720706,Hsing,529,Spain,Female,39,2,82766.43,1,1,1,122925.44,0 +5683,15759290,Coleman,620,Spain,Male,29,9,0,2,1,0,13133.88,0 +5684,15651664,Wilder,615,France,Female,61,1,104267.7,1,1,0,62845.64,1 +5685,15795132,Molineux,735,France,Female,25,3,91718.8,1,0,0,28411.23,0 +5686,15811565,Cocci,705,Spain,Female,47,3,63488.7,1,0,1,28640.92,1 +5687,15713774,Chikwendu,644,Spain,Female,46,6,12459.19,1,0,0,156787.34,1 +5688,15691840,Fraser,505,Germany,Female,37,6,159863.9,2,0,1,125307.87,0 +5689,15682021,Lai,471,Germany,Male,23,6,104592.55,2,1,0,131736.23,0 +5690,15612931,Korovin,722,Spain,Female,50,4,132088.59,1,1,1,128262.14,0 +5691,15676707,Sidorov,577,Spain,Female,39,4,0,2,1,0,91366.42,0 +5692,15601383,Ibrahimova,744,Spain,Male,44,5,120654.68,1,1,0,82290.81,0 +5693,15662662,Duigan,573,France,Female,30,6,0,2,1,0,66190.21,0 +5694,15752694,Taylor,653,France,Female,32,4,83772.95,1,0,1,23920.65,0 +5695,15590683,Donaldson,660,France,Female,31,6,172325.67,1,0,1,45438.38,0 +5696,15773591,Jobson,787,France,Male,46,7,117685.31,2,1,1,93360.35,0 +5697,15723620,Lu,617,France,Male,41,7,0,2,0,1,14496.67,0 +5698,15671779,Nebechi,567,France,Male,39,5,0,2,0,0,168521.72,0 +5699,15672966,Cross,682,Spain,Female,64,9,0,2,1,1,103318.44,0 +5700,15624667,Wallace,684,France,Male,35,6,135871.5,1,1,1,87219.41,0 +5701,15812888,Perreault,447,France,Male,41,3,0,4,1,1,197490.39,1 +5702,15724154,Manna,625,Germany,Female,49,4,128504.76,1,1,0,126812.63,1 +5703,15749540,Hsiung,585,France,Male,36,7,0,2,1,0,94283.09,0 +5704,15621063,Gibbons,516,France,Female,42,8,56228.25,1,1,0,46857.52,0 +5705,15661626,Algeranoff,732,Germany,Female,45,6,98792.4,1,1,0,81491.7,1 +5706,15698703,Doherty,628,Germany,Male,40,5,181768.32,2,1,1,129107.97,0 +5707,15801431,Rowe,682,Spain,Female,48,9,101198.01,1,1,1,49732.9,0 +5708,15649451,Yates,746,France,Male,25,9,0,2,0,1,88728.47,0 +5709,15626156,Galloway,655,France,Female,60,3,0,2,1,1,86981.45,0 +5710,15606158,Genovese,644,France,Female,39,9,0,1,1,0,3740.93,0 +5711,15589496,Arrington,778,France,Male,34,5,139064.06,2,0,0,67949.32,0 +5712,15730345,Miah,617,France,Female,35,2,104508.1,1,1,1,147636.46,0 +5713,15572038,Chijindum,660,Germany,Male,35,9,113948.58,1,1,0,188891.96,1 +5714,15643439,Ferguson,537,France,Male,47,10,0,2,0,1,25482.62,0 +5715,15604158,Smith,554,France,Female,39,10,0,2,1,1,18391.93,0 +5716,15657396,Marshall,806,France,Male,31,9,0,2,0,1,140168.36,0 +5717,15709478,P'an,611,Germany,Male,37,1,117524.72,2,0,1,161064.29,0 +5718,15628824,Burton,665,France,Female,37,5,160389.82,1,0,1,183542.08,0 +5719,15814519,Kamdibe,648,France,Female,37,7,0,2,1,0,194238.92,0 +5720,15636520,Milani,692,France,Male,27,1,125547.53,1,0,0,7900.46,0 +5721,15794414,Forbes,507,Spain,Male,46,6,92783.68,1,1,1,51424.29,0 +5722,15643671,Chiekwugo,696,Germany,Male,49,5,97036.22,2,1,0,152450.84,1 +5723,15700650,Cousens,681,France,Male,34,3,0,2,0,0,55816.2,0 +5724,15680224,Ross,687,France,Female,26,6,0,2,1,1,32909.13,0 +5725,15784286,Wood,641,Spain,Male,40,5,102145.13,1,1,1,100637.07,0 +5726,15693996,Hawks,507,France,Female,33,1,113452.66,1,0,0,142911.99,0 +5727,15764343,T'ien,688,Spain,Female,46,8,155681.72,1,1,0,26287.21,0 +5728,15704168,Ting,535,Germany,Male,38,8,127475.24,1,0,0,60775.76,1 +5729,15680197,Thynne,701,France,Male,41,10,0,2,1,1,146257.77,0 +5730,15633729,Wang,488,France,Male,43,10,112751.13,1,1,1,28332,0 +5731,15577683,Maclean,539,France,Female,29,4,0,2,1,1,100919.19,0 +5732,15800746,Watson,674,France,Male,45,7,144889.18,1,1,1,102591.9,1 +5733,15788686,Gibson,538,Spain,Male,40,8,0,2,1,1,25554.4,0 +5734,15742798,French,829,France,Female,22,7,150126.44,1,1,0,152107.93,1 +5735,15596647,Henderson,768,France,Male,54,8,69712.74,1,1,1,69381.05,0 +5736,15756070,Greenwood,585,Spain,Female,44,4,0,2,0,1,101728.46,0 +5737,15775116,Anderson,581,France,Male,31,3,0,2,0,0,89040.61,0 +5738,15575428,Mistry,682,Germany,Female,35,2,117438.92,2,1,1,16910.98,0 +5739,15654074,Tuan,653,France,Male,38,8,119315.75,1,1,0,150468.35,0 +5740,15695872,Fiorentini,712,France,Female,30,1,89571.59,1,1,1,177613.19,0 +5741,15568885,Scott,620,Germany,Female,34,8,102251.57,1,1,0,120672.09,0 +5742,15725036,Jideofor,709,France,Male,42,9,118546.71,1,0,1,77142.85,0 +5743,15632665,Yevseyev,832,France,Male,61,2,0,1,0,1,127804.66,1 +5744,15571476,Kelly,635,Spain,Male,38,0,103257.14,1,0,0,158344.63,0 +5745,15776850,Smith,749,Spain,Female,43,1,124209.02,1,1,1,167179.48,0 +5746,15623649,Ogle,629,Spain,Male,32,3,0,2,1,1,15404.64,0 +5747,15751131,Moss,836,Spain,Female,41,7,150302.84,1,1,1,156036.19,0 +5748,15688128,Loggia,542,Spain,Male,34,8,108653.93,1,0,1,144725.14,0 +5749,15678412,Nwankwo,645,France,Female,45,8,85325.93,1,0,0,22558.74,0 +5750,15770291,Allan,844,France,Female,29,8,0,2,0,0,147342.03,0 +5751,15583392,Woronoff,747,Germany,Male,37,9,135776.36,3,1,0,85470.45,1 +5752,15690731,Wolfe,645,France,Male,40,6,131411.24,1,1,1,194656.11,0 +5753,15697948,Henderson,752,Spain,Female,36,3,0,2,1,1,48505.1,0 +5754,15608328,Sutherland,760,Spain,Female,41,6,0,2,0,0,101491.23,0 +5755,15766378,Marsden,714,Germany,Female,45,9,106431.97,2,1,1,164117.69,0 +5756,15600813,Hyde,717,France,Male,50,9,90305.76,1,1,1,124626.57,0 +5757,15706217,Kao,645,Germany,Male,28,7,117466.03,2,1,1,34490.06,0 +5758,15601417,T'ang,681,France,Male,32,3,148884.47,2,1,1,90967.37,0 +5759,15610972,Crawford,681,Germany,Female,44,4,91115.76,2,0,0,24208.84,1 +5760,15674620,Dilibe,679,Germany,Female,37,8,77373.87,2,0,1,174873.09,0 +5761,15785350,Austin,528,Spain,Male,23,7,104744.89,1,1,0,170262.97,0 +5762,15749119,Santiago,710,France,Female,31,3,0,2,1,1,112289.06,0 +5763,15756535,Chibugo,733,Germany,Male,39,5,91538.51,1,1,1,93783,0 +5764,15700965,Toscano,724,France,Female,32,6,0,2,1,1,150026.79,0 +5765,15791851,Afanasyeva,726,France,Female,34,0,185734.75,1,1,1,102036.82,0 +5766,15717156,Sokolov,520,France,Male,30,3,143396.54,2,1,1,898.51,0 +5767,15740846,Wei,556,France,Male,40,5,125909.85,1,1,1,95124.4,0 +5768,15573284,Olisanugo,579,France,Female,45,2,0,2,0,0,11514.39,0 +5769,15729083,Gorman,674,France,Male,36,2,154525.7,1,0,1,27468.72,0 +5770,15611612,Priestley,570,France,Female,29,0,0,1,1,0,37092.43,0 +5771,15694381,Lloyd,631,France,Male,51,8,100654.8,1,1,0,171587.9,0 +5772,15651737,Salmond,623,Spain,Male,44,1,83325.77,1,0,1,80828.78,0 +5773,15663168,MacDonald,665,France,Male,35,8,110934.54,1,1,0,169287.99,0 +5774,15643426,Robertson,523,Spain,Female,36,8,113680.54,1,0,0,13197.44,0 +5775,15618245,Chukwumaobim,706,Germany,Male,31,1,117020.08,2,1,0,54439.53,0 +5776,15717527,Ifeanacho,619,France,Female,49,9,145359.99,1,1,0,38186.85,0 +5777,15793478,Li Fonti,593,Germany,Female,39,8,151391.68,1,1,0,27274.6,1 +5778,15642248,Ko,608,Spain,Male,66,8,123935.35,1,1,1,65758.19,0 +5779,15640377,Goloubev,526,France,Female,36,0,0,2,1,0,97767.63,0 +5780,15723950,Kruglov,684,Spain,Male,40,2,70291.02,1,1,1,115468.84,1 +5781,15590327,Liao,604,Germany,Female,42,10,166031.45,1,1,0,98293.14,0 +5782,15706199,White,636,Germany,Male,36,6,96643.32,1,0,0,182059.28,0 +5783,15671514,Sinclair,669,Spain,Female,33,8,0,2,0,1,128538.05,0 +5784,15727041,Fiorentini,624,France,Male,71,7,0,2,1,1,108841.83,0 +5785,15738063,Shen,631,France,Male,29,2,0,2,1,1,18581.84,0 +5786,15711733,Rapuokwu,753,France,Male,48,4,0,2,0,1,146821.42,0 +5787,15652320,Woronoff,588,France,Male,40,5,0,2,0,0,100727.68,0 +5788,15634180,Holden,729,Germany,Male,26,4,97268.1,2,1,0,39356.38,0 +5789,15694566,Roberts,602,France,Female,42,10,0,2,0,0,169921.11,1 +5790,15726103,Tsou,689,Germany,Female,55,1,76296.81,1,1,0,42364.75,1 +5791,15646351,Somerville,486,Spain,Male,27,7,0,2,1,0,28823.04,0 +5792,15730044,Greco,809,Germany,Female,42,6,64497.94,3,0,1,182436.81,1 +5793,15795186,Leonard,562,France,Male,38,5,0,1,1,0,115700.2,0 +5794,15784890,McKenzie,763,Spain,Female,32,8,0,2,1,0,16725.53,0 +5795,15694125,McElhone,669,France,Male,57,5,0,2,1,1,56875.76,0 +5796,15565891,Dipietro,709,France,Male,39,8,0,2,1,0,56214.09,0 +5797,15674254,Kerr,554,Spain,Female,45,4,0,2,1,1,193412.05,0 +5798,15775206,Hunter,699,France,Male,37,10,0,2,0,0,83263.04,0 +5799,15797627,Niehaus,732,Spain,Male,54,0,134249.7,1,0,1,13404.4,0 +5800,15649853,Craig,625,France,Female,45,3,0,1,1,1,184474.15,1 +5801,15610379,Barclay-Harvey,599,France,Male,30,9,105443.68,1,1,1,121124.53,0 +5802,15659800,Teng,584,Spain,Female,50,1,0,1,0,1,152567.75,1 +5803,15716236,Milani,499,France,Male,35,10,0,2,1,0,10722.54,0 +5804,15672053,Mistry,526,Spain,Male,38,2,0,2,0,0,58010.98,0 +5805,15663933,Jamieson,625,Germany,Female,35,5,86147.46,2,1,0,163440.8,1 +5806,15814236,Kay,537,Spain,Female,38,1,96939.06,1,1,1,102606.92,0 +5807,15583597,Ikedinachukwu,696,Spain,Male,47,1,106758.6,1,1,1,80591.18,0 +5808,15607395,Holt,679,France,Female,33,9,112528.65,2,1,0,177362.45,0 +5809,15694556,Nkemakolam,684,France,Male,60,2,116563.58,1,1,0,120257.7,1 +5810,15744109,Hartung,850,France,Male,32,4,0,1,1,1,180622.02,0 +5811,15800688,Ch'en,495,Spain,Female,42,7,0,2,0,0,130404.53,0 +5812,15810878,Baker,537,Spain,Female,38,6,141786.78,1,0,1,147797.54,0 +5813,15587835,Osinachi,850,France,Male,41,3,136416.82,1,0,1,57844.26,0 +5814,15763515,Shih,513,France,Male,30,5,0,2,1,0,162523.66,0 +5815,15725882,Feng,618,Germany,Female,40,1,133245.52,2,1,1,54495.82,0 +5816,15788022,Sternberg,802,Germany,Female,41,4,90757.64,2,0,1,169183.66,0 +5817,15663917,Adams,547,France,Male,43,1,92350.36,1,0,1,80262.91,0 +5818,15656865,Gray,613,Germany,Male,69,9,78778.49,1,0,1,8751.59,0 +5819,15667971,Shepherd,592,Germany,Female,34,6,102143.93,2,1,1,102628.98,0 +5820,15800366,Walton,546,France,Male,29,5,0,1,1,1,94823.95,0 +5821,15717231,Yang,721,Germany,Male,37,4,98459.6,1,0,0,90821.66,0 +5822,15643188,Barnett,671,Germany,Female,47,7,114603.76,2,1,0,153194.32,1 +5823,15671351,Romani,624,Spain,Male,35,2,0,2,1,0,87310.59,0 +5824,15573628,Greene,751,Germany,Female,51,7,148074.79,1,1,0,146411.41,1 +5825,15698953,Hart,636,Spain,Male,36,1,0,3,1,1,74048.1,1 +5826,15753888,Johnston,607,Spain,Female,62,8,108004.64,1,1,1,23386.77,1 +5827,15737961,Miller,509,Germany,Female,29,0,107712.57,2,1,1,92898.17,0 +5828,15801701,Robson,653,Spain,Male,35,9,0,2,1,1,45956.05,0 +5829,15684419,Wallace,709,Spain,Female,37,8,0,3,1,0,71738.56,0 +5830,15794266,Cross,559,France,Male,32,9,145303.52,1,1,0,103560.98,0 +5831,15810711,Marcum,684,Germany,Male,37,4,138476.41,2,1,1,52367.29,0 +5832,15771270,North,635,France,Female,27,8,127471.56,1,1,1,152916.05,1 +5833,15607786,Mao,709,France,Male,26,6,156551.63,1,0,1,4410.77,0 +5834,15624519,Calabrese,656,Germany,Female,49,9,97092.87,1,1,0,74771.22,1 +5835,15799910,Martin,793,France,Male,32,2,0,2,1,0,193817.63,1 +5836,15602479,Fleming,609,Spain,Male,37,5,129312.79,1,1,1,26793.82,0 +5837,15617419,Roberts,618,Germany,Female,29,10,100315.1,2,1,1,32526.64,0 +5838,15657603,Finch,850,France,Female,35,6,81684.97,1,1,0,824,0 +5839,15570379,Whitelegge,669,Spain,Male,51,3,88827.53,1,0,0,85250.77,1 +5840,15772996,Rooke,594,Germany,Male,40,0,152092.44,2,1,1,83508.93,0 +5841,15729574,Lu,616,Spain,Male,71,4,0,2,1,1,173599.38,0 +5842,15737267,Marcelo,676,France,Female,49,1,0,1,1,0,79342.31,1 +5843,15799128,Matthews,608,Spain,Female,38,9,102406.76,1,0,1,57600.66,0 +5844,15813327,Romani,710,France,Male,21,4,109130.96,2,1,1,56191.99,0 +5845,15711921,Scott,695,France,Male,29,5,0,2,1,1,6770.44,0 +5846,15654300,Mao,530,Germany,Male,33,9,75242.28,1,0,1,101694.67,0 +5847,15569945,Horsley,509,Spain,Male,29,1,0,2,1,0,69113.14,0 +5848,15569666,Goddard,517,France,Female,45,4,0,1,0,0,172674.36,1 +5849,15681887,Eskridge,758,Germany,Male,33,0,129142.54,2,1,1,26606.28,0 +5850,15608873,Smith,665,France,Male,51,2,0,1,0,0,53353.36,0 +5851,15762091,Simpson,631,Germany,Female,22,6,139129.92,1,1,1,63747.51,0 +5852,15722053,Oguejiofor,576,Spain,Male,33,3,0,2,0,1,190112.05,0 +5853,15782100,Holloway,544,Spain,Male,22,3,66483.32,1,0,1,110317.39,0 +5854,15765300,L?,596,Germany,Male,40,5,62389.03,3,1,0,148623.43,1 +5855,15743570,Feng,481,France,Female,34,5,0,2,1,1,125253.46,0 +5856,15608541,Claiborne,498,France,Male,46,1,91857.66,1,1,0,101954.78,1 +5857,15750671,Egobudike,512,Spain,Male,31,6,0,2,1,0,168462.26,0 +5858,15813659,Folliero,594,France,Female,56,7,0,1,1,0,26215.85,1 +5859,15757867,Bray,570,France,Female,30,10,176173.52,1,1,0,97045.32,1 +5860,15652914,Ibrahimov,721,Spain,Male,38,7,0,1,0,1,53534.8,0 +5861,15723818,Carpenter,453,France,Female,37,4,131834.76,2,1,0,8949.2,0 +5862,15713819,Walsh,562,France,Male,48,3,92347.96,1,1,1,163116.75,0 +5863,15656484,Woods,682,France,Male,40,4,0,2,1,1,140745.91,0 +5864,15778515,Wu,748,France,Male,40,3,95297.11,1,0,0,171515.84,0 +5865,15803840,Forbes,729,France,Female,32,9,0,2,0,0,150803.44,0 +5866,15735339,Lynch,663,France,Male,39,4,0,1,1,0,76884.05,0 +5867,15600392,Amaechi,735,France,Female,53,8,123845.36,2,0,1,170454.93,1 +5868,15625740,Enriquez,627,Germany,Male,62,3,143426.34,2,1,1,143104.3,0 +5869,15663817,Y?an,713,France,Male,46,5,0,1,1,1,55701.62,0 +5870,15734461,Brooks,562,Germany,Male,31,2,112708.2,1,0,1,186370.3,0 +5871,15780142,Wang,632,France,Male,43,2,100013.51,1,1,0,24275.32,0 +5872,15709920,Burke,479,France,Female,33,2,208165.53,1,0,0,50774.81,1 +5873,15684248,Meng,658,Spain,Male,21,7,0,2,0,1,154279.87,0 +5874,15643158,Chiganu,598,France,Female,40,9,0,1,1,0,68462.59,1 +5875,15693902,Hunt,597,France,Male,19,2,0,2,1,1,91036.74,0 +5876,15578307,Lucchese,512,France,Female,33,6,121685.31,2,1,1,83681.97,0 +5877,15585379,Humphries,704,France,Male,39,2,111525.02,1,1,0,199484.96,0 +5878,15758510,Frolova,474,France,Male,26,6,0,2,0,0,152491.22,0 +5879,15692918,Hsing,604,Germany,Male,36,10,113546.3,1,1,1,134875.37,0 +5880,15705301,Parkes,683,France,Male,41,6,95696.52,2,1,1,184366.14,0 +5881,15718231,Gregory,537,France,Male,28,0,88963.31,2,1,1,189839.93,0 +5882,15567991,Obiuto,794,Spain,Male,31,0,144880.34,2,0,1,175643.44,0 +5883,15772650,Longo,732,France,Male,55,9,136576.02,1,0,1,3268.17,1 +5884,15574795,Lombardo,495,France,Female,38,2,63093.01,1,1,1,47089.72,0 +5885,15706036,Lombardo,552,Germany,Male,38,10,132271.12,2,1,1,46562.02,0 +5886,15723856,Gonzalez,602,France,Female,29,3,88814.4,2,1,1,62487.97,0 +5887,15812920,Nwabugwu,607,Germany,Male,40,5,90594.55,1,0,1,181598.25,0 +5888,15691287,Ford,675,Germany,Female,33,0,141816.25,1,1,0,64815.05,1 +5889,15804797,Gilleland,443,France,Female,54,3,138547.97,1,1,1,70196.23,1 +5890,15708650,Fullwood,727,France,Female,31,2,52192.08,2,0,1,160383.47,0 +5891,15712777,Kao,482,France,Male,38,4,124976.19,1,1,0,35848.12,0 +5892,15786469,Montalvo,686,France,Female,34,1,0,2,1,0,87278.48,0 +5893,15669219,Wilson,588,Germany,Male,35,3,104356.38,1,1,0,94498.82,0 +5894,15641004,Doyne,605,Spain,Female,48,10,150315.92,1,0,1,133486.36,0 +5895,15648067,Onwuamaeze,583,France,Male,39,1,129299.28,2,1,0,73107.6,0 +5896,15704014,K'ung,738,Germany,Male,37,7,140950.92,2,1,0,195333.98,0 +5897,15645136,O'Donnell,744,Spain,Male,30,1,128065.12,1,1,0,121525.48,0 +5898,15709604,McMillan,781,France,Male,23,2,107433.48,1,1,0,173843.21,0 +5899,15713637,Chinedum,699,France,Male,34,2,117468.67,1,1,0,185227.42,0 +5900,15793901,Capon,639,France,Female,27,2,0,2,0,0,125244.18,0 +5901,15569759,Rawling,583,France,Female,27,4,0,3,1,0,163113.41,0 +5902,15712930,Duncan,587,France,Male,42,1,0,1,0,0,123006.91,0 +5903,15586504,Trevisani,694,France,Male,40,9,0,2,1,0,40463.03,0 +5904,15677317,Ankudinova,570,France,Female,29,4,153040.03,1,1,1,131363.57,1 +5905,15664270,Balsillie,692,Germany,Male,45,6,142084.04,4,1,0,188305.85,1 +5906,15731519,Kerr,511,France,Female,30,5,0,2,1,0,143994.86,0 +5907,15745623,Worsnop,788,France,Male,32,4,112079.58,1,0,0,89368.59,0 +5908,15813862,Yevseyev,526,Spain,Male,66,7,132044.6,2,1,1,158365.89,0 +5909,15641934,Manna,749,Spain,Female,46,9,66582.81,1,1,0,78753.12,1 +5910,15713043,Siciliani,691,France,Female,33,6,0,2,1,1,100408.31,0 +5911,15700749,Powell,481,France,Female,39,6,0,1,1,1,24677.54,0 +5912,15697567,Bazarova,752,France,Male,33,4,0,2,1,1,39570.78,0 +5913,15715414,White,658,France,Female,38,6,102895.1,1,0,0,155665.76,0 +5914,15639530,Buda,679,Spain,Male,42,2,0,1,1,1,168294.27,0 +5915,15726058,Cattaneo,754,Germany,Male,27,7,117578.35,2,0,1,87908.01,0 +5916,15725665,Lo,679,France,Male,47,10,198546.1,2,1,0,191198.92,1 +5917,15698872,Brown,633,Spain,Female,39,2,0,2,0,0,191207.03,0 +5918,15812184,Rose,674,France,Female,31,1,0,1,1,0,128954.05,0 +5919,15742609,Lombardo,600,Germany,Male,28,2,116623.31,1,0,1,59905.29,0 +5920,15815043,McMillan,645,Spain,Male,49,8,0,2,1,0,162012.6,0 +5921,15640648,Howe,698,France,Male,36,6,0,2,0,1,19231.98,0 +5922,15627203,Hsu,508,Spain,Male,54,10,0,1,1,1,175749.36,0 +5923,15786196,Han,555,France,Female,44,3,105770.7,3,1,0,60533.96,1 +5924,15612095,Calabrese,751,France,Female,48,9,0,1,1,0,137508.42,1 +5925,15674368,Riley,738,France,Female,39,1,94435.45,2,0,1,189430.86,0 +5926,15783477,Biryukov,706,Germany,Female,39,8,112889.91,1,0,1,6723.66,0 +5927,15757559,Broadhurst,595,France,Female,53,7,0,2,1,0,41371.68,1 +5928,15591036,Genovesi,577,Germany,Female,43,3,127940.47,1,0,0,125140.72,1 +5929,15761241,Hsieh,578,Germany,Female,36,8,129745.1,1,1,1,143683.75,0 +5930,15695078,Kemp,699,France,Male,32,3,0,2,1,1,170770.44,0 +5931,15645744,Chukwudi,826,France,Female,30,5,0,2,0,1,157397.57,0 +5932,15566988,Iqbal,656,Germany,Female,46,7,141535.52,1,1,0,50595.15,1 +5933,15749300,Teng,556,France,Female,47,2,139914.27,1,1,1,50390.98,0 +5934,15594340,Tao,569,France,Male,41,4,120243.49,1,1,0,163150.03,1 +5935,15607065,Chinedum,765,France,Male,34,9,91835.16,1,0,0,138280.17,0 +5936,15778089,Stevenson,544,Spain,Male,37,2,0,2,0,0,135067.02,0 +5937,15773723,Duncan,588,Spain,Female,22,9,67178.19,1,1,1,163534.75,1 +5938,15697035,Garrett,740,Spain,Female,31,8,0,2,0,0,86657.48,0 +5939,15679668,Yao,850,Spain,Male,38,7,115378.94,1,0,1,162087.82,0 +5940,15709861,He,766,Germany,Male,30,4,127786.28,2,1,1,28879.3,0 +5941,15791958,Mazzi,849,France,Female,41,6,0,2,1,1,169203.51,1 +5942,15791030,Edwards,612,France,Female,33,0,64900.32,2,1,0,102426.12,0 +5943,15695339,Lucchesi,517,Germany,Male,53,0,109172.88,1,1,0,54676.1,1 +5944,15658813,Siciliani,645,France,Female,55,7,0,2,1,1,18369.33,0 +5945,15715709,Shih,696,Germany,Male,43,4,114091.38,1,0,1,159888.1,0 +5946,15722533,Logue,716,France,Female,40,3,0,2,0,1,167636.15,0 +5947,15683118,Rechner,590,France,Male,32,9,0,2,1,0,138889.15,0 +5948,15672798,O'Brien,656,France,Female,45,7,145933.27,1,1,1,199392.14,0 +5949,15680112,Stewart,473,Germany,Female,35,7,131504.73,1,1,0,189560.43,0 +5950,15714575,Batt,742,Germany,Female,44,8,107926.02,1,0,1,17375.27,1 +5951,15806808,Hope,834,Germany,Female,57,8,112281.6,3,1,0,140225.14,1 +5952,15590637,Ahmed,721,France,Male,41,7,0,2,0,1,61018.85,0 +5953,15657535,Pearson,590,Spain,Male,29,10,0,1,1,1,51907.72,1 +5954,15696141,Kruglov,516,Spain,Female,31,7,0,1,1,0,47018.75,0 +5955,15811947,Gordon,850,France,Male,33,0,124781.67,1,0,1,33700.52,0 +5956,15649024,Trujillo,748,France,Female,39,9,132865.56,1,1,1,59636.43,1 +5957,15594928,Pagnotto,798,Germany,Female,38,4,129055.13,1,1,0,157147.59,0 +5958,15765532,Horton,612,Germany,Male,76,6,96166.88,1,1,1,191393.26,0 +5959,15741719,DeRose,540,France,Female,40,3,165298.12,1,0,1,199862.75,0 +5960,15665629,Chiang,719,Spain,Female,33,7,0,2,1,0,20016.59,0 +5961,15728917,Gill,598,France,Male,48,6,120682.53,1,1,0,30635.52,1 +5962,15762993,Trevisano,796,Spain,Male,32,5,102773.15,2,0,1,117832.88,0 +5963,15571193,Morrison,579,Germany,Male,42,0,144386.32,1,1,1,22497.1,1 +5964,15653521,Onuora,850,Germany,Female,40,7,104449.8,1,1,1,747.88,0 +5965,15802220,Ikenna,599,Spain,Male,35,6,137102.65,1,0,0,76870.81,0 +5966,15644132,Mancini,724,France,Female,30,9,142475.87,1,1,1,107848.24,0 +5967,15600832,Moss,508,France,Female,43,9,0,1,1,0,103726.71,0 +5968,15797919,Ting,773,Spain,Male,37,2,103195.2,2,1,0,178268.36,0 +5969,15603743,Tai,526,France,Male,28,1,112070.44,1,0,1,126281.83,0 +5970,15579714,Pan,542,France,Female,29,7,0,2,0,1,196651.72,0 +5971,15634295,Wilson,470,France,Male,35,1,96473.59,1,0,0,5962.3,0 +5972,15786680,Bianchi,805,Spain,Male,37,5,0,2,1,0,21928.81,0 +5973,15623499,Holman,548,Germany,Male,49,9,108437.89,1,0,0,127022.87,1 +5974,15691823,Obidimkpa,672,France,Male,37,5,153195.59,1,1,1,162763.01,0 +5975,15809279,Wallace,773,France,Male,45,8,96877.21,1,1,1,113950.51,0 +5976,15758039,Ash,614,France,Male,44,6,0,2,0,1,104930.46,0 +5977,15807163,Ku,537,France,Female,38,10,0,1,0,0,52337.97,1 +5978,15631639,Uspensky,704,France,Female,40,6,95452.89,1,0,1,179964.55,0 +5979,15713770,Shih,586,Spain,Male,41,3,63873.56,1,1,0,83753.64,0 +5980,15698167,Kumm,677,France,Female,24,0,148298.59,2,0,0,182913.95,0 +5981,15781710,Carey,558,Spain,Female,31,7,0,2,1,0,166720.28,0 +5982,15801296,Farber,634,Germany,Female,37,7,143258.85,2,1,0,192721.98,0 +5983,15704378,Calabrese,655,Germany,Male,37,9,121342.24,1,1,1,180241.44,0 +5984,15767891,Findlay,619,Germany,Female,28,6,99152.73,2,1,0,48475.12,0 +5985,15640667,Yu,662,France,Female,41,4,0,2,1,0,126551.48,0 +5986,15702145,Edments,705,Spain,Male,33,7,68423.89,1,1,1,64872.55,0 +5987,15679738,Brown,527,Spain,Female,35,8,0,1,1,0,98031.53,1 +5988,15636634,Lindon,630,Germany,Female,25,7,79656.81,1,1,0,93524.22,0 +5989,15809227,Chukwudi,850,France,Male,35,2,0,2,1,1,56991.66,0 +5990,15601811,Caldwell,668,France,Female,53,10,110240.04,1,0,0,183980.56,1 +5991,15625494,Li Fonti,573,France,Female,32,9,125321.84,2,1,1,130234.63,0 +5992,15723737,Pitcher,680,France,Male,27,3,0,1,1,0,32454.26,0 +5993,15682955,Capon,758,France,Female,32,2,84378.9,1,1,1,75396.43,0 +5994,15758856,Kable,597,France,Male,45,7,0,2,0,0,167756.45,0 +5995,15746065,Lo Duca,580,Germany,Male,35,10,136281.41,2,1,1,24799.47,0 +5996,15783865,Kulikova,622,France,Male,59,5,119380.37,1,1,1,60429.43,0 +5997,15745455,Navarrete,638,Germany,Male,62,4,108716.59,2,1,1,74241.09,0 +5998,15583033,Huguley,640,France,Female,20,4,0,2,0,1,78310.82,0 +5999,15644212,Han,644,Spain,Male,28,0,0,2,1,0,119419.37,0 +6000,15735688,Horsley,753,France,Female,31,6,106596.29,1,0,0,91305.77,0 +6001,15658577,Massie,629,France,Female,37,10,99546.25,3,0,1,25136.95,1 +6002,15606887,Singh,775,France,Female,30,5,0,1,1,0,193880.6,1 +6003,15783026,H?,701,France,Female,41,2,0,1,1,0,47856.78,0 +6004,15579892,Doyle,708,Spain,Male,19,7,112615.86,1,1,1,4491.77,0 +6005,15802088,Grant,521,Spain,Female,22,10,0,1,1,1,101311.95,0 +6006,15589323,Law,636,France,Female,24,9,0,2,0,1,38830.72,0 +6007,15636395,King,529,France,Female,31,5,0,2,1,0,26817.23,0 +6008,15712772,Onwubiko,757,France,Male,28,3,75381.15,1,1,1,199727.72,0 +6009,15700937,Romano,767,Spain,Female,24,5,0,2,1,1,67445.85,0 +6010,15766659,Okwudilichukwu,525,Spain,Male,33,5,0,2,1,0,161002.29,0 +6011,15814033,Milano,759,Spain,Male,38,1,0,2,1,0,20778.39,0 +6012,15783007,Parker,520,Germany,Female,45,1,123086.39,1,1,1,41042.4,1 +6013,15654183,Aitken,738,France,Female,26,3,0,2,1,0,67484.16,0 +6014,15609899,Obiora,548,Spain,Male,37,4,0,1,1,0,121763.68,0 +6015,15747323,Vasilyeva,535,Spain,Male,48,9,109472.47,1,1,0,157358.43,1 +6016,15582591,Chiabuotu,615,Spain,Male,59,4,155766.05,1,1,1,110275.17,0 +6017,15738835,Slater,850,Germany,Male,38,7,101985.81,2,0,0,43801.27,0 +6018,15782404,Hughes,487,France,Female,34,2,96019.5,1,0,0,9085,0 +6019,15697480,Menkens,731,France,Male,30,7,0,2,0,1,143086.09,0 +6020,15697045,Pisani,726,Spain,Female,35,9,0,2,0,1,100556.98,0 +6021,15781234,Y?an,609,France,Female,35,2,147900.43,1,1,0,140000.29,0 +6022,15579891,Milani,714,France,Male,52,4,100755.66,1,1,1,186775.25,0 +6023,15805690,Chin,694,Spain,Female,35,7,0,1,1,0,133570.43,1 +6024,15612139,Fu,786,France,Female,33,0,83036.05,1,0,1,154990.58,1 +6025,15568834,Howells,698,Spain,Male,27,6,125427.37,2,0,0,27654.44,0 +6026,15709917,Ni,601,France,Female,46,3,98202.76,1,0,0,137763.93,0 +6027,15718843,Maslova,769,Spain,Male,41,1,72509.91,1,1,0,25723.73,0 +6028,15799494,Forster,850,Germany,Male,44,3,140393.65,2,0,1,186285.52,0 +6029,15673439,Sun,646,Spain,Female,50,5,142644.64,2,1,1,142208.5,1 +6030,15669011,Bocharova,659,France,Female,44,9,23503.31,1,0,1,169862.01,1 +6031,15581388,Y?an,487,Spain,Male,33,8,145729.71,1,1,0,41365.85,0 +6032,15743153,Singh,740,Germany,Female,40,2,122295.17,2,1,1,30812.84,0 +6033,15579787,Nkemakonam,686,France,Male,39,4,0,2,1,0,155023.93,0 +6034,15759966,Chiemenam,612,Spain,Female,36,5,119799.27,2,1,0,159416.58,0 +6035,15601045,Angelo,655,Spain,Male,37,8,163708.58,2,0,0,76259.23,0 +6036,15764021,Frolov,617,France,Male,34,1,61687.33,2,1,0,105965.25,0 +6037,15687218,West,674,France,Female,27,4,79144.34,1,0,1,50743.83,0 +6038,15626452,Beatham,711,Spain,Male,32,5,0,2,1,1,147720.27,0 +6039,15700964,Pollard,624,Germany,Female,27,7,104848.68,1,1,1,167387.36,0 +6040,15768887,Hsing,597,Spain,Male,26,5,0,2,0,1,95159.13,0 +6041,15735358,Dowse,682,Spain,Male,46,4,0,1,1,1,4654.28,0 +6042,15749472,Lucciano,775,France,Male,45,8,0,1,1,0,130376.68,0 +6043,15685872,Godfrey,727,France,Female,29,1,146652.01,1,1,1,173486.39,0 +6044,15760851,Gratton,629,France,Male,31,6,0,2,1,0,93881.75,0 +6045,15734588,Manning,684,France,Male,46,0,0,2,1,1,36376.97,0 +6046,15784594,Mazzi,549,Germany,Female,37,1,130622.34,2,1,1,128499.94,0 +6047,15606435,Wall,593,Germany,Male,69,2,187013.13,2,0,1,105898.69,0 +6048,15790247,Sims,536,Spain,Male,40,9,0,2,1,1,11959.03,0 +6049,15676433,Allan,707,France,Female,36,6,0,1,0,0,98810.78,0 +6050,15625905,Griffen,592,Spain,Male,41,0,0,2,1,0,65906.07,0 +6051,15626414,Russell,703,France,Male,44,6,98862.54,1,1,0,151516.7,0 +6052,15623220,Brown,723,Spain,Female,45,4,0,2,1,0,37214.39,0 +6053,15752857,Palerma,452,Germany,Male,52,1,98443.14,2,0,0,92033.98,0 +6054,15677908,Gilbert,552,Spain,Male,42,4,0,2,0,0,195692.3,0 +6055,15773013,Uvarov,633,France,Female,47,0,0,1,1,1,6342.84,1 +6056,15623972,Wisdom,479,Germany,Female,23,9,123575.51,1,0,1,95148.28,0 +6057,15738627,Hussain,768,France,Male,25,6,0,2,1,1,21215.67,0 +6058,15643392,Woods,742,France,Male,31,4,105239.1,1,1,1,19700.24,0 +6059,15684868,Cameron,668,Germany,Male,56,9,110993.79,1,1,0,134396.64,1 +6060,15627854,Mai,707,Spain,Male,44,3,0,2,1,1,135077.01,0 +6061,15669253,Gibson,754,Spain,Male,39,7,157691.98,2,1,0,133600.89,1 +6062,15758023,Grigoryeva,544,Germany,Male,47,5,105245.21,1,0,0,99922.08,1 +6063,15574558,Gunter,718,Spain,Male,32,8,0,2,1,1,41399.33,0 +6064,15635256,Arcuri,762,France,Male,31,7,117687.35,1,1,1,159344.43,0 +6065,15680399,Tung,772,France,Male,23,2,0,2,1,0,18364.19,0 +6066,15674720,Smith,691,Germany,Female,37,7,123067.63,1,1,1,98162.44,1 +6067,15580249,Lori,502,France,Male,45,0,0,1,0,0,84663.21,0 +6068,15675431,Chidimma,563,France,Female,34,6,0,2,0,0,36536.93,0 +6069,15698285,Ting,676,France,Female,41,4,101457.14,1,1,1,79101.67,0 +6070,15810775,Tsao,576,Spain,Male,52,2,100549.43,2,1,1,16644.16,0 +6071,15678173,Collee,629,Spain,Male,35,4,174588.8,2,0,1,158420.14,0 +6072,15665222,Lettiere,625,Spain,Male,52,8,121161.57,1,1,0,48988.28,0 +6073,15803908,Fu,628,France,Male,45,9,0,2,1,1,96862.56,0 +6074,15586039,Bergamaschi,471,Germany,Female,36,5,90063.74,2,1,1,96366.7,0 +6075,15802570,Dyer,811,France,Female,45,5,0,2,1,1,146123.19,0 +6076,15781451,Buccho,504,France,Male,42,3,134936.97,2,0,0,135178.91,0 +6077,15721019,Jones,687,France,Female,24,3,110495.27,1,1,0,158615.41,0 +6078,15738588,Nebechi,660,Germany,Female,37,2,133200.09,1,0,0,71433.88,0 +6079,15730657,Ibekwe,548,France,Female,41,4,82596.8,1,0,1,55672.09,0 +6080,15739292,Gorshkov,609,Germany,Male,31,9,103837.75,1,1,1,150218.11,0 +6081,15725945,Nweke,659,Spain,Female,42,2,0,1,0,0,162734.31,1 +6082,15813159,Hairston,526,France,Male,52,8,93590.47,1,0,1,21228.71,1 +6083,15636820,Loggia,725,Germany,Male,40,8,104149.66,1,1,0,62027.9,0 +6084,15603880,Morgan,519,Germany,Male,38,1,114141.64,1,1,1,60988.21,1 +6085,15619494,Abdulov,562,Germany,Female,31,9,117153,1,1,1,108675.01,0 +6086,15596992,Norris,482,Germany,Male,45,7,156353.46,1,1,0,72643.95,1 +6087,15735025,Clark,535,Spain,Male,37,3,175534.78,2,1,1,9241.52,0 +6088,15730759,Chukwudi,561,France,Female,27,9,135637,1,1,0,153080.4,1 +6089,15752912,Perkin,661,France,Female,30,7,0,2,1,0,72196.57,0 +6090,15711316,Ch'ang,771,France,Male,27,2,0,2,1,1,199527.34,0 +6091,15738785,Kang,545,France,Male,26,7,0,2,0,1,156598.23,0 +6092,15777896,Chukwudi,850,Germany,Female,33,2,83415.04,1,0,1,74917.64,0 +6093,15628963,Frolova,601,Germany,Male,43,3,141859.12,2,1,1,111249.62,0 +6094,15742126,Chiu,712,Germany,Male,38,7,132767.66,2,1,1,59115.77,0 +6095,15575623,Simpson,589,France,Female,31,10,110635.32,1,1,0,148218.86,0 +6096,15741652,McLean,600,Spain,Male,37,8,177657.35,1,1,1,77142.32,0 +6097,15738884,Hu,642,Germany,Male,41,4,157777.58,1,1,0,67484.6,0 +6098,15615050,Savage,575,Germany,Male,47,9,107915.94,2,1,1,63452.18,1 +6099,15803005,Wallace,570,Germany,Female,57,5,86568.75,1,0,1,103660.31,0 +6100,15743498,Winter,532,Germany,Male,52,9,137755.76,1,1,0,163191.99,1 +6101,15720463,Ho,796,France,Male,30,2,137262.71,2,1,0,62905.29,0 +6102,15588695,Su,833,Spain,Male,32,6,0,1,1,1,44323.22,1 +6103,15665802,Li Fonti,642,Spain,Female,36,6,0,2,1,1,97938.59,0 +6104,15571144,Ives,655,France,Male,28,10,0,2,0,1,126565.21,0 +6105,15750731,Trevisani,736,Germany,Male,50,9,116309.01,1,1,0,185360.4,1 +6106,15605134,Bond,617,France,Female,34,0,131244.65,2,1,0,183229.02,0 +6107,15626044,Lettiere,762,Germany,Male,28,3,125155.83,2,1,1,106024.02,0 +6108,15737910,Houghton,703,Germany,Male,35,5,140691.08,2,1,0,167810.26,0 +6109,15761076,Lei,507,France,Male,41,3,58820.32,2,1,1,138536.09,0 +6110,15710105,Stirling,581,Germany,Female,26,3,105099.45,1,1,1,184520,1 +6111,15577402,Grant,593,France,Male,31,9,0,2,0,1,20492.16,0 +6112,15803337,Baresi,648,France,Male,23,9,168372.52,1,1,0,134676.72,0 +6113,15654372,Pearce,462,Germany,Male,34,1,94682.56,2,1,0,138478.2,0 +6114,15585867,Rutledge,596,Spain,Male,36,2,0,2,0,1,125557.95,0 +6115,15662488,Udegbunam,627,France,Female,44,5,0,2,1,0,82969.61,1 +6116,15604813,Zaytseva,494,France,Male,40,7,0,2,0,1,158071.69,0 +6117,15611644,Onyemauchechukwu,627,France,Male,73,0,146329.73,1,0,1,43615.67,0 +6118,15674928,Mullah,850,Spain,Male,37,2,0,2,1,0,119969.99,0 +6119,15656100,Candler,632,France,Female,49,5,167962.7,1,0,0,140201.21,0 +6120,15764293,Konovalova,490,France,Male,33,1,0,2,1,1,80792.83,0 +6121,15636423,Lei,715,France,Male,40,7,0,1,1,1,141359.11,0 +6122,15607629,Hollis,679,France,Male,48,8,0,2,1,0,23344.94,0 +6123,15577313,Lionel,619,France,Male,44,3,116967.68,1,1,0,5075.17,1 +6124,15714493,Francis,465,Spain,Female,33,6,0,2,1,1,95500.98,0 +6125,15643359,Carter,736,Spain,Male,32,7,0,1,0,1,79082.62,0 +6126,15687913,Mai,501,Germany,Female,34,7,93244.42,1,0,1,199805.63,0 +6127,15790935,Johnson,535,France,Female,29,5,0,2,0,1,52709.55,0 +6128,15708693,Sherman,759,France,Female,33,2,0,2,1,0,56583.88,0 +6129,15672016,Sabbatini,819,France,Male,35,1,0,2,0,1,3385.04,0 +6130,15727605,Shih,533,Germany,Male,43,4,80442.06,2,0,1,12537.42,0 +6131,15651144,Yao,632,Germany,Female,35,2,150561.03,2,0,0,64722.61,0 +6132,15749401,Ko,686,France,Male,60,9,0,3,1,1,75246.21,1 +6133,15691874,Kazakova,687,France,Female,34,9,125474.44,1,1,0,198929.84,0 +6134,15620735,Chiganu,667,Germany,Female,33,4,127076.68,2,1,0,69011.66,0 +6135,15769781,Nucci,699,Spain,Female,25,8,0,2,1,1,52404.47,0 +6136,15624611,Marsden,497,Spain,Male,37,8,128650.11,2,1,1,163641.53,0 +6137,15773071,Serena,780,Spain,Female,33,6,145580.61,1,1,1,154598.56,0 +6138,15720371,McLean,652,France,Female,51,3,0,1,1,0,173989.47,1 +6139,15717984,Longo,477,France,Male,47,9,144900.58,1,1,0,61315.37,1 +6140,15806407,Wilson,652,France,Female,37,4,0,2,1,0,143393.24,0 +6141,15785042,Hsiung,488,France,Female,31,8,97588.6,1,0,0,124210.53,0 +6142,15809302,Wright,572,France,Male,24,1,0,2,1,1,151460.84,0 +6143,15677550,Folliero,755,France,Female,38,1,0,2,1,0,20734.81,0 +6144,15654096,Johnston,779,Germany,Female,24,10,122200.31,2,1,0,43705.56,0 +6145,15617320,Palermo,693,Spain,Female,46,3,151709.33,1,1,0,180736.24,0 +6146,15653065,Nwabugwu,530,Spain,Female,22,7,0,2,1,0,104170.48,0 +6147,15649112,Endrizzi,738,Spain,Female,33,3,122134.4,2,0,1,27867.59,0 +6148,15690526,Tuan,690,Germany,Male,31,2,137260.45,2,1,0,55387.28,0 +6149,15806945,Udobata,611,France,Female,30,9,88594.14,1,1,0,196332.45,0 +6150,15670066,Ibezimako,643,Spain,Male,34,6,0,2,1,1,116046.22,0 +6151,15625761,Maclean,632,Germany,Male,41,8,127205.32,4,1,0,93874.87,1 +6152,15761525,Shaw,727,Spain,Female,31,10,96997.09,2,0,0,76614.04,0 +6153,15735080,Cummins,508,France,Female,64,2,0,1,1,1,6076.62,0 +6154,15619537,Lavrentiev,550,France,Male,31,5,142200.19,2,1,1,122221.71,0 +6155,15598162,Saunders,754,Germany,Female,39,3,160761.41,1,1,1,24156.03,0 +6156,15694300,Fiorentino,759,France,Male,26,4,0,2,1,0,135394.62,0 +6157,15637235,Knight,794,Spain,Male,33,8,0,2,0,0,91340.02,0 +6158,15612444,Manfrin,549,France,Male,29,3,0,2,1,0,146090.38,0 +6159,15626457,Zetticci,671,France,Male,31,0,116234.61,1,1,0,172096.08,0 +6160,15627995,Angelo,756,Germany,Female,26,5,155143.52,1,0,1,135034.57,1 +6161,15706128,Zhdanov,632,France,Female,21,1,0,2,1,0,84008.66,0 +6162,15666430,Peck,579,France,Male,38,8,0,2,0,0,91763.67,0 +6163,15627385,Uwaezuoke,748,France,Male,34,5,84009.47,1,1,1,137001.1,0 +6164,15581323,White,488,Germany,Female,28,7,139246.22,2,1,0,106799.49,0 +6165,15608109,Greco,710,Germany,Male,58,7,170113,2,0,1,10494.64,0 +6166,15801942,Chu,619,Spain,Female,41,8,0,3,1,1,79866.73,1 +6167,15567431,Kodilinyechukwu,773,France,Male,64,2,145578.28,1,0,1,186172.85,0 +6168,15810167,Scott,657,Spain,Male,75,7,126273.95,1,0,1,91673.6,0 +6169,15644501,Enyinnaya,579,France,Female,26,10,162482.76,1,1,1,18458.2,0 +6170,15785290,Hao,542,France,Male,29,9,0,1,1,0,8342.35,0 +6171,15611157,McElhone,709,France,Female,32,2,87814.89,1,1,0,138578.37,0 +6172,15673837,Ko,617,Spain,Male,61,3,113858.95,1,1,1,38129.22,0 +6173,15656822,Day,568,Germany,Male,43,5,87612.64,4,1,1,107155.4,1 +6174,15580560,Harris,769,France,Female,73,1,0,1,1,1,29792.11,0 +6175,15760641,Gerald,608,Germany,Male,26,1,106648.98,1,0,1,7063.6,0 +6176,15587584,Nebeuwa,503,Spain,Male,31,4,0,2,1,1,21645.06,0 +6177,15604146,Kaodilinakachukwu,608,Germany,Female,38,8,103653.51,2,1,1,137079.86,0 +6178,15813974,Maruff,731,Germany,Male,37,3,116880.53,1,0,0,172718.35,1 +6179,15746986,Howe,850,Germany,Female,40,4,97990.49,2,0,0,106691.02,0 +6180,15759741,Knepper,591,Germany,Female,34,4,150635.3,1,1,1,72274.84,0 +6181,15734892,Fennell,579,Spain,Male,37,4,0,2,1,1,32246.63,0 +6182,15797194,T'ao,570,France,Male,39,10,129674.89,2,1,0,80552.36,0 +6183,15723786,Morris,709,France,Female,37,9,0,2,1,0,16733.59,0 +6184,15642726,Holmes,611,France,Male,53,3,83568.26,1,0,0,1235.49,0 +6185,15664339,Yu,775,Spain,Male,48,4,178144.91,2,0,0,50168.41,1 +6186,15754526,Walker,699,Germany,Male,36,6,147137.74,1,1,1,33687.9,0 +6187,15703037,Edwards,618,France,Male,37,5,0,1,0,1,178705.45,1 +6188,15751412,Harvey,704,France,Male,36,3,114370.41,1,0,1,66810.48,0 +6189,15609558,McDonald,835,Germany,Female,47,5,108289.28,2,1,1,45859.55,1 +6190,15572408,Chambers,714,Germany,Male,39,3,149887.49,2,1,0,63846.36,0 +6191,15613923,Reed,581,Spain,Female,43,4,170172.9,1,0,1,100236.02,0 +6192,15747000,Shih,592,France,Male,27,3,0,2,1,1,19645.65,0 +6193,15731781,Onyemachukwu,551,France,Male,43,7,0,2,1,0,178393.68,0 +6194,15727198,Teng,689,Germany,Female,28,2,64808.32,2,0,0,78591.15,0 +6195,15794273,Hand,604,France,Female,56,0,62732.65,1,0,1,124954.56,0 +6196,15804950,Onyemauchechukwu,514,France,Female,41,7,0,2,1,1,3756.65,0 +6197,15576304,Bailey,698,France,Male,29,5,95167.55,1,1,1,152723.23,0 +6198,15645200,Chiang,581,Germany,Female,54,2,152508.99,1,1,0,187597.98,1 +6199,15779627,Maclean,573,Germany,Male,31,0,134644.19,1,1,1,70381.49,0 +6200,15750755,Yobachi,449,Spain,Female,33,8,0,2,0,0,156792.89,0 +6201,15569654,Munro,850,Germany,Female,31,3,51293.47,1,0,0,35534.68,0 +6202,15753079,Chidi,612,France,Male,41,5,0,3,0,0,151256.22,0 +6203,15684995,Chamberlain,690,Spain,Male,49,8,116622.73,1,0,1,51011.29,0 +6204,15790763,Trujillo,599,Spain,Female,49,2,0,2,1,0,111190.53,0 +6205,15766458,Tang,498,France,Male,33,1,198113.86,1,1,0,69664.35,0 +6206,15616221,Wilson,497,France,Female,29,4,85646.81,1,0,0,63233.02,1 +6207,15776124,Mann,802,Spain,Male,51,7,0,1,0,1,40855.79,0 +6208,15665811,Parry,644,France,Male,33,9,141234.98,1,1,0,95673.05,0 +6209,15729804,Manfrin,714,France,Male,34,10,0,2,1,1,80234.14,0 +6210,15714062,Millar,690,France,Female,40,9,77641.99,1,0,0,189051.59,1 +6211,15592197,Simmons,522,Spain,Male,30,3,0,2,1,0,145490.85,0 +6212,15793116,Beneventi,502,Germany,Female,40,7,117304.29,1,0,0,196278.32,0 +6213,15638231,Chung,730,Spain,Female,62,2,0,2,1,1,162889.1,0 +6214,15697678,Maxwell,590,Germany,Male,36,6,92340.69,2,1,1,174667.58,0 +6215,15800412,Dale,458,Germany,Male,35,9,146780.52,2,1,1,3476.38,0 +6216,15597610,Stevens,553,Spain,Male,41,6,144974.55,1,1,1,19344.92,0 +6217,15726634,Wei,479,France,Male,47,1,0,1,1,0,95270.83,0 +6218,15670866,Chiu,693,France,Male,31,2,0,2,1,1,107759.31,0 +6219,15667462,Duncan,707,Spain,Male,43,10,0,2,1,0,118368.2,0 +6220,15662574,Brady,636,Spain,Male,37,1,115137.26,1,1,0,52484.01,0 +6221,15716926,Macleod,807,France,Male,33,10,101952.97,2,1,0,178153.65,0 +6222,15603554,Berkeley,513,France,Female,45,0,164649.52,3,1,0,49915.52,1 +6223,15716800,Kaur,582,France,Male,31,2,0,2,1,1,33747.03,0 +6224,15679429,Bell,694,France,Male,32,0,91956.49,1,1,1,59961.81,0 +6225,15616122,Nwokike,777,France,Male,39,8,0,2,1,1,18613.52,0 +6226,15742172,Williamson,598,Germany,Male,32,9,123938.6,2,1,0,198894.42,0 +6227,15792305,Mountgarrett,762,Germany,Male,46,6,123571.77,3,0,1,57014.17,1 +6228,15636016,Wreford,588,France,Female,34,3,120777.88,1,1,1,131729.52,0 +6229,15733138,Paterson,663,Germany,Male,42,5,90248.79,1,1,1,79169.73,0 +6230,15669741,Hou,777,France,Male,36,7,0,1,1,0,106472.34,0 +6231,15616954,Smith,592,France,Male,71,4,0,2,0,1,17013.54,0 +6232,15729238,Peng,631,Germany,Male,48,1,106396.48,1,1,1,150661.42,1 +6233,15718242,Wollstonecraft,725,Germany,Female,47,1,104887.43,1,0,0,86622.56,1 +6234,15682914,Bolton,850,France,Male,34,2,72079.71,1,1,1,115767.93,0 +6235,15654274,Corrie,540,France,Male,37,6,0,2,1,0,141998.89,0 +6236,15691457,Boyle,674,Spain,Male,36,2,0,2,1,1,182787.17,0 +6237,15719649,Lambie,553,France,Male,38,3,99844.68,1,0,0,187915.7,0 +6238,15778897,Cartwright,630,France,Female,28,1,0,2,1,1,133267.78,0 +6239,15589437,Lu,466,France,Male,26,3,156815.71,1,1,1,137476.09,0 +6240,15682369,Pisano,613,France,Male,47,6,146034.74,1,1,1,77146.14,0 +6241,15626507,Chukwubuikem,558,France,Male,27,1,152283.39,1,1,0,183271.15,0 +6242,15571995,Harper,775,Germany,Female,33,1,118897.1,2,1,1,26362.4,0 +6243,15673333,Wilson,698,Germany,Male,52,8,96781.39,1,1,1,153373.71,0 +6244,15748752,Ch'in,608,Germany,Male,33,1,102772.67,2,1,0,70705.58,0 +6245,15725302,Streeton,670,Spain,Female,20,4,0,2,1,0,119759.24,0 +6246,15722083,Ch'ang,591,Spain,Male,39,8,0,2,0,0,42392.24,0 +6247,15771442,Pennington,633,France,Male,40,4,150578,1,0,1,34670.62,1 +6248,15803633,T'ien,678,France,Female,46,1,0,2,0,0,82106.19,0 +6249,15672185,Liu,590,France,Male,47,3,0,2,1,0,171774.5,0 +6250,15806486,Cunningham,705,France,Female,48,0,0,2,0,0,149772.61,0 +6251,15570895,Ch'in,608,France,Male,42,10,163548.07,1,1,0,38866.85,0 +6252,15614520,Smith,682,France,Female,37,8,148580.12,1,1,0,35179.18,0 +6253,15687492,Anderson,596,Germany,Male,32,3,96709.07,2,0,0,41788.37,0 +6254,15675337,Forbes,395,Germany,Female,34,5,106011.59,1,1,1,17376.57,1 +6255,15721047,Ansell,578,Germany,Male,37,1,135650.88,1,1,0,199428.19,0 +6256,15589017,Chiu,547,Germany,Male,55,4,111362.76,3,1,0,16922.28,1 +6257,15611186,Yevdokimova,609,France,Male,37,1,39344.83,1,1,1,178291.89,1 +6258,15617301,Chamberlin,774,Germany,Male,36,9,130809.77,1,1,0,152290.28,0 +6259,15726046,Johnston,712,France,Female,27,2,133009.51,1,1,0,126809.15,0 +6260,15585748,McDonald,585,Germany,Female,28,9,135337.49,2,1,1,40385.61,0 +6261,15672826,Chen,666,France,Female,32,10,112536.57,2,1,1,34350.54,0 +6262,15595162,Cattaneo,708,Spain,Female,35,8,122570.69,1,0,0,199005.88,0 +6263,15650026,Barclay-Harvey,513,France,Male,44,1,63562.02,2,0,1,52629.73,1 +6264,15745826,Dawson,445,France,Male,37,3,0,2,1,1,180012.39,0 +6265,15708610,Costa,690,Germany,Male,44,9,100368.63,2,0,0,35342.33,0 +6266,15624471,Chikwado,850,France,Male,37,6,0,2,1,0,109291.22,0 +6267,15590097,Ch'eng,537,Spain,Female,33,7,136082,1,1,0,62746.54,0 +6268,15689328,Harrison,705,Germany,Male,48,9,114169.16,1,0,0,173273.2,1 +6269,15582154,Crawford,670,France,Female,45,5,47884.92,1,1,1,54340.24,0 +6270,15734626,Gibson,652,Spain,Female,36,1,0,2,1,1,19302.78,0 +6271,15702806,Martin,696,Spain,Male,24,9,0,1,0,0,10883.52,0 +6272,15620756,Stokes,747,France,Male,49,6,202904.64,1,1,1,17298.72,1 +6273,15611331,Niu,511,France,Female,46,1,0,1,1,1,115779.48,1 +6274,15576935,Ampt,743,Spain,Male,43,2,161807.18,2,0,1,93228.86,1 +6275,15661275,Wynn,532,Germany,Male,52,3,110791.97,1,1,0,148704.77,1 +6276,15814940,Lawrence,642,Spain,Female,33,9,0,2,1,1,150475.14,0 +6277,15768471,Wagner,554,Germany,Female,54,6,108755,1,1,0,40914.32,1 +6278,15697391,Argyle,604,Spain,Female,34,3,0,2,1,0,38587.7,0 +6279,15793346,Ofodile,602,France,Female,72,3,0,2,1,1,171260.66,0 +6280,15608338,Chiemenam,757,Spain,Female,55,9,117294.12,4,1,0,94187.47,1 +6281,15578546,Akobundu,491,Germany,Male,26,4,102251.14,1,1,1,145900.89,0 +6282,15656921,Locke,850,France,Male,31,4,0,2,0,0,152298.28,0 +6283,15761340,Bullen,521,France,Male,22,5,0,2,1,1,99828.45,0 +6284,15591135,Forster,726,France,Male,37,2,132057.92,2,1,0,34743.98,0 +6285,15623219,Smith,596,France,Male,33,8,0,1,1,0,121189.3,1 +6286,15655229,Craig,850,Germany,Female,35,7,114285.2,1,0,1,129660.59,0 +6287,15805884,Archer,637,France,Female,41,9,0,2,1,0,145477.36,0 +6288,15668289,McWilliams,690,Spain,Male,32,2,76087.98,1,0,1,151822.66,0 +6289,15568562,Moss,689,France,Male,40,8,160272.27,1,1,0,49656.24,0 +6290,15773276,Townsend,633,Spain,Male,63,4,114552.6,1,1,0,73856.28,1 +6291,15622801,Brown,555,France,Female,27,8,102000.17,1,1,1,116757,0 +6292,15779886,Munson,563,Spain,Male,24,7,0,2,0,0,16319.56,0 +6293,15713673,T'ien,494,France,Female,33,1,137853,1,0,1,90273.85,0 +6294,15783083,Shubin,534,France,Male,27,9,0,2,1,0,161344.13,0 +6295,15742824,Isayeva,696,Germany,Male,42,7,162318.61,1,1,0,121061.89,0 +6296,15621550,Hung,535,Spain,Female,50,1,140292.58,3,0,0,69531.22,1 +6297,15799480,Webb,600,France,Male,34,0,0,2,0,1,3756.23,0 +6298,15625247,Scott,807,France,Female,34,1,0,1,0,0,114448.13,0 +6299,15755241,Rahman,714,France,Female,52,2,0,1,0,1,144045.08,1 +6300,15575679,Lori,590,France,Male,24,7,126431.54,1,1,0,58781.11,0 +6301,15668235,Cooke,614,France,Female,41,3,123475.04,1,1,1,179227.52,0 +6302,15683183,Volkova,766,Germany,Female,45,6,97652.96,1,1,0,127332.33,0 +6303,15684592,Lamb,557,Spain,Male,42,4,0,2,0,1,86642.38,0 +6304,15591169,Hawes,788,Germany,Female,49,4,137455.99,1,1,0,184178.29,1 +6305,15653455,Smith,648,France,Female,38,2,0,2,0,1,9551.49,0 +6306,15732563,Swanton,726,Germany,Female,33,7,99046.31,2,1,1,56053.06,0 +6307,15656471,Mitchell,773,France,Male,33,9,0,2,1,1,1118.31,0 +6308,15598510,Colombo,583,Germany,Male,27,4,105907.42,2,1,1,195732.04,0 +6309,15766427,Shaw,565,Germany,Male,52,5,97720.35,2,1,0,175070.94,1 +6310,15785342,Shipp,705,France,Male,25,9,0,2,0,1,112331.19,0 +6311,15641595,Jonathan,685,Spain,Male,43,4,97392.18,2,1,0,43956.83,0 +6312,15798429,Hernandez,741,France,Male,29,8,0,2,1,1,115994.52,0 +6313,15648136,Green,658,Germany,Female,28,9,152812.58,1,1,0,166682.57,0 +6314,15812482,Young,575,France,Male,27,3,139301.68,1,1,0,99843.98,0 +6315,15790810,Han,844,France,Female,41,10,76319.64,1,1,1,141175.18,1 +6316,15687421,Highland,559,Spain,Male,67,9,125919.35,1,1,0,175910.95,1 +6317,15765643,Hamilton,725,France,Male,37,6,124348.38,2,0,1,176984.34,0 +6318,15654878,Yobanna,450,France,Male,29,7,117199.8,1,1,1,43480.63,0 +6319,15686835,Crawford,738,Germany,Female,57,9,148384.64,1,0,0,155047.11,1 +6320,15768340,Beavers,642,Germany,Female,19,3,113905.48,1,1,1,176137.2,0 +6321,15673599,Williamson,618,Spain,Male,32,5,133476.09,1,0,1,154843.4,0 +6322,15689096,Beneventi,590,France,Male,47,0,117879.32,1,1,1,8214.46,0 +6323,15684294,Chidumaga,735,France,Male,50,2,0,2,0,1,147075.69,0 +6324,15615828,Mitchell,550,France,Male,34,8,122359.5,1,0,0,116495.55,0 +6325,15746012,Chibugo,729,Spain,Female,28,0,0,2,1,1,31165.06,1 +6326,15615797,Hyde,743,Germany,Male,59,5,108585.35,1,1,1,192127.22,1 +6327,15788494,Alekseeva,555,France,Male,31,8,145875.74,1,1,0,137491.23,0 +6328,15793856,Abdulov,667,Spain,Female,36,3,121542.57,2,1,1,186841.71,0 +6329,15629545,Buckley,790,Spain,Female,41,7,109508.68,1,0,0,86776.38,0 +6330,15661198,Howard,727,Germany,Male,34,2,146407.11,1,1,1,72073.72,0 +6331,15715117,Peel,744,France,Female,39,6,0,1,0,0,10662.58,0 +6332,15701074,Herz,629,Germany,Male,35,8,112330.83,1,1,1,91001.02,0 +6333,15793046,Holden,619,France,Female,35,4,90413.12,1,1,1,20555.21,0 +6334,15623744,McLean,634,France,Male,34,8,105302.66,1,1,1,123164.97,0 +6335,15611329,Findlay,608,Spain,Female,35,6,0,2,1,1,143463.28,0 +6336,15740428,Wyatt,507,France,Female,35,1,0,2,0,0,92131.54,0 +6337,15781534,Rapuluolisa,536,Germany,Female,35,4,121520.36,1,0,0,77178.42,0 +6338,15618243,Buckland,730,Spain,Female,43,1,103960.38,1,1,1,193650.16,0 +6339,15784161,Hargreaves,583,Germany,Male,39,8,102945.01,1,0,0,52861.89,0 +6340,15700325,Onyeoruru,644,France,Female,24,8,92760.55,1,1,0,35896.75,0 +6341,15659064,Salas,790,Spain,Male,37,8,0,2,1,1,149418.41,0 +6342,15658364,Laney,807,Germany,Female,40,1,134590.21,1,1,1,46253.65,0 +6343,15704340,Fu,581,France,Female,37,10,104255.03,1,1,0,86609.37,0 +6344,15793455,Tien,627,Spain,Female,55,6,0,1,0,0,91943.94,1 +6345,15579777,Sazonova,850,France,Male,41,3,0,2,1,0,128892.36,0 +6346,15632345,Tuan,754,France,Female,35,4,0,2,1,0,44830.71,0 +6347,15814468,Wei,551,Germany,Male,50,1,121399.98,1,0,1,84508.44,1 +6348,15754820,Bergamaschi,637,Germany,Male,35,8,147127.81,2,1,1,84760.7,0 +6349,15707505,Taylor,699,Spain,Male,31,8,125927.51,2,1,0,147661.47,0 +6350,15699507,Messersmith,542,France,Female,25,7,0,2,0,1,82393.08,0 +6351,15799600,Coles,640,Germany,Male,48,1,111599.32,1,0,1,135995.58,0 +6352,15794472,Brookes,553,France,Female,27,3,0,2,0,0,159800.16,0 +6353,15646632,Reid,741,France,Male,38,9,0,2,1,0,14379.01,0 +6354,15676353,Etheridge,598,France,Male,35,8,114212.6,1,1,1,74322.85,0 +6355,15566312,Jolly,660,Spain,Female,42,5,0,3,1,1,189016.24,1 +6356,15570414,Chizoba,618,Spain,Male,41,4,115251.64,1,0,0,136435.75,0 +6357,15776743,Eberegbulam,647,France,Male,43,9,0,2,1,1,78488.39,0 +6358,15674637,Pagnotto,491,France,Female,68,3,107571.61,1,0,1,113695.99,0 +6359,15730418,Lucchesi,652,France,Female,32,2,0,2,1,0,54628.11,0 +6360,15739972,Hughes,650,Germany,Female,45,9,152367.21,3,1,0,150835.21,1 +6361,15661591,Panicucci,413,Germany,Male,39,1,130969.77,2,1,1,158891.79,0 +6362,15675585,Burns,416,Germany,Female,25,0,97738.97,2,1,1,160523.33,0 +6363,15814750,Ricci,629,Spain,Male,34,8,0,2,1,1,180595.02,0 +6364,15593454,Lambert,678,Spain,Female,40,4,113794.22,1,1,0,16618.76,0 +6365,15663421,Esposito,527,Spain,Male,28,6,128396.33,2,1,0,79919.97,0 +6366,15576196,Benson,743,Spain,Female,48,5,118207.69,2,0,0,186489.14,1 +6367,15677324,Botts,683,Germany,Male,73,9,124730.26,1,1,1,51999.5,0 +6368,15568742,Parkes,536,France,Female,41,9,0,1,1,0,121299.14,0 +6369,15693764,Mai,663,Spain,Male,52,0,136298.65,1,1,0,144593.3,1 +6370,15714260,Castiglione,646,France,Female,38,2,0,2,0,0,178752.73,0 +6371,15798200,Manna,707,France,Male,35,2,0,3,1,1,94148.3,0 +6372,15656627,Lin,602,France,Male,34,5,0,2,1,1,77414.45,0 +6373,15791111,Fink,635,France,Female,47,2,125724.95,2,1,0,63236.97,0 +6374,15638269,Baresi,597,France,Male,67,2,0,2,0,1,108645.85,0 +6375,15807473,Morehead,503,France,Male,38,1,0,2,1,1,95153.24,0 +6376,15708534,Afamefuna,524,Spain,Female,64,5,0,1,1,0,136079.64,1 +6377,15640686,Greco,700,France,Male,46,5,95872.86,1,1,0,98273.01,1 +6378,15588904,Balashova,692,France,Male,33,9,0,1,1,0,113505.93,1 +6379,15768763,Bogdanov,562,France,Male,37,2,0,1,0,1,52525.15,1 +6380,15770543,Lowe,679,France,Male,37,7,74260.03,1,1,0,194617.98,0 +6381,15642162,Ponce,603,Germany,Male,35,1,123407.69,1,1,0,152541.89,1 +6382,15714046,Trevisano,720,Spain,Male,33,3,123783.91,2,1,1,142903.44,0 +6383,15575060,Gardner,797,France,Male,24,5,0,2,1,0,182257.61,0 +6384,15812040,Lorenzo,594,France,Male,36,6,153880.15,1,0,0,135431.72,0 +6385,15812073,Palmer,529,France,Female,31,7,0,2,1,1,175697.87,0 +6386,15706810,Zuyeva,606,Germany,Female,32,1,106301.85,2,0,1,59061.25,0 +6387,15584090,Jen,621,Spain,Female,40,7,0,2,0,1,131283.6,1 +6388,15810807,Alekseeva,513,France,Female,43,9,0,2,1,0,152499.8,0 +6389,15582033,Manfrin,753,Germany,Male,44,3,138076.47,1,1,0,15523.09,1 +6390,15687607,Chiemenam,605,France,Female,30,9,135422.31,1,0,1,186418.85,0 +6391,15588406,Chiemenam,574,Spain,Female,37,7,0,2,1,0,32262.28,0 +6392,15784099,Clark,726,France,Female,38,5,126875.62,1,1,0,128052.29,0 +6393,15701352,Fanucci,611,Spain,Female,28,3,96381.68,2,1,0,181419.29,0 +6394,15789371,Cattaneo,593,Germany,Female,41,4,119703.1,2,1,1,109783.29,0 +6395,15602845,Udinesi,466,Germany,Male,41,2,152102.18,2,1,0,181879.56,0 +6396,15707918,Bentley,741,Germany,Female,36,0,127675.39,2,1,0,74260.16,0 +6397,15602812,Holmes,684,Germany,Female,44,2,133776.86,2,0,1,49865.04,0 +6398,15675888,Austin,550,Spain,Female,33,9,72788.03,1,1,1,103608.06,0 +6399,15591822,Mackenzie,593,Spain,Male,26,9,76226.9,1,1,0,167564.82,0 +6400,15738501,Booth,601,Germany,Male,48,9,163630.76,1,0,1,41816.49,1 +6401,15585907,Collier,676,Spain,Female,30,5,0,2,0,0,179066.58,0 +6402,15579040,Hs?,556,France,Female,46,10,0,2,0,0,109184.24,0 +6403,15804211,Oluchukwu,719,France,Male,36,3,155423.17,1,1,1,199841.32,0 +6404,15736126,Sung,850,Germany,Male,55,0,98710.89,1,1,1,83617.17,1 +6405,15745399,Marino,649,Spain,Female,49,2,0,1,1,0,84863.85,1 +6406,15760749,Vinogradov,509,Spain,Male,41,7,126683.8,1,0,1,114775.53,0 +6407,15637118,Burns,684,France,Male,33,4,140700.61,1,1,0,103557.93,0 +6408,15657829,Fanucci,806,Germany,Male,30,8,168078.83,1,1,0,85028.36,1 +6409,15738497,Chukwujamuike,729,Spain,Male,44,4,107726.93,2,1,0,153064.87,0 +6410,15690695,Flynn,683,France,Female,33,9,0,2,1,1,38784.42,0 +6411,15762351,Chao,689,Spain,Female,63,1,0,2,1,1,186526.12,0 +6412,15791172,Yeh,672,Germany,Female,21,1,35741.69,1,1,0,28789.94,0 +6413,15598982,Klein,602,Germany,Female,53,5,98268.84,1,0,1,45038.29,1 +6414,15734765,Mahmood,739,France,Female,20,4,133800.98,1,0,1,150245.81,0 +6415,15642912,Tu,618,France,Female,21,2,125682.79,1,0,0,57762,0 +6416,15769516,Shcherbakov,674,France,Female,42,9,0,2,1,0,4292.72,0 +6417,15789379,Zetticci,762,France,Male,26,6,130428.78,1,1,0,173365.89,0 +6418,15695103,Carr,790,Spain,Male,37,6,0,2,1,1,119484.01,0 +6419,15801924,Browne,754,Spain,Female,27,8,0,2,0,0,121821.16,0 +6420,15767804,Feng,729,France,Male,44,6,0,2,1,0,151733.43,0 +6421,15718039,Ferguson,606,Germany,Female,47,0,137138.2,2,0,1,53784.22,0 +6422,15579994,Shaw,616,France,Male,23,8,73112.95,1,1,1,62733.05,0 +6423,15595037,Palermo,772,France,Male,47,9,152347.01,1,0,1,17671.78,0 +6424,15600720,Moore,652,Spain,Male,41,8,115144.68,1,1,0,188905.43,0 +6425,15782608,Huang,743,France,Male,43,5,0,2,0,0,113079.19,1 +6426,15566894,Gray,793,France,Male,39,3,137817.52,1,0,0,83997.79,0 +6427,15749123,Sokolova,743,Spain,Male,45,7,157332.26,1,1,0,125424.42,0 +6428,15668943,Henderson,746,France,Male,37,2,0,2,1,0,143194.05,0 +6429,15577423,Mosley,627,Germany,Female,39,5,124586.93,1,1,0,93132.61,1 +6430,15623102,Nnaemeka,713,Spain,Male,38,6,116980.78,2,0,1,76038.38,0 +6431,15728012,Everett,678,Spain,Female,40,3,128398.38,1,1,0,168658.3,0 +6432,15683363,Goddard,540,Spain,Male,39,1,0,1,0,1,108419.41,0 +6433,15699335,Kuo,615,Germany,Female,33,3,137657.25,2,1,1,171657.57,0 +6434,15574369,Bianchi,415,Spain,Male,53,5,167259.44,1,1,1,22357.25,0 +6435,15703167,Rouse,628,France,Female,45,8,0,2,1,0,193903.06,0 +6436,15754874,Nwoye,700,France,Male,26,4,119009.57,1,1,0,141926.43,0 +6437,15723216,Greco,623,Germany,Male,33,2,80002.33,1,1,1,104079.62,0 +6438,15725094,Fang,623,France,Female,37,4,140211.88,1,1,1,93832.33,0 +6439,15647974,Chiemenam,679,France,Female,44,3,118742.74,2,1,0,1568.91,0 +6440,15583371,Artemiev,632,Spain,Male,37,1,138207.08,1,1,0,60778.11,1 +6441,15772559,Burrows,790,France,Female,47,10,148636.21,1,0,1,16119.96,1 +6442,15711251,Chizuoke,514,France,Male,45,1,178827.79,1,1,0,60375.18,0 +6443,15719212,T'ien,491,France,Male,33,5,83134.3,1,1,0,187946.55,0 +6444,15764927,Rogova,753,France,Male,92,3,121513.31,1,0,1,195563.99,0 +6445,15731412,Trevisano,693,Germany,Female,37,6,95900.04,1,1,1,38196.24,0 +6446,15719170,Sagese,679,France,Female,30,1,112543.42,1,1,1,179435.21,0 +6447,15596011,Artyomova,529,Spain,Male,34,9,0,1,1,1,93208.22,0 +6448,15614834,Long,619,Spain,Female,31,3,141751.82,1,0,1,61531.86,0 +6449,15600510,Hsueh,680,Spain,Female,37,6,124140.57,2,1,0,92826.35,0 +6450,15625706,White,693,Germany,Male,45,2,116546.59,2,0,0,23140.28,1 +6451,15781409,Lazarev,834,France,Female,28,6,0,1,1,0,74287.53,0 +6452,15722583,Benjamin,636,Spain,Female,29,6,157576.47,2,1,1,101102.39,0 +6453,15677243,Wan,538,Spain,Male,43,5,0,2,1,0,126933.73,0 +6454,15815070,Romano,566,Germany,Female,44,5,141428.99,2,0,0,68408.74,0 +6455,15705899,Craig,597,Spain,Male,35,0,127510.99,1,1,1,155356.34,0 +6456,15701522,Yermolayeva,711,France,Female,29,9,0,2,0,1,3234.8,0 +6457,15755978,Tseng,606,France,Male,31,10,0,2,1,0,195209.4,0 +6458,15722090,Tseng,615,Spain,Male,51,6,81818.49,1,1,1,169149.38,0 +6459,15783526,Le Hunte,589,France,Male,36,1,100895.54,1,1,1,68075.14,0 +6460,15632125,Blake,606,Germany,Male,45,5,63832.43,1,1,1,93707.8,0 +6461,15688395,Lane,582,France,Male,29,4,0,2,0,0,156153.27,0 +6462,15666975,Sparks,710,France,Female,36,4,116085.06,1,1,0,58601.61,0 +6463,15682211,Tu,467,France,Male,57,1,0,2,1,1,114448.77,0 +6464,15637411,Tochukwu,749,France,Male,30,1,0,2,0,1,126551.65,0 +6465,15591512,Whittaker,564,Germany,Female,33,2,115761.51,1,0,1,112350.21,1 +6466,15606855,Wang,730,Spain,Male,26,6,0,2,1,1,185808.7,0 +6467,15763683,Northern,678,Germany,Male,32,4,139626.01,1,1,1,118235.52,1 +6468,15641782,Humphries,540,France,Female,31,7,0,1,0,1,183051.6,1 +6469,15677184,Cremonesi,767,France,Female,35,6,115576.44,1,0,1,27922.45,0 +6470,15775042,Ku,615,France,Female,23,4,0,2,1,0,196476.19,0 +6471,15616630,Tobenna,583,Germany,Female,41,5,77647.6,1,1,0,190429.52,0 +6472,15800233,Okwuadigbo,850,France,Female,40,5,0,2,1,0,35034.15,0 +6473,15588419,Johnston,651,Germany,Female,34,10,148962.46,1,1,0,66389.43,1 +6474,15595557,Li,798,France,Male,22,8,0,2,1,0,107615.43,0 +6475,15626143,Talbot,695,France,Male,37,2,0,2,1,1,99692.65,0 +6476,15566030,Tu,497,Germany,Male,41,5,80542.81,1,0,0,88729.22,1 +6477,15701412,T'ien,739,France,Male,40,4,0,2,0,0,173321.65,0 +6478,15702464,Ross,549,France,Female,34,4,0,2,0,0,139463.57,0 +6479,15573348,Maclean,850,France,Male,35,9,102050.47,1,1,1,3769.71,0 +6480,15704160,Wan,648,Spain,Male,49,5,0,1,1,0,149946.43,1 +6481,15693704,Tsou,679,France,Female,24,6,114948.76,2,0,1,135768.25,0 +6482,15664752,Jack,606,Germany,Male,39,8,136000.45,2,1,0,31708.53,0 +6483,15628292,Lucchesi,850,France,Male,32,4,156001.68,2,1,1,151677.31,0 +6484,15621195,Ch'eng,619,Germany,Male,41,3,147974.16,2,1,0,170518.83,0 +6485,15668629,Saunders,719,Spain,Male,44,2,0,2,1,0,196582.19,0 +6486,15635197,Glover,640,Germany,Male,26,5,90402.77,1,1,1,3298.65,0 +6487,15592761,Tung,710,France,Male,40,5,0,2,0,0,162878.96,0 +6488,15574283,Padovano,580,France,Male,31,2,0,2,0,1,64014.24,0 +6489,15598097,Johnstone,550,France,Male,44,9,0,2,1,0,26257.01,0 +6490,15711352,Endrizzi,841,France,Female,31,3,162701.65,2,1,1,126794.56,0 +6491,15620751,Secombe,760,France,Male,34,2,0,2,1,0,164162.44,0 +6492,15656717,Elewechi,687,France,Female,30,6,0,2,0,0,179206.92,0 +6493,15643121,Chu,753,Germany,Female,35,5,82453.96,2,0,0,18254.75,0 +6494,15723671,Lucciano,661,France,Male,35,9,100107.99,1,1,0,83949.68,0 +6495,15752846,Pinto,699,France,Male,28,7,0,2,1,1,22684.78,0 +6496,15640852,McGregor,617,Germany,Female,39,5,83348.89,3,1,0,7953.62,1 +6497,15789313,Ugorji,595,Germany,Female,44,4,96553.52,2,1,0,143952.24,1 +6498,15793688,Bancks,669,France,Male,50,9,201009.64,1,1,0,158032.5,1 +6499,15770405,Warlow-Davies,613,France,Female,27,5,125167.74,1,1,0,199104.52,0 +6500,15702561,Dale,782,France,Male,32,9,0,1,1,1,87566.97,0 +6501,15625964,Buckley,582,France,Female,43,5,153313.67,1,0,0,170563.73,0 +6502,15761364,Nkemjika,679,France,Male,30,9,0,2,1,0,157871.55,0 +6503,15590286,Fairley,611,France,Female,40,2,125879.29,1,1,0,93203.43,0 +6504,15587978,Boothby,455,Germany,Female,37,6,170057.62,1,0,1,54398.56,0 +6505,15773242,Chukwuhaenye,621,France,Male,32,1,0,2,1,1,168779.47,0 +6506,15761053,Lock,596,Germany,Male,48,2,131326.47,1,0,0,1140.02,1 +6507,15702095,Clarke,585,Spain,Female,56,1,128472.8,1,1,0,186476.91,1 +6508,15764253,Ramsey,742,France,Male,32,6,160485.16,1,1,0,29023.03,0 +6509,15700801,Eipper,850,Germany,Male,42,6,84445.68,3,0,1,60021.34,1 +6510,15730590,Ko,738,Germany,Female,40,1,115409.18,2,0,0,180456.8,0 +6511,15643916,Munro,619,Spain,Male,46,8,62400.48,1,1,1,132498.39,1 +6512,15720636,McGregor,628,France,Female,50,4,143054.56,1,0,1,109608.81,1 +6513,15795429,Henderson,487,France,Male,24,7,133628.09,2,1,1,98570.01,0 +6514,15609254,Fernandez,513,Spain,Female,41,9,107135.04,2,1,1,160546.58,0 +6515,15625141,Porter,563,Spain,Male,26,7,0,2,0,0,6139.74,0 +6516,15810898,Pan,803,France,Female,65,2,151659.52,2,0,1,6930.17,0 +6517,15775797,Esposito,607,Spain,Female,32,7,0,3,0,1,10674.62,0 +6518,15795246,Kaeppel,628,Germany,Female,51,9,155903.82,2,1,1,71159.84,0 +6519,15795275,Lamb,521,Spain,Female,49,4,82940.25,2,0,0,62413.01,1 +6520,15571869,Lei,669,Germany,Female,50,4,112650.89,1,0,0,166386.22,1 +6521,15694143,Conti,686,France,Female,41,10,0,1,1,0,133086.45,0 +6522,15748231,Hargreaves,700,Germany,Male,35,4,95853.39,2,1,0,192933.37,0 +6523,15632185,Yermolayev,663,France,Female,42,1,82228.67,2,1,0,71359.78,0 +6524,15806249,Kerr,671,Spain,Female,31,4,0,2,0,1,79270.02,0 +6525,15743293,Waters,651,Germany,Female,35,1,163700.78,3,1,1,29583.48,1 +6526,15598157,Onyeorulu,728,France,Male,34,4,106328.08,1,1,0,88680.65,0 +6527,15700946,Kolesnikova,574,France,Female,34,7,152992.91,1,1,1,134691.2,0 +6528,15722692,Kazakova,464,France,Male,38,3,116439.65,1,1,0,75574.48,0 +6529,15696506,MacDonald,604,Spain,Male,27,9,101352.78,1,0,0,30252.3,0 +6530,15728823,Sharwood,836,Spain,Female,37,10,0,2,1,0,111324.41,0 +6531,15808851,Bufkin,511,Germany,Female,75,9,105609.17,1,0,1,105425.18,0 +6532,15675231,Nwankwo,518,France,Female,45,8,0,2,1,1,36193.07,0 +6533,15732299,Boniwell,756,France,Male,67,4,0,3,1,1,93081.87,0 +6534,15706269,Willis,489,France,Female,47,8,103894.38,2,1,1,107625.46,0 +6535,15590078,Burns,622,Spain,Male,27,9,139834.93,1,1,1,152733.89,0 +6536,15776985,Kung,652,France,Female,36,6,112518.71,2,0,1,110421.31,0 +6537,15756743,Howells,625,France,Female,37,7,115895.42,1,1,0,48486.25,0 +6538,15782364,Bevan,521,Spain,Female,39,3,146408.68,1,0,0,72993.67,0 +6539,15604093,Neitenstein,546,France,Male,34,4,165363.31,2,1,1,25744.13,1 +6540,15749328,Johnson,697,France,Female,45,1,0,2,1,0,46807.62,1 +6541,15656322,Sandover,571,Germany,Male,33,3,71843.15,1,1,0,26772.04,0 +6542,15685564,Nnamutaezinwa,748,Spain,Male,35,5,105492.53,1,1,1,150057.2,0 +6543,15785831,Sinclair,591,France,Male,35,7,183027.25,1,1,1,56028.79,0 +6544,15796218,Wei,814,Germany,Male,29,1,131968.57,2,1,1,147693.92,0 +6545,15716218,Higgins,709,France,Female,45,3,104118.5,1,0,1,174032,0 +6546,15572735,Chang,433,Spain,Male,27,2,0,2,1,1,153698.65,0 +6547,15633840,Henderson,781,France,Male,20,0,125023.1,2,1,1,108301.45,0 +6548,15608760,Cox,656,France,Female,30,4,74323.2,1,1,1,22929.08,0 +6549,15627848,Tsui,683,France,Male,38,7,109346.13,2,1,0,102665.92,0 +6550,15792029,Lee,620,France,Male,32,6,0,2,1,0,56139.09,0 +6551,15617331,Sergeyeva,637,Germany,Female,39,3,109698.41,1,1,1,88391.29,1 +6552,15651740,Napolitani,525,Spain,Female,30,5,0,2,0,1,149195.44,0 +6553,15636407,Beatham,793,Germany,Female,34,5,127758.09,1,1,0,143357.03,0 +6554,15607526,Lu,638,Germany,Male,50,1,102645.48,1,1,0,168359.98,1 +6555,15632576,Yashina,520,France,Male,31,4,93249.4,1,1,0,77335.75,0 +6556,15581505,Bales,641,France,Male,35,5,0,2,1,0,93148.93,0 +6557,15612207,Hill,840,Germany,Female,51,1,87779.83,1,0,1,36687.11,1 +6558,15707242,Ibeamaka,504,Spain,Male,40,5,0,2,0,0,146703.36,0 +6559,15721937,Romilly,686,France,Male,38,0,138131.34,1,0,1,115927.85,0 +6560,15773852,Hayes,533,Germany,Male,38,4,70362.52,2,1,1,104189.46,0 +6561,15719778,Chiu,577,France,Female,32,1,0,2,1,0,9902.39,0 +6562,15650538,Sun,445,Germany,Female,48,7,168286.58,1,1,0,16645.77,1 +6563,15797475,Brennan,720,France,Male,44,3,86102.27,1,1,0,180134.88,1 +6564,15780359,Storey,643,Germany,Male,25,4,115142.9,1,1,1,148098.95,0 +6565,15737104,Lawson,652,Germany,Female,47,0,126597.89,2,1,1,38798.79,1 +6566,15789936,T'ao,663,France,Female,33,2,0,2,1,0,153295,0 +6567,15709523,Yao,525,Germany,Female,30,0,157989.21,2,1,1,100687.67,0 +6568,15593425,Bracewell,662,Spain,Female,54,1,187997.15,1,0,0,111442.71,1 +6569,15776725,Kerr,724,Germany,Male,54,8,172192.49,1,1,1,136902.01,0 +6570,15604706,Blake,581,Germany,Male,38,1,133105.47,1,1,0,105732.9,1 +6571,15790958,Sanders,685,Spain,Male,38,4,0,2,1,1,35884.91,0 +6572,15747534,Torkelson,595,France,Male,46,10,0,1,1,0,73489.15,1 +6573,15574237,Hsueh,588,France,Female,21,8,0,2,1,1,110114.19,0 +6574,15690332,Wang,647,Germany,Male,35,3,192407.97,1,1,1,40145.28,0 +6575,15661290,Hightower,785,Germany,Female,38,9,107199.75,1,0,0,146398.51,0 +6576,15651883,Genovesi,794,Germany,Female,55,6,115796.7,1,1,0,160526.36,1 +6577,15808905,Levan,823,France,Male,37,5,164858.18,1,1,1,173516.71,0 +6578,15715532,Lai,687,Germany,Male,38,4,117633.28,1,0,1,88396.6,0 +6579,15786078,Loginov,850,France,Female,28,9,0,2,1,0,185821.41,0 +6580,15652401,Lafleur,496,France,Female,36,7,0,2,0,0,108098.28,0 +6581,15673074,Obidimkpa,527,Germany,Female,30,6,126663.51,1,1,1,162267.91,0 +6582,15598744,Ch'ang,576,Germany,Female,71,6,140273.47,1,1,1,193135.25,1 +6583,15785975,Mason,525,Spain,Female,60,7,0,2,0,1,168034.9,0 +6584,15613180,Miranda,727,Germany,Male,21,8,153344.72,1,1,1,163295.87,0 +6585,15584229,Simon,671,Germany,Female,23,9,123943.18,1,1,1,159553.27,0 +6586,15773804,Golubeva,625,France,Male,39,5,0,1,1,0,99800.87,0 +6587,15699515,Manfrin,643,Germany,Male,33,7,98630.31,2,1,1,40250.82,0 +6588,15705313,Stange,707,France,Female,33,2,58036.33,1,1,1,83335.78,0 +6589,15693817,Ferrari,539,Spain,Male,28,5,0,2,1,0,48382.4,0 +6590,15673790,Taylor,498,Germany,Male,45,7,109200.74,2,0,1,165990.44,0 +6591,15674868,Wei,696,Spain,Female,30,0,0,2,1,1,9002.8,0 +6592,15692110,Ch'eng,758,France,Female,33,7,0,1,1,0,188156.34,0 +6593,15645904,Parsons,685,France,Female,33,6,0,2,0,1,186785.01,0 +6594,15581332,Pan,655,Germany,Female,30,1,83173.98,2,1,1,184259.6,0 +6595,15808544,Cameron,747,France,Female,40,3,0,1,0,0,57817.84,1 +6596,15734948,Igwebuike,601,Spain,Male,24,7,0,2,0,0,144660.42,0 +6597,15654531,Tuan,477,France,Male,22,5,82559.42,2,0,0,163112.9,1 +6598,15637774,Fraser,558,France,Male,32,5,73494.21,1,0,0,136301.1,0 +6599,15677141,Turnbull,586,Spain,Male,29,2,132450.24,1,1,1,36176.63,0 +6600,15739578,Chiazagomekpere,850,France,Male,49,6,128663.9,1,1,0,65769.3,1 +6601,15697360,Yudina,505,France,Female,36,2,79951.9,1,0,1,174123.16,1 +6602,15655213,Udinese,591,Germany,Female,51,8,132508.3,1,1,1,161304.68,1 +6603,15580872,Chinweike,761,Germany,Female,38,1,120530.13,2,1,0,109394.62,0 +6604,15683213,Bergamaschi,554,France,Female,35,10,74988.59,2,0,1,190155.13,0 +6605,15801188,Milliner,774,France,Female,47,6,94722.88,1,0,1,61450.96,0 +6606,15645029,Knowles,771,Spain,Female,33,5,0,2,1,0,8673.43,0 +6607,15633181,Swinton,792,France,Male,31,6,71269.89,2,0,1,125912.77,0 +6608,15598259,Gregory,673,Germany,Female,41,9,98612.1,1,1,0,151349.35,0 +6609,15576000,Chibueze,765,France,Male,40,6,138033.55,1,1,1,67972.45,0 +6610,15766047,Sukhorukova,748,France,Female,41,2,91621.69,1,1,1,71139.31,0 +6611,15596339,French,422,France,Male,54,3,140014.42,1,0,1,86350.97,0 +6612,15715199,Estrada,568,Spain,Male,27,5,126815.97,2,0,1,118648.12,0 +6613,15615938,Fleming,502,France,Female,64,3,139663.37,1,0,1,100995.11,0 +6614,15679991,Kennedy,524,France,Female,28,7,0,2,0,1,147100.72,0 +6615,15626135,Combes,689,France,Male,34,1,165312.27,1,1,0,155495.63,0 +6616,15792934,Carruthers,661,France,Male,26,8,0,2,0,0,196875.87,0 +6617,15744046,Andrejew,606,Spain,Male,33,8,0,2,1,1,63176.77,0 +6618,15700826,Ko,678,Germany,Female,54,1,123699.28,2,0,1,105221.76,0 +6619,15756301,Daniels,636,Germany,Female,29,3,97325.15,1,0,1,131924.38,0 +6620,15586517,Toscano,647,France,Male,32,5,97041.16,1,1,1,23132.73,0 +6621,15751297,Wilson,732,France,Male,36,5,0,2,1,0,161428.25,0 +6622,15710365,Thomson,646,France,Male,50,0,104129.24,2,1,0,181794.86,1 +6623,15679307,Kazantseva,559,France,Female,43,1,0,1,0,1,86634.3,0 +6624,15610753,Cremonesi,581,France,Male,28,3,104367.5,1,1,1,29937.75,0 +6625,15811036,Ferri,565,France,Male,46,7,135369.71,1,0,1,140130.22,0 +6626,15610912,Ferri,657,Spain,Female,41,6,112119.48,1,1,0,17536.82,0 +6627,15619932,Lombardi,847,France,Male,66,7,123760.68,1,0,1,53157.16,0 +6628,15746199,Eluemuno,558,France,Female,41,6,0,1,1,1,143585.29,1 +6629,15584967,Chiganu,596,Spain,Male,57,6,0,2,1,1,72402,0 +6630,15734365,Hsueh,579,France,Male,39,5,0,2,0,1,39891.84,0 +6631,15726960,O'Brien,741,France,Female,36,3,0,2,1,1,89804.83,0 +6632,15665177,Booth,613,France,Male,44,3,0,2,0,1,136491.72,0 +6633,15779915,O'Loghlin,694,Spain,Male,31,5,0,1,1,0,35593.18,0 +6634,15729110,Lavrov,729,Spain,Female,42,7,0,2,1,0,58268.2,1 +6635,15575399,Somadina,480,France,Female,42,1,152160.21,2,1,0,101778.9,0 +6636,15678374,Colombo,666,France,Female,59,5,0,2,1,1,185123.09,0 +6637,15792679,Troupe,575,France,Male,24,2,0,2,1,1,119927.81,0 +6638,15668767,Kenenna,850,France,Male,36,3,0,2,1,0,195033.07,0 +6639,15761886,Franklin,740,France,Male,36,4,172381.8,1,1,1,86480.29,0 +6640,15583076,Deleon,588,Germany,Male,41,6,106116.56,2,1,0,198766.61,0 +6641,15815615,Kung,681,France,Male,36,5,141952.07,1,1,1,185144.08,0 +6642,15591942,Zito,611,Spain,Female,33,7,0,2,1,1,3729.89,0 +6643,15724924,Giordano,589,France,Female,37,6,138497.84,1,0,1,18988.58,0 +6644,15762123,Davide,717,Spain,Female,34,1,0,2,1,0,119313.74,0 +6645,15567893,Lei,556,Germany,Male,33,3,124213.36,2,1,0,62627.55,0 +6646,15648989,Moss,850,France,Male,37,4,126872.6,1,1,0,197266.58,0 +6647,15662021,Lucciano,685,Spain,Female,42,2,0,2,0,0,199992.48,0 +6648,15691627,Tai,713,France,Female,37,8,0,1,1,1,16403.41,0 +6649,15731751,Osinachi,437,France,Female,26,1,120923.52,1,0,1,78854.57,0 +6650,15635277,Coates,605,Spain,Male,47,7,142643.54,1,1,0,189310.27,0 +6651,15655252,Larionova,758,Germany,Male,41,10,79857.64,1,1,1,78088.17,0 +6652,15803941,Seleznev,600,France,Male,46,10,95502.21,1,0,0,19842.18,0 +6653,15714380,Butcher,827,France,Male,38,5,0,2,0,0,103305.01,0 +6654,15666559,Gould,608,Germany,Male,23,8,197715.93,2,1,1,116124.28,0 +6655,15799998,Cunningham,608,France,Female,30,8,85859.76,1,0,0,142730.27,0 +6656,15703763,Sanderson,554,France,Male,44,7,85304.27,1,1,1,58076.52,0 +6657,15795640,Mai,683,Germany,Female,35,1,132371.3,2,0,0,186123.57,0 +6658,15780056,Reid,660,Spain,Male,33,4,0,1,1,0,29664.45,0 +6659,15777873,Downer,628,France,Female,31,5,0,1,0,0,147963.07,1 +6660,15584749,Humphries,668,Germany,Male,39,4,79896,1,1,0,38466.39,0 +6661,15765258,Bochsa,776,France,Female,29,5,0,2,1,1,143301.49,0 +6662,15623346,Czajkowski,820,France,Male,36,4,0,2,1,0,31422.69,0 +6663,15614054,Pankhurst,665,France,Male,36,1,0,2,0,1,121505.61,0 +6664,15766185,She,850,Germany,Male,31,4,146587.3,1,1,1,89874.82,0 +6665,15667632,Birdseye,703,France,Female,42,7,0,2,0,1,72500.68,0 +6666,15599024,Hope,506,Spain,Male,32,8,0,2,0,1,182692.8,0 +6667,15798709,Gill,588,Spain,Male,32,3,109109.33,1,0,1,4993.94,0 +6668,15741921,Moon,622,Spain,Female,26,8,0,2,1,1,124964.82,0 +6669,15793671,Watt,606,France,Male,34,5,0,1,1,0,161971.42,0 +6670,15797900,Chinomso,517,France,Male,56,9,142147.32,1,0,0,39488.04,1 +6671,15667932,Bellucci,758,Spain,Female,43,10,0,2,1,1,55313.44,0 +6672,15795933,Barese,677,France,Female,49,3,0,2,1,1,187811.71,0 +6673,15660403,Fleming,827,Spain,Female,35,0,0,2,0,1,184514.01,0 +6674,15736299,Bell,729,France,Female,36,8,109106.8,1,0,0,121311.12,0 +6675,15759034,Li Fonti,654,France,Male,36,2,112262.84,1,1,0,12873.39,0 +6676,15724663,Christmas,654,Spain,Female,36,5,0,2,0,0,157238.05,0 +6677,15594556,Chuter,619,Spain,Male,52,8,0,2,1,1,123242.11,0 +6678,15737169,Johnson,642,Spain,Male,26,8,144238.7,1,1,1,184399.76,0 +6679,15632472,Scott,472,Spain,Female,32,1,159397.75,1,0,1,57323.18,0 +6680,15722813,Byrne,470,Spain,Male,30,4,125385.01,1,1,0,68293.93,0 +6681,15588450,Chukwudi,633,France,Female,60,8,69365.25,1,1,1,10288.24,0 +6682,15736717,Ma,602,France,Male,31,7,155271.83,1,1,1,179446.31,0 +6683,15680683,Simmons,640,Spain,Male,29,5,197200.04,2,1,0,141453.62,0 +6684,15710316,Fang,454,Spain,Female,48,5,144837.79,1,1,1,93151.77,0 +6685,15746333,Blake,562,France,Female,57,3,0,3,1,0,6554.97,1 +6686,15606861,Tien,636,France,Male,34,8,0,2,1,0,38570.13,0 +6687,15641285,Yusupova,621,Spain,Male,50,3,163085.79,1,0,1,131048.36,0 +6688,15662908,Davidson,795,Germany,Male,38,7,125903.22,2,1,1,127068.92,0 +6689,15814267,Zhdanova,550,France,Male,22,6,154377.3,1,1,1,51721.52,0 +6690,15614923,Nielson,630,Spain,Male,41,7,107511.52,1,0,1,46156.87,0 +6691,15579223,Niu,573,Germany,Male,30,8,127406.5,1,1,0,192950.6,0 +6692,15651389,Kay,561,Spain,Male,24,8,143656.55,1,0,1,180932.46,0 +6693,15677087,Green,662,France,Female,39,5,138106.75,1,0,0,19596.73,0 +6694,15665784,She,637,France,Male,27,9,128940.24,1,1,0,46786.92,0 +6695,15576706,Ajuluchukwu,651,Germany,Male,37,9,114453.58,1,0,1,175820.91,0 +6696,15615473,Sabbatini,646,France,Female,33,2,0,2,0,0,198208,0 +6697,15587299,Board,567,France,Female,48,3,0,1,1,0,55362.45,0 +6698,15655389,Leckie,638,France,Male,41,1,131762.94,1,1,1,47675.29,0 +6699,15784491,Ho,725,France,Female,31,6,0,1,0,0,61326.43,0 +6700,15809999,Gordon,709,France,Female,41,3,150300.65,2,1,0,71672.86,0 +6701,15681115,Iroawuchi,787,Spain,Male,39,10,108935.39,1,1,1,101168.3,0 +6702,15629390,Liao,653,France,Male,37,7,135847.47,1,1,0,144880.81,0 +6703,15792668,Hamilton,661,Germany,Male,37,7,109908.06,2,1,0,115037.67,1 +6704,15583863,Chimaobim,681,Germany,Male,49,8,142946.18,1,0,0,187280.51,1 +6705,15681878,Fan,436,Germany,Male,45,3,104339.11,2,1,1,183540.22,1 +6706,15782875,Cayley,663,France,Male,33,5,157274.36,2,1,1,28531.81,0 +6707,15732235,Kuykendall,662,France,Male,64,0,98848.19,1,0,1,42730.12,0 +6708,15735909,McDonald,607,Germany,Female,39,8,105103.33,1,1,0,104721.5,1 +6709,15653448,Duncan,754,France,Male,34,7,0,2,1,1,65219.85,0 +6710,15587647,Browne,850,Germany,Female,66,0,127120.62,1,0,1,118929.64,1 +6711,15701037,Barton,578,France,Male,39,2,0,2,1,0,70563.9,0 +6712,15727499,Boyle,666,Germany,Female,36,3,129118.5,2,0,0,139435.12,0 +6713,15724838,Moretti,599,France,Female,43,4,0,1,1,0,170347.1,0 +6714,15666711,Ukaegbulam,586,France,Female,46,0,0,3,0,1,131553.82,1 +6715,15588933,Nwankwo,825,France,Female,36,3,146053.66,1,1,1,138344.7,0 +6716,15763111,Niu,808,Spain,Female,67,10,124577.15,1,0,1,169894.4,0 +6717,15805676,Hsu,515,Spain,Male,29,4,151012.55,2,1,0,9770.97,0 +6718,15586674,Shaw,663,Spain,Female,58,5,216109.88,1,0,1,74176.71,1 +6719,15744553,Ho,444,France,Male,34,2,144318.97,1,1,0,112668.06,0 +6720,15776629,Christie,650,France,Female,39,4,0,2,0,0,186275.7,0 +6721,15647207,Onwuemelie,609,France,Male,26,7,0,2,1,0,98463.99,0 +6722,15715638,Ch'ang,824,Germany,Male,77,3,27517.15,2,0,1,2746.41,0 +6723,15750602,Clendinnen,662,France,Male,29,5,147092.65,1,1,0,10928.3,0 +6724,15766810,Onyemauchechi,699,Germany,Female,51,2,92246.14,2,0,1,91346.03,0 +6725,15756625,Crawford,752,France,Female,41,8,0,2,1,0,139844.04,1 +6726,15639552,Mellor,603,Germany,Female,40,8,148897.02,1,0,0,105052.9,0 +6727,15633213,Rizzo,628,Spain,Male,50,8,0,1,0,0,144366.83,1 +6728,15610416,Christie,745,France,Female,36,9,0,1,1,0,19605.18,1 +6729,15715208,Watkins,804,Germany,Female,33,10,138335.96,1,1,1,80483.76,0 +6730,15619608,Ojiofor,454,Germany,Female,50,10,92895.56,1,1,0,154344,1 +6731,15628697,Tung,631,Spain,Male,46,9,160736.63,1,0,1,93503.02,0 +6732,15643826,McKay,503,France,Male,32,4,0,2,1,1,153036.97,0 +6733,15718588,Meng,548,France,Female,37,9,0,2,0,0,98029.58,0 +6734,15709741,Hussain,668,France,Male,28,4,107141.27,1,1,0,193018.71,0 +6735,15723318,Mactier,619,France,Female,55,0,0,3,0,0,60810.64,1 +6736,15717328,Hsueh,842,France,Female,37,4,132446.08,2,1,0,87071.18,1 +6737,15771299,Nnachetam,707,France,Female,57,1,92053,1,1,1,164064.44,1 +6738,15706223,Barnes,715,Spain,Male,38,2,96798.79,2,1,1,4554.67,0 +6739,15612358,Christie,573,Germany,Male,35,9,134498.54,2,1,1,119924.8,0 +6740,15769191,Lipton,509,France,Male,55,8,132387.91,2,1,1,170360.11,0 +6741,15618816,Yu,670,Germany,Female,40,2,147171.2,1,0,1,69850.04,0 +6742,15730810,Storey,613,Spain,Male,44,9,100524.69,1,1,1,47298.95,0 +6743,15783463,Read,678,France,Female,26,1,0,2,1,0,45443.68,0 +6744,15616213,Levy,555,Germany,Female,51,9,138214.5,1,1,0,198715.27,1 +6745,15611287,Chiu,777,France,Female,30,4,0,2,0,1,115611.97,0 +6746,15786454,Moore,552,Spain,Male,55,3,0,1,1,1,40333.94,0 +6747,15768682,Amies,640,Spain,Male,39,3,0,1,1,1,105997.25,0 +6748,15766172,Tsao,541,France,Male,34,3,128743.55,1,1,0,134851.12,0 +6749,15637646,Rowley,756,France,Male,31,10,122647.32,1,0,0,61666.87,0 +6750,15653404,Aliyev,684,Spain,Female,24,9,79263.9,1,0,1,196574.48,0 +6751,15690546,Riley,618,France,Female,42,2,0,4,0,0,111097.39,1 +6752,15735636,Toscano,604,France,Female,53,2,121389.78,1,1,1,48201.64,1 +6753,15605424,Oluchukwu,624,Spain,Male,38,7,123906.55,1,1,0,135096.78,0 +6754,15568449,Fu,661,Spain,Male,38,7,143006.7,1,1,1,15650.89,0 +6755,15688085,Warner,627,Spain,Female,28,3,157597.61,1,0,1,34097.22,0 +6756,15683483,Fleming,812,Spain,Male,38,3,127117.8,2,1,1,174822.74,0 +6757,15659567,Ch'iu,473,France,Female,39,9,117103.26,2,1,1,85937.52,1 +6758,15766667,Langler,717,Spain,Male,36,2,102989.83,2,0,1,49185.57,0 +6759,15624975,Angelo,693,Spain,Male,28,1,145118.83,1,0,1,77742.38,0 +6760,15660878,T'ien,705,France,Male,92,1,126076.24,2,1,1,34436.83,0 +6761,15586557,Milani,661,France,Male,41,5,0,1,0,1,88279.6,0 +6762,15746183,Pye,573,France,Female,27,4,0,2,1,1,157549.6,0 +6763,15631457,Asher,639,France,Male,37,5,98186.7,1,0,1,173386.95,0 +6764,15754053,Chung,718,France,Female,67,7,0,3,1,1,82782.08,0 +6765,15645839,Yudin,570,France,Male,37,6,0,1,1,1,187758.5,0 +6766,15689955,Arcuri,461,France,Female,40,7,0,2,1,0,176547.8,0 +6767,15593510,Capon,638,Germany,Female,33,5,129335.65,1,1,1,56585.2,1 +6768,15654964,Piccio,608,Spain,Male,48,7,75801.74,1,1,0,125762.95,0 +6769,15594039,Lung,599,Spain,Male,42,6,0,2,1,0,113868.4,0 +6770,15625929,Trevisan,762,France,Female,44,7,159316.64,1,0,0,24780.13,0 +6771,15815295,John,662,France,Female,38,2,96479.81,1,1,0,120259.41,0 +6772,15621818,Anayolisa,747,Germany,Male,29,7,117726.33,1,1,1,175398.34,0 +6773,15652700,Ritchie,539,France,Male,39,6,0,2,1,1,86767.48,0 +6774,15636860,Ch'eng,625,France,Male,43,4,122351.29,1,1,0,71216.6,0 +6775,15569432,Macleod,656,France,Female,48,9,0,2,1,1,85240.61,1 +6776,15751455,Boyle,469,France,Female,48,5,0,1,1,0,160529.71,1 +6777,15800583,Chukwuemeka,621,Spain,Female,43,8,0,1,0,0,102806.6,0 +6778,15770214,Bryant,754,France,Female,27,7,0,2,1,0,144134.64,0 +6779,15613463,Hackett,679,Germany,Female,50,6,132598.38,2,1,1,184017.98,0 +6780,15587066,Kovaleva,535,France,Male,38,2,119272.29,1,0,0,195896.59,1 +6781,15693752,Reed,487,France,Male,37,2,0,2,1,1,126722.57,0 +6782,15714874,Major,850,France,Female,42,3,0,2,1,1,176883.42,0 +6783,15657809,Lo,585,France,Male,55,10,106415.57,3,1,1,122960.98,1 +6784,15651955,Hanson,603,France,Male,31,4,0,2,0,1,9607.1,0 +6785,15570912,Ogbonnaya,728,Germany,Female,32,9,127772.1,2,1,1,152643.48,0 +6786,15640266,Windsor,621,Spain,Male,41,5,104631.67,1,1,1,95551.22,0 +6787,15652069,Calabrese,833,France,Male,30,1,0,2,1,0,141860.62,0 +6788,15596074,Keating,502,France,Male,37,10,0,1,1,1,76642.68,0 +6789,15800268,Costa,825,Germany,Male,37,6,118050.79,1,0,1,52301.15,0 +6790,15809847,Tan,668,France,Male,46,0,0,2,0,0,29388.02,0 +6791,15599074,Ma,487,Spain,Female,40,6,136093.74,1,0,1,193408.43,0 +6792,15599591,Martin,600,Germany,Female,39,7,88477.36,2,1,0,58632.37,0 +6793,15776096,Halpern,606,Spain,Male,34,3,161572.24,1,0,1,191076.22,0 +6794,15611669,Nyhan,623,Germany,Male,50,7,126608.37,1,0,1,645.61,1 +6795,15694098,Jackson,575,France,Female,54,9,68332.96,1,1,1,144390.75,0 +6796,15713347,Reynolds,577,Spain,Male,48,6,179852.26,1,1,0,193580.32,0 +6797,15713094,Tai,651,France,Female,25,8,0,2,1,1,126761.2,0 +6798,15811978,Trevisani,693,Germany,Male,46,2,104763.41,1,1,1,62368.33,0 +6799,15799925,Uwakwe,800,France,Male,60,6,88541.57,2,1,1,131718.12,0 +6800,15692575,Kerr,760,France,Male,38,6,162888.73,1,1,0,91098.76,1 +6801,15743149,Findlay,711,France,Female,35,8,0,1,1,1,67508.01,0 +6802,15776947,Ugorji,637,Spain,Male,43,8,0,1,1,0,12156.93,1 +6803,15700656,Balashova,662,France,Male,32,9,0,2,0,0,65089.38,0 +6804,15594515,Cheng,568,France,Female,44,7,0,2,0,0,62370.67,1 +6805,15787884,Martin,692,France,Female,30,7,0,2,1,1,18826.34,0 +6806,15577988,Skinner,614,France,Female,35,1,0,2,1,1,3342.62,0 +6807,15795586,McDonald,478,France,Male,35,1,92474.05,1,1,0,178626.07,0 +6808,15677739,Dellucci,562,France,Male,36,6,0,2,1,0,32845.32,0 +6809,15720134,Reynolds,709,Germany,Male,30,9,115479.48,2,1,1,134732.99,0 +6810,15688868,Birdsall,684,France,Female,26,5,87098.91,1,0,0,106095.82,0 +6811,15642996,Tsai,546,Germany,Female,42,9,86351.85,2,1,0,57380.13,0 +6812,15771222,Oguejiofor,779,France,Female,42,5,0,2,0,0,25951.91,0 +6813,15605059,Mackie,576,Germany,Male,63,3,148843.56,1,1,0,69414.13,1 +6814,15568088,Jamieson,481,Germany,Male,44,3,163714.52,1,1,0,96123.72,0 +6815,15665943,Mai,445,France,Male,25,6,0,2,1,0,119425.94,0 +6816,15795571,Patterson,606,Spain,Male,36,0,94153.56,1,0,1,120138.27,0 +6817,15662243,Taylor,559,France,Male,50,5,162702.35,1,0,0,150548.5,1 +6818,15593128,Vinogradoff,608,France,Female,56,10,129255.2,2,1,0,142492.04,1 +6819,15589739,North,698,France,Male,41,3,90605.29,1,1,1,14357,0 +6820,15787602,Carter,568,Spain,Male,39,5,0,2,1,1,129569.92,0 +6821,15685019,Graham,528,France,Male,29,3,102787.42,1,1,0,55972.56,0 +6822,15704209,Noble,802,France,Female,39,7,120145.96,2,0,1,59497.01,1 +6823,15605264,Walker,669,Germany,Male,47,0,63723.78,2,1,1,181928.25,0 +6824,15708265,Chibugo,581,Spain,Female,24,10,159203.71,1,1,1,102517.83,1 +6825,15740264,Yobachi,640,France,Male,38,9,0,2,1,0,88827.67,0 +6826,15615477,Ignatyeva,529,Spain,Female,44,1,0,2,0,0,14161.3,0 +6827,15727361,Chiemela,547,France,Female,51,1,0,2,1,1,56908.41,0 +6828,15760216,Pokrovskaya,718,France,Female,49,10,0,1,1,0,184474.72,1 +6829,15806134,Storey,707,Germany,Male,34,9,162691.16,2,1,0,94912.78,0 +6830,15601351,Moroney,735,France,Male,43,9,127806.91,1,1,1,73069.59,0 +6831,15669262,Maslov,765,France,Male,43,9,157960.49,2,0,0,136602.8,0 +6832,15696989,Chukwueloka,469,Germany,Female,52,8,139493.25,3,0,0,150093.32,1 +6833,15688498,Chu,594,Germany,Female,21,2,87096.82,2,1,0,168186.11,0 +6834,15686964,Spence,675,France,Female,34,10,84944.58,1,0,0,146230.63,0 +6835,15625035,Mills,703,France,Male,50,8,160139.59,2,1,1,79314.1,0 +6836,15618391,Doyle,810,France,Male,33,6,0,2,1,1,77965.67,0 +6837,15591344,Donnelly,715,Spain,Male,42,6,0,2,1,1,128745.69,0 +6838,15605455,Tai,664,France,Male,40,9,0,2,1,0,194767.3,0 +6839,15680804,Abbott,850,France,Male,29,6,0,2,1,1,10672.54,0 +6840,15768282,Perez,724,Germany,Male,36,6,94615.11,2,1,1,10627.21,0 +6841,15685826,Hsiung,563,France,Male,30,7,90727.79,1,1,0,122268.75,0 +6842,15793491,Cherkasova,714,Germany,Male,26,3,119545.48,2,1,0,65482.94,0 +6843,15797787,Denisov,614,France,Male,36,1,118311.76,1,1,0,146134.68,0 +6844,15611171,Fowler,740,France,Male,33,1,129574.98,1,1,1,123300.38,0 +6845,15601627,Siciliano,587,France,Male,33,8,148163.57,1,0,0,122925.4,0 +6846,15734085,Crocker,465,Germany,Male,24,5,117154.9,1,1,1,127744.02,0 +6847,15809309,Longo,689,Spain,Female,40,5,154251.67,1,0,1,118319.5,0 +6848,15809462,Polyakova,656,France,Male,30,3,0,2,0,1,17104,0 +6849,15634628,Brown,579,France,Female,33,1,65667.79,2,0,0,164608.98,0 +6850,15775678,Uspensky,716,France,Female,44,1,0,1,1,1,152108.47,0 +6851,15579526,O'Meara,551,France,Male,42,1,50194.59,1,1,1,23399.58,0 +6852,15779103,Cantamessa,527,Germany,Female,39,9,96748.89,2,1,0,94711.43,0 +6853,15738715,Alexander,600,France,Female,37,4,0,3,1,0,7312.25,1 +6854,15593943,Chinagorom,685,France,Female,43,1,132667.17,1,1,1,41876.98,0 +6855,15754574,Tomlinson,738,Spain,Male,36,5,0,2,1,1,96881.32,0 +6856,15737814,Lo,622,France,Male,41,2,127087.06,1,1,0,102402.91,1 +6857,15670889,Nwachukwu,528,France,Male,34,1,125566.9,1,1,1,176763.27,0 +6858,15629299,Yang,546,Germany,Female,52,1,106074.89,1,1,1,23548.45,1 +6859,15771569,Bage,576,Germany,Male,46,4,137367.94,1,1,1,33450.11,0 +6860,15811927,Marcelo,733,France,Female,38,3,157658.36,1,0,0,19658.43,0 +6861,15785654,Ofodile,727,Germany,Male,45,6,114422.85,2,1,1,104678.78,1 +6862,15665524,Savage,605,Spain,Male,41,5,103154.66,1,0,0,143203.78,0 +6863,15736287,Piccio,586,France,Male,33,9,0,1,1,0,6975.02,0 +6864,15765732,Simmons,564,Spain,Female,24,6,149592.14,1,1,1,153771.8,0 +6865,15797381,DeRose,593,Germany,Female,48,3,133903.12,2,1,1,85902.39,1 +6866,15598536,Onuchukwu,736,Germany,Female,26,0,84587.9,1,0,1,188037.76,0 +6867,15664506,Goodwin,675,Spain,Male,32,8,197436.82,1,1,1,52710.7,0 +6868,15575619,Teakle,656,Spain,Female,32,1,104254.27,1,1,1,17034.37,0 +6869,15587394,Thomson,462,France,Male,39,4,140133.08,2,0,0,131304.45,0 +6870,15654457,Cross,685,Spain,Female,30,2,0,3,1,1,172576.43,1 +6871,15762793,Jones,850,Germany,Female,36,0,136980.23,2,1,1,99019.65,0 +6872,15658067,Walker,636,Germany,Female,48,3,120568.41,1,1,0,190160.04,1 +6873,15642816,De Salis,850,France,Female,27,7,43658.33,2,1,1,3025.49,0 +6874,15693088,Oliver,628,France,Female,37,9,0,2,1,1,34689.77,0 +6875,15793883,Lo Duca,798,France,Male,28,3,0,2,1,0,2305.27,0 +6876,15665283,Brookes,610,France,Female,57,7,72092.95,4,0,1,113228.82,1 +6877,15680421,Challis,591,France,Female,42,10,0,2,0,0,171099.22,0 +6878,15695148,Ibeabuchi,614,Spain,Female,37,9,0,2,1,1,62023.1,0 +6879,15636592,Iroawuchi,651,France,Male,35,0,181821.96,2,0,1,36923.67,1 +6880,15772618,Tyler,665,France,Male,25,7,90920.75,1,0,1,112256.57,0 +6881,15724453,Fan,570,France,Male,23,2,0,1,0,0,198830.98,0 +6882,15565878,Bates,631,Spain,Male,29,3,0,2,1,1,197963.46,0 +6883,15609160,Marsden,586,France,Male,32,1,0,2,0,0,31635.99,0 +6884,15678460,Dodgshun,691,France,Male,30,9,0,1,1,0,49594.02,0 +6885,15662571,Maclean,639,France,Male,35,8,0,2,1,0,170483.9,0 +6886,15606849,Blackall,698,France,Female,27,1,94920.71,1,1,1,40339.9,0 +6887,15670738,Mazzanti,733,Germany,Male,45,2,113939.36,2,1,0,3218.71,0 +6888,15662641,Amadi,850,France,Male,19,8,0,1,1,1,68569.89,0 +6889,15727539,Schoenheimer,618,France,Female,31,4,0,2,1,0,29176.04,0 +6890,15651020,Fiorentino,473,France,Female,25,6,110666.42,2,0,0,46758.42,0 +6891,15673877,Murray,490,France,Male,39,1,0,3,1,0,171060.01,1 +6892,15760865,Fan,754,Germany,Female,48,7,141819.02,1,1,0,93550.53,1 +6893,15705009,Cartwright,649,France,Female,56,8,156974.26,1,1,0,89405.26,1 +6894,15657540,Cremonesi,578,France,Male,50,5,151215.34,2,1,0,169804.4,0 +6895,15707441,White,690,Spain,Male,26,8,116318.23,1,1,1,83253.05,0 +6896,15694765,Sabbatini,610,Germany,Male,49,6,113882.33,1,1,0,195813.81,1 +6897,15649086,Patterson,596,France,Male,42,7,0,2,1,1,121568.37,0 +6898,15650488,Bromley,492,France,Female,48,6,127253.98,1,1,1,92144.09,1 +6899,15760924,Doherty,575,Spain,Male,41,2,100062.39,1,0,0,126307.25,0 +6900,15700263,Ifeatu,569,France,Male,66,2,0,1,1,0,130784.2,1 +6901,15806922,Bergamaschi,674,Spain,Female,41,4,126605.14,1,1,1,166694.93,0 +6902,15637522,Shubina,507,France,Female,31,0,106942.08,1,0,1,44001.11,0 +6903,15636548,Lung,457,Spain,Male,44,7,0,2,0,0,185992.36,0 +6904,15566891,Kinder,584,Germany,Female,41,3,88594.93,1,1,0,178997.89,0 +6905,15627185,Terry,744,Germany,Male,29,6,123737.04,2,1,0,141558.04,0 +6906,15754012,Shepherdson,687,France,Female,35,1,110752.15,2,1,1,47921.22,0 +6907,15627514,Short,688,Spain,Female,46,3,0,2,0,1,104902.68,0 +6908,15661433,Zetticci,519,France,Male,34,5,0,1,1,0,68479.6,0 +6909,15610653,Belov,733,Spain,Female,38,5,0,2,1,1,1271.51,0 +6910,15667002,Knight,666,Spain,Male,43,5,0,2,1,0,29346.1,0 +6911,15709199,Burson,511,Spain,Female,40,1,0,1,1,1,184118.73,0 +6912,15710087,Nicholls,705,Germany,Female,54,3,125889.3,3,1,0,96013.5,1 +6913,15679884,Hs?eh,544,France,Male,48,10,78314.63,3,1,1,103713.93,1 +6914,15784180,Ku,564,France,Female,36,7,206329.65,1,1,1,46632.87,1 +6915,15808849,T'ien,702,France,Male,40,7,145536.9,1,0,1,135334.24,0 +6916,15751549,H?,658,Germany,Male,31,2,77082.65,2,0,0,13482.28,0 +6917,15588235,Vasilieva,654,France,Female,24,8,145081.73,1,1,1,130075.07,0 +6918,15640418,Omeokachie,649,Germany,Female,41,4,115897.73,1,1,0,143544.48,0 +6919,15721116,Napolitano,597,Spain,Male,24,0,108058.07,2,1,1,187826.11,0 +6920,15599084,Hopwood,782,France,Male,33,7,191523.09,1,1,1,167058.75,0 +6921,15773394,Bergamaschi,644,France,Male,38,3,0,2,1,1,79928.41,0 +6922,15625713,Lindeman,679,Spain,Female,39,7,91187.9,1,0,1,6075.36,0 +6923,15766417,McKinley,678,France,Female,60,2,0,2,1,1,43821.56,0 +6924,15622578,Sergeyev,806,France,Male,34,5,113958.55,1,0,1,32125.98,0 +6925,15799924,Sanchez,668,Spain,Male,43,1,147167.25,1,0,0,141679.73,0 +6926,15618363,Muomelu,659,Germany,Male,29,9,82916.48,1,1,1,84133.48,0 +6927,15637138,Murray,660,France,Male,34,1,0,2,1,0,9692.58,0 +6928,15781665,Ibekwe,601,France,Female,37,5,0,1,0,0,20708.6,0 +6929,15804853,McVey,781,France,Female,48,0,57098.96,1,1,0,85644.06,1 +6930,15651627,White,628,Germany,Male,39,1,115341.19,1,1,1,107674.3,1 +6931,15680685,Patterson,751,France,Male,30,3,165257.2,1,0,0,134822.05,0 +6932,15808930,Mai,531,France,Female,37,1,0,1,1,0,4606.97,0 +6933,15570970,Han,647,France,Female,42,9,0,2,1,1,51362.82,0 +6934,15679961,Davidson,708,Spain,Male,46,7,68799.72,1,1,1,39704.14,0 +6935,15705458,Parkin,550,Spain,Male,39,2,116120.19,2,1,1,195638.13,0 +6936,15750396,McKissick,670,France,Male,33,1,0,2,1,1,86413.11,0 +6937,15679928,Horsfall,592,France,Female,31,2,84102.11,2,0,1,116385.24,0 +6938,15711181,Clapp,589,France,Female,50,4,0,2,0,1,182076.97,0 +6939,15698324,Azikiwe,725,France,Female,33,4,0,1,1,1,67879.8,0 +6940,15807433,Zubarev,570,France,Female,43,9,0,2,0,1,11417.26,0 +6941,15636590,Pisano,575,France,Male,46,1,0,2,1,1,65998.26,0 +6942,15628950,Coates,501,Germany,Male,25,6,104013.79,1,1,0,114774.35,0 +6943,15617206,Trentino,431,Germany,Male,42,8,120822.86,2,1,0,126153.24,0 +6944,15603741,MacDonnell,719,Spain,Male,40,4,128389.12,1,1,1,176091.31,0 +6945,15742607,Ermakov,850,Germany,Male,36,7,102800.72,1,1,1,87352.43,0 +6946,15747821,K?,554,Germany,Female,31,6,135470.9,1,1,0,107074.81,0 +6947,15612043,Hammonds,418,France,Male,36,7,90145.04,1,1,1,69157.93,0 +6948,15809558,Peppin,715,Spain,Male,31,7,0,1,1,1,149970.59,0 +6949,15803750,Ball,750,Spain,Female,33,3,161801.47,1,0,1,153288.97,1 +6950,15704681,Yeh,766,Germany,Male,37,2,99660.13,2,0,1,147700.78,0 +6951,15667392,L?,652,Spain,Female,38,6,123081.84,2,1,1,188657.97,0 +6952,15738889,Shih,658,France,Male,42,8,102870.93,1,0,1,103764.55,1 +6953,15598838,Greco,659,France,Female,37,1,151105.68,1,1,1,140934.57,0 +6954,15579109,Napolitano,574,Germany,Male,35,5,163856.76,1,1,1,15118.2,0 +6955,15799042,Zaytseva,611,France,Male,38,7,0,1,1,1,63202,0 +6956,15697042,Genovesi,738,Spain,Male,35,8,127290.61,1,1,0,16081.62,0 +6957,15696605,Angelo,571,France,Male,49,4,180614.04,1,0,0,523,0 +6958,15802274,Waters,686,France,Female,44,7,55053.62,1,1,0,181757.19,0 +6959,15596808,Maclean,679,Spain,Male,33,4,96110.22,1,1,0,1173.23,0 +6960,15705403,Seleznyova,617,Spain,Female,46,3,106521.49,1,0,1,86587.37,0 +6961,15732903,Fontenot,673,France,Male,39,7,82255.51,2,1,0,109545.56,0 +6962,15581968,Reid,745,France,Female,33,1,0,2,1,1,174431.01,0 +6963,15683892,Fraser,677,Germany,Female,26,3,102395.79,1,1,0,119368.99,0 +6964,15595447,Tuan,613,Spain,Male,39,8,118201.41,1,1,0,23315.59,0 +6965,15569249,Howarth,576,France,Female,55,6,44582.07,3,0,1,67539.85,1 +6966,15656188,Davis,584,Spain,Female,30,5,0,2,1,1,185201.58,0 +6967,15689661,Gorbunov,663,France,Male,22,6,0,2,0,1,131827.15,0 +6968,15644934,Gentry,466,France,Male,26,9,105522.06,1,1,0,10842.46,0 +6969,15721793,Chiu,510,Germany,Female,50,7,123936.54,1,1,1,23768.01,0 +6970,15687413,Sunderland,619,Spain,Female,38,6,0,2,1,1,117616.29,0 +6971,15761286,Fan,696,Germany,Female,66,7,119499.42,2,1,1,174027.3,0 +6972,15658240,Parry,554,France,Female,44,9,135814.7,2,0,0,115091.38,0 +6973,15706232,Niu,595,France,Male,52,9,0,1,1,1,106340.66,1 +6974,15583394,Zuyev,659,Germany,Male,39,8,106259.63,2,1,1,198103.32,0 +6975,15715643,Ijendu,662,France,Male,44,8,0,2,1,1,175314.87,0 +6976,15644856,Bird,556,Spain,Male,38,2,115463.16,1,1,0,150679.65,0 +6977,15785488,Palmer,701,Spain,Female,39,9,0,2,1,1,110043.88,0 +6978,15711571,Y?,587,Spain,Male,42,5,120233.83,1,1,0,194890.33,0 +6979,15778604,Nicholson,571,France,Female,47,7,0,2,0,0,112366.98,0 +6980,15751180,Adams,539,France,Female,40,7,81132.21,1,1,0,167289.82,0 +6981,15748360,Cocci,644,Germany,Female,34,10,122196.99,2,1,1,182099.71,0 +6982,15770039,Kuo,572,Germany,Male,39,4,112290.22,1,1,0,49373.97,1 +6983,15685096,Trevisani,753,France,Female,50,4,0,2,1,1,861.4,0 +6984,15669501,Kuo,706,France,Male,35,5,0,2,1,1,81718.37,0 +6985,15622631,H?,588,France,Male,44,8,154409.74,1,1,0,49324.03,1 +6986,15586699,Thomson,825,France,Male,32,9,0,2,0,0,9751.03,0 +6987,15702377,Knorr,627,Spain,Male,48,1,132759.8,1,1,0,78899.22,0 +6988,15577170,Manfrin,532,France,Male,60,5,76705.87,2,0,1,13889.73,0 +6989,15769451,Hayes,764,France,Female,44,1,0,2,1,1,11467.38,0 +6990,15811877,Shao,700,France,Female,36,4,0,2,1,0,130789.15,0 +6991,15648725,Sinclair,660,France,Male,41,3,0,2,1,1,108665.89,0 +6992,15752801,Bradshaw,518,Germany,Male,29,9,125961.74,2,1,0,160303.08,1 +6993,15808175,Castiglione,557,France,Female,39,7,49572.73,1,1,0,115287.99,1 +6994,15681342,Hurst,639,France,Female,35,1,103015.12,2,1,1,139094.12,0 +6995,15589210,Adamson,557,France,Female,24,4,0,1,0,0,20515.72,0 +6996,15696826,James,633,France,Female,32,1,104001.38,1,0,1,36642.65,0 +6997,15614962,Pavlova,623,Spain,Female,50,2,87116.71,1,1,1,104382.11,0 +6998,15689061,Davey,611,France,Male,68,5,82547.11,2,1,1,146448.01,0 +6999,15640074,Barrett,666,Spain,Female,47,5,0,1,0,0,166650.9,1 +7000,15776156,Dolgorukova,521,France,Male,27,4,121325.84,1,1,1,164223.7,1 +7001,15739548,Johnson,775,France,Male,28,9,111167.7,1,1,0,149331.01,0 +7002,15662854,Manna,681,Germany,Male,48,5,139714.4,2,0,0,73066.72,0 +7003,15687688,Hou,564,Germany,Female,32,10,139875.2,2,1,0,15378.23,0 +7004,15715750,Okeke,646,Germany,Female,44,2,113063.83,1,0,0,53072.49,1 +7005,15571121,Kodilinyechukwu,670,France,Female,50,8,138340.06,1,0,1,3159.15,0 +7006,15726466,Esposito,751,France,Male,43,1,114974.24,1,1,0,125920.54,0 +7007,15660390,Boyle,544,France,Female,33,6,0,2,1,1,124113.04,0 +7008,15663942,Hsiung,639,France,Female,38,5,0,2,0,0,93716.38,0 +7009,15638610,Kennedy,635,Germany,Female,65,5,117325.54,1,1,0,155799.86,1 +7010,15644446,Norton,672,France,Female,28,6,0,1,0,1,8814.69,0 +7011,15585892,Zakharov,639,France,Female,35,8,0,1,0,0,164453.98,0 +7012,15609356,Chimaraoke,697,France,Female,25,1,0,2,0,0,87803.32,0 +7013,15803378,Small,850,Spain,Male,44,8,0,2,1,1,183617.32,0 +7014,15599440,McGregor,748,France,Female,34,8,0,2,1,0,53584.03,0 +7015,15692408,Brown,463,Spain,Female,35,2,0,2,1,1,1950.93,0 +7016,15683168,Frederickson,572,France,Female,30,6,0,1,0,1,175025.27,0 +7017,15790254,Wood,741,Spain,Male,50,1,78737.61,1,1,1,13018.96,0 +7018,15767729,Smith,646,Spain,Male,25,5,182876.88,2,1,1,42537.59,1 +7019,15768600,Harris,805,Germany,Male,50,9,130023.38,1,1,0,62989.82,1 +7020,15699839,Hall,637,France,Male,36,2,152606.82,1,1,1,71692.8,0 +7021,15786237,Pickworth,651,France,Male,28,7,0,2,1,0,823.96,0 +7022,15694530,Porter,672,France,Male,28,4,167268.98,1,1,1,169469.3,0 +7023,15796813,Storey,493,France,Male,54,3,167831.88,2,1,0,150159.95,1 +7024,15605791,Li,524,Germany,Male,29,9,144287.6,2,1,0,32063.3,0 +7025,15714087,McGill,624,Germany,Female,45,5,151855.33,1,1,0,68794.15,0 +7026,15711446,Sinclair,569,Spain,Female,51,3,0,3,1,0,75084.96,1 +7027,15588123,Horton,677,France,Female,27,2,0,2,0,1,114685.92,0 +7028,15748552,Sal,464,Germany,Male,37,4,155994.15,1,0,0,143665.44,0 +7029,15618410,Murray,718,Germany,Male,26,7,147527.03,1,0,0,51099.56,0 +7030,15672432,Giles,594,France,Female,53,4,0,1,1,0,5408.74,1 +7031,15610042,Brown,574,France,Male,33,8,100267.03,1,1,0,103006.27,0 +7032,15580914,Okechukwu,478,Spain,Male,48,0,83287.05,2,0,1,44147.95,1 +7033,15583680,White,615,Spain,Male,41,4,0,1,0,1,149278.96,0 +7034,15813718,Kirillova,651,Spain,Male,45,4,0,2,0,0,193009.21,0 +7035,15767264,Lawson,465,Germany,Male,53,1,117438.17,1,0,0,74898.8,1 +7036,15686461,Sarratt,558,France,Female,56,7,121235.05,2,1,1,116253.1,0 +7037,15678882,Hay,540,Germany,Male,37,3,129965.18,1,0,0,19374.08,0 +7038,15789611,Lin,568,Germany,Male,46,8,150836.92,1,0,0,64516.8,1 +7039,15668679,Ozerova,630,France,Male,31,0,0,2,1,1,34475.14,0 +7040,15631685,Lambert,523,Germany,Male,60,1,163894.35,1,0,1,57061.71,0 +7041,15655658,Bulgakov,678,France,Female,48,2,0,2,1,1,32301.88,0 +7042,15753591,He,438,France,Male,38,2,0,2,1,0,136859.55,0 +7043,15617348,Uchechukwu,544,France,Male,44,1,0,2,0,0,69244.24,0 +7044,15704581,Robertson,595,Germany,Male,34,2,87967.42,2,0,1,156309.52,0 +7045,15738487,Leworthy,678,France,Male,26,3,0,2,1,0,4989.33,0 +7046,15648069,Onyemachukwu,850,France,Female,36,6,0,2,1,1,190194.95,0 +7047,15737627,Rivero,589,Germany,Female,20,2,121093.29,2,1,0,3529.72,0 +7048,15731586,Lai,785,Spain,Female,31,2,121691.54,2,0,0,81778.72,0 +7049,15757467,Feng,563,Spain,Male,57,6,0,2,1,1,39297.48,0 +7050,15597709,Hornung,602,France,Female,39,6,154121.32,2,1,0,176614.86,1 +7051,15720529,Schiavone,591,France,Male,29,6,0,2,1,1,108684.65,0 +7052,15596797,Barnet,643,Spain,Male,43,1,0,2,1,1,145764.4,0 +7053,15681755,Dennys,605,France,Female,32,5,0,2,1,1,42135.28,0 +7054,15815271,Ritchie,755,Germany,Male,43,6,165048.5,3,1,0,16929.41,1 +7055,15682860,Lo,769,Spain,Male,38,6,0,2,0,0,104393.78,0 +7056,15621546,Yuriev,620,France,Female,33,9,127638.35,1,1,1,192717.57,0 +7057,15705918,Howarth,725,France,Male,31,8,0,2,1,1,59650.42,0 +7058,15684512,Gibson,818,Germany,Female,72,8,135290.42,2,1,1,63729.72,0 +7059,15671769,Zikoranachidimma,624,France,Female,71,4,170252.05,3,1,1,73679.59,1 +7060,15642934,Mason,669,Germany,Female,35,4,108269.2,2,1,0,174969.92,0 +7061,15594305,Rizzo,712,France,Female,32,1,0,2,1,0,1703.58,0 +7062,15789201,Thomson,603,Germany,Female,35,9,145623.36,1,1,0,163181.62,0 +7063,15706762,Ignatyev,597,France,Female,41,4,145809.53,2,1,1,52319.26,0 +7064,15766183,Ferguson,580,Germany,Male,76,2,130334.84,2,1,1,51672.08,0 +7065,15777994,Woods,718,France,Female,39,3,0,2,1,1,145355.11,0 +7066,15568162,Sung,527,Spain,Male,53,8,0,1,1,1,51711.57,0 +7067,15680643,Lo,729,Spain,Female,42,1,0,2,1,1,149535.97,0 +7068,15761854,Burn,746,France,Female,24,4,0,1,0,1,94105,0 +7069,15730793,Russell,699,Germany,Female,54,3,111009.32,1,1,1,155905.79,1 +7070,15692137,Jen,759,France,Female,46,2,0,1,1,1,138380.11,0 +7071,15608595,Lo Duca,748,France,Female,39,3,157371.54,1,0,1,97734.3,0 +7072,15709459,Oluchi,698,Spain,Female,63,5,0,1,1,1,173576.71,0 +7073,15775750,Yao,686,France,Male,37,9,134560.62,1,1,0,27596.39,0 +7074,15585855,Gould,679,France,Male,40,1,0,1,1,1,16897.19,0 +7075,15752139,Salter,682,Germany,Male,36,5,72373.62,2,1,0,36895.99,0 +7076,15768295,Warner,778,France,Female,34,7,109564.1,1,0,1,113046.81,0 +7077,15766906,Salier,742,France,Female,25,4,132116.13,2,1,0,129933.5,0 +7078,15725776,Lazar,649,Germany,Male,24,7,101195.23,1,0,0,133091.32,0 +7079,15682576,Onyenachiya,763,France,Male,67,1,149436.73,2,0,1,106282.74,0 +7080,15704081,Findlay,595,Germany,Male,30,9,130682.11,2,1,1,57862.88,0 +7081,15719940,Gibbons,628,Germany,Female,51,10,115280.49,2,0,0,12628.61,1 +7082,15672894,McCawley,625,France,Female,36,8,129944.39,2,0,0,198914.8,0 +7083,15667451,Taylor,733,France,Male,36,5,0,2,1,1,109127.54,0 +7084,15636767,Yang,665,Spain,Female,32,10,0,1,1,1,22487.45,0 +7085,15571415,Okwudiliolisa,805,Germany,Male,56,6,151802.29,1,1,0,46791.09,1 +7086,15575605,Napolitano,725,France,Male,38,6,0,2,1,1,158697.28,0 +7087,15649160,Vavilov,554,France,Female,38,3,138731.95,1,1,1,194138.36,0 +7088,15615832,Teague,675,Spain,Female,35,8,155621.08,1,0,1,35177.31,0 +7089,15600975,Chiemenam,556,France,Female,54,4,150005.38,1,1,0,157015.5,1 +7090,15690772,Hughes,635,Spain,Female,48,2,0,2,1,1,136551.25,0 +7091,15565714,Cattaneo,601,France,Male,47,1,64430.06,2,0,1,96517.97,0 +7092,15763108,Davis,600,Germany,Male,53,7,106261.63,1,1,0,93629.66,1 +7093,15723884,Nekrasova,758,Spain,Male,40,3,0,2,0,0,96097.65,0 +7094,15644453,Loggia,606,Germany,Female,41,4,132670.53,1,1,0,156476.36,1 +7095,15655464,Combes,640,France,Female,67,3,0,1,0,1,42964.63,0 +7096,15783883,Onwuka,753,Germany,Female,38,1,117314.92,1,1,0,122021.33,1 +7097,15787693,Kharlamov,559,Spain,Male,38,3,145874.35,1,1,0,56311.39,1 +7098,15664793,Scott,754,Spain,Female,50,7,146777.44,2,0,1,150685.52,0 +7099,15642391,Lettiere,621,Germany,Male,51,4,109978.83,1,0,0,177740.58,1 +7100,15756538,Osonduagwuike,654,France,Female,37,5,0,1,0,1,71492.28,0 +7101,15668830,Wan,650,Spain,Male,24,8,108881.73,1,1,0,104492.83,0 +7102,15796569,Donaldson,831,Spain,Female,44,10,0,1,0,1,47729.33,0 +7103,15677112,Chukwufumnanya,519,France,Male,39,2,112957.26,2,1,0,97593.16,0 +7104,15815040,Ma,552,Germany,Female,42,8,103362.14,1,0,1,186869.58,1 +7105,15590434,Alexander,577,Spain,Male,41,4,89015.61,1,0,1,135227.23,0 +7106,15597536,Nkemjika,576,Spain,Male,45,5,133618.01,1,0,0,135244.87,0 +7107,15723989,Carroll,646,France,Male,40,5,93680.43,2,1,1,179473.26,0 +7108,15767358,Obioma,711,Germany,Female,45,1,97486.15,2,1,0,50610.62,0 +7109,15594812,Campbell,806,Spain,Female,37,2,137794.18,2,0,1,75232.02,0 +7110,15688210,Sims,670,France,Female,39,8,101928.51,1,0,0,89205.54,0 +7111,15681509,McKay,679,Spain,Female,28,9,0,2,0,1,61761.77,0 +7112,15572390,Huang,850,Spain,Female,39,6,0,2,1,0,103921.43,0 +7113,15801441,Campbell,670,Germany,Female,35,2,79585.96,1,0,1,198802.9,0 +7114,15783859,Boni,733,France,Female,24,3,161884.99,1,1,1,9617.24,0 +7115,15575243,Gorbunova,764,France,Female,39,1,129068.54,2,1,1,187905.12,0 +7116,15773421,Genovese,673,France,Female,42,4,0,2,1,0,121440.8,0 +7117,15788776,Landor,588,Germany,Male,49,6,132623.76,3,1,0,36292.94,1 +7118,15765257,Meng,564,Spain,Male,31,5,121461.87,1,1,1,20432.09,1 +7119,15661412,Wardell,715,France,Male,32,8,175307.32,1,1,0,187051.23,0 +7120,15636478,Williams,621,France,Male,31,7,136658.61,1,1,1,148689.13,0 +7121,15603683,Ofodile,796,Spain,Female,23,3,146584.19,2,0,0,125445.8,0 +7122,15651868,Clark,672,France,Male,34,6,0,1,0,0,22736.06,0 +7123,15815443,Lo,527,Spain,Female,46,10,131414.76,1,1,0,54947.51,0 +7124,15682686,Chukwuemeka,722,France,Female,38,3,0,2,0,1,167984.72,0 +7125,15697460,Lai,596,Germany,Male,34,4,99441.21,2,0,1,4802.27,0 +7126,15748432,Arcuri,746,France,Female,32,4,0,2,1,1,72909.75,0 +7127,15698271,Graham,523,France,Female,26,4,0,2,1,0,185488.81,0 +7128,15808662,Krylov,624,France,Male,44,3,0,2,1,0,88407.51,0 +7129,15690372,Henry,553,Spain,Male,38,1,181110.13,2,1,0,184544.59,0 +7130,15781875,Jamieson,850,Spain,Male,33,3,100476.46,2,1,1,136539.13,0 +7131,15801473,Moore,599,Germany,Male,33,2,51949.95,2,1,0,85045.92,0 +7132,15704509,Tan,492,France,Male,35,8,121063.49,1,0,0,85421.48,0 +7133,15694666,Thornton,707,Spain,Male,48,8,88441.64,1,1,1,119903.2,1 +7134,15731166,Macleod,743,France,Female,30,1,127023.39,1,1,1,138780.89,0 +7135,15728523,Rizzo,522,France,Male,41,5,144147.68,1,1,1,14789.9,0 +7136,15788442,Chukwukadibia,681,Spain,Female,57,2,173306.13,1,0,1,131964.66,0 +7137,15689781,Ts'ai,826,France,Female,49,0,0,1,0,0,178709.98,1 +7138,15764226,Lu,630,Germany,Female,28,8,106425.75,1,1,1,20344.84,0 +7139,15809837,Kent,430,Germany,Female,66,6,135392.31,2,1,1,172852.06,1 +7140,15805212,Black,806,France,Female,67,1,0,2,0,1,103945.58,0 +7141,15716082,Chukwubuikem,703,Spain,Male,39,6,152685.4,1,0,0,183656.12,0 +7142,15643056,McMillan,755,Germany,Female,38,1,82083.52,1,0,1,10333.78,0 +7143,15654859,Ngozichukwuka,612,Spain,Female,63,2,131629.17,2,1,0,122109.58,1 +7144,15761158,Y?an,719,France,Female,54,7,0,2,1,1,125041.52,0 +7145,15577515,Sung,554,Germany,Female,55,0,108477.27,1,0,1,140003,1 +7146,15723827,Macartney,683,France,Male,30,4,114779.35,1,0,0,183171.47,0 +7147,15646594,Ali,749,France,Male,41,5,57568.94,1,1,1,61128.29,0 +7148,15712877,Morley,724,Spain,Male,36,1,0,2,1,0,52462.25,0 +7149,15598802,Martin,770,Spain,Male,30,8,0,2,0,1,50839.85,0 +7150,15699340,Okorie,680,France,Male,37,4,0,2,1,0,61240.87,0 +7151,15691150,Ku,699,France,Female,32,4,110559.46,1,1,1,127429.56,0 +7152,15608688,Andreyeva,442,France,Male,34,4,0,2,1,0,68343.08,0 +7153,15737998,Cheng,529,France,Male,46,8,0,1,0,0,126511.94,1 +7154,15735837,Hsia,574,Spain,Male,36,3,0,2,1,1,8559.66,0 +7155,15659100,Lane,605,France,Male,33,9,128152.82,1,0,0,147822.81,0 +7156,15609070,Findlay,515,Germany,Male,45,7,120961.5,3,1,1,39288.11,1 +7157,15650313,Okonkwo,632,Germany,Male,65,6,129472.33,1,1,1,85179.48,0 +7158,15627699,Pirogova,558,France,Male,32,10,105000.23,1,1,0,190019.61,0 +7159,15591010,McDonald,434,Germany,Male,55,8,109339.17,2,1,0,96405.88,1 +7160,15798895,Okonkwo,525,France,Female,59,6,55328.4,1,1,0,83342.73,1 +7161,15745375,Nnanna,640,Germany,Male,23,3,72012.76,1,1,0,161333.13,0 +7162,15775235,Ku,690,France,Female,36,6,110480.48,1,0,0,81292.33,0 +7163,15780088,Porter,607,Spain,Male,34,9,132439.99,1,1,0,177747.72,0 +7164,15649379,Somayina,850,France,Female,46,3,0,2,1,1,187980.21,0 +7165,15713983,Mao,780,Germany,Male,34,5,94108.54,2,1,0,177235.21,0 +7166,15709252,Fuller,616,Germany,Female,28,10,105173.99,1,0,1,29835.37,1 +7167,15699238,Craig,618,Spain,Female,40,8,0,2,1,0,80204.38,0 +7168,15732884,Trevisano,676,France,Male,29,7,131959.86,1,0,0,189268.81,0 +7169,15587297,Ruiz,507,France,Male,33,7,0,2,1,1,85411.01,0 +7170,15684722,Fraser,490,France,Male,34,5,122952.9,2,0,0,154360.97,0 +7171,15621244,Gallo,678,France,Male,36,0,107379.68,1,1,1,84460.18,0 +7172,15744273,Waterhouse,637,Germany,Male,30,6,122641.56,2,1,0,65618.01,0 +7173,15682540,Cremonesi,602,France,Female,33,8,0,2,1,1,112928.74,0 +7174,15636521,Feng,744,Spain,Female,30,1,124037.28,1,1,1,142210.94,0 +7175,15785339,H?,640,France,Female,50,9,117565.03,2,0,0,82559.77,0 +7176,15638983,Jara,684,France,Female,38,5,133189.4,1,0,0,127388.06,0 +7177,15654625,Wilson,495,Germany,Male,39,8,120252.02,2,1,1,10160.23,0 +7178,15697310,O'Callaghan,559,Germany,Female,28,3,152264.81,1,0,0,64242.31,0 +7179,15678210,Robson,684,France,Male,38,5,105069.98,2,1,1,198355.28,0 +7180,15575438,Pease,613,France,Male,42,7,115076.06,1,1,1,79323.61,0 +7181,15632789,Maclean,794,France,Male,30,8,0,2,1,1,24113.91,0 +7182,15621423,Lavrentyev,736,France,Female,42,7,117280.23,3,0,0,41921.06,1 +7183,15573520,Rhodes,692,Germany,Male,49,6,110540.43,2,0,1,107472.99,0 +7184,15740458,Murphy,703,Spain,Male,36,7,135095.47,1,1,0,143859.66,0 +7185,15762799,Alexander,720,Germany,Male,23,0,187861.18,2,1,1,104120.17,0 +7186,15686885,Nekrasov,777,Germany,Male,44,3,124655.59,2,0,1,79792.3,0 +7187,15565996,Arnold,653,France,Male,44,8,0,2,1,1,154639.72,0 +7188,15662152,Trevisan,552,France,Female,38,9,134105.01,1,0,0,57850.1,0 +7189,15711742,Mason,708,France,Female,34,4,0,1,1,1,62868.33,0 +7190,15701885,Tucker,647,France,Female,40,9,0,2,0,1,92357.21,0 +7191,15774262,Hobson,597,Germany,Male,52,8,83693.34,2,1,1,161083.53,0 +7192,15567839,Gordon,501,France,Male,42,9,114631.23,1,0,1,91429.74,0 +7193,15644400,Anderson,709,France,Male,44,9,128601.98,1,1,0,117031.2,0 +7194,15797246,Terry,621,Germany,Female,34,2,91258.52,2,1,0,44857.4,0 +7195,15778290,Lappin,799,France,Male,70,8,70416.75,1,1,1,36483.52,0 +7196,15708714,Santiago,675,France,Female,33,6,0,2,1,0,34045.61,0 +7197,15586183,Wallace,561,France,Female,35,5,0,2,1,0,59981.62,0 +7198,15761733,King,707,France,Female,42,10,0,2,1,1,152944.39,0 +7199,15773934,Fang,670,France,Male,33,6,88294.6,1,1,0,66979.06,0 +7200,15705343,May,649,Spain,Female,32,7,0,1,1,0,28797.32,0 +7201,15593959,Travis,524,France,Male,28,1,93577.3,1,1,1,51670.82,0 +7202,15664615,Nnachetam,689,Germany,Female,30,5,136650.89,1,1,1,41865.72,1 +7203,15671014,Zhdanova,573,Spain,Female,72,8,98765.84,1,1,1,96015.53,0 +7204,15657778,Jefferson,657,France,Male,33,1,84309.57,2,0,0,103914.4,0 +7205,15585192,Cremonesi,686,Spain,Male,39,10,136258.06,1,0,0,89199.51,0 +7206,15592914,Fang,683,France,Female,29,9,0,2,1,1,48849.89,0 +7207,15770995,Sinclair,753,Germany,Female,47,1,131160.85,1,1,0,197444.69,0 +7208,15570990,Begley,520,Spain,Female,30,4,145222.99,2,0,0,145160.96,0 +7209,15596165,Degtyarev,547,Germany,Male,25,4,98141.57,2,1,1,52309.8,0 +7210,15788131,Atkins,653,France,Male,47,6,0,1,1,0,50695.93,1 +7211,15800773,Ikenna,648,Spain,Female,28,9,102282.61,1,1,1,157891.11,0 +7212,15690153,Sun,639,France,Female,37,4,116121.84,2,0,1,181850.74,0 +7213,15638989,Lettiere,711,France,Female,25,5,190066.54,1,0,0,51345.39,1 +7214,15623210,Smith,484,Germany,Female,55,8,149349.58,3,0,0,137519.92,1 +7215,15652658,Finch,721,France,Male,36,1,155176.83,2,1,1,49653.37,0 +7216,15684440,Monaldo,548,Germany,Male,32,2,98986.28,1,1,1,55867.38,0 +7217,15730287,Ugonna,679,France,Male,41,8,147726.98,3,1,0,172749.4,1 +7218,15720353,Chiang,553,France,Male,41,1,0,2,1,0,90607.31,0 +7219,15767231,Sun,757,France,Male,36,7,144852.06,1,0,0,130861.95,0 +7220,15761554,Blackburn,581,France,Male,54,4,89299.81,1,0,0,5558.47,1 +7221,15706637,Chang,718,Spain,Male,40,9,0,2,0,0,121537.91,0 +7222,15690492,Palermo,625,France,Male,41,6,97663.16,2,1,0,57128.78,0 +7223,15694237,McEwan,744,Spain,Male,39,4,95161.75,1,1,0,19409.77,0 +7224,15729771,Davide,799,Germany,Male,31,9,154586.92,1,0,1,88604.89,1 +7225,15609823,Chieloka,751,Spain,Female,34,8,127095.14,2,0,0,479.54,0 +7226,15793366,Humphreys,781,Germany,Male,35,7,92526.15,2,1,1,173837.54,0 +7227,15614813,Cocci,777,Germany,Female,46,0,107362.8,1,1,0,487.3,0 +7228,15566495,Hanson,704,Spain,Female,24,2,0,1,1,0,35600.25,1 +7229,15707602,Macleod,539,France,Female,47,2,127286.04,2,1,1,166929.43,1 +7230,15635244,Ritchie,716,France,Female,29,6,0,2,1,1,98998.61,0 +7231,15805627,Nebechukwu,670,France,Male,37,2,0,2,1,1,54229.74,0 +7232,15607986,Nnamutaezinwa,555,France,Male,40,10,139930.18,1,1,1,105720.09,0 +7233,15799785,Ikemefuna,679,Germany,Female,30,4,77949.69,1,1,1,121151.46,0 +7234,15699963,Scott,571,France,Male,38,1,121405.04,1,1,1,154844.22,0 +7235,15624595,Chiang,512,Spain,Female,35,5,124580.69,1,1,1,18785.48,0 +7236,15629750,Artyomova,697,France,Male,35,5,133087.76,1,1,0,64771.61,0 +7237,15651460,Hsieh,424,Spain,Male,34,7,0,1,1,1,16250.61,0 +7238,15753550,Levien,684,France,Female,43,7,0,2,1,0,131093.99,0 +7239,15594133,Erskine,697,Spain,Male,62,7,0,1,1,0,129188.18,1 +7240,15772329,Fiorentino,580,Germany,Male,45,8,103741.14,1,1,0,47428.73,1 +7241,15591552,Okonkwo,600,France,Female,32,7,98877.95,1,1,0,132973.21,0 +7242,15750921,Monds,521,France,Male,37,5,105843.26,2,1,1,84908.2,0 +7243,15701687,Campbell,664,Spain,Male,44,7,77526.66,3,0,0,57338.56,1 +7244,15728906,Ibekwe,634,France,Male,77,5,0,2,1,1,161579.85,0 +7245,15670029,Marcelo,445,France,Female,33,7,0,2,1,0,122625.68,0 +7246,15763579,Castro,702,Germany,Female,36,2,105264.88,2,1,1,52909.87,0 +7247,15728010,Capon,485,France,Male,37,5,0,2,0,1,170226.47,0 +7248,15663194,Voronova,582,Germany,Female,40,3,110150.43,1,1,1,191757.65,1 +7249,15736510,Loggia,605,Spain,Female,57,2,0,3,1,0,66652.75,1 +7250,15745804,Law,628,France,Male,25,7,0,2,1,1,195977.75,0 +7251,15631451,Grant,604,Spain,Female,28,6,0,2,1,1,69056.26,0 +7252,15746995,Greco,724,Germany,Male,31,9,138166.3,1,1,0,12920.43,0 +7253,15730673,Dietz,567,Germany,Male,40,7,122265.24,1,1,0,138552.74,0 +7254,15734649,Martel,779,Spain,Female,55,0,133295.98,1,1,0,22832.71,1 +7255,15701081,Jarvis,785,France,Male,36,2,0,1,0,1,61811.1,0 +7256,15632503,Meng,563,France,Female,32,0,148326.09,1,1,0,191604.27,1 +7257,15585928,Hay,821,Germany,Female,31,2,68927.57,1,1,1,25445,0 +7258,15648681,Voronoff,747,France,Female,47,5,139914.6,4,0,1,129964.56,1 +7259,15747757,Trevascus,600,Germany,Female,58,8,118723.11,1,0,0,6209.51,1 +7260,15718921,Ho,625,Spain,Male,32,7,106957.28,1,1,1,134794.02,0 +7261,15571081,Hansen,773,France,Female,41,7,190238.93,1,1,1,57549.65,0 +7262,15734578,Craig,726,France,Female,53,1,113537.73,1,0,1,28367.21,0 +7263,15579583,Hall,641,Spain,Female,40,4,101090.27,1,1,1,51703.09,0 +7264,15622729,Sun,649,France,Female,46,2,0,2,1,1,66602.7,0 +7265,15662189,Durant,434,Spain,Male,33,3,0,1,1,1,2739.71,0 +7266,15692718,Jackson,738,France,Female,38,7,0,2,0,0,69227.42,0 +7267,15762716,Chigozie,762,Spain,Female,60,10,168920.75,1,1,0,31445.03,1 +7268,15724851,Farmer,507,Germany,Male,31,9,111589.67,1,1,0,150037.19,0 +7269,15587266,Douglas,606,Germany,Female,27,6,172310.33,1,0,1,111448.92,0 +7270,15675926,Ardis,655,Germany,Male,34,7,118028.35,1,1,0,51226.32,1 +7271,15706268,Smith,697,Germany,Male,51,1,147910.3,1,1,1,53581.14,0 +7272,15581871,Butler,504,Germany,Male,42,7,131287.36,2,1,1,149697.78,0 +7273,15666166,Pettry,653,France,Female,74,0,121276.32,1,1,1,160348.31,0 +7274,15671582,John,660,Spain,Male,38,6,109869.32,1,1,1,154641.91,0 +7275,15680901,Potter,652,France,Female,34,6,97435.85,2,1,1,104331.76,0 +7276,15642336,Shaw,669,France,Female,42,9,0,2,0,0,135630.32,0 +7277,15653147,Boyle,594,France,Male,35,2,133853.27,1,1,1,65361.66,0 +7278,15571284,Elmore,756,Germany,Male,32,0,109528.16,2,1,1,56176.31,0 +7279,15591360,Udinesi,642,France,Female,33,4,84607.34,2,0,1,60059.47,0 +7280,15810485,Sun,486,Germany,Male,37,1,101438,1,0,0,51364.56,0 +7281,15611973,Tuan,804,France,Male,55,7,0,2,1,1,118752.6,0 +7282,15735572,Lawrence,629,France,Male,59,9,113657.83,1,1,1,116848.79,1 +7283,15567860,Burrows,581,Spain,Female,44,7,189318.16,2,1,0,45026.23,1 +7284,15795690,Shao,667,France,Male,31,3,99513.91,1,1,1,189657.26,0 +7285,15706464,White,667,Spain,Male,35,4,97585.32,2,0,0,57213.46,0 +7286,15725028,Chialuka,679,France,Male,29,3,0,2,1,1,63687.06,0 +7287,15751167,Toscano,680,France,Female,43,4,0,2,1,1,58761.33,0 +7288,15633944,McKay,644,Spain,Male,32,3,136659.74,1,1,1,14187.78,0 +7289,15672637,Voronkov,571,France,Female,30,4,85755.86,1,1,0,145115.95,0 +7290,15680895,Sal,627,Spain,Female,35,7,0,1,1,0,187718.26,0 +7291,15793825,Ikechukwu,536,France,Male,39,4,0,2,1,0,27150.35,0 +7292,15611318,Kruglova,599,Spain,Male,33,4,51690.89,1,1,0,111622.76,1 +7293,15768474,Clements,744,Spain,Male,34,3,0,2,1,0,27244.35,0 +7294,15716276,Kennedy,709,France,Female,34,2,111669.68,1,1,0,57029.66,0 +7295,15623668,Johnson,653,Germany,Male,31,2,154741.45,2,0,0,25183.01,0 +7296,15696361,Chung,648,Germany,Male,31,7,125681.51,1,0,1,129980.93,0 +7297,15607988,Garland,663,Germany,Female,37,8,155303.71,1,1,0,118716.63,0 +7298,15637891,Docherty,613,Germany,Female,43,4,140681.68,1,0,1,20134.07,0 +7299,15789865,Nnaife,620,France,Male,28,9,71902.52,1,0,1,190208.23,0 +7300,15627190,Lettiere,661,France,Male,51,6,146606.6,1,1,1,68021.9,0 +7301,15788224,Sanderson,669,Germany,Male,45,1,123949.75,1,0,0,110881.56,0 +7302,15702149,Fomin,767,Germany,Female,33,1,144753.21,1,1,1,132480.75,0 +7303,15708236,Wright,491,France,Female,72,6,91285.22,1,1,1,7032.95,0 +7304,15568469,Buckley,653,France,Male,43,0,0,2,1,0,27862.58,0 +7305,15764444,Pan,679,Germany,Male,58,8,125850.53,2,1,1,87008.17,0 +7306,15794204,Manna,687,France,Male,28,7,108116.66,1,1,1,27411.19,0 +7307,15807546,Chinwendu,837,France,Female,38,2,0,2,1,1,46395.21,0 +7308,15782159,Ndubuagha,850,France,Male,28,8,67639.56,2,1,1,194245.29,0 +7309,15618703,White,663,Spain,Female,53,6,150200.23,1,0,1,151317.27,1 +7310,15793317,Hale,547,Spain,Female,22,7,141287.15,1,1,0,118142.79,0 +7311,15740487,Ross,627,France,Female,41,6,0,3,1,1,138700.75,1 +7312,15722479,Ikenna,707,France,Male,37,1,0,2,0,1,6035.51,0 +7313,15688264,Nkemdilim,629,France,Female,43,0,0,2,1,1,41263.69,0 +7314,15583067,McMillan,687,France,Female,36,4,97157.96,1,0,1,63185.05,0 +7315,15686670,Duke,588,France,Female,36,2,0,2,1,0,92536,1 +7316,15593345,Bradbury,502,Germany,Female,33,6,125241.17,2,1,1,158736.07,0 +7317,15811690,Bayley,793,Germany,Male,54,2,128966.13,1,0,0,18633.4,1 +7318,15734008,Bartlett,727,Germany,Male,59,5,152581.06,1,1,0,71830.1,1 +7319,15771856,Cremin,632,Spain,Female,32,1,0,2,1,0,19525.65,0 +7320,15762045,Gilchrist,474,Germany,Female,37,5,142688.57,2,1,1,110953.33,0 +7321,15778142,Shih,850,Germany,Female,31,1,130089.56,2,1,1,4466.21,0 +7322,15689268,Fitzpatrick,584,France,Male,36,9,0,1,1,1,105818.51,0 +7323,15721507,Pagan,713,France,Female,32,1,117094.02,1,0,0,149558.83,1 +7324,15750476,Hendrick,742,Spain,Male,24,8,0,2,1,0,4070.28,0 +7325,15810723,Sanderson,607,France,Female,39,10,0,3,1,0,132741.13,1 +7326,15787229,Samsonova,761,Spain,Female,34,2,0,2,1,0,61251.25,0 +7327,15570508,Azubuike,600,France,Male,49,7,90218.9,1,1,0,91347.76,0 +7328,15617065,Pan,650,Spain,Male,42,4,194532.66,1,1,0,171045.31,1 +7329,15689786,Massie,850,Germany,Male,56,1,169743.83,1,0,0,155850.4,1 +7330,15648876,Sandover,501,France,Female,34,5,0,1,1,0,27380.99,0 +7331,15802106,Craig,418,France,Male,34,8,155973.88,1,1,0,154208.96,0 +7332,15773869,Onwudiwe,797,Spain,Male,59,4,129321.44,1,1,1,93624.55,0 +7333,15711635,Chu,788,Germany,Female,42,6,138650.49,2,1,0,64746.07,0 +7334,15795527,Zetticci,699,Spain,Male,43,2,136487.86,2,1,0,82815.93,0 +7335,15759133,Vaguine,616,France,Male,18,6,0,2,1,1,27308.58,0 +7336,15679394,Owen,651,France,Female,41,4,38617.2,1,1,1,104876.8,0 +7337,15801072,Hurst,654,France,Female,28,7,0,2,1,0,151316.37,0 +7338,15646082,Harding,676,France,Female,34,8,82909.14,1,1,0,91817.38,1 +7339,15796111,Smith,708,Germany,Female,54,8,145151.4,1,0,1,125311.17,1 +7340,15670646,Moore,499,Spain,Female,42,0,147187.84,1,1,1,14868.94,1 +7341,15578722,Bradley,689,France,Male,39,4,0,2,1,0,196112.45,0 +7342,15815095,Burfitt,850,Spain,Male,54,7,108185.81,2,0,0,24093.4,1 +7343,15730360,Mackenzie,502,France,Male,30,4,0,2,1,1,66263.87,0 +7344,15763194,Milanesi,643,France,Male,34,7,0,2,0,1,100304.13,0 +7345,15720725,Shubin,762,France,Male,28,2,0,2,1,0,167909.52,0 +7346,15567834,Nieves,719,France,Male,49,5,105918.1,1,1,1,16246.59,0 +7347,15720644,Martin,789,France,Male,27,6,0,2,1,0,103603.65,0 +7348,15811742,Jen,553,Spain,Male,42,7,0,2,1,0,7680.23,0 +7349,15813363,Woods,448,Spain,Male,25,2,0,2,0,0,95215.73,0 +7350,15717629,Docherty,632,Germany,Male,42,6,59972.26,2,0,1,148172.94,0 +7351,15713160,Lin,669,Spain,Male,25,7,157228.61,2,1,0,124382.9,0 +7352,15568878,Cheng,654,Spain,Male,34,5,0,2,1,0,159311.46,0 +7353,15809800,Korovina,726,France,Female,38,4,0,2,0,0,6787.48,0 +7354,15736420,Macdonald,596,France,Male,21,4,210433.08,2,0,1,197297.77,1 +7355,15757933,Hardy,733,Germany,Female,30,1,102452.71,1,1,0,21556.95,0 +7356,15623072,Shaw,529,Spain,Female,35,5,0,2,1,0,56518,0 +7357,15683993,Knight,493,France,Female,37,8,142987.46,2,1,0,158840.99,0 +7358,15570947,Bruny,615,Spain,Female,29,7,143330.56,2,1,1,126396.01,0 +7359,15797767,Ikedinachukwu,600,France,Female,49,6,0,1,0,1,148087.88,1 +7360,15731989,Moran,666,France,Male,36,4,120165.4,2,1,0,33701.5,0 +7361,15591035,Macleod,644,Spain,Male,54,6,0,1,0,1,84622.37,0 +7362,15586479,Yin,692,France,Female,36,4,0,1,1,0,185580.89,1 +7363,15605872,Felix,707,France,Male,73,6,66573.17,1,1,1,62768.8,0 +7364,15666012,Rippey,603,France,Male,40,4,102833.46,2,1,1,38829.11,0 +7365,15641733,Mishina,671,France,Female,34,5,164757.56,1,1,0,110748.88,0 +7366,15593178,Graham,568,Spain,Female,36,10,153610.61,1,1,1,54083.8,1 +7367,15649183,Johnston,598,Spain,Female,35,8,0,3,0,1,88658.73,0 +7368,15736399,Korovin,606,Spain,Male,42,10,0,2,1,0,177938.52,0 +7369,15751137,Lei,850,Germany,Female,36,3,169025.83,1,1,0,174235.06,0 +7370,15757188,Chimaijem,644,Spain,Female,26,4,153455.72,2,1,1,82696.84,0 +7371,15726167,Scott,655,France,Male,37,4,0,2,1,1,142415.97,0 +7372,15624850,Grant,850,France,Male,30,10,153972.89,2,1,0,62811.03,0 +7373,15717700,McIntyre,683,Spain,Male,34,9,114609.55,2,0,1,25339.29,0 +7374,15716347,Griffin,663,Germany,Male,37,7,143625.83,2,0,1,176487.05,0 +7375,15696287,Converse,682,Germany,Female,38,1,116520.28,1,1,1,49833.5,1 +7376,15638871,Ch'ang,639,France,Male,77,6,80926.02,2,1,1,55829.25,0 +7377,15765093,Coates,704,France,Male,23,6,166594.78,1,1,1,155823.2,0 +7378,15592999,Reid,691,France,Female,40,0,115465.98,1,1,1,60622.61,0 +7379,15641715,Ts'ui,599,France,Male,34,8,0,2,1,1,174196.68,0 +7380,15607746,Belstead,573,France,Female,36,1,0,1,1,1,56905.38,0 +7381,15625311,Dickinson,589,Germany,Female,41,7,92618.62,1,1,1,101178.85,0 +7382,15573077,Nwora,620,Germany,Female,25,8,141825.88,1,1,1,73857.94,1 +7383,15735106,Bishop,647,Spain,Male,28,6,149594.02,2,1,0,102325.19,0 +7384,15672912,Loggia,737,Spain,Female,39,7,130051.66,2,0,0,55356.39,1 +7385,15589881,Rowe,634,France,Female,41,7,0,2,1,1,131284.93,0 +7386,15660144,Balashov,660,France,Male,38,4,0,2,0,0,88080.43,0 +7387,15664083,Ulyanova,666,Germany,Female,37,2,158468.76,1,0,1,93266.01,0 +7388,15690898,Bogolyubova,696,France,Male,44,8,161889.79,1,0,0,75562.47,0 +7389,15808023,Remington,836,France,Female,29,9,133681.78,1,1,1,153747.73,0 +7390,15676909,Mishin,667,Spain,Female,34,5,0,2,1,0,163830.64,0 +7391,15764922,Tu,596,Spain,Male,20,3,187294.46,1,1,0,103456.47,0 +7392,15766734,Castiglione,430,France,Male,31,5,0,1,1,0,95655.16,0 +7393,15795079,Nnaife,596,Spain,Male,67,6,0,2,1,1,138350.74,0 +7394,15757434,Yang,599,France,Male,28,7,119706.22,1,0,0,31190.42,0 +7395,15673747,Ayers,519,France,Female,22,8,0,1,0,1,167553.06,0 +7396,15808386,Cocci,721,Germany,Female,45,7,138523.2,1,0,0,59604.45,1 +7397,15603565,Mackenzie,603,Spain,Female,56,5,90778.76,2,1,0,162223.67,1 +7398,15744044,Fiorentini,572,Germany,Male,47,4,99353.42,1,1,0,196549.85,1 +7399,15577771,Akabueze,453,Germany,Female,40,1,111524.49,1,1,1,120373.84,1 +7400,15769548,Hyde,668,France,Female,37,7,128645.67,1,1,0,92149.64,0 +7401,15802071,Levi,762,Germany,Male,35,1,117458.51,1,0,1,178361.48,1 +7402,15677395,Nwabugwu,633,France,Female,39,9,129189.15,2,0,0,170998.83,0 +7403,15632010,Chia,647,Spain,Male,33,7,121260.19,2,1,0,77216.48,0 +7404,15779492,Trevisano,796,Spain,Male,56,6,94231.13,1,0,0,121164.6,1 +7405,15694677,Bennetts,733,France,Male,39,1,0,2,1,1,141841.31,0 +7406,15704315,Teng,556,France,Male,34,8,163757.06,1,1,1,104000.06,0 +7407,15742009,Hsueh,489,Spain,Male,58,4,0,2,1,1,191419.32,0 +7408,15766663,Mahmood,639,France,Male,22,4,0,2,1,0,28188.96,0 +7409,15742297,Sinclair,715,France,Male,35,2,141005.47,1,1,1,60407.93,0 +7410,15688059,Chin,807,Germany,Female,42,9,105356.09,2,1,1,130489.37,0 +7411,15752344,She,714,Spain,Male,34,5,0,2,1,0,193040.32,0 +7412,15698749,He,626,Germany,Female,23,6,85897.95,1,1,0,109742.8,0 +7413,15631693,Hill,697,France,Male,36,7,0,2,1,1,74760.32,0 +7414,15604536,Vachon,850,Germany,Female,31,4,164672.66,1,0,1,61936.1,0 +7415,15802869,Ball,737,Germany,Female,45,2,99169.67,2,1,1,78650.95,0 +7416,15635598,Hsieh,812,France,Male,29,6,0,2,0,0,168023.6,0 +7417,15592326,Baker,583,France,Male,36,8,0,2,0,1,5571.59,0 +7418,15736533,Monaldo,730,Germany,Female,37,5,124053.03,1,1,0,118591.67,0 +7419,15647191,Lucchesi,677,France,Male,36,4,0,2,1,0,7824.31,0 +7420,15622507,Hamilton,748,Germany,Female,40,3,103499.09,2,0,0,38153.19,0 +7421,15765487,Kuo,753,Germany,Female,38,9,151766.71,1,1,1,180829.99,0 +7422,15646521,Fan,634,Spain,Female,36,1,0,1,1,1,143960.72,0 +7423,15746258,Wright,622,France,Male,29,7,101486.96,1,1,1,8788.35,0 +7424,15692430,Milano,699,Germany,Male,36,2,123601.56,2,1,0,103557.85,0 +7425,15625501,Wall,570,Germany,Male,38,1,127201.58,1,1,0,147168.28,1 +7426,15640521,Chidumaga,552,Germany,Male,33,3,144962.74,1,1,0,58844.84,1 +7427,15790630,Olisaemeka,619,France,Female,48,4,0,1,0,0,18094.96,1 +7428,15664720,Kovalyova,714,Spain,Male,33,8,122017.19,1,0,0,162515.17,0 +7429,15750055,Onio,503,Spain,Male,32,9,100262.88,2,1,1,157921.25,0 +7430,15644878,Hill,685,Spain,Female,43,6,117302.62,1,0,0,68701.73,0 +7431,15754578,Okeke,606,France,Female,35,0,135984.15,2,1,0,186778.89,0 +7432,15705379,Upjohn,678,France,Male,38,3,0,2,1,0,66561.6,0 +7433,15761047,H?,724,Germany,Male,31,2,160997.54,2,0,1,64831.36,0 +7434,15671293,Marcus,779,Germany,Female,37,2,128389.63,1,1,1,6589.16,1 +7435,15687527,Yobachukwu,638,Spain,Male,35,1,0,2,1,0,165370.66,0 +7436,15647898,Russell,610,Spain,Female,50,5,130554.51,3,1,0,184758.17,1 +7437,15671534,Hovell,646,Germany,Female,57,6,90212,1,1,0,13911.27,1 +7438,15591248,Chukwumaobim,628,France,Female,29,9,71996.29,1,1,1,34857.46,0 +7439,15676156,Boyle,528,France,Female,32,4,85615.66,2,1,0,156192.43,0 +7440,15812918,Scott,432,France,Female,27,6,62339.81,2,0,0,53874.67,0 +7441,15604130,Johnstone,622,Spain,Female,47,6,142319.03,1,0,0,100183.05,0 +7442,15700549,Alvares,721,France,Male,54,5,0,2,1,1,4493.12,0 +7443,15715519,McDavid,614,Spain,Male,36,5,0,2,1,0,130610.78,0 +7444,15707042,Dellucci,634,France,Female,24,2,87413.19,1,1,0,63340.65,0 +7445,15605276,Brothers,742,France,Female,29,4,0,2,1,1,180066.59,0 +7446,15630592,Sanders,516,France,Female,45,4,0,1,1,0,95273.73,1 +7447,15636626,Morrison,718,France,Male,35,3,97560.16,1,1,1,53511.74,0 +7448,15740411,Molle,636,Germany,Male,30,8,141787.31,2,1,1,109685.61,0 +7449,15593834,Genovese,691,Spain,Male,36,7,129934.64,1,0,0,75664.56,1 +7450,15804235,Zetticci,698,France,Female,37,2,166178.02,2,1,1,71972.95,0 +7451,15679801,Hsueh,712,Spain,Female,39,5,163097.55,2,1,1,23702.42,0 +7452,15673907,Alexander,659,France,Male,20,8,0,2,0,0,112572.02,0 +7453,15636562,Muravyova,573,Spain,Male,44,8,0,2,0,0,62424.46,0 +7454,15702571,Wright,778,Germany,Female,35,1,151958.19,3,1,1,131238.37,1 +7455,15627365,Calabresi,732,France,Male,46,0,0,2,1,1,184350.78,0 +7456,15748499,Johnson,550,Germany,Male,33,4,118400.91,1,0,1,13999.64,1 +7457,15598614,Lucchesi,790,Spain,Male,20,8,0,2,1,0,168152.76,0 +7458,15668889,Galgano,665,Germany,Female,43,2,116322.27,4,1,0,35640.12,1 +7459,15800049,Grigoryeva,728,Spain,Female,43,5,0,1,1,1,120088.17,0 +7460,15583724,Raymond,645,Spain,Female,29,4,0,2,1,1,74346.11,0 +7461,15622083,Paterson,647,Germany,Male,30,6,143138.91,2,1,0,2955.46,0 +7462,15645571,Genovese,596,Spain,Male,32,4,0,2,0,1,146504.35,0 +7463,15598266,Martin,610,France,Male,40,9,0,1,1,1,149602.54,0 +7464,15667934,Moretti,512,France,Male,36,0,129804.17,1,1,0,53020.9,0 +7465,15569682,Leckie,768,Germany,Male,37,9,108308.11,1,1,0,41788.25,1 +7466,15772941,Lane,666,Germany,Male,30,3,110153.27,1,0,1,74849.46,0 +7467,15586174,Brodney,700,Germany,Female,30,4,116377.48,1,1,1,134417.31,0 +7468,15803682,Angelo,651,Germany,Female,37,10,117791.06,2,1,1,75837.58,0 +7469,15627328,Millar,542,Spain,Female,26,2,0,2,1,1,54869.54,0 +7470,15717065,Balashov,686,France,Female,35,8,105419.73,1,1,0,35356.46,0 +7471,15602456,Afanasyev,850,Germany,Female,47,4,99219.47,2,1,1,122141.13,0 +7472,15721569,Chialuka,658,Germany,Female,55,8,119327.93,1,0,1,119439.66,0 +7473,15573798,Yermolayev,448,France,Female,36,6,83947.12,2,1,0,81999.53,0 +7474,15638272,Tien,609,Spain,Male,32,4,99883.16,1,1,1,120594.85,0 +7475,15799859,Lucchesi,704,France,Male,50,4,165438.26,1,1,0,120770.75,1 +7476,15599152,Lai,698,France,Male,31,1,156111.24,1,0,0,134790.74,0 +7477,15737909,Bates,759,France,Male,44,2,111095.58,2,1,0,100137.7,0 +7478,15646190,Saunders,677,France,Female,56,0,119963.45,1,0,0,158325.87,1 +7479,15711249,Chukwuemeka,544,Spain,Male,22,4,0,2,1,0,70007.67,0 +7480,15671987,Meagher,567,Spain,Male,35,8,153137.74,1,1,0,88659.07,0 +7481,15812766,Golubeva,490,Spain,Male,40,6,156111.08,1,0,0,190889.13,0 +7482,15778589,Collier,626,France,Male,34,7,113014.7,2,1,1,56646.28,0 +7483,15750104,Chan,718,Germany,Male,43,5,132615.73,2,1,0,32999.1,0 +7484,15784526,Chen,616,France,Male,44,5,102016.38,1,0,1,178235.37,1 +7485,15646563,Wright,772,France,Female,35,9,0,1,0,1,25448.31,0 +7486,15744423,Cocci,561,France,Male,32,5,0,2,1,0,84871.99,0 +7487,15593694,Williams,814,France,Male,49,8,0,2,0,0,157822.54,0 +7488,15785367,McGuffog,651,France,Female,56,4,0,1,0,0,84383.22,1 +7489,15687765,Chukwujamuike,538,Germany,Female,42,4,80380.24,1,1,0,119216.46,0 +7490,15789014,Scott,600,France,Female,26,6,108909.12,1,1,0,82547.01,0 +7491,15703177,Bell,654,France,Female,35,2,90865.8,1,1,1,86764.46,0 +7492,15660263,Olisaemeka,622,France,Male,40,4,99799.76,2,1,0,197372.13,0 +7493,15776545,Napolitani,682,France,Male,28,10,200724.96,1,0,1,82872.64,1 +7494,15683276,Sargood,610,Spain,Female,37,10,140363.95,2,1,1,129563.86,0 +7495,15599272,Harrington,795,France,Female,36,1,151844.64,1,1,1,135388.89,0 +7496,15589541,Sutherland,557,France,Female,27,2,0,2,0,1,4497.55,0 +7497,15608804,Allan,824,Germany,Male,49,8,133231.48,1,1,1,67885.37,0 +7498,15645820,Folliero,698,France,Male,27,7,0,2,1,0,111471.55,0 +7499,15659031,Mordvinova,630,France,Female,36,8,126598.99,2,1,1,134407.93,0 +7500,15790113,Schofield,609,Germany,Female,71,6,113317.1,1,1,0,108258.22,1 +7501,15652289,Williams,694,France,Male,47,4,0,2,1,0,197528.62,0 +7502,15605341,Baird,681,France,Female,58,8,93173.88,1,1,1,139761.25,0 +7503,15697844,Whitehouse,721,Spain,Female,32,10,0,1,1,0,136119.96,1 +7504,15652048,Thompson,563,Germany,Male,44,7,105007.31,2,1,1,197812.16,0 +7505,15587038,Ogochukwu,654,Spain,Female,32,2,0,1,1,1,51972.92,1 +7506,15660528,Niu,659,Spain,Male,27,4,0,2,1,0,99341.87,0 +7507,15700300,Okoli,674,Germany,Female,44,4,131593.85,1,0,1,171345.02,1 +7508,15642001,Lorenzen,576,Germany,Male,44,9,119530.52,1,1,0,119056.68,1 +7509,15580366,Okechukwu,566,Germany,Male,54,4,118614.6,2,1,1,172601.62,0 +7510,15657228,Anderson,545,Germany,Male,37,9,95829.13,2,0,1,104936.88,0 +7511,15729377,Ku,798,France,Male,36,1,0,2,1,1,159044.1,0 +7512,15686913,Kung,757,France,Male,38,0,0,1,1,0,83263.06,0 +7513,15631267,Lu,641,France,Male,50,6,153590.73,2,1,1,130910.78,0 +7514,15632275,Trevisano,718,France,Male,29,2,0,1,1,0,126336.72,0 +7515,15715907,Onwubiko,699,France,Male,64,9,113109.52,1,1,0,27980.8,1 +7516,15764841,Vidler,623,France,Female,35,0,130557.24,1,1,1,47880.71,0 +7517,15748649,Shen,644,France,Male,40,8,93183.19,1,1,0,73882.49,0 +7518,15771409,McGregor,586,France,Male,58,7,151933.63,1,1,0,162960.05,1 +7519,15779207,Nnamdi,500,Germany,Male,30,2,125495.64,2,1,1,68807.47,0 +7520,15814116,Castiglione,583,France,Female,42,7,0,2,1,0,144039.05,0 +7521,15665087,Bergamaschi,595,Germany,Female,26,8,118547.72,1,1,1,151192.18,0 +7522,15611189,Allingham,670,Spain,Male,43,1,97792.21,1,0,0,120225.62,0 +7523,15729718,Stelzer,610,France,Male,41,6,0,3,0,0,56118.81,1 +7524,15733602,Rubin,814,Spain,Female,72,2,0,2,0,1,130853.03,0 +7525,15620103,Ho,660,France,Female,40,8,167181.01,1,1,1,185156.94,0 +7526,15770406,Watson,580,Germany,Male,35,9,121355.19,1,0,1,35671.45,0 +7527,15800554,Perry,850,France,Female,81,1,0,2,1,1,59568.24,0 +7528,15611409,Sun,676,Spain,Male,35,0,0,2,0,0,139911.58,0 +7529,15646535,Harrell,578,France,Male,46,5,113226.47,1,1,0,56770.76,0 +7530,15575430,Robson,579,France,Female,33,1,118392.75,1,1,1,157564.75,0 +7531,15711299,Wilson,711,Germany,Female,52,8,145262.54,1,0,1,131473.31,0 +7532,15642063,Kelechi,692,France,Male,40,6,163505.16,1,0,0,90424.09,0 +7533,15706602,Bates,760,Spain,Female,33,1,118114.28,2,0,1,156660.21,0 +7534,15592773,Eberegbulam,630,Germany,Female,51,0,108449.23,3,0,0,88372.69,1 +7535,15786539,Olisaemeka,808,France,Male,32,1,0,2,1,1,46200.71,0 +7536,15737542,Davey,611,Germany,Female,36,10,103294.56,1,1,0,160548.12,0 +7537,15590234,De Luca,697,France,Female,42,1,0,1,1,0,1262.83,1 +7538,15773776,Ho,655,France,Female,38,6,0,1,1,1,188639.28,0 +7539,15728082,Vasiliev,601,Spain,Male,28,6,0,2,1,0,14665.28,0 +7540,15609987,Smith,755,France,Male,42,2,119919.12,1,1,0,156868.21,0 +7541,15735330,Sung,553,France,Male,37,1,0,1,1,0,30461.55,0 +7542,15649430,White,723,France,Male,28,4,0,2,1,1,123885.88,0 +7543,15768777,Wang,507,Spain,Female,34,4,0,2,1,1,60688.38,0 +7544,15777893,Davide,777,France,Male,43,1,0,2,1,0,21785.91,0 +7545,15791326,Nnamdi,566,France,Male,34,3,0,1,0,0,188135.69,0 +7546,15615176,Welsh,732,France,Male,26,7,0,2,1,0,154364.66,0 +7547,15735221,Sousa,697,France,Female,42,10,0,2,1,0,61312.15,0 +7548,15617991,Andrews,555,France,Male,29,4,128744.04,1,1,1,47454.93,0 +7549,15658504,Chiawuotu,584,Germany,Female,62,9,137727.34,2,0,1,121102.9,0 +7550,15785705,Thomson,705,Germany,Female,44,10,106731.58,1,1,0,137419.87,1 +7551,15801817,Carpenter,688,France,Female,38,7,123544.21,1,1,1,157664.02,0 +7552,15752578,Yefimova,626,France,Female,37,2,133968.96,2,1,0,148689.65,0 +7553,15781574,Ma,636,Spain,Male,76,9,126534.6,1,1,1,39789.62,0 +7554,15792107,Black,719,Spain,Female,35,8,0,1,1,1,165162.4,0 +7555,15569917,Obijiaku,706,Spain,Male,30,6,87609.68,2,0,0,137674.55,1 +7556,15721504,King,731,Spain,Male,41,3,0,2,1,0,101371.72,0 +7557,15757306,Miller,738,Spain,Male,49,3,0,3,1,1,65066.48,1 +7558,15647295,Chin,426,France,Male,34,9,0,2,1,0,107876.91,0 +7559,15642098,Cox,622,Spain,Female,36,0,108960,2,1,0,111180.3,1 +7560,15696120,Wallace,701,Spain,Female,30,2,0,2,1,0,115650.63,0 +7561,15675176,Price,512,France,Male,51,6,144953.31,1,1,1,165035.17,0 +7562,15700046,Yuan,635,France,Male,41,4,103544.88,2,1,0,193746.55,0 +7563,15782089,Mullen,685,France,Male,33,6,0,1,1,0,58458.26,0 +7564,15706394,Howell,609,France,Male,53,7,0,2,0,1,52332.85,0 +7565,15759387,McIntosh,598,Germany,Male,38,1,101487.18,1,1,1,75959.1,1 +7566,15623369,Clifton,708,France,Male,52,10,105355.81,1,1,0,123.07,1 +7567,15732943,Okwuoma,574,Spain,Male,36,4,77967.5,1,1,0,167066.95,1 +7568,15750545,Chidiebere,629,France,Male,44,5,0,4,0,0,117572.59,1 +7569,15809909,Fan,422,Spain,Female,54,4,0,2,1,1,7166.71,0 +7570,15642448,Onyemauchechukwu,656,Spain,Male,28,8,120047.77,1,1,1,137173.39,0 +7571,15791944,Harker,697,France,Male,32,7,175464.85,3,1,0,116442.42,1 +7572,15768342,Bolton,718,France,Male,52,8,79475.3,3,1,1,32421.32,1 +7573,15567919,Lazarev,586,Germany,Male,37,8,167735.69,2,0,1,104665.79,0 +7574,15674750,Alexeyeva,481,Spain,Female,37,8,0,2,1,0,44215.86,0 +7575,15778345,Stevens,749,France,Female,33,1,74385.98,1,1,0,20164.47,0 +7576,15687634,Glover,561,Germany,Male,49,5,94754,1,1,1,26691.31,0 +7577,15666096,Ibekwe,676,Spain,Male,27,4,0,1,0,1,107955.67,0 +7578,15581700,Paterson,615,Germany,Male,43,3,86920.86,1,1,1,150048.37,0 +7579,15656417,Marsh,582,France,Female,39,1,132077.48,2,1,0,192255.15,0 +7580,15649101,Reeves,601,France,Male,40,10,127847.86,1,0,0,173245.68,0 +7581,15781975,Rees,708,France,Male,34,3,0,1,0,1,121457.88,1 +7582,15700511,Hanson,708,Germany,Male,42,9,176702.36,2,1,1,104804.74,0 +7583,15770255,Onwughara,797,Germany,Female,33,10,83555.58,1,0,0,69767.14,0 +7584,15643574,Odinakachukwu,682,France,Male,26,8,0,2,1,0,178373.43,0 +7585,15595010,Huang,694,Spain,Female,39,9,0,2,0,0,99924.04,0 +7586,15580579,Trevisani,490,France,Female,40,1,0,1,1,1,49594.19,1 +7587,15748532,Dale,828,Spain,Male,42,10,0,1,1,1,186071.14,0 +7588,15773789,Pavlova,594,Spain,Female,38,7,96858.35,1,1,0,77511.45,0 +7589,15600027,Meng,579,Spain,Male,33,1,0,2,1,1,54816.57,0 +7590,15620832,Dean,723,France,Female,35,0,0,2,0,1,61290.99,0 +7591,15568819,Chiganu,619,Germany,Female,42,8,132796.04,3,1,1,191821.35,1 +7592,15748691,Lung,794,Spain,Female,30,1,154970.54,1,0,1,156768.45,0 +7593,15583552,Donaldson,674,Germany,Male,44,3,88902.21,1,1,0,73731.32,0 +7594,15588019,Li Fonti,418,France,Male,28,7,98738.92,1,1,0,122190.22,0 +7595,15713250,Izmailova,502,France,Male,33,8,0,2,1,1,123509.01,0 +7596,15569595,Walker,678,France,Female,50,6,0,1,1,0,8199.5,0 +7597,15794868,Nnonso,599,Germany,Male,40,10,137456.28,2,1,1,14113.11,0 +7598,15576680,Stevenson,736,France,Male,29,4,0,2,0,0,51705.01,0 +7599,15613699,Schnaars,430,France,Female,60,7,73937.02,1,1,0,161937.62,1 +7600,15609758,Geoghegan,537,France,Female,45,7,158621.04,1,1,0,120892.96,1 +7601,15762392,Ilyina,683,Spain,Male,30,1,113257.2,1,1,1,65035.02,0 +7602,15693382,Muir,828,France,Male,31,9,0,1,0,1,164257.37,0 +7603,15791769,Gardener,691,France,Female,29,9,116536.43,1,1,0,51987.99,0 +7604,15712483,Chidi,608,Spain,Female,28,4,0,2,1,0,10899.63,1 +7605,15636454,Fu,691,France,Female,60,6,101070.69,1,1,0,177355.8,1 +7606,15710138,Sun,718,Spain,Male,39,6,0,2,0,1,63889.1,0 +7607,15571571,Ting,680,Germany,Female,31,3,127331.46,3,1,1,176433.6,0 +7608,15638751,Ashton,838,Spain,Female,41,5,0,2,1,0,81313.51,0 +7609,15598574,Uwakwe,695,Spain,Female,31,5,0,2,0,1,13998.88,0 +7610,15796787,Vassiliev,681,France,Male,46,0,105969.42,1,1,0,5771.56,0 +7611,15615670,Kazakova,762,France,Male,36,5,119547.46,1,1,1,42693.65,0 +7612,15705506,Perry,751,Spain,Male,38,7,0,2,0,0,90839.61,0 +7613,15599535,Howell,678,Spain,Male,28,5,138668.18,1,1,1,54144.01,0 +7614,15768449,Ricci,634,France,Female,37,7,51582.5,2,1,1,184312.88,0 +7615,15725002,Smith,749,France,Male,37,7,0,2,1,0,20306.79,0 +7616,15611682,Rossi,590,Spain,Male,37,6,169902.92,1,1,1,128256.18,0 +7617,15749964,Jones,610,France,Female,27,4,87262.4,2,1,0,182720.07,0 +7618,15678779,Quezada,502,France,Male,33,7,0,2,0,1,4082.52,0 +7619,15752601,McCulloch,578,France,Female,40,7,0,2,0,0,102233.73,0 +7620,15758477,Tobeolisa,547,France,Female,32,2,0,2,1,0,132002.83,0 +7621,15629133,Black,579,France,Female,27,9,0,2,1,0,126838.7,0 +7622,15604963,Fraser,661,France,Male,39,5,0,2,0,0,181461.46,0 +7623,15796413,Green,794,France,Male,46,6,0,2,1,0,195325.74,0 +7624,15812470,Allan,719,France,Male,61,5,0,2,0,1,29132.43,0 +7625,15587443,Akudinobi,728,France,Female,69,1,0,2,1,1,131804.86,0 +7626,15689692,Walker,598,Germany,Male,19,3,150348.37,1,1,1,173784.04,0 +7627,15779586,Olisaemeka,822,Germany,Female,46,3,115074.02,2,1,0,26249.86,0 +7628,15667588,Arcuri,670,Spain,Female,40,3,0,1,1,1,182650.15,0 +7629,15624423,Liu,850,France,Male,28,8,99986.98,1,1,0,196582.55,0 +7630,15591107,Flemming,723,Germany,Female,68,3,110357,1,0,0,141977.54,1 +7631,15748986,Bischof,705,Germany,Male,42,8,166685.92,2,1,1,55313.51,0 +7632,15793896,John,677,Spain,Male,40,7,95312.8,1,1,1,62944.75,0 +7633,15620570,Sinnett,736,France,Male,43,4,202443.47,1,1,0,72375.03,0 +7634,15727811,Ts'ui,661,Germany,Female,47,0,109493.62,1,0,0,188324.01,1 +7635,15707681,Pokrovsky,501,Germany,Male,38,9,88977.39,2,0,1,133403.07,0 +7636,15702030,Azarov,516,France,Female,29,2,104982.57,1,1,0,157378.5,0 +7637,15673238,McCarthy,517,Germany,Female,59,8,154110.99,2,1,0,101240.08,1 +7638,15604196,Simpson,766,France,Male,32,6,185714.28,1,1,1,102502.5,0 +7639,15769356,Stevenson,520,Germany,Female,23,3,116022.53,2,1,1,37577.66,0 +7640,15665590,Moore,541,France,Male,46,6,0,2,1,1,83456.67,0 +7641,15572361,Chill,790,Germany,Female,34,2,164011.48,1,1,0,199420.41,0 +7642,15667460,Moore,797,France,Male,31,9,0,2,1,1,24748.89,0 +7643,15654760,Su,811,France,Male,40,1,101514.89,1,1,1,121765,0 +7644,15632669,Rees,722,Spain,Female,32,4,0,2,1,1,113666.48,0 +7645,15613673,Lung,675,France,Male,28,9,0,1,1,0,134110.93,0 +7646,15698522,Thomas,660,Germany,Male,39,9,134599.33,2,1,0,183095.87,0 +7647,15741633,Fuller,566,Spain,Male,32,10,147511.26,1,1,1,159891.03,0 +7648,15674583,Trevisani,768,France,Male,25,0,78396.08,1,1,1,8316.19,0 +7649,15665374,Dumolo,610,Spain,Female,31,5,0,2,0,0,63736.36,0 +7650,15588854,Wu,715,France,Female,31,3,110581.29,1,1,1,94715.24,0 +7651,15810716,Kerr,750,Germany,Male,42,8,151836.36,2,1,0,68695.38,0 +7652,15776921,Geoghegan,431,Germany,Male,45,5,83624.55,2,0,0,36899.62,0 +7653,15569394,Bailey,704,France,Male,24,2,148197.15,2,1,0,182775.08,0 +7654,15788215,Hsia,535,Spain,Female,30,5,122924.75,1,0,0,62390.59,1 +7655,15641007,Holden,614,France,Female,38,4,72594,1,1,1,76042.48,0 +7656,15594651,Milani,748,France,Male,38,4,115221.36,1,0,1,70956.75,0 +7657,15575146,Jamieson,492,Germany,Male,51,8,117808.74,2,1,1,67311.12,0 +7658,15608916,Ndubueze,573,France,Male,40,7,147754.68,1,1,1,110454.46,0 +7659,15666297,Abramova,706,Spain,Female,53,3,0,3,0,0,88479.02,1 +7660,15598586,Wetherspoon,680,France,Male,31,10,113292.17,1,1,1,122639.73,0 +7661,15665014,Middleton,458,Spain,Male,36,5,0,2,1,0,79723.78,0 +7662,15701738,Arcuri,612,Germany,Male,44,2,115163.38,1,1,1,97677.52,1 +7663,15650591,Calabrese,809,Germany,Male,50,10,118098.62,1,1,1,100720.02,1 +7664,15652667,Hampton,590,France,Male,39,9,0,2,1,1,104730.52,0 +7665,15679622,Clayton,602,France,Male,35,8,0,1,1,1,22499.29,0 +7666,15730150,Otutodilichukwu,540,Spain,Male,37,0,120825.7,1,1,0,28257.89,0 +7667,15813192,Chukwuemeka,494,France,Male,25,6,0,2,0,1,109988.09,0 +7668,15606554,Douglas,797,France,Male,29,1,0,1,0,1,149991.32,0 +7669,15611794,Galloway,526,Germany,Male,61,6,133845.28,2,1,1,45180.8,0 +7670,15672357,Sochima,631,Spain,Male,38,7,0,2,1,0,181605.85,0 +7671,15711759,Wilkins,576,France,Female,29,5,108541.04,1,1,1,126469.09,0 +7672,15615296,Rice,405,France,Male,39,10,0,1,1,0,160810.85,1 +7673,15699294,Pope,555,France,Male,30,1,0,2,0,0,88146.86,0 +7674,15788634,Romani,750,Spain,Female,37,2,113817.06,1,0,0,88333.74,0 +7675,15660871,Ch'ang,665,France,Male,28,8,137300.23,1,1,0,90174.83,0 +7676,15618258,Chizuoke,640,Spain,Male,37,5,158024.38,1,1,0,81298.09,0 +7677,15722535,Ireland,457,France,Female,33,7,127837.54,1,0,1,60013.17,0 +7678,15711977,Finch,695,France,Male,36,4,161533,1,1,0,100940.91,0 +7679,15690169,Meng,645,France,Male,31,7,161171.7,2,1,0,12599.94,1 +7680,15790689,Hibbins,647,Spain,Male,32,9,80958.36,1,1,1,128590.73,0 +7681,15665181,Chung,808,Spain,Male,25,7,0,2,0,1,23180.37,0 +7682,15633608,Black,641,France,Male,33,2,146193.6,2,1,1,55796.83,1 +7683,15805261,Balashov,700,Spain,Male,29,8,0,2,0,1,152097.02,0 +7684,15740356,Palmer,660,Germany,Male,26,4,115021.76,1,0,1,162443.05,0 +7685,15808223,Lea,615,Spain,Male,41,1,126773.43,1,1,1,55551.26,0 +7686,15769980,Singleton,705,Germany,Female,40,3,92889.91,1,1,1,109496.69,0 +7687,15675450,Burt,718,France,Male,48,9,0,2,1,1,72105.63,0 +7688,15776494,Siciliano,754,France,Male,61,5,146622.35,1,1,1,41815.22,1 +7689,15592412,Sun,713,Germany,Male,45,4,131038.14,1,1,0,74005.04,1 +7690,15777452,Sauve,587,France,Female,46,6,88820.29,1,0,0,70224.34,0 +7691,15692258,Thompson,569,Spain,Male,31,1,115406.97,1,0,0,145528.22,0 +7692,15791045,Boni,568,France,Female,38,3,132951.92,1,0,1,124486.28,0 +7693,15807889,Wood,634,Germany,Male,74,5,108891.7,1,1,0,10078.02,0 +7694,15602043,Buccho,770,Germany,Female,46,5,141788.63,2,0,0,164967.21,0 +7695,15807335,Spencer,676,Spain,Female,64,4,116954.32,1,1,1,91149.48,0 +7696,15629985,Eidson,723,Germany,Female,47,10,90450,2,0,0,103379.31,1 +7697,15679453,Hung,614,Germany,Female,39,8,125997.22,1,1,1,128049.34,1 +7698,15637315,Melvin,601,Spain,Female,41,3,0,2,1,0,54342.83,0 +7699,15691513,Dawkins,592,France,Male,60,9,0,4,1,1,13614.01,1 +7700,15622289,Rizzo,605,Spain,Female,36,9,0,2,0,1,35521.63,0 +7701,15715184,Capon,752,Spain,Female,31,4,144637.86,2,1,0,40496.72,0 +7702,15702801,Ts'ao,677,France,Female,29,3,86616.35,1,0,0,91903.9,1 +7703,15719931,Johnstone,850,France,Male,31,8,0,2,1,0,178667.7,0 +7704,15806081,Fleming,608,Germany,Female,48,2,127924.25,2,1,0,32202.61,0 +7705,15796336,Chang,786,Spain,Female,34,9,0,2,1,0,117034.32,0 +7706,15647306,Gibbs,777,France,Female,29,9,131240.61,1,1,1,163746.09,1 +7707,15742369,Rita,667,Spain,Male,31,5,0,2,1,1,20346.69,0 +7708,15655859,Munro,848,Spain,Male,35,5,120046.74,2,1,0,84710.65,0 +7709,15675650,Duncan,486,France,Female,39,8,97819.36,1,0,1,120531.31,0 +7710,15574119,Okwuadigbo,598,Spain,Female,64,1,62979.93,1,1,1,152273.57,0 +7711,15754168,McIntosh,506,France,Female,40,3,0,1,1,1,144345.58,0 +7712,15763029,Ch'iu,612,Germany,Male,46,9,161450.03,1,1,1,96961,1 +7713,15765048,Watt,545,France,Male,30,3,0,2,1,0,170307.43,0 +7714,15786215,Udinese,793,France,Male,56,8,119496.25,2,1,0,29880.99,0 +7715,15707559,Clark,682,France,Female,30,9,0,2,1,1,195104.91,0 +7716,15582129,Hsia,517,France,Male,62,1,43772.66,3,1,0,187756.24,1 +7717,15687540,Obiuto,684,France,Male,32,9,100249.41,2,0,1,67599.69,0 +7718,15787196,T'ien,692,Spain,Male,46,2,0,2,1,1,105983.09,0 +7719,15670898,McKenzie,740,France,Female,60,5,108028.08,2,0,0,25980.42,1 +7720,15775433,Tang,666,Germany,Male,71,1,53013.29,2,1,1,112222.64,0 +7721,15700693,Tu,693,France,Male,68,2,0,2,1,1,59864.96,0 +7722,15677955,Tsui,757,Germany,Male,33,1,122088.67,1,1,0,42581.09,0 +7723,15570086,Lynch,684,Germany,Male,18,9,90544,1,0,1,4777.23,0 +7724,15794875,Hung,691,Spain,Male,35,6,0,2,0,1,178038.17,0 +7725,15673591,Oluchukwu,842,France,Male,44,3,141252.18,4,0,1,128521.16,1 +7726,15631756,Tuan,482,France,Female,35,5,147813.05,2,0,0,109029.72,0 +7727,15757617,Lewis,735,France,Male,55,6,134140.68,1,1,0,2267.88,0 +7728,15612729,Chidiebere,681,France,Female,63,7,0,2,1,1,55054.48,0 +7729,15637857,Woolacott,616,France,Female,31,8,0,1,0,1,76456.17,0 +7730,15681007,Yen,850,France,Female,35,2,128548.49,4,1,0,75478.95,1 +7731,15593622,Service,635,France,Male,43,10,122198.21,2,0,1,179144.54,0 +7732,15629273,Lin,638,Germany,Male,42,8,145177.84,1,1,0,193471.74,1 +7733,15765846,Chuang,820,Spain,Female,31,2,94222.53,1,1,0,103570.8,0 +7734,15596013,Akhtar,694,Germany,Female,58,1,143212.22,1,0,0,102628.56,1 +7735,15722473,Faulkner,713,France,Male,41,3,0,2,1,0,55772.04,0 +7736,15774936,Liang,543,Germany,Male,41,6,143350.41,1,1,1,192070.16,1 +7737,15685640,Dancy,649,France,Female,41,3,130931.83,1,1,1,144808.37,0 +7738,15566563,Duigan,777,France,Female,30,4,137851.31,1,1,0,5008.23,1 +7739,15768746,McLean,561,France,Male,33,6,0,2,0,0,173680.39,0 +7740,15689952,Zuyeva,724,Spain,Male,41,5,0,1,0,1,115753.94,0 +7741,15725906,Hankinson,665,Spain,Female,51,8,0,1,1,1,38928.48,1 +7742,15634501,Wei,441,France,Male,60,1,140614.15,1,0,1,174381.23,0 +7743,15571940,Afamefula,579,Spain,Male,22,3,118680.57,1,1,1,49829.8,0 +7744,15741643,Chiang,777,Germany,Male,35,7,122917.69,1,1,1,76169.68,0 +7745,15806822,Myers,739,France,Female,36,0,0,2,0,0,133465.57,0 +7746,15701166,Chinedum,660,France,Male,40,5,131754.11,2,1,1,38761.61,0 +7747,15718531,Ukaegbunam,554,France,Female,35,8,0,2,1,1,176779.46,0 +7748,15628308,Akubundu,850,France,Female,24,6,0,2,1,1,13159.9,0 +7749,15585287,Sal,842,Germany,Female,35,9,119948.09,1,1,0,48217.97,1 +7750,15781619,Stevenson,785,France,Female,38,1,0,1,1,0,134964.85,1 +7751,15805162,Sutherland,550,France,Male,25,0,0,2,1,1,184221.11,0 +7752,15588535,Ts'ao,750,Spain,Female,39,6,0,2,0,0,19264.33,0 +7753,15775307,Sung,490,Spain,Female,38,3,97266.1,1,1,1,92797.23,0 +7754,15777616,Pisani,605,Germany,Male,28,10,113690.83,1,1,0,33114.24,0 +7755,15692291,Hs?eh,563,Spain,Female,42,6,99056.22,2,1,0,154347.95,1 +7756,15680843,Sherrod,675,France,Male,34,8,0,2,1,1,184842.21,0 +7757,15606232,Holloway,621,Spain,Female,36,7,116338.68,1,1,1,155743.48,0 +7758,15641585,Newton,850,France,Male,40,6,97339.99,1,0,1,88815.25,0 +7759,15684358,Kang,711,France,Male,41,3,0,2,1,1,193747.57,0 +7760,15806389,Walton,549,Germany,Female,55,1,137592.31,2,0,1,116548.02,1 +7761,15641860,Bradley,764,Germany,Male,34,6,108760.27,2,1,0,166324.79,1 +7762,15814237,Watkins,627,Germany,Male,30,3,128770.88,2,1,1,40199.01,0 +7763,15808780,Tien,850,France,Female,34,2,0,2,0,0,51919.04,0 +7764,15767064,Davide,614,Spain,Female,36,1,44054.84,1,1,1,73329.08,0 +7765,15751177,Milne,685,Germany,Female,44,2,119657.53,1,1,0,145387.05,1 +7766,15613427,Barling,683,Germany,Female,49,7,108797.63,2,0,0,140763.18,0 +7767,15647259,Barnett,643,Spain,Male,35,2,0,2,0,0,67979.35,0 +7768,15748660,Ellis,561,Germany,Female,49,1,102025.32,1,1,0,133051.64,1 +7769,15726695,Hsia,601,Spain,Female,20,9,122446.61,2,1,0,86791.9,0 +7770,15757473,Chukwujamuike,766,France,Female,27,7,158786.67,2,0,1,47579.25,0 +7771,15809509,Venables,699,France,Male,29,3,125689.29,1,1,1,151623.71,0 +7772,15715512,Hsia,850,Germany,Male,29,1,154640.41,1,1,1,164039.51,0 +7773,15614168,Alexander,792,Germany,Female,50,4,146710.76,1,1,0,16528.4,1 +7774,15679818,Yuan,636,Germany,Male,67,7,136709.35,1,0,1,66753.1,1 +7775,15609928,Johnston,850,Germany,Male,43,5,129305.09,2,0,1,19244.58,0 +7776,15731246,Hobler,628,Spain,Male,40,10,0,2,1,0,103832.58,0 +7777,15685243,Jamieson,736,France,Female,63,10,0,2,0,1,502.7,0 +7778,15638730,Macleod,711,France,Female,21,0,82844.33,2,0,1,1408.68,0 +7779,15697034,Norris,583,Spain,Female,22,2,0,2,0,1,5985.36,0 +7780,15699225,Pirozzi,757,France,Male,46,0,0,2,1,0,37460.05,0 +7781,15677387,Folliero,749,Germany,Female,33,10,76692.22,1,0,1,30396.43,0 +7782,15759184,Russell,705,France,Male,34,7,117715.84,1,1,0,2498.67,0 +7783,15595991,Hsiung,585,France,Male,54,8,87105.32,1,1,1,55346.14,0 +7784,15681332,Tate,437,France,Female,43,6,0,1,1,0,148330.97,1 +7785,15756299,Davis,741,France,Female,64,2,69311.16,1,1,1,59237.72,0 +7786,15750547,Bair,738,France,Male,26,9,0,2,1,1,48644.94,0 +7787,15566380,Drury,586,Spain,Female,33,10,66948.67,2,1,1,140759.03,0 +7788,15675963,Padovano,627,France,Female,57,9,0,2,1,1,107712.42,0 +7789,15674671,Conway,551,Spain,Male,76,2,128410.71,2,1,1,181718.73,0 +7790,15621466,Waters,606,Germany,Male,38,3,99897.53,1,0,0,37054.65,0 +7791,15607176,Kang,674,France,Male,22,3,0,1,1,1,173940.59,0 +7792,15570299,Martin,584,Germany,Female,31,6,152622.34,1,1,0,99298.8,0 +7793,15613197,Ugochukwutubelum,590,France,Male,40,8,0,2,1,0,62933.03,0 +7794,15798885,Burns,585,France,Male,56,4,138227.19,2,1,1,55287.84,0 +7795,15714883,Genovese,508,France,Female,25,2,111395.53,1,0,1,48197.06,0 +7796,15604497,Beale,458,Germany,Male,44,7,84386.57,1,1,0,178642.73,0 +7797,15773949,Cherkasova,692,France,Female,36,3,0,2,1,1,8282.22,0 +7798,15774164,Coles,502,Germany,Male,33,5,174673.65,2,1,0,33300.56,0 +7799,15774127,Potter,518,France,Male,46,3,0,2,1,0,76515.79,0 +7800,15619016,McMinn,660,Germany,Male,46,5,109019.65,2,1,1,33680.56,0 +7801,15795759,Bergamaschi,698,Germany,Female,52,1,107906.75,1,1,0,168886.39,1 +7802,15798844,Chijindum,678,France,Male,54,7,128914.97,1,0,0,191746.23,1 +7803,15717962,Ch'iu,773,Spain,Male,63,9,111179.83,1,1,1,93091.02,0 +7804,15691504,Yusupova,619,Germany,Female,52,8,124099.13,1,0,0,23904.52,0 +7805,15693893,Davis,684,Germany,Male,59,9,122471.09,1,0,1,15807.07,0 +7806,15672499,Iadanza,635,France,Male,34,3,134692.4,2,1,1,83773.02,0 +7807,15750410,Jordan,680,France,Female,25,4,123816.5,1,1,1,90162.35,0 +7808,15568904,Kruglova,608,Germany,Male,34,3,106288.54,1,1,1,36639.25,0 +7809,15649033,Echezonachukwu,603,Germany,Female,55,7,127723.25,2,1,0,139469.11,1 +7810,15780989,Hajek,579,Spain,Male,43,2,145843.82,1,1,1,198402.37,1 +7811,15771059,Welch,756,Germany,Female,34,2,148200.72,1,0,0,194584.48,0 +7812,15687852,Vinogradoff,611,France,Male,30,2,104145.65,1,0,0,159629.64,0 +7813,15695280,Hung,532,Germany,Male,24,8,142755.25,1,0,0,34231.48,0 +7814,15592751,Okwudiliolisa,684,Germany,Female,63,3,81245.79,1,1,0,69643.31,1 +7815,15598338,Mays,647,Germany,Female,33,3,168560.46,2,0,0,90270.16,0 +7816,15735784,Gardner,583,France,Male,38,8,0,1,1,0,47848.56,0 +7817,15629128,Mamelu,774,Germany,Male,42,2,132193.94,2,1,1,162865.52,0 +7818,15642870,Ross,677,France,Male,58,9,0,1,0,1,168650.4,0 +7819,15637977,Barese,542,Germany,Male,25,8,139330.1,1,0,0,54372.37,0 +7820,15600792,Swayne,613,Spain,Male,29,0,0,2,0,1,133897.32,0 +7821,15576131,Phillips,666,France,Male,40,5,0,2,1,0,147878.05,0 +7822,15686588,Manfrin,777,France,Female,28,2,134571.5,1,0,1,118313.38,0 +7823,15761018,Tan,581,Germany,Male,50,2,143829.2,2,1,0,181224.24,1 +7824,15616029,Adams,705,France,Male,32,7,0,2,1,0,7921.57,0 +7825,15761149,Teng,673,France,Female,44,8,133444.97,1,0,1,5708.19,0 +7826,15802758,Chinwendu,594,Germany,Female,23,4,104753.84,2,1,0,56756.52,1 +7827,15647838,Davison,648,Germany,Female,51,2,116574.84,1,1,0,4121.04,1 +7828,15735968,Hsing,605,France,Male,41,10,0,2,0,1,97213.09,0 +7829,15581286,Castro,734,France,Female,40,9,176914.8,1,1,1,12799.23,0 +7830,15625445,Parkin,572,France,Female,36,8,68348.18,2,0,1,50400.32,0 +7831,15600173,Manna,595,France,Female,33,9,0,2,1,1,41447.86,0 +7832,15635143,Fennescey,749,France,Male,42,2,56726.83,2,0,1,185543.35,0 +7833,15664849,Colon,573,Spain,Male,46,3,65269.23,1,0,1,189988.65,1 +7834,15762455,Yeh,624,Spain,Male,33,6,66220.17,1,0,1,170819.01,0 +7835,15797165,Bergamaschi,703,France,Male,56,9,0,1,0,0,85547.33,1 +7836,15788189,Matveyeva,665,France,Female,41,8,96147.55,1,1,0,137037.97,0 +7837,15780492,Ignatyeva,648,France,Male,42,4,0,2,1,0,19283.14,0 +7838,15678497,Lederer,850,Spain,Male,48,2,0,1,1,0,169425.3,1 +7839,15588560,Nwabugwu,569,Germany,Female,32,8,145330.43,1,1,1,132038.65,0 +7840,15606003,Abramowitz,566,France,Female,21,3,0,2,1,1,3626.47,0 +7841,15611756,Chapman,537,Germany,Female,47,4,124192.28,2,1,1,50881.51,0 +7842,15789563,Fiorentino,706,Germany,Female,46,7,111288.18,1,1,1,149170.25,1 +7843,15702416,Cecil,734,France,Male,43,7,107805.67,1,0,0,182505.68,0 +7844,15766288,Ikechukwu,586,Germany,Female,36,5,103700.69,1,1,0,194072.56,1 +7845,15667633,Allen,612,France,Female,38,1,0,2,1,1,9209.21,0 +7846,15622774,Kao,648,France,Male,34,0,0,1,1,1,167931.81,0 +7847,15755416,Hart,557,France,Female,27,3,87739.08,1,1,1,123096.56,0 +7848,15769915,Charlton,643,Spain,Female,20,0,133313.34,1,1,1,3965.69,0 +7849,15643908,Turnbull,433,France,Female,49,10,0,1,1,1,87711.61,0 +7850,15627395,Manners,643,Germany,Male,41,7,154902.66,1,1,1,49667.28,0 +7851,15679663,Chiazagomekpere,488,France,Female,36,0,0,2,1,0,136675.22,0 +7852,15651581,Lavrentyev,758,Germany,Male,68,6,112595.85,1,1,0,35865.44,1 +7853,15596379,Wallace,743,Germany,Male,39,3,119695.75,1,0,1,26136.13,0 +7854,15746674,Miller,730,France,Female,47,7,0,1,1,0,33373.26,1 +7855,15801256,Bazhenov,746,Spain,Male,49,7,0,2,0,1,10096.25,0 +7856,15663808,Ifesinachi,666,Germany,Female,59,8,152614.51,2,1,1,188782.3,0 +7857,15598521,Ma,580,Germany,Female,33,7,131647.01,2,0,0,79775.19,0 +7858,15621457,Chu,850,France,Male,27,6,96654.72,2,0,0,152740.16,0 +7859,15764726,Kerr,563,France,Male,22,3,137583.04,1,0,1,5791.85,0 +7860,15646374,Wynne,766,Germany,Female,28,3,62717.84,2,1,1,13182.43,0 +7861,15716501,Moon,659,France,Male,32,9,95377.13,1,0,1,187551.24,0 +7862,15589948,Disher,607,Spain,Male,28,1,135936.1,2,1,1,110560.14,0 +7863,15811343,Cattaneo,644,Germany,Male,35,5,161591.11,3,1,1,63795.62,0 +7864,15659677,Beluchi,746,France,Male,47,8,142382.03,1,1,1,62086.62,0 +7865,15594436,Mazzi,588,Spain,Male,33,2,0,2,1,1,12483.56,0 +7866,15748995,Ifeajuna,691,Spain,Male,30,9,0,2,0,1,10963.04,0 +7867,15677062,Howe,666,France,Female,38,6,127043.09,1,1,1,8247,0 +7868,15697201,Yocum,640,Spain,Female,46,3,0,1,1,1,156260.08,0 +7869,15666453,Moore,611,Germany,Female,29,4,78885.88,2,1,1,26927.69,0 +7870,15693771,Y?an,651,Spain,Female,45,8,95922.9,1,1,0,84782.42,1 +7871,15569867,Chinweuba,529,France,Female,29,8,0,2,1,0,19842.11,0 +7872,15711602,Lowrie,676,France,Female,36,3,91711.59,1,1,1,95393.43,0 +7873,15717736,Shen,639,Germany,Female,46,10,110031.09,2,1,1,133995.59,0 +7874,15750441,Lavarack,782,France,Male,36,5,81210.72,2,0,1,108003.38,0 +7875,15732791,Davide,641,Germany,Male,32,5,122947.92,1,1,1,99154.86,0 +7876,15775104,Gomes,697,France,Female,38,1,182065.85,1,1,0,49503.5,0 +7877,15757607,Matveyeva,623,France,Male,45,0,0,1,1,0,196533.72,1 +7878,15793070,Fiorentino,494,Spain,Female,41,2,69974.66,2,1,0,188426.13,1 +7879,15760456,Eberechukwu,731,France,Female,38,10,123711.73,2,1,0,171340.68,1 +7880,15665385,Gibney,657,France,Male,44,6,76495.04,1,1,0,79071.89,0 +7881,15612418,Virgo,744,France,Female,38,9,0,2,0,0,20940.76,0 +7882,15727138,Kulikova,774,Spain,Male,46,9,0,2,1,1,34774.26,0 +7883,15732061,Liu,850,Germany,Female,45,1,121874.89,1,0,0,6865.41,1 +7884,15776051,Kao,551,France,Female,45,6,0,2,1,1,51143.43,0 +7885,15616530,Foran,638,France,Male,36,6,188455.19,1,0,0,47031.4,1 +7886,15632344,Jones,792,France,Female,42,0,99045.93,2,1,0,47160.01,0 +7887,15744979,Fowler,666,France,Female,36,8,0,1,0,1,158666.99,0 +7888,15745433,Conti,716,Germany,Female,30,2,205770.78,2,0,0,65464.66,0 +7889,15683657,Stephenson,594,France,Female,31,0,79340.95,1,1,0,78255.86,0 +7890,15718572,Willis,600,Germany,Male,57,9,138456.03,2,1,1,103548.25,0 +7891,15665783,Ts'ui,565,France,Male,49,7,0,2,1,1,89609.26,0 +7892,15652782,Chibuzo,678,Germany,Male,48,2,101099.9,2,0,1,193476.04,0 +7893,15707025,Fang,648,Spain,Female,31,5,0,2,1,1,5199.02,0 +7894,15647807,Wyckoff,642,France,Male,40,8,109219.83,1,1,0,52827.51,0 +7895,15718281,Muir,706,Germany,Male,67,1,123276.69,2,1,1,86507.88,1 +7896,15660571,Halpern,668,Spain,Male,43,10,113034.31,1,1,1,100423.88,0 +7897,15727857,Flynn,635,Spain,Male,41,1,0,2,1,0,175611.5,0 +7898,15639252,Shao,603,Spain,Male,30,6,129548.5,2,1,1,19282.85,0 +7899,15628144,Soares,635,France,Female,72,4,74812.84,1,0,1,27448.33,0 +7900,15683560,Gallo,642,France,Female,40,7,0,2,1,0,183963.34,0 +7901,15653275,Lei,785,Spain,Female,54,1,0,2,1,0,45113.92,1 +7902,15622182,Daniels,628,Germany,Female,28,3,153538.13,2,1,0,110776.01,0 +7903,15613962,Kenechi,499,France,Female,38,9,0,2,0,1,183042.2,0 +7904,15618437,Singleton,567,Spain,Male,34,10,0,2,0,1,161571.79,0 +7905,15783338,Williams,449,Spain,Male,32,0,155619.36,1,1,1,166692.03,0 +7906,15764491,Greece,701,Spain,Male,35,10,159693.9,2,1,1,71173.64,0 +7907,15712960,Olisanugo,613,Spain,Male,37,3,171653.17,1,0,1,5353.12,0 +7908,15688157,Padovano,683,Germany,Female,39,2,47685.47,2,1,1,86019.48,0 +7909,15579287,Rossi,581,France,Male,35,4,0,2,0,1,86383.82,0 +7910,15570931,Grant,620,France,Male,61,5,0,1,0,0,31641.52,1 +7911,15615177,Ebelegbulam,561,Spain,Male,28,6,123692,1,1,1,70548.96,0 +7912,15809906,Mitchell,558,Germany,Male,26,1,148853.29,2,1,1,24411.02,0 +7913,15652169,Buckley,642,France,Male,35,2,133161.95,1,0,1,122254.86,0 +7914,15649450,Repina,805,Germany,Male,24,6,143221.35,2,1,0,186035.72,0 +7915,15777179,Ellis,687,France,Male,35,9,0,2,0,1,73133.82,0 +7916,15803538,Douglas,695,Spain,Male,56,1,0,3,1,0,187734.49,1 +7917,15610936,Becher,562,France,Male,33,6,0,2,1,0,111590.35,0 +7918,15590094,Nwachukwu,613,Germany,Male,38,9,126265.88,2,0,0,15859.95,0 +7919,15572706,Smith,589,France,Male,37,5,0,1,1,0,61324.87,0 +7920,15634564,Aksyonov,593,Spain,Male,31,8,112713.34,1,1,1,176868.89,0 +7921,15684296,Artyomova,714,France,Male,34,5,141173.03,1,0,1,98896.06,0 +7922,15702293,Medvedeva,588,Spain,Female,35,7,0,2,1,1,108739.15,0 +7923,15642099,Tsui,679,Spain,Male,39,6,0,2,1,0,12266.06,0 +7924,15773273,Runyon,730,Spain,Male,38,5,118866.36,1,1,1,163317.5,0 +7925,15613337,Gallo,833,France,Male,47,2,0,2,1,1,182247.77,0 +7926,15800482,Bradshaw,586,Spain,Female,33,7,0,2,1,1,168261.4,0 +7927,15732644,Evans,567,Spain,Female,54,5,92316.31,2,1,0,158590.66,1 +7928,15713426,Hancock,637,Germany,Male,30,1,122185.53,1,1,0,102566.46,1 +7929,15640789,Butler,711,France,Male,38,4,123345.85,1,1,0,141827.83,0 +7930,15598892,Bradshaw,828,France,Male,30,4,73070.18,2,0,0,161671.15,0 +7931,15606436,Bergamaschi,500,Spain,Male,38,7,0,2,0,0,192013.23,0 +7932,15751227,Ebelegbulam,807,France,Male,47,1,95120.59,1,0,0,127875.1,0 +7933,15812365,Greco,850,France,Male,40,8,102800.65,1,1,0,60811.56,0 +7934,15616088,Lucas,782,France,Female,70,7,97072.42,1,0,1,131177.22,0 +7935,15803886,Barber,629,Spain,Male,31,6,132876.55,1,1,1,130862.11,0 +7936,15587311,Dobbs,582,Spain,Male,33,6,0,2,0,1,72970.93,0 +7937,15617401,Thomson,468,France,Male,22,2,0,2,1,0,28123.99,0 +7938,15775886,Su,670,France,Male,36,3,0,1,1,0,140754.19,1 +7939,15807305,Watkins,805,France,Male,39,2,0,1,0,0,166650.32,0 +7940,15761717,Ch'ien,720,France,Male,26,10,51962.91,2,1,0,45507.24,0 +7941,15628008,Monds,781,Spain,Female,29,6,98759.89,1,0,0,112202.64,0 +7942,15583755,McClemans,592,Germany,Male,33,2,156570.86,1,1,1,37140.2,0 +7943,15661409,Shen,542,France,Female,42,1,0,1,1,1,178256.58,1 +7944,15774250,Gallo,532,France,Male,42,1,159024.71,1,1,0,100982.93,1 +7945,15681476,Foveaux,520,France,Female,39,1,73493.17,1,0,1,109626.13,1 +7946,15654870,Longo,759,France,Female,45,8,0,2,1,1,99251.24,0 +7947,15790448,Calabresi,473,France,Female,35,6,69617.36,1,1,0,143345.69,0 +7948,15785326,Randall,639,Spain,Female,35,5,136526.26,2,1,0,59653.03,0 +7949,15592854,Garcia,705,France,Male,25,3,113736.27,1,0,1,196864.61,0 +7950,15617486,Sullivan,530,France,Male,52,1,106723.28,1,0,0,109960.4,1 +7951,15806796,Higgins,516,Germany,Female,33,10,138847.9,1,1,1,127256.7,0 +7952,15644699,Crawford,850,France,Female,40,0,0,2,1,0,1099.95,0 +7953,15622305,Martin,746,Germany,Female,33,2,107868.14,2,1,1,146192.4,0 +7954,15608209,Currey,622,Germany,Male,33,3,96926.12,2,1,0,48553.77,0 +7955,15626898,Teng,743,France,Male,30,7,77599.23,1,0,0,144407.1,0 +7956,15644297,Austin,732,Germany,Male,38,5,178787.54,1,1,1,195760.53,0 +7957,15731569,Hudson,850,France,Male,81,5,0,2,1,1,44827.47,0 +7958,15582149,Ts'ui,850,Germany,Female,34,3,129668.43,2,1,1,88743.99,0 +7959,15802483,Hancock,686,France,Male,34,6,146178.13,2,1,1,88837.11,0 +7960,15686999,Nicholas,556,France,Female,40,8,0,2,1,0,62112.7,0 +7961,15772479,Napolitano,673,France,Male,37,4,0,2,0,0,163563.07,0 +7962,15778884,Jamieson,809,France,Female,38,2,154763.21,2,1,1,174800.31,0 +7963,15623630,Foster,634,Germany,Female,56,3,116251.24,1,0,1,42429.88,1 +7964,15774316,Moretti,630,France,Male,37,6,0,2,1,1,82647.65,0 +7965,15695097,Chiedozie,564,Germany,Female,30,0,100954.88,2,0,0,134175.15,0 +7966,15645404,Okwukwe,625,France,Female,51,4,124620.01,2,1,0,92243.94,1 +7967,15750574,Lumholtz,677,Spain,Female,34,4,0,2,1,1,6175.53,0 +7968,15636812,Rose,583,France,Male,40,9,112701.04,1,0,0,29213.63,0 +7969,15712068,Wan,592,Spain,Male,45,8,84692.5,1,0,1,67214.02,0 +7970,15652030,De Bernales,637,Germany,Male,49,2,108204.52,1,1,0,169037.84,1 +7971,15577398,Ch'eng,850,France,Male,30,6,86449.39,1,1,1,188809.23,0 +7972,15756848,Edmondson,633,Spain,Male,42,10,0,1,0,1,79408.17,0 +7973,15806929,Ch'ien,751,Germany,Male,36,5,73194.99,1,1,1,89222.66,0 +7974,15656005,Millar,592,Germany,Male,31,7,124593.23,1,1,0,86079.67,0 +7975,15722632,Dickson,716,Germany,Male,50,2,119655.77,1,1,1,12944.17,1 +7976,15794356,Toscani,641,Germany,Male,42,3,121765.37,2,1,1,166516.84,0 +7977,15659656,Pan,849,France,Male,35,4,110837.73,1,0,0,126419.8,0 +7978,15588341,Chigozie,647,Spain,Male,47,10,99835.17,1,0,1,89103.05,0 +7979,15709142,Sagese,608,Germany,Female,30,2,91057.37,2,1,0,132973.17,0 +7980,15627042,Reilly,555,France,Female,26,7,0,2,1,0,93122.41,0 +7981,15627517,Taylor,497,Spain,Male,27,7,149400.27,1,0,0,167522.19,0 +7982,15803032,Yen,599,Germany,Male,38,9,89111.63,1,0,0,157239.6,0 +7983,15665129,Kapustin,545,Germany,Male,33,1,132527.9,2,0,1,107429.71,0 +7984,15628272,Singh,774,France,Female,36,9,114997.42,1,1,0,75304.09,0 +7985,15678206,Yeh,464,France,Male,46,6,161798.53,1,1,0,182944.47,0 +7986,15678427,Genovese,696,Germany,Female,27,2,96129.32,2,1,1,5983.7,0 +7987,15678067,Boyle,667,Spain,Male,45,3,0,2,0,0,163655.01,0 +7988,15793331,Blair,812,France,Male,32,5,133050.97,2,1,0,89385.92,0 +7989,15699532,Okagbue,516,France,Male,51,8,120124.35,2,0,1,168773.54,0 +7990,15605827,Khan,645,France,Male,39,8,0,2,0,0,96864.36,0 +7991,15643635,Robertson,664,Spain,Male,32,5,133705.74,1,0,0,134455.84,0 +7992,15787710,Tikhonov,427,Spain,Female,39,9,0,2,1,0,28368.37,0 +7993,15614137,MacDonald,685,France,Female,40,7,0,2,1,0,103898.59,0 +7994,15754494,Ah Mouy,585,France,Female,33,4,152805.05,1,1,0,63239.65,0 +7995,15713440,Barese,519,Germany,Female,21,1,151701.45,3,1,1,170138.68,1 +7996,15803479,Winter-Irving,708,France,Female,67,1,0,2,0,1,3837.08,0 +7997,15709639,Wilson,717,France,Female,22,5,112465.06,1,1,1,92977.75,0 +7998,15601719,Fiorentino,465,Germany,Male,24,6,156007.09,1,1,0,191368.37,0 +7999,15772482,Iloerika,829,Germany,Male,28,3,132405.52,3,1,0,104889.2,1 +8000,15591489,Davison,826,France,Male,26,5,142662.68,1,0,0,60285.3,0 +8001,15629002,Hamilton,747,Germany,Male,36,8,102603.3,2,1,1,180693.61,0 +8002,15798053,Nnachetam,707,Spain,Male,32,9,0,2,1,0,126475.79,0 +8003,15753895,Blue,590,Spain,Male,37,1,0,2,0,0,133535.99,0 +8004,15595426,Madukwe,603,Spain,Male,57,6,105000.85,2,1,1,87412.24,1 +8005,15645815,Mills,615,France,Male,45,5,0,2,1,1,164886.64,0 +8006,15632848,Ferrari,634,France,Female,36,1,69518.95,1,1,0,116238.39,0 +8007,15703068,Nixon,716,Germany,Male,41,8,126145.54,2,1,1,138051.19,0 +8008,15791513,Manfrin,647,France,Male,41,4,138937.35,1,1,1,101617.64,1 +8009,15587210,McCartney,591,Germany,Female,44,10,113581.98,1,1,0,1985.41,0 +8010,15793803,Robinson,574,France,Male,34,1,112572.39,1,0,0,165626.6,0 +8011,15787756,Nkemdirim,467,Germany,Male,51,10,114514.71,2,1,0,177784.68,1 +8012,15723437,Sal,701,France,Female,35,2,0,2,1,1,65765.22,0 +8013,15702715,Kao,747,France,Female,34,10,0,2,1,1,50759.8,0 +8014,15809872,Ikechukwu,650,France,Male,32,2,84906.45,1,1,0,163216.48,0 +8015,15644295,Hargreaves,731,Spain,Female,39,2,126816.18,1,1,1,74850.93,0 +8016,15778694,Sievier,638,Germany,Female,26,1,105249.76,2,1,1,23491.09,0 +8017,15759555,Murphy,569,Spain,Male,41,2,0,2,1,0,134272.57,0 +8018,15631406,Munro,459,Germany,Male,50,5,109387.9,1,1,0,155721.15,0 +8019,15616676,Donnelly,632,Germany,Male,23,3,122478.51,1,1,0,147230.77,1 +8020,15771154,North,683,France,Female,73,8,137732.23,2,1,1,133210.44,0 +8021,15669491,Cruz,850,France,Female,46,2,157866.77,1,1,1,18986.12,0 +8022,15697691,Sinclair,512,France,Female,41,6,0,1,1,1,100507.81,0 +8023,15665180,Vasiliev,616,France,Female,31,3,136789.14,1,1,0,59346.4,1 +8024,15752588,Vasilyeva,664,France,Male,36,1,0,2,1,1,95372.64,0 +8025,15743051,Hamilton,694,France,Male,30,10,144684.03,1,1,1,31805.49,0 +8026,15571873,Sung,655,France,Male,24,9,107065.31,1,1,1,51959.82,0 +8027,15679743,Genovesi,607,France,Female,33,8,91301.72,1,0,1,130824.57,0 +8028,15769412,Atkinson,684,Spain,Male,39,4,207034.96,2,0,0,157694.76,1 +8029,15775124,Watterston,763,Spain,Male,37,8,0,2,1,1,933.38,0 +8030,15732113,Butters,671,Spain,Male,50,8,0,1,0,1,2560.11,0 +8031,15578141,Chien,592,Spain,Male,38,3,0,1,1,1,12905.89,1 +8032,15595874,Gorbunova,666,Spain,Female,36,6,0,2,1,0,176692.87,0 +8033,15755642,Bulgakov,667,France,Male,34,5,0,2,1,1,102908.63,0 +8034,15576526,Steele,850,Spain,Male,36,6,0,2,0,1,41291.05,0 +8035,15792489,Polyakova,622,Spain,Male,42,9,0,2,1,0,119127.06,0 +8036,15733705,Bull,577,France,Female,30,8,92472.1,2,0,1,126434.61,0 +8037,15807221,Weaver,555,Spain,Male,21,1,0,2,0,0,103901.35,0 +8038,15573045,Earl,547,France,Male,62,10,127738.75,2,1,1,85153,0 +8039,15756824,Giordano,613,Germany,Female,50,5,101242.98,2,1,0,12493.61,0 +8040,15773520,Begg,672,France,Female,43,4,92599.55,2,1,1,167336.78,0 +8041,15627439,Pickering,624,Spain,Female,36,10,0,2,0,1,186180.42,0 +8042,15701439,Fanucci,698,Spain,Female,50,1,0,4,1,0,88566.9,1 +8043,15785352,Chang,606,France,Male,37,6,82373.94,1,0,0,172526.9,1 +8044,15616525,Sopuluchi,720,Spain,Male,31,4,141356.47,1,0,0,137985.69,0 +8045,15717489,Martin,835,France,Male,23,9,0,1,1,0,19793.73,1 +8046,15795737,McNaughtan,771,Spain,Female,47,3,72664,2,1,1,107874.39,0 +8047,15693877,Stewart,811,France,Female,47,3,123365.34,2,0,0,171995.34,0 +8048,15576111,Reagan,734,Germany,Male,33,5,121898.58,1,1,0,61829.89,0 +8049,15595713,Heller,548,Spain,Male,33,6,0,1,1,1,31728.35,0 +8050,15808868,Nwokeocha,652,France,Female,31,3,103696.97,3,0,0,155221.05,1 +8051,15708193,Liu,707,France,Male,33,2,0,2,0,0,130866.95,0 +8052,15697801,Sokolova,605,Germany,Female,56,1,74129.18,2,1,1,62199.78,1 +8053,15770121,Bancroft,623,France,Female,34,9,0,1,1,0,24255.21,0 +8054,15800524,Nnanna,686,Germany,Male,29,3,185379.02,1,1,0,64679.07,0 +8055,15686236,Trevisani,525,Germany,Female,47,1,118087.68,1,1,0,88120.78,1 +8056,15659807,Nwachinemelu,657,Spain,Male,41,8,109402.13,1,1,1,66463.62,0 +8057,15736078,Ting,730,Germany,Female,33,7,130367.87,1,1,0,15142.1,1 +8058,15620836,Lo Duca,816,Germany,Female,34,2,108410.87,2,1,0,102908.91,0 +8059,15698184,Marshall,484,France,Female,50,2,90408.16,2,0,0,48170.57,0 +8060,15717643,Band,728,France,Female,34,6,90425.15,2,1,1,11597.69,0 +8061,15776596,Ferri,730,Spain,Female,39,6,140094.59,1,1,0,172450.04,1 +8062,15814757,Carter,477,Spain,Male,31,9,0,2,0,1,184061.17,0 +8063,15812607,Wilson,663,Germany,Female,46,6,95439.4,1,1,1,21038.58,1 +8064,15663888,Connor,549,Germany,Male,34,6,204017.4,2,1,0,109538.35,0 +8065,15748882,Reid,714,Spain,Male,29,9,0,2,1,0,129192.55,0 +8066,15690829,Sandefur,430,Germany,Male,49,3,137115.16,1,1,0,146516.86,1 +8067,15695819,Bidwill,504,Germany,Male,43,5,134740.19,2,1,0,181430.91,0 +8068,15696834,Cone,530,France,Female,29,5,0,2,0,0,121451.21,0 +8069,15797710,Saunders,619,Germany,Male,29,4,98955.87,1,0,1,131712.51,0 +8070,15700654,Liardet,617,Germany,Male,44,9,49157.09,2,1,0,53294.17,0 +8071,15583764,Wilkes,791,Germany,Male,31,1,130240.33,1,0,0,96546.55,0 +8072,15688849,Martin,609,France,Male,48,1,108019.27,3,1,1,184524.65,1 +8073,15661473,Boni,780,Germany,Male,51,4,126725.25,1,1,0,195259.31,1 +8074,15601030,Patel,777,Germany,Female,34,5,96693.66,1,1,1,172618.52,0 +8075,15789557,Howell-Price,817,Germany,Female,27,7,129810.6,1,1,1,59259.44,0 +8076,15745250,Simpson,850,France,Male,58,8,156652.13,1,0,0,25899.21,1 +8077,15590349,Rowland,732,France,Female,36,9,0,1,0,0,3749,1 +8078,15741693,Barnard,693,France,Male,40,4,130661.96,1,1,1,101918.96,0 +8079,15618446,Nnonso,576,France,Female,50,8,0,2,1,1,57802.62,0 +8080,15766552,Rossi,643,France,Male,37,6,0,2,0,0,142454.77,0 +8081,15668775,Pendred,757,France,Male,47,3,130747.1,1,1,0,143829.54,0 +8082,15757895,Martin,569,Germany,Male,30,6,106629.49,1,0,1,44114.88,0 +8083,15774551,K?,772,Spain,Male,36,3,112029.83,1,1,1,186948.35,0 +8084,15684011,Miller,576,Germany,Male,29,7,130575.26,1,0,1,173629.78,0 +8085,15736146,Afamefula,608,Germany,Male,28,4,96679.71,1,1,1,49133.45,0 +8086,15656286,Sims,794,France,Male,33,0,0,2,0,0,178122.71,0 +8087,15774847,Knight,593,France,Male,50,6,171740.69,1,0,0,20893.61,0 +8088,15619340,Obijiaku,597,Spain,Male,38,1,0,2,1,0,41303.29,0 +8089,15815656,Hopkins,541,Germany,Female,39,9,100116.67,1,1,1,199808.1,1 +8090,15623357,Onio,692,Germany,Male,24,2,120596.93,1,0,1,180490.53,0 +8091,15601324,Black,697,France,Female,48,1,0,2,1,1,87400.53,0 +8092,15715510,Eluemuno,768,France,Male,29,2,95984.69,2,1,1,73686.75,0 +8093,15663770,Doyle,802,France,Male,38,1,142557.11,1,1,1,172497.73,0 +8094,15779267,Onyemere,584,France,Male,47,5,0,2,1,0,89286.29,0 +8095,15597957,Rahman,614,Spain,Male,66,2,0,2,0,1,180082.7,0 +8096,15584620,Su,850,Germany,Female,36,6,143644.16,1,1,0,22102.25,1 +8097,15750772,Walker,671,France,Female,38,6,132129.72,1,0,1,76068.95,0 +8098,15706557,Ferguson,626,France,Female,52,0,0,2,1,0,32159.46,1 +8099,15594391,Samaniego,770,France,Female,68,2,183555.24,1,0,0,159557.28,1 +8100,15661656,Onwumelu,633,France,Male,38,2,91902.56,2,1,1,107673.35,0 +8101,15631217,Young,663,France,Male,40,6,156218.19,1,0,1,33607.72,0 +8102,15588955,Mazzi,581,Germany,Female,43,5,93259.57,3,1,0,141035.65,1 +8103,15758252,Toscano,561,Germany,Female,45,2,168085.38,2,0,1,115719.08,0 +8104,15740223,Walton,479,Germany,Male,51,1,107714.74,3,1,0,86128.21,1 +8105,15805413,Chiang,769,France,Female,31,6,117852.26,2,1,0,147668.64,0 +8106,15635116,Burgos,659,Spain,Male,60,2,0,1,1,0,177480.45,1 +8107,15764892,Spinelli,590,Spain,Female,51,10,84474.62,2,1,1,190937.09,0 +8108,15795936,Lung,560,France,Male,50,3,0,2,1,0,84531.79,0 +8109,15655232,Noble,437,Germany,Male,35,6,126803.34,2,1,1,161133.4,0 +8110,15640133,Pai,661,France,Female,34,0,0,2,1,0,185555.63,0 +8111,15751524,Chigozie,677,Germany,Female,36,10,68806.84,1,1,0,33075.24,0 +8112,15670552,Peavy,560,France,Female,31,3,115141.18,1,1,0,39806.75,0 +8113,15623966,Yermakov,578,France,Female,35,2,0,2,0,1,26389.92,0 +8114,15752193,Burton,421,Spain,Male,34,6,90723.36,1,1,1,12162.76,0 +8115,15607269,Costa,492,Germany,Female,49,2,151249.45,2,1,1,167237.94,0 +8116,15700752,Pugliesi,545,France,Female,32,6,0,2,1,1,52067.37,0 +8117,15777901,Lindell,640,Germany,Female,43,9,94752.49,1,1,0,184006.36,1 +8118,15639117,Sorenson,624,Spain,Female,34,6,0,1,1,0,582.59,1 +8119,15720203,Arcuri,577,Spain,Male,28,7,0,1,1,0,143274.41,0 +8120,15586236,Banks,704,France,Male,31,5,132084.66,3,1,1,54474.48,1 +8121,15676645,Parry,523,France,Male,45,5,0,2,1,1,121428.2,0 +8122,15715988,Cockett,793,France,Male,35,2,0,2,1,1,79704.12,0 +8123,15603749,Galkina,564,France,Female,53,2,45472.28,1,1,1,41055.71,1 +8124,15608956,Su,711,France,Male,33,1,0,1,0,0,41590.4,0 +8125,15733872,Marino,791,Germany,Female,33,10,130229.71,2,0,0,54019.93,1 +8126,15666982,Spears,629,Germany,Female,38,9,123948.85,1,1,0,76053.07,0 +8127,15602647,Cunningham,729,Germany,Male,39,6,127415.85,1,1,1,184977.2,1 +8128,15623063,Taylor,651,Germany,Male,35,8,110067.71,1,1,0,127678.95,1 +8129,15682928,Chiazagomekpere,695,Spain,Male,39,4,65521.2,1,1,1,1243.97,0 +8130,15729246,Hardacre,847,Spain,Male,31,5,0,2,1,1,76326.67,0 +8131,15588928,Maslow,704,France,Male,47,5,0,2,1,1,145338.61,0 +8132,15803352,Scott,613,Germany,Male,33,3,155736.42,2,1,1,57751.21,0 +8133,15607485,Wakelin,692,Spain,Female,29,4,0,2,0,0,138880.24,0 +8134,15656249,Esposito,720,France,Female,34,3,118307.57,2,1,1,136120.29,0 +8135,15761783,Shah,577,France,Male,41,6,0,1,1,1,167621.18,0 +8136,15716605,Chukwufumnanya,710,Germany,Female,24,7,103099.17,2,1,0,173276.62,0 +8137,15757425,Fleming,716,France,Female,38,1,0,2,1,1,99661.46,0 +8138,15603096,Lori,410,France,Male,33,6,125789.69,1,0,0,66333.56,1 +8139,15588580,Kennedy,584,Germany,Female,36,4,109646.83,1,1,1,70240.79,0 +8140,15770539,Walters,792,France,Male,30,1,127187.86,1,1,1,113553.42,0 +8141,15572022,Han,605,France,Female,36,6,0,1,0,1,690.84,0 +8142,15571843,Lawrence,486,Spain,Male,24,1,0,1,1,0,98802.76,0 +8143,15752502,Cooke,615,France,Male,41,4,130385.82,1,0,1,130661.95,0 +8144,15609058,Wan,676,France,Male,23,1,107787.47,1,0,1,116378.82,0 +8145,15775108,Lo Duca,571,France,Male,34,1,99325.04,2,0,1,186052.15,0 +8146,15708904,Yermakova,850,France,Female,37,9,0,1,0,0,100101.06,0 +8147,15600086,Combs,717,France,Male,48,7,123764.95,1,1,1,169952.82,0 +8148,15814675,Chien,642,Germany,Female,39,8,128264.03,1,1,0,61792.76,1 +8149,15572777,Meng,780,Spain,Male,47,7,86006.21,1,1,1,37973.13,0 +8150,15585106,Calabresi,492,Germany,Female,38,8,57068.43,2,1,0,188974.81,0 +8151,15738936,Stevenson,760,Germany,Male,29,5,103607.24,2,0,1,86334.64,0 +8152,15750970,Davidson,500,Spain,Male,40,1,99004.24,1,1,1,152845.99,0 +8153,15725772,Ch'in,654,Spain,Female,36,2,0,2,1,1,146652.11,0 +8154,15692106,Rose,606,Spain,Female,25,3,147386.72,3,1,0,45482.04,1 +8155,15791533,Ch'ien,367,Spain,Male,42,6,93608.28,1,1,0,168816.73,1 +8156,15715715,Artyomova,799,Spain,Male,38,2,0,2,1,1,59297.34,0 +8157,15785576,Mayrhofer,434,Germany,Male,71,9,119496.87,1,1,0,125848.88,0 +8158,15798834,Yefremov,719,Spain,Female,32,7,0,1,0,0,76264.27,0 +8159,15744127,Kosovich,641,France,Female,37,2,0,2,1,0,3939.87,0 +8160,15637427,Lu,461,Spain,Female,25,6,0,2,1,1,15306.29,0 +8161,15576990,Taplin,790,Germany,Female,25,5,152885.77,1,1,0,58214.79,0 +8162,15615352,Ebelechukwu,588,France,Male,31,4,99607.37,2,0,1,35877.03,0 +8163,15647333,Fleming,621,France,Male,27,4,137003.68,1,1,0,21254.06,0 +8164,15572050,Yefimov,768,Germany,Male,48,3,122831.58,1,1,1,24533.89,1 +8165,15581370,Andreyeva,681,Spain,Male,38,2,99811.44,2,1,0,23531.5,0 +8166,15813503,Pickering,606,Spain,Male,37,8,154712.58,2,1,0,89099.18,0 +8167,15769783,Allan,542,Spain,Male,37,8,0,1,1,1,807.06,0 +8168,15793135,Wang,713,Germany,Female,24,7,147687.24,1,1,1,121592.5,0 +8169,15599182,Reynolds,597,Spain,Female,33,2,0,2,1,1,4700.66,0 +8170,15689517,Hales,635,France,Male,27,3,127009.83,1,1,0,161909.95,0 +8171,15641366,Y?an,599,Germany,Male,61,1,124737.96,1,0,1,90389.61,1 +8172,15588859,Rowley,496,Spain,Female,44,0,179356.28,2,1,0,2919.21,1 +8173,15732293,Chia,759,Spain,Male,31,8,0,2,1,1,99086.74,0 +8174,15568032,Moore,757,Germany,Male,31,1,127320.36,3,1,0,163170.32,0 +8175,15623525,Copeland,564,Spain,Male,31,0,125175.58,1,1,1,72757.33,0 +8176,15606601,Rishel,561,France,Female,22,6,186788.96,2,1,0,73286.8,0 +8177,15800811,Wan,702,France,Male,40,3,148556.74,1,0,1,146056.29,0 +8178,15610711,Eluemuno,678,Germany,Female,40,8,128644.46,1,0,0,167673.37,0 +8179,15809654,Hsia,707,France,Female,46,7,127476.73,2,1,1,146011.55,0 +8180,15576077,Kelly,610,France,Female,27,9,159561.93,1,0,1,103381.47,0 +8181,15643378,Muir,744,France,Male,42,1,112419.92,1,1,1,83022.92,0 +8182,15566790,McIntyre,598,France,Male,28,8,129991.76,2,0,1,46041.08,0 +8183,15774402,Donaldson,562,Spain,Male,36,5,0,1,0,1,182843.24,0 +8184,15694641,Wright,621,Spain,Female,59,2,0,2,1,1,171364.18,0 +8185,15605916,Uvarova,659,France,Female,50,3,0,1,1,0,183399.12,1 +8186,15812356,Doherty,722,Germany,Female,40,6,89175.06,2,0,1,152883.95,0 +8187,15644179,Allen,606,France,Female,39,3,0,2,1,0,50560.45,1 +8188,15771674,Ma,603,Spain,Female,39,5,162390.52,2,1,0,54702.66,0 +8189,15623314,Tucker,506,Germany,Female,59,3,190353.08,1,1,0,78365.75,0 +8190,15613292,Ch'eng,715,France,Male,21,8,0,2,1,0,68666.63,0 +8191,15813871,Hs?,690,France,Male,47,2,0,2,1,0,151375.73,0 +8192,15759480,H?,644,France,Female,40,10,139180.97,1,1,1,19959.67,0 +8193,15587712,Chimaijem,589,France,Male,36,8,114435.47,1,1,0,26955.72,0 +8194,15671165,Esomchi,592,France,Female,66,5,149950.19,1,1,1,76267.59,0 +8195,15620746,Lorenzo,632,France,Male,42,4,126115.6,1,1,0,100998.5,0 +8196,15706537,Pirogov,577,Germany,Female,59,7,111396.97,1,0,1,191070.01,0 +8197,15589312,Larkin,588,France,Male,30,3,115007.08,1,0,0,176858.5,0 +8198,15741180,Eddy,617,France,Male,54,6,102141.9,1,1,1,45325.26,0 +8199,15733888,Sells,668,Spain,Female,36,3,133686.52,1,1,0,190958.48,1 +8200,15798532,Crawford,810,France,Male,32,9,120879.73,2,0,1,78896.59,0 +8201,15577359,Bezrukov,767,Spain,Male,47,5,0,1,1,0,121964.46,1 +8202,15614936,Mancini,718,Spain,Female,49,10,82321.88,1,0,1,11144.4,0 +8203,15747647,Iadanza,589,Spain,Female,27,4,0,2,1,0,144181.48,0 +8204,15588566,Wilkinson,778,Spain,Male,33,5,116474.28,2,1,1,32757.55,0 +8205,15570141,P'eng,724,France,Female,34,3,132352.69,1,1,0,80320.3,0 +8206,15800793,St Clair,477,Germany,Female,39,4,182491.57,1,1,0,185830.72,0 +8207,15572415,Preston,580,France,Male,34,6,0,2,1,1,160095.31,0 +8208,15635125,Findlay,566,Spain,Male,63,2,120787.18,2,1,1,52198.84,0 +8209,15636551,Nixon,711,France,Female,29,3,130181.47,2,1,0,31811.44,0 +8210,15600912,Gorshkov,706,Germany,Male,32,5,88348.43,2,1,1,104181.78,0 +8211,15768476,Chukwubuikem,703,Spain,Male,31,6,0,2,1,1,67667.19,0 +8212,15650266,Medvedeva,679,Germany,Male,39,2,146186.28,2,1,1,193974.47,0 +8213,15621004,Chukwuhaenye,603,France,Male,32,7,0,1,1,0,198055.94,1 +8214,15748352,Endrizzi,598,Spain,Male,34,0,104488.17,1,0,1,43249.67,0 +8215,15788920,Ch'ang,836,Germany,Female,32,4,109196.67,2,1,0,55218.02,0 +8216,15743236,Piccio,687,France,Female,61,7,80538.56,1,1,0,131305.37,1 +8217,15637717,Lockington,704,Germany,Male,41,4,109026.8,2,1,1,43117.1,0 +8218,15635500,Seleznyov,605,Germany,Male,75,2,61319.63,1,0,1,186655.11,0 +8219,15634792,Weston,516,France,Female,40,9,0,2,0,1,33266.29,0 +8220,15607560,Groom,572,France,Female,39,2,0,2,1,1,555.28,0 +8221,15727177,Manfrin,557,France,Male,42,6,177822.03,1,1,0,150944.31,1 +8222,15774358,Robertson,443,Germany,Male,59,4,110939.3,1,1,0,72846.58,1 +8223,15791304,Ch'ang,604,Germany,Male,25,7,165413.43,1,1,1,35279.74,0 +8224,15603328,Lucchesi,483,France,Male,27,1,77805.66,1,1,1,2101.89,0 +8225,15804937,Cambage,702,France,Male,50,3,0,2,0,0,94949.84,0 +8226,15804142,Tan,670,Spain,Female,57,3,175575.95,2,1,0,99061.75,1 +8227,15608845,Tao,804,Spain,Female,38,3,124197.22,1,1,0,74692.06,0 +8228,15702434,Hsieh,850,France,Female,30,3,0,2,1,0,116692.8,0 +8229,15632609,Burdekin,554,France,Female,39,10,160132.75,1,1,0,32824.15,0 +8230,15603550,Longo,588,Germany,Female,37,7,70258.88,2,1,0,139607.61,0 +8231,15755239,Maughan,758,Germany,Male,32,4,162657.64,2,1,1,115525.13,0 +8232,15670528,Franz,787,Germany,Male,43,0,132217.45,1,1,0,20955.03,1 +8233,15732704,Piazza,582,Spain,Male,25,9,148042.97,2,1,0,52341.15,0 +8234,15589019,Morant,633,Spain,Female,33,4,92855.02,1,1,1,159813.18,0 +8235,15677796,Becher,766,Germany,Male,47,9,129289.98,1,1,0,169935.46,1 +8236,15760177,Lombardi,564,Spain,Male,37,9,100252.18,1,1,1,146033.52,0 +8237,15636595,Loton,602,Spain,Male,37,3,107592.89,2,0,1,153122.73,0 +8238,15737275,Conti,649,France,Male,39,3,113096.41,1,1,1,60335.24,0 +8239,15672905,Sani,679,Spain,Female,40,7,0,2,1,1,163757.29,0 +8240,15753955,Lori,639,Spain,Male,34,7,149940.04,2,0,0,156648.81,0 +8241,15708504,Wong,790,Germany,Male,50,8,121438.58,1,1,1,176471.78,1 +8242,15592451,Lombardi,565,France,Male,32,9,0,2,1,0,5388.3,0 +8243,15790455,Obialo,478,France,Female,50,2,0,1,0,1,93332.64,1 +8244,15572174,Mazzi,825,France,Male,29,3,148874.01,2,0,1,71192.82,0 +8245,15656330,Von Doussa,528,Spain,Female,32,0,68138.37,1,1,1,170309.19,0 +8246,15569626,Miller,577,Spain,Male,35,5,110080.3,1,1,1,109794.31,0 +8247,15608726,Miracle,663,France,Male,24,7,0,2,1,1,166310.82,0 +8248,15637366,Su,505,Germany,Female,25,5,114268.85,2,1,1,126728.27,0 +8249,15778049,Wyatt,633,Germany,Male,29,6,117412.35,1,0,0,30338.94,0 +8250,15727421,Anayolisa,586,France,Female,38,6,0,2,1,1,37935.83,0 +8251,15688865,Wade,850,France,Female,35,9,0,2,0,0,25329.48,0 +8252,15751032,Enemuo,629,Germany,Female,37,1,35549.81,2,0,0,49676.33,0 +8253,15734737,Bruno,744,France,Male,56,9,0,2,1,1,169498.61,0 +8254,15746515,Greece,750,France,Male,36,7,136492.92,3,1,1,26500.29,1 +8255,15664311,Yang,637,Germany,Male,28,3,123675.69,1,1,1,166458.41,0 +8256,15708139,Brown,575,France,Female,40,1,139532.34,1,1,0,181294.39,0 +8257,15768574,Anderson,671,Spain,Male,58,1,178713.98,1,1,1,21768.21,0 +8258,15738018,Johnston,571,France,Male,40,5,0,2,0,0,72849.29,0 +8259,15699753,Zakharov,590,France,Male,41,1,89086.31,1,1,0,24499.97,0 +8260,15703199,Golibe,619,Spain,Male,38,3,96143.47,1,0,0,98994.92,0 +8261,15627830,Nikitina,640,Germany,Female,30,5,32197.64,1,0,1,141446.01,0 +8262,15570855,Leonard,670,France,Male,38,7,0,2,1,1,77864.41,0 +8263,15772503,Burns,737,France,Female,33,4,0,2,1,0,115115.32,0 +8264,15584453,Burtch,555,Spain,Male,32,10,0,2,0,1,168605.96,0 +8265,15710111,Clark,742,France,Male,33,6,0,2,0,0,38550.4,0 +8266,15618562,Woodward,618,Germany,Female,40,0,140306.38,1,1,0,160618.61,1 +8267,15706764,Spencer,560,France,Female,35,1,0,2,1,0,3701.63,0 +8268,15798737,Chao,654,France,Male,38,8,0,2,1,0,88659.44,0 +8269,15712608,Costa,787,Germany,Female,42,2,74483.97,2,0,1,44273.91,0 +8270,15636736,McLachlan,611,France,Female,53,7,0,2,0,1,156495.39,1 +8271,15703544,Hung,559,Spain,Male,34,0,0,1,1,0,182988.94,0 +8272,15815645,Akhtar,481,France,Male,37,8,152303.66,2,1,1,175082.2,0 +8273,15705739,Toscani,753,Germany,Male,32,5,159904.79,1,1,0,148811.14,0 +8274,15709643,Gray,675,France,Male,32,1,0,3,1,0,85901.09,0 +8275,15669805,Warren,748,Germany,Female,31,1,99557.94,1,1,0,199255.32,0 +8276,15737489,Ramsden,610,Spain,Female,46,5,116886.59,1,0,0,107973.44,0 +8277,15775131,Bartlett,580,Spain,Male,32,9,142188.2,2,0,1,128028.6,0 +8278,15765283,Wenz,624,Germany,Female,40,3,149961.99,2,1,0,104610.86,0 +8279,15628715,Kisch,709,France,Female,36,8,0,2,1,1,69676.55,0 +8280,15813283,Mai,605,France,Female,34,2,0,1,0,0,35982.42,0 +8281,15745716,McGregor,706,Spain,Male,53,7,0,2,0,1,117939.17,0 +8282,15598485,Pinto,567,Spain,Male,40,8,28649.64,1,1,1,95140.62,0 +8283,15696552,Newman,747,France,Female,21,4,81025.6,2,1,0,167682.57,0 +8284,15754569,Pagnotto,664,France,Male,57,1,0,2,1,1,56562.57,0 +8285,15701741,Williams,711,France,Female,39,3,152462.79,1,1,0,90305.97,0 +8286,15572631,Ndubuisi,609,France,Male,25,10,0,1,0,1,109895.16,0 +8287,15636069,Plummer,632,Spain,Male,28,7,155519.59,1,1,0,1843.24,0 +8288,15682467,Chimezie,725,France,Female,36,1,118851.05,1,1,1,102747.02,0 +8289,15790744,Nash,850,France,Female,34,9,92899.27,2,1,0,97465.89,0 +8290,15625023,Onochie,682,France,Male,40,4,0,1,0,1,105352.55,0 +8291,15731267,Rizzo,797,France,Male,37,4,75263.7,1,1,0,85801.77,0 +8292,15742879,Boni,668,Spain,Male,38,1,147904.31,1,1,1,69370.05,0 +8293,15757015,Davies,783,Germany,Female,41,5,106640.5,1,1,0,176945.96,0 +8294,15770711,Lu,766,Germany,Female,28,4,90696.78,1,0,1,21597.2,0 +8295,15569430,Burrows,704,Spain,Female,36,2,175509.8,2,1,0,152039.67,0 +8296,15617304,Ershova,722,France,Male,40,6,0,2,1,1,111893.09,0 +8297,15704466,Udokamma,692,France,Female,34,7,0,2,1,0,195074.62,0 +8298,15664681,Aitken,584,France,Female,35,2,114321.28,2,0,0,15959.01,0 +8299,15605534,Turnbull,644,Germany,Female,51,4,95560.04,1,0,0,72628.84,1 +8300,15792473,Reilly,598,Germany,Female,50,5,88379.81,3,0,1,64157.24,1 +8301,15802625,Hardy,733,Germany,Male,48,7,85915.52,1,1,1,23860.5,0 +8302,15766017,Brookman,615,Germany,Male,58,3,72309.3,1,1,1,85687.09,1 +8303,15762172,Kerr,850,France,Female,39,2,0,2,1,0,179451.42,0 +8304,15728333,McBurney,521,France,Male,43,8,0,1,1,1,93180.09,0 +8305,15792868,Mickey,675,France,Male,69,1,0,2,1,0,157097.09,0 +8306,15605698,Harrison,746,France,Male,58,3,0,3,1,1,80344.96,1 +8307,15777060,Olszewski,770,France,Female,33,4,0,1,1,0,26080.54,1 +8308,15626243,Chijioke,618,France,Male,30,3,133844.22,1,1,1,31406.93,0 +8309,15719898,Young,556,France,Male,36,7,154872.08,2,1,1,32044.64,0 +8310,15599976,Bellasis,749,France,Female,27,9,0,2,1,0,132734.87,0 +8311,15752809,De Mestre,702,Spain,Male,43,6,116121.67,1,1,0,61602.42,0 +8312,15589698,De Luca,555,Germany,Male,42,6,107104.5,1,1,1,41304.44,1 +8313,15609977,Mundy,587,France,Male,47,6,71026.77,1,1,0,57962.41,0 +8314,15750121,Tung,639,France,Male,38,3,0,1,1,0,42862.82,0 +8315,15734177,Donahue,643,France,Male,33,4,0,2,1,1,152992.04,0 +8316,15781347,Okagbue,600,France,Female,41,1,0,2,1,1,91193.65,0 +8317,15592025,Nnaemeka,651,France,Male,53,7,0,2,1,1,130132.41,0 +8318,15670163,Verjus,666,France,Female,27,4,0,2,0,0,88751.45,0 +8319,15765402,H?,520,France,Female,39,6,145644.05,1,0,0,104118.93,0 +8320,15624343,Napolitani,650,Spain,Female,50,7,129667.77,1,0,0,42028.16,0 +8321,15602354,Ginikanwa,564,Germany,Male,33,3,109341.87,1,1,0,75632.78,0 +8322,15579183,Spaull,586,France,Male,64,1,0,2,1,1,53710.23,0 +8323,15584899,Siciliani,617,France,Female,35,5,0,2,0,1,13066.3,0 +8324,15723658,Voronina,712,Spain,Female,30,6,0,2,1,0,152417.97,0 +8325,15803965,Tang,654,France,Male,55,3,87485.67,1,1,1,3299.01,0 +8326,15682489,Crumbley,605,France,Male,27,9,0,2,1,0,198091.81,0 +8327,15813645,Hamilton,491,France,Female,36,0,53369.13,1,1,1,103934.12,0 +8328,15766787,Piazza,707,France,Female,35,9,0,2,1,1,70403.65,0 +8329,15687171,Birch,638,Spain,Male,34,5,146679.77,1,1,0,102179.86,0 +8330,15690744,Custance,683,France,Male,43,2,112499.42,2,1,0,30375.18,0 +8331,15707974,Anayochukwu,815,Spain,Female,38,2,48387,1,1,0,184796.84,0 +8332,15673084,Galkin,645,Spain,Male,38,1,68079.8,1,0,1,166264.89,0 +8333,15814772,Adams,645,Germany,Male,49,4,160133.88,1,0,1,88391.97,0 +8334,15743709,Toomey,683,France,Male,30,4,66190.33,1,1,1,115186.97,0 +8335,15610343,Marshall-Hall,705,France,Female,37,10,0,2,1,1,13935.53,1 +8336,15737414,Shen,647,France,Male,35,4,123761.68,1,1,0,83910.4,0 +8337,15788480,Pagnotto,786,Germany,Female,33,0,122325.58,1,0,0,34712.34,1 +8338,15568519,Wood,534,France,Male,41,9,0,2,1,0,13871.34,0 +8339,15792453,More,602,Spain,Female,42,1,138912.17,1,1,1,139494.75,0 +8340,15658100,Piccio,695,France,Female,42,0,0,2,0,1,140724.64,0 +8341,15695197,Tochukwu,553,Germany,Female,25,7,128524.19,2,1,0,20682.46,0 +8342,15749807,Graham,516,Spain,Female,31,3,0,2,1,0,124202.26,0 +8343,15773876,Tung,655,France,Female,34,3,0,2,1,0,159638.77,0 +8344,15591698,P'eng,849,Germany,Female,49,9,132934.89,1,1,0,171056.65,1 +8345,15712813,Nevzorova,520,Germany,Male,43,3,150805.17,3,0,1,25333.03,1 +8346,15763898,Toscani,568,Spain,Female,46,3,0,2,1,1,29372.62,0 +8347,15793324,McKenzie,695,Spain,Male,32,9,0,3,0,1,38533.79,0 +8348,15757759,Okwuoma,807,Spain,Female,28,7,165969.26,3,1,0,156122.13,1 +8349,15796230,Morley,642,Germany,Female,36,2,124495.98,3,1,1,57904.22,1 +8350,15611729,Kerr,703,Germany,Male,39,1,141559.5,1,1,1,31257.1,1 +8351,15709531,Harding,556,France,Male,38,2,114756.14,1,1,0,193214.05,0 +8352,15650751,Butler,585,France,Female,30,6,0,2,1,1,137757.69,0 +8353,15641413,Crawford,587,Germany,Female,49,7,155393.98,2,1,0,13308.2,1 +8354,15753840,Brown,524,Spain,Female,32,6,0,1,1,1,132861.9,1 +8355,15669994,Greece,556,Germany,Female,31,1,128663.81,2,1,0,125083.29,0 +8356,15695301,Matthews,504,Spain,Male,44,4,113522.64,1,1,1,12405.2,0 +8357,15792004,Heath,731,Spain,Female,26,3,0,2,1,0,37697.29,0 +8358,15603035,Vincent,651,France,Male,34,3,0,2,1,1,105599.65,0 +8359,15717286,Sal,675,Spain,Female,40,8,79035.95,1,1,0,142783.98,1 +8360,15577107,Milne,657,Spain,Female,22,6,0,3,0,1,168412.07,1 +8361,15754747,Bazile,686,Germany,Male,33,9,141918.09,2,0,1,184036.47,0 +8362,15705676,Wardle,690,France,Female,35,9,107944.33,2,0,0,48478.47,0 +8363,15751912,Lilly,567,France,Male,36,7,0,2,0,1,3896.08,0 +8364,15677336,Aitken,557,Germany,Male,57,1,120043.13,1,1,0,132370.75,1 +8365,15684395,Enderby,446,Spain,Female,45,10,125191.69,1,1,1,128260.86,1 +8366,15659949,Chiu,850,France,Male,31,1,96399.31,2,1,0,106534.15,0 +8367,15812422,Ugorji,637,France,Male,41,2,0,2,0,1,102515.42,0 +8368,15806941,Sharpe,499,France,Male,60,7,76961.6,2,1,1,83643.87,0 +8369,15637690,Houghton,622,Germany,Female,34,7,98675.74,1,1,0,138906.85,1 +8370,15632882,Konovalova,684,Germany,Male,37,1,126817.13,2,1,1,29995.83,1 +8371,15807107,Patel,612,France,Male,32,3,121394.42,1,1,0,164081.42,0 +8372,15661034,Ngozichukwuka,813,Germany,Female,29,5,106059.4,1,0,0,187976.88,1 +8373,15811958,Medland,850,Germany,Male,44,2,112755.34,2,0,0,158171.36,0 +8374,15785167,Padovano,795,Spain,Male,29,4,0,2,0,0,155711.64,0 +8375,15646720,Tsui,628,Spain,Female,55,7,0,3,1,0,85890.75,1 +8376,15658614,H?,565,Germany,Female,38,7,145400.69,2,1,1,83844.79,0 +8377,15704657,Denman,601,France,Male,39,3,72647.64,1,1,0,41777.9,1 +8378,15567147,Ratten,802,Spain,Male,40,4,0,2,1,1,81908.09,0 +8379,15701319,Baxter,614,Germany,Female,37,6,96340.81,2,1,1,139377.24,1 +8380,15745266,Norman,434,Spain,Male,55,6,0,1,0,1,73562.05,1 +8381,15650437,Shen,522,Germany,Male,32,8,124450.36,2,1,1,165786.1,0 +8382,15764314,Reilly,550,Germany,Male,36,2,113877.23,2,1,0,174921.91,0 +8383,15612594,Ifeanacho,599,Spain,Male,25,3,0,2,1,1,120790.02,0 +8384,15593501,Graham,493,France,Female,36,5,148667.81,2,1,0,56092.51,0 +8385,15804150,Lysaght,755,France,Male,34,3,0,2,1,1,158816.03,0 +8386,15649297,T'ang,605,France,Female,62,4,111065.93,2,0,1,125660.99,0 +8387,15641110,Abron,708,France,Male,41,0,0,1,1,0,128400.62,0 +8388,15660608,Chimaraoke,699,France,Male,44,8,158697.61,1,1,0,107181.22,0 +8389,15806570,Y?an,763,France,Female,53,4,0,1,1,0,77203.72,1 +8390,15715345,Sergeyeva,743,Spain,Male,25,6,0,2,1,0,129740.11,0 +8391,15755521,Ma,660,France,Female,48,0,90044.32,2,0,1,187604.97,1 +8392,15579074,Obiajulu,619,Germany,Male,38,10,84651.79,1,1,1,184754.26,0 +8393,15641158,Belcher,739,Germany,Male,32,3,102128.27,1,1,0,63981.37,1 +8394,15752507,K?,769,Germany,Male,60,9,148846.39,1,1,0,192831.67,1 +8395,15597983,Brown,692,France,Male,69,10,154953.94,1,1,1,70849.47,0 +8396,15586069,Abernathy,560,France,Female,30,0,108883.29,1,1,0,27914.95,0 +8397,15655082,Pape,607,France,Female,48,4,112070.86,3,1,0,173568.3,1 +8398,15720155,Tao,630,Germany,Male,29,6,131354.39,1,0,1,9324.31,1 +8399,15582116,Ma,767,Germany,Female,45,7,132746.2,2,1,0,26628.88,1 +8400,15749365,Earle,543,France,Female,34,8,0,2,0,1,145601.8,0 +8401,15632069,Kazantsev,776,France,Male,39,8,125211.55,2,1,0,144496.07,0 +8402,15663134,Uspenskaya,535,Spain,Male,58,1,0,2,1,1,11779.98,1 +8403,15766683,Coombes,549,Germany,Male,36,6,139422.37,1,0,0,83983.39,1 +8404,15707219,Hopman,844,France,Female,28,4,0,2,0,1,123318.37,0 +8405,15709232,McKay,586,Germany,Female,47,5,157099.47,2,1,1,65481.86,0 +8406,15801351,Milanesi,583,France,Male,40,3,0,2,1,0,47728,0 +8407,15578747,Chineze,701,Spain,Male,26,5,83600.24,1,0,1,59195.05,0 +8408,15675626,Dawson,726,France,Male,28,2,0,1,0,0,98060.51,0 +8409,15583736,Shih,829,Germany,Male,36,4,81795.74,2,1,0,90106.94,0 +8410,15590011,Hughes,749,Spain,Male,38,9,129378.32,1,1,1,13549.34,0 +8411,15609913,Clark,743,France,Female,46,9,0,1,1,0,113436.08,0 +8412,15719479,Chukwuhaenye,619,Spain,Female,56,7,0,2,1,1,42442.21,0 +8413,15575147,Wall,699,France,Male,22,9,99339,1,1,0,68297.61,1 +8414,15597309,Howell,749,Spain,Male,36,7,0,2,0,0,80134.65,0 +8415,15648367,Lo,600,Germany,Female,29,6,74430.1,2,1,1,96051.1,0 +8416,15758031,Lazarev,760,Spain,Male,38,3,91241.85,1,0,1,80682.35,0 +8417,15751771,Lowe,528,Germany,Male,32,2,99092.45,1,0,1,111149.98,0 +8418,15689288,Folliero,630,France,Female,26,5,0,2,1,0,182612.38,0 +8419,15731026,Han,683,Germany,Female,39,2,100062.16,2,1,0,109201.43,0 +8420,15775809,Holloway,677,Germany,Female,26,6,98723.67,1,0,1,151146.67,0 +8421,15743076,Pai,669,Spain,Male,29,9,0,1,1,1,93901.61,0 +8422,15658258,Trejo,693,France,Male,43,6,128760.32,1,1,0,36342.79,0 +8423,15756321,Johnston,612,Spain,Female,52,5,144772.69,1,0,0,98302.57,1 +8424,15706799,Macknight,719,Spain,Male,44,4,0,1,0,0,84972.9,1 +8425,15775703,Lo,702,France,Male,26,2,71281.29,1,1,1,108747.12,1 +8426,15642636,Glossop,755,France,Male,29,9,117035.89,1,1,1,21862.19,0 +8427,15704651,Bishop,514,France,Male,26,1,0,2,0,0,121551.93,0 +8428,15806771,Yefremova,753,France,Female,40,0,3768.69,2,1,0,177065.24,1 +8429,15566735,Obialo,548,Germany,Female,36,2,108913.84,2,1,1,140460.01,0 +8430,15681671,Nkemjika,850,Germany,Male,28,2,101100.22,2,1,1,35337.31,0 +8431,15775949,Trevisani,612,France,Female,38,7,110615.47,1,1,1,193502.93,0 +8432,15586752,Parkes,628,Germany,Male,33,8,152143.89,1,1,1,32174.03,0 +8433,15582519,Seleznyov,479,France,Male,47,6,121797.09,1,0,1,5811.9,1 +8434,15658233,Naylor,724,France,Female,41,5,109798.25,1,0,1,149593.61,0 +8435,15755330,Forbes,512,Germany,Male,41,7,122403.24,1,0,1,37439.9,1 +8436,15605072,Douglas,638,France,Female,43,3,145860.98,1,1,1,142763.51,1 +8437,15617538,Nwankwo,834,Spain,Male,40,7,0,2,0,0,45038.74,0 +8438,15591428,Myers,781,France,Male,29,9,0,2,0,0,172097.4,0 +8439,15692142,Rogova,707,Germany,Female,48,7,105086.74,1,1,1,180344.69,1 +8440,15692931,Hsing,670,France,Male,22,2,114991.45,1,1,1,37392.56,0 +8441,15781127,Giordano,663,Spain,Female,33,8,96769.04,1,1,1,36864.05,0 +8442,15677136,Okwukwe,624,France,Female,23,5,0,2,0,0,132418.59,0 +8443,15677828,Chalmers,598,France,Female,34,4,0,2,0,0,60894.26,0 +8444,15567897,Chiazagomekpere,619,Germany,Male,23,5,132725.1,1,1,1,143913.33,0 +8445,15793641,Evseyev,792,France,Female,70,3,0,2,1,1,172240.27,0 +8446,15678333,Parry-Okeden,683,France,Female,26,7,0,2,1,0,86619.77,0 +8447,15630511,Picot,691,France,Female,33,6,0,2,1,0,164074.89,0 +8448,15792627,Reid,765,Spain,Female,33,5,84557.82,1,1,1,69039.43,0 +8449,15717191,Ferri,508,France,Male,49,1,93817.41,2,1,1,132468.76,1 +8450,15625716,Genovesi,637,France,Female,33,9,113913.53,1,0,1,65316.5,0 +8451,15710053,Neumayer,667,Germany,Female,44,5,140406.68,2,0,1,57164.19,0 +8452,15580043,Murray,575,Spain,Female,22,8,105229.34,1,1,1,34397.08,0 +8453,15601410,Tien,744,Spain,Female,46,1,0,3,1,1,177431.59,1 +8454,15684669,Parkes,567,France,Female,41,9,137891.35,1,1,0,142009.46,1 +8455,15619083,Yip,502,France,Female,35,6,0,2,1,1,80618.47,0 +8456,15692207,Ingle,609,France,Female,53,6,0,2,1,1,124218.27,0 +8457,15730705,Chidubem,715,France,Male,37,9,165252.52,1,1,0,85286.3,0 +8458,15749688,Lu,541,France,Male,32,8,0,2,0,0,40889.14,0 +8459,15728542,Vorobyova,850,France,Female,71,4,0,2,1,1,107236.87,0 +8460,15760063,Chiedozie,595,Spain,Male,23,7,0,2,1,1,168085.97,0 +8461,15658982,Napolitani,650,Germany,Female,28,5,122034.4,3,0,1,146663.43,1 +8462,15758769,Coffey,625,France,Female,44,7,0,1,1,0,4791.8,0 +8463,15778481,Chigbogu,817,France,Male,59,1,118962.58,1,1,1,120819.58,0 +8464,15661162,Akabueze,526,Spain,Male,49,2,0,1,1,0,114539.67,1 +8465,15568164,Istomin,850,France,Female,34,4,71379.53,2,1,1,154000.99,0 +8466,15601569,Ndubueze,598,France,Female,40,2,171178.25,1,1,0,137980.58,1 +8467,15772383,Toscani,613,France,Male,36,9,131307.11,1,0,0,83343.73,0 +8468,15667456,Ross,709,Spain,Male,62,3,0,2,1,1,82195.15,0 +8469,15672983,Fernando,678,Spain,Female,27,5,87099.85,2,1,0,149550.95,0 +8470,15799534,McClaran,720,France,Male,71,5,183135.39,2,1,1,197688.5,0 +8471,15582847,Yermakova,662,France,Male,26,0,0,2,0,1,72929.96,0 +8472,15612478,Somadina,525,France,Male,51,10,0,3,1,0,171045.35,1 +8473,15709621,Wan,662,France,Male,31,3,0,2,0,1,27731.05,0 +8474,15802009,Mazzi,770,France,Female,33,6,0,2,1,1,126131.9,0 +8475,15698816,Tuan,721,Spain,Female,33,4,72535.45,1,1,1,103931.49,0 +8476,15574830,Townsley,633,Germany,Male,58,2,128137.42,2,1,0,147635.33,1 +8477,15603082,Yashina,701,France,Male,51,9,0,2,0,0,61961.57,0 +8478,15685947,Henderson,556,Germany,Male,42,0,115915.53,2,0,1,125435.47,1 +8479,15643048,Mueller,639,France,Male,66,0,0,2,0,1,42240.54,0 +8480,15807568,Wright,632,France,Male,50,2,0,2,0,0,57942.88,0 +8481,15597591,Lung,456,France,Male,29,5,107000.49,1,1,1,153419.62,0 +8482,15747558,Bryant,729,Spain,Female,38,10,0,2,1,0,189727.12,0 +8483,15756655,Madukaife,632,France,Female,34,2,0,2,0,0,165385.55,0 +8484,15589949,Maclean,433,Spain,Male,34,9,152806.74,1,1,0,19687.99,0 +8485,15601012,Abdullah,802,France,Female,60,3,92887.06,1,1,0,39473.63,1 +8486,15724269,Yao,670,France,Male,25,7,0,2,1,1,144723.38,0 +8487,15567506,Cheatham,738,Germany,Female,40,6,114940.67,2,1,1,194895.57,1 +8488,15791877,Gallagher,706,Germany,Male,34,0,140641.26,2,1,1,77271.91,0 +8489,15794360,Hao,592,Germany,Female,70,5,71816.74,2,1,0,105096.82,1 +8490,15686538,Nixon,522,France,Female,41,7,0,2,0,1,176780.39,0 +8491,15585985,Wang,746,France,Male,48,5,165282.42,1,1,0,153786.46,1 +8492,15699257,Kerr,651,Spain,Male,42,2,143145.87,2,1,0,43612.06,0 +8493,15804104,Romani,494,France,Male,28,9,114731.76,2,0,1,79479.74,0 +8494,15727619,Lock,753,Germany,Female,46,9,113909.69,3,1,0,92320.37,1 +8495,15740237,Millar,671,Germany,Male,36,2,116695.27,1,0,0,193201.86,0 +8496,15801436,K'ung,696,France,Male,42,4,0,1,0,0,126353.13,1 +8497,15705735,Onyekachi,577,Spain,Male,43,3,0,2,1,1,135008.92,0 +8498,15649359,Somayina,587,France,Male,36,1,0,2,0,1,17135.6,0 +8499,15624892,Dennis,712,Germany,Male,37,7,93978.96,2,1,0,60651.77,0 +8500,15784918,Brown,498,Germany,Male,35,2,121968.11,2,0,1,188343.05,0 +8501,15584785,Ogochukwu,660,France,Male,37,2,97324.91,1,1,0,23291.83,0 +8502,15797197,Macleod,678,Spain,Male,29,6,0,2,1,0,64443.75,0 +8503,15574858,Page,530,France,Male,37,8,0,2,1,1,287.99,0 +8504,15794101,Barese,559,France,Female,48,2,0,2,0,1,137961.41,0 +8505,15743245,Agafonova,624,France,Male,42,3,145155.37,1,1,0,72169.95,1 +8506,15791535,Caraway,592,France,Male,28,5,137222.77,1,0,0,39608.58,0 +8507,15605215,Stevenson,767,France,Male,48,9,0,2,0,1,175458.21,0 +8508,15771749,Duncan,653,Germany,Female,38,5,114268.22,2,1,1,89524.83,0 +8509,15616833,Wang,678,Spain,Male,27,2,0,2,1,1,13221.25,0 +8510,15750728,Kaur,586,Spain,Female,42,2,0,1,1,0,102889.34,0 +8511,15769353,Jenkins,550,France,Female,40,8,150490.32,1,0,0,166468.21,1 +8512,15770091,Edwards,643,Germany,Male,28,9,160858.13,2,1,0,27149.27,0 +8513,15716420,Kelly,612,Spain,Male,39,5,170288.38,1,1,1,59601.15,0 +8514,15740602,Boyle,674,Germany,Female,27,4,111568.01,1,0,1,22026.18,0 +8515,15796071,Loane,657,Spain,Male,29,7,83889.03,1,1,0,153059.62,0 +8516,15811389,Padovano,724,Germany,Female,35,0,171982.95,2,0,1,167313.07,0 +8517,15783875,Li Fonti,500,France,Female,34,4,0,2,1,0,12833.96,0 +8518,15671800,Robinson,688,France,Male,20,8,137624.4,2,1,1,197582.79,0 +8519,15677288,Geach,599,France,Male,50,3,121159.65,1,0,0,4033.39,1 +8520,15633525,Payne,631,France,Male,29,7,0,2,0,1,125877.22,0 +8521,15634606,Chinonyelum,634,Spain,Male,52,1,0,2,1,1,176913.42,0 +8522,15579207,Watkins,545,France,Male,37,3,91184.01,1,1,0,105476.65,0 +8523,15619892,Page,644,Spain,Male,18,8,0,2,1,0,59172.42,0 +8524,15567778,Genovese,690,Germany,Female,54,1,144027.8,1,1,1,108731.02,1 +8525,15711750,Watson,711,France,Female,34,6,0,2,1,1,175310.38,0 +8526,15751084,Mancini,712,France,Female,29,8,140170.61,1,1,1,38170.04,0 +8527,15768945,Chibueze,627,France,Male,27,1,62092.9,1,1,1,105887.04,0 +8528,15586931,Hunter,694,Spain,Male,39,3,0,1,1,1,95625.03,0 +8529,15636353,Buchi,534,Spain,Male,35,4,0,2,0,0,9541.15,0 +8530,15623858,Charteris,603,France,Male,45,9,0,1,0,0,148516.79,0 +8531,15703354,Aksenov,808,France,Female,33,2,103516.87,1,1,0,113907.8,0 +8532,15663987,Wright,723,Spain,Male,30,1,0,3,1,0,164647.72,1 +8533,15780805,Lu,585,France,Female,35,2,0,2,1,0,98621.04,1 +8534,15768566,K?,706,France,Male,34,8,0,2,1,1,37479.97,0 +8535,15643229,Hou,671,France,Female,31,6,0,2,1,1,15846.42,0 +8536,15754940,Descoteaux,597,Spain,Male,43,2,85162.26,1,0,1,5104.08,1 +8537,15676576,Stephenson,646,France,Female,43,8,143061.88,1,1,0,61937.6,0 +8538,15800068,Cooper,801,Spain,Female,46,6,0,2,1,1,170008.74,0 +8539,15648030,Crump,731,Spain,Female,33,5,137388.01,2,1,0,165000.68,0 +8540,15668594,Diggs,620,Germany,Female,25,1,137712.01,1,1,1,76197.05,0 +8541,15728709,Shih,484,Germany,Male,40,7,106901.42,2,0,0,118045.98,0 +8542,15724181,Hudson,647,Spain,Male,47,5,105603.21,2,1,1,157360.9,0 +8543,15647546,Carvosso,688,Germany,Female,40,8,150679.71,2,0,1,196226.38,0 +8544,15702601,Wyatt,680,Germany,Male,30,4,108300.27,2,0,1,44384.57,1 +8545,15567725,Kodilinyechukwu,689,France,Female,46,7,52016.08,2,1,1,72993.65,0 +8546,15674179,Vorobyova,513,Germany,Male,34,7,60515.13,1,0,0,124571.09,0 +8547,15686957,Piccio,553,Germany,Male,35,2,158584.28,2,1,0,43640.16,0 +8548,15607690,Hsing,689,Germany,Male,47,2,118812.5,2,0,0,31121.42,0 +8549,15806546,Lucas,517,Spain,Male,46,4,0,1,1,0,22372.78,0 +8550,15632850,T'ang,731,France,Male,37,8,0,2,1,1,170338.35,0 +8551,15709016,North,687,Germany,Female,47,1,91219.29,1,0,0,158845.49,1 +8552,15638068,Thompson,507,Spain,Male,32,7,0,2,1,0,67926.18,0 +8553,15749345,Simpson,468,France,Female,22,1,76318.64,1,1,1,194783.12,0 +8554,15791321,Nwora,682,Spain,Female,58,4,0,1,1,0,176036.01,0 +8555,15699095,Chandler,603,France,Female,24,3,0,1,1,1,198826.03,1 +8556,15638329,Uspensky,522,Germany,Male,25,1,111432.13,1,1,1,168683.57,0 +8557,15575445,Ferguson,629,Spain,Male,41,10,150148.51,1,0,0,6936.27,0 +8558,15752622,Kerr,729,France,Female,32,7,38550.06,1,0,1,179230.23,0 +8559,15774507,Furneaux,574,France,Female,39,5,119013.86,1,1,0,103421.91,0 +8560,15570857,Kambinachi,677,Germany,Female,39,0,111213.64,2,1,1,147578.26,0 +8561,15599386,Black,627,Germany,Male,28,5,71097.23,1,1,1,130504.49,0 +8562,15744913,Chizoba,788,Spain,Male,36,10,109632.85,1,1,1,16149.13,0 +8563,15647292,Peng,697,France,Male,63,7,148368.02,1,0,0,118862.08,1 +8564,15728838,Leach,578,France,Male,45,1,148600.91,1,1,0,143397.14,1 +8565,15584704,Chiazagomekpele,519,France,Male,48,10,71083.98,1,1,0,137959,0 +8566,15749068,Nickson,632,France,Female,40,9,139625.34,1,1,0,93702.96,1 +8567,15622985,Lin,679,France,Female,39,4,0,1,0,0,172939.3,1 +8568,15587676,Alexeieva,699,France,Male,30,9,0,1,1,1,108162.13,0 +8569,15779496,Sykes,615,France,Male,64,0,81564.1,2,0,1,35896.09,0 +8570,15733460,Martin,622,Spain,Male,36,9,0,2,1,1,104852.6,0 +8571,15711457,Herz,755,France,Female,28,7,124540.28,1,0,1,188850.89,0 +8572,15795290,Nikitina,767,France,Female,42,2,133616.39,1,1,0,28615.8,0 +8573,15611223,Ko,752,Germany,Female,38,10,101648.5,2,1,0,172001.44,0 +8574,15794159,Highett,633,France,Female,26,8,124281.84,1,1,1,60116.57,0 +8575,15780677,Jackson,717,France,Female,59,4,0,2,1,1,170528.63,0 +8576,15690175,Ball,585,Spain,Male,45,0,0,2,0,0,189683.7,0 +8577,15722599,Nelson,751,France,Female,37,9,183613.66,2,0,0,49734.94,0 +8578,15569976,Woronoff,754,Germany,Male,65,1,136186.44,1,1,1,121529.59,1 +8579,15707011,Morrison,495,France,Male,47,10,137682.68,1,1,0,71071.47,0 +8580,15702277,Smith,650,France,Male,34,4,106005.54,1,0,1,142995.32,0 +8581,15801915,Rendall,529,France,Female,31,6,152310.55,1,1,0,13054.25,0 +8582,15580213,McIntyre,585,France,Female,43,2,0,2,1,0,89402.54,0 +8583,15637947,Wei,668,Spain,Male,32,1,134446.04,1,0,1,111241.37,0 +8584,15715888,Allardyce,591,France,Female,38,2,142289.28,1,0,1,119638.85,0 +8585,15732967,Cremonesi,731,France,Male,19,6,0,2,1,1,151581.79,0 +8586,15737047,Weatherford,754,France,Female,45,6,0,1,1,0,73881.68,1 +8587,15694039,Jen,650,Germany,Female,46,9,149003.76,2,1,0,176902.83,0 +8588,15649457,Macleod,588,Germany,Male,41,2,131341.46,2,0,1,7034.94,0 +8589,15742809,Mironova,712,Spain,Female,29,7,77919.78,1,1,0,122547.58,0 +8590,15637829,Sharpe,691,France,Female,34,7,0,2,0,1,161559.12,0 +8591,15633194,Osborne,771,France,Female,41,10,108309,4,1,1,137510.41,1 +8592,15611635,Chu,678,Spain,Female,39,6,0,1,0,1,185366.56,0 +8593,15638774,Chong,719,Spain,Female,40,9,0,2,1,0,182224.14,0 +8594,15722037,Alvarez,610,Germany,Male,36,7,115462.02,1,0,1,42581.04,0 +8595,15672930,Palerma,722,Spain,Male,37,9,0,2,1,0,31921.95,0 +8596,15668774,Chiemenam,758,Germany,Female,23,5,122739.1,1,1,0,102460.84,1 +8597,15780966,Pritchard,709,France,Female,32,2,0,2,0,0,109681.29,0 +8598,15659694,Wallis,634,Germany,Female,53,3,113781.5,2,1,1,106345.05,1 +8599,15624424,Palerma,678,Spain,Female,49,1,0,2,1,1,102472.9,0 +8600,15708713,Hill,633,France,Male,35,3,0,2,1,1,36249.76,0 +8601,15755405,Hudson,710,France,Male,43,9,128284.45,1,1,0,32996.89,1 +8602,15647570,Chung,640,Germany,Male,45,8,120591.19,1,0,0,195123.94,0 +8603,15684348,Zhdanova,656,France,Male,63,8,0,2,0,1,57014.43,0 +8604,15702541,Fraser,551,France,Female,59,2,166968.28,1,1,0,159483.76,1 +8605,15646942,Meng,786,Spain,Female,39,7,0,2,0,0,100929.59,0 +8606,15748920,Cherkasova,561,France,Female,49,8,0,2,1,1,12513.07,0 +8607,15694581,Rawlings,807,Spain,Male,42,5,0,2,1,1,74900.9,0 +8608,15643215,Jen,602,Germany,Male,38,2,71667.97,2,0,0,137111.89,0 +8609,15649060,Chien,727,Germany,Female,31,3,82729.47,2,1,0,60212.51,0 +8610,15774258,Gorbunov,678,France,Male,40,1,0,2,1,1,187343.4,0 +8611,15731553,Lucas,730,France,Male,23,8,0,2,1,0,183284.53,0 +8612,15617029,Young,596,Spain,Female,30,1,0,2,1,0,8125.39,0 +8613,15780716,Colombo,686,Germany,Male,39,3,129626.19,2,1,1,103220.56,0 +8614,15577018,Tsao,684,Germany,Female,26,2,114035.39,1,0,0,96885.19,0 +8615,15809515,Lewis,797,Germany,Male,32,1,151922.94,1,1,0,8877.06,0 +8616,15789924,Hussain,658,France,Female,39,4,0,1,1,1,147530.06,0 +8617,15725076,Anderson,653,Spain,Female,27,6,107751.68,2,1,1,33389.42,0 +8618,15672481,Ulyanov,641,France,Male,37,6,0,2,1,0,45309.24,0 +8619,15574115,Shaw,656,Spain,Female,41,6,101179.23,2,1,1,35230.61,0 +8620,15661830,Lucciano,750,Spain,Female,36,6,0,2,1,1,59816.41,0 +8621,15665879,Gordon,768,France,Female,40,8,0,2,0,1,69080.46,0 +8622,15673820,Woodward,568,France,Male,33,7,0,2,1,0,143450.61,0 +8623,15747772,Cunningham,706,Germany,Male,36,9,58571.18,2,1,0,40774.01,0 +8624,15666197,Boni,430,Germany,Female,38,8,153058.64,1,1,0,99377.27,0 +8625,15773639,Truscott,745,Germany,Male,35,4,98270.34,1,1,0,133617.43,0 +8626,15581893,Ginikanwa,747,France,Male,43,1,130788.71,1,0,1,101495,1 +8627,15672447,Bailey,657,Germany,Male,40,7,99165.84,1,0,1,119333.95,1 +8628,15777830,Hutchinson,639,France,Female,42,4,0,2,0,0,167682.37,0 +8629,15713890,Maclean,704,France,Male,44,3,0,2,0,1,152884.85,0 +8630,15577598,Chiang,651,Spain,Male,23,4,115636.05,2,1,0,70400.86,0 +8631,15786042,Willmore,706,Germany,Female,44,2,185932.18,2,1,0,65413.41,0 +8632,15753462,Godson,632,Germany,Male,30,2,72549,2,0,1,182728.8,0 +8633,15759690,Smith,751,France,Male,42,4,0,2,1,1,81442.6,0 +8634,15801414,Bitter,767,France,Female,35,2,0,2,0,0,144251.38,0 +8635,15656141,Ts'ao,741,France,Male,39,5,0,1,0,1,40207.06,0 +8636,15608701,Chialuka,651,Germany,Male,29,3,121890.06,1,1,0,54530.51,1 +8637,15582892,Scott,601,France,Male,46,2,99786.07,1,1,1,32683.88,1 +8638,15632967,Feng,520,France,Male,34,3,0,2,1,1,104703.96,0 +8639,15587573,Castiglione,626,Germany,Male,27,4,115084.53,2,0,1,26907.43,0 +8640,15654891,He,811,France,Male,30,6,0,2,1,1,180591.32,0 +8641,15611365,Fanucci,730,France,Female,32,9,127661.69,1,0,0,60905.51,0 +8642,15749103,Ginikanwa,604,Germany,Female,47,4,118907.6,1,0,1,47777.15,1 +8643,15810203,Manning,499,Germany,Female,44,6,77627.33,2,1,0,108222.68,0 +8644,15813660,Forlonge,754,Spain,Male,40,2,160625.17,1,0,1,3554.63,0 +8645,15605673,Liang,716,Spain,Female,29,8,0,2,0,0,78616.92,0 +8646,15669282,Uchechukwu,636,France,Female,20,10,124266.86,1,0,0,100566.81,0 +8647,15792726,Sung,470,France,Female,25,8,127974.06,2,1,1,183259.35,0 +8648,15593241,Tochukwu,444,France,Male,43,3,0,2,1,1,159131.21,0 +8649,15683053,Reyna,809,Spain,Female,48,2,0,1,1,0,160976.85,1 +8650,15632736,Liang,850,Germany,Female,30,3,104911.35,2,1,1,42933.26,0 +8651,15731865,Unwin,637,France,Male,27,1,0,2,1,0,91291.2,0 +8652,15760450,Rutherford,512,France,Male,43,1,0,2,1,1,52471.36,0 +8653,15787204,Howe,774,Spain,Female,43,1,110646.54,1,0,0,108804.28,0 +8654,15650454,Tran,641,France,Male,57,5,0,2,1,1,122449.18,0 +8655,15573730,Thompson,586,Germany,Male,42,6,126704.49,2,1,0,41682.3,0 +8656,15705050,Linger,611,France,Male,30,9,0,2,1,1,148887.69,0 +8657,15791342,Johnston,660,Spain,Male,31,1,84560.04,1,1,1,137784.25,0 +8658,15684316,Udokamma,532,France,Male,43,9,0,2,0,0,190573.91,1 +8659,15700540,Barrera,557,Germany,Female,38,2,129893.56,1,0,0,102076.03,0 +8660,15770631,Sutherland,730,Spain,Male,25,5,167385.81,1,1,1,56307.51,0 +8661,15790594,Bednall,535,France,Female,27,6,0,2,0,1,49775.58,0 +8662,15604020,Otoole,773,Germany,Female,36,4,105858.71,1,0,1,4395.45,0 +8663,15637599,Cremonesi,510,Germany,Female,44,4,123070.89,1,1,0,28461.29,1 +8664,15736578,Hamilton,539,France,Male,39,1,0,1,1,1,28184.7,0 +8665,15666332,Donaldson,690,Spain,Female,48,2,0,2,1,1,3149.1,0 +8666,15727291,McKay,821,France,Female,40,1,0,2,1,0,194273.12,0 +8667,15785920,Black,687,Germany,Male,35,1,125141.24,2,1,1,148537.07,0 +8668,15658987,Kane,557,France,Female,46,4,96173.17,2,1,1,116378.31,0 +8669,15687719,She,532,Spain,Female,37,5,0,2,0,1,6761.84,0 +8670,15799641,Bruno,540,Spain,Male,39,2,0,2,1,0,81995.92,0 +8671,15758702,Watson,705,France,Female,55,8,0,2,1,1,14392.68,0 +8672,15689526,Shih,542,Germany,Female,35,9,127543.11,2,1,0,468.94,1 +8673,15586848,Rose,706,France,Male,38,1,0,2,1,0,122379.54,0 +8674,15707637,Zikoranachukwudimma,765,France,Female,56,1,0,1,1,0,13228.93,1 +8675,15719426,Cole,529,France,Male,67,8,103101.56,2,1,1,154002.02,1 +8676,15639265,Isaacs,714,France,Male,54,7,126113.28,1,1,0,112777.38,0 +8677,15576124,Muravyova,582,France,Male,41,1,40488.76,1,1,0,128528.83,0 +8678,15757829,Timperley,609,Germany,Female,40,10,137389.77,2,1,0,170122.22,0 +8679,15633227,Kenechukwu,518,France,Female,28,9,85146.36,1,0,0,2803.89,0 +8680,15753092,He,791,Germany,Male,35,5,129828.58,1,1,1,181918.26,1 +8681,15782939,Storey,747,France,Male,42,4,80214.36,1,1,0,115241.96,1 +8682,15746338,Onyekachukwu,565,France,Female,40,2,0,2,1,1,129956.13,0 +8683,15590676,Kharlamova,735,France,Male,34,1,141796.43,1,1,0,45858.49,0 +8684,15599329,Christopher,697,France,Female,49,7,195238.29,4,0,1,131083.56,1 +8685,15783097,Lombardo,813,Germany,Male,27,6,111348.15,1,1,0,46422.46,0 +8686,15597885,Kerr,772,France,Male,43,6,0,2,1,1,57675.88,0 +8687,15597467,Duncan,606,France,Female,71,8,0,2,1,1,169741.96,0 +8688,15724764,Lawley,667,Germany,Female,42,10,64404.26,2,0,0,26022.37,0 +8689,15778418,Burns,637,Germany,Male,40,9,154309.67,1,1,1,125334.16,1 +8690,15684769,Whitson,542,France,Male,67,10,129431.36,1,0,1,21343.74,0 +8691,15756167,Doyne,762,Spain,Female,43,5,134204.67,1,1,1,139971.01,0 +8692,15632439,Pinto,698,France,Female,39,4,0,2,0,1,47455.82,0 +8693,15755138,Chin,850,France,Female,32,8,0,2,1,1,55593.8,0 +8694,15659092,Davide,621,France,Female,50,5,0,2,1,0,191756.54,1 +8695,15742116,Torres,671,Germany,Female,48,9,116711.06,2,0,0,76373.38,0 +8696,15801994,Buccho,775,France,Male,31,9,0,2,1,0,169278.51,0 +8697,15647572,Greece,504,Spain,Male,34,0,54980.81,1,1,1,136909.88,0 +8698,15644551,Wimble,751,Spain,Female,37,3,99773.85,2,1,0,54865.92,0 +8699,15709135,Pirozzi,691,Germany,Male,30,7,101231.77,2,0,0,156529.44,0 +8700,15684469,Hsiung,841,Germany,Male,32,2,117070.21,1,1,0,113482.2,0 +8701,15627637,Obioma,709,Germany,Male,23,8,73314.04,2,1,0,63446.47,0 +8702,15667093,Onio,673,France,Male,37,2,0,1,1,1,13624.02,0 +8703,15690589,Udinesi,541,France,Male,37,9,212314.03,1,0,1,148814.54,0 +8704,15595350,Fermin,661,France,Female,31,3,136067.82,2,1,0,65567.91,0 +8705,15777586,Moss,784,Spain,Female,42,2,109052.04,2,1,0,6409.55,0 +8706,15804064,Docherty,742,France,Female,35,2,79126.17,1,1,1,126997.53,0 +8707,15717770,Marcelo,850,Spain,Female,55,7,0,1,0,0,171762.87,1 +8708,15754443,Fadden,443,France,Female,35,9,108308,1,1,0,129031.19,1 +8709,15776939,Zox,778,Germany,Female,48,3,102290.56,2,1,0,182691.31,0 +8710,15713517,Otitodilinna,529,France,Male,39,6,102025.08,2,1,0,12351.01,0 +8711,15683522,Kennedy,678,Germany,Female,37,2,113383.07,1,1,1,135123.96,0 +8712,15673995,Tu,516,Spain,Female,65,9,102541.1,1,1,0,181490.42,0 +8713,15771054,Barnes,469,Spain,Male,35,5,0,2,1,0,186490.37,0 +8714,15578788,Bibi,786,Spain,Male,40,6,0,2,0,0,41248.8,0 +8715,15737408,L?,703,France,Female,41,6,109941.51,1,1,0,116267.28,0 +8716,15750837,Landseer,579,Germany,Male,41,0,141749.68,1,0,1,9201.53,0 +8717,15576022,Nwachinemelu,565,France,Male,38,5,0,2,0,1,80630.32,0 +8718,15635502,Ch'iu,443,France,Male,44,2,0,1,1,0,159165.7,0 +8719,15627298,Vinogradova,589,France,Male,37,7,85146.48,2,1,0,86490.09,1 +8720,15811415,Jenks,691,France,Female,44,6,134066.1,2,1,1,197572.41,0 +8721,15645059,Crace,711,France,Female,28,8,0,2,0,0,105159.89,0 +8722,15689671,Packham,775,Spain,Male,27,4,0,1,1,1,40807.26,0 +8723,15718667,T'ien,621,France,Male,35,7,87619.29,1,1,0,143.34,0 +8724,15803202,Onyekachi,350,France,Male,51,10,0,1,1,1,125823.79,1 +8725,15593683,Solomina,668,Spain,Female,30,8,0,2,1,0,138465.7,0 +8726,15703394,Hawes,633,Spain,Male,27,3,0,2,1,0,44008.91,0 +8727,15570289,Benson,697,Germany,Male,43,8,103409.16,1,1,0,66893.28,1 +8728,15567437,Emenike,734,Germany,Female,30,7,123040.38,1,1,1,76503.06,0 +8729,15711687,Nero,434,France,Male,41,4,108128.52,1,0,1,56784.11,0 +8730,15656592,Toscano,646,Germany,Male,48,8,169023.33,2,1,1,175657.55,0 +8731,15634373,Yang,764,France,Male,30,5,0,2,0,1,105155.66,0 +8732,15769125,Palerma,727,Spain,Female,41,10,0,2,0,1,47468.56,0 +8733,15711386,Trentini,724,France,Female,29,6,0,2,0,1,64729.51,0 +8734,15714241,Haddon,749,Spain,Male,42,9,222267.63,1,0,0,101108.85,1 +8735,15642530,Coates,706,Germany,Female,47,10,144090.42,1,1,0,140938.95,1 +8736,15713599,Castiglione,728,France,Male,30,10,114835.43,1,0,1,37662.49,0 +8737,15744770,Stone,636,France,Male,44,2,0,2,0,0,86414.41,0 +8738,15780498,Maynard,634,France,Male,34,3,145030.92,1,1,1,41820.65,0 +8739,15624397,Moore,627,France,Male,43,8,71240.3,1,0,1,127734.16,0 +8740,15615219,Obielumani,518,France,Male,59,5,138772.15,1,0,1,123872,0 +8741,15570908,Harding,687,Spain,Female,29,7,93617.07,1,0,1,113050.92,0 +8742,15762855,Hill,622,Spain,Female,23,8,0,2,1,1,131389.39,0 +8743,15661827,Brown,693,Spain,Female,45,4,0,2,1,1,26589.56,0 +8744,15746035,Pagnotto,450,Spain,Male,25,9,74237.2,2,0,1,195463.35,0 +8745,15691906,Esposito,664,Germany,Female,49,5,127421.78,2,1,0,108876.75,1 +8746,15793424,Tan,663,Spain,Female,28,8,61274.7,2,1,0,136054.45,0 +8747,15577905,Hammond,660,France,Male,34,8,106486.66,2,0,1,182262.66,0 +8748,15667216,Chung,579,France,Female,29,10,73194.52,2,1,1,129209.09,0 +8749,15673971,Houghton,655,Germany,Female,44,6,146498.76,1,1,0,64853.51,1 +8750,15701238,Chia,683,France,Male,47,1,0,2,1,0,148989.15,0 +8751,15644849,Zikoranachidimma,655,France,Female,32,2,0,1,1,1,71047.51,0 +8752,15635531,Boag,575,Spain,Female,30,8,0,2,1,0,185341.63,0 +8753,15632263,Pagnotto,574,Spain,Male,30,5,120355,1,1,0,137793.35,0 +8754,15720110,Oluchukwu,795,France,Male,32,2,117265.21,1,1,1,198317.23,0 +8755,15619045,Baxter,776,France,Female,43,4,0,2,0,1,162137.5,0 +8756,15697510,Tien,707,Spain,Female,52,7,0,1,1,0,109688.82,1 +8757,15784923,Chimezie,705,Germany,Female,37,3,109974.22,1,1,1,36320.87,1 +8758,15567383,Slone,678,Germany,Female,44,2,98009.13,2,0,1,31384.86,0 +8759,15732621,Martin,663,France,Male,34,10,0,1,1,1,114083.73,0 +8760,15757981,Loggia,748,France,Male,66,8,0,1,1,1,163331.65,0 +8761,15727819,Hartley,677,Spain,Female,34,10,171671.9,1,1,1,50777.77,0 +8762,15738088,Parkin,634,Spain,Male,63,10,0,2,1,0,30772.86,1 +8763,15765173,Lin,350,France,Female,60,3,0,1,0,0,113796.15,1 +8764,15665159,Brooks,727,France,Male,61,0,128213.96,2,1,1,188729.08,1 +8765,15618203,Tien,773,Germany,Male,51,8,116197.65,2,1,1,86701.4,0 +8766,15791452,Dann,675,France,Male,39,1,0,2,1,0,153129.22,0 +8767,15638159,Trentino,649,Spain,Female,36,6,86607.39,1,0,0,19825.09,0 +8768,15585466,Russo,552,France,Male,29,10,0,2,1,0,12186.83,0 +8769,15677310,Christie,761,Germany,Male,62,5,98854.34,1,0,0,86920.97,1 +8770,15646262,Ross,622,France,Male,31,7,0,1,1,0,35408.77,0 +8771,15656901,Nnonso,615,France,Male,59,8,0,2,1,1,165576.55,0 +8772,15621093,Teng,681,Germany,Male,31,4,97338.19,2,0,0,48226.76,0 +8773,15592123,Buccho,768,France,Male,30,6,0,2,1,1,199454.37,0 +8774,15589200,Madukaife,617,Spain,Male,34,9,0,2,1,0,118749.58,0 +8775,15602934,Dunn,452,France,Female,33,6,131698.57,2,1,0,151623.91,0 +8776,15812720,Hooker,807,Germany,Male,37,10,130110.45,2,0,1,172097.95,0 +8777,15695383,Griffin,567,Spain,Male,44,9,0,2,1,0,87677.15,0 +8778,15723064,Kistler,603,Spain,Male,24,1,165149.13,2,1,0,21858.28,0 +8779,15761606,Law,617,Spain,Female,37,9,101707.8,1,1,0,123866.28,0 +8780,15650322,Grigoryeva,701,France,Female,34,3,105588.66,1,0,1,74694.41,0 +8781,15669782,Chu,820,Germany,Male,39,9,111336.89,1,1,0,16770.31,1 +8782,15751628,Onyemachukwu,438,France,Male,60,7,78391.17,1,0,1,49424.6,0 +8783,15809057,Lu,600,Spain,Female,27,6,0,2,1,1,172031.22,0 +8784,15617052,Watson,782,France,Male,34,9,0,1,1,0,183021.06,1 +8785,15590810,Fallaci,638,Germany,Female,41,9,144326.09,1,1,0,73979.85,1 +8786,15801293,Ni,850,Germany,Male,27,1,101278.25,2,1,1,26265.18,0 +8787,15770968,Leason,741,Germany,Female,19,8,108711.57,2,1,0,24857.25,0 +8788,15572356,Tsai,689,Spain,Male,73,1,108555.07,1,0,1,167969.15,0 +8789,15603247,Bruner,743,Germany,Female,35,1,146781.24,1,1,0,189307.7,0 +8790,15619116,Wallace,493,France,Female,36,2,0,2,0,1,99770.3,0 +8791,15691792,Young,416,Spain,Male,35,8,0,1,0,0,119712.78,0 +8792,15783276,Forbes,725,France,Female,25,9,0,2,1,1,168607.74,0 +8793,15766137,Muir,497,France,Male,34,2,0,2,1,1,83087.13,0 +8794,15574554,Pugh,537,Germany,Male,66,8,103291.25,2,1,1,130664.79,0 +8795,15578671,Webb,706,Spain,Female,29,1,209490.21,1,1,1,133267.69,1 +8796,15716608,Walker,651,Spain,Male,38,2,0,3,1,0,67029.82,1 +8797,15690670,Cox,720,France,Male,33,2,0,2,0,1,141031.08,0 +8798,15630466,Maclean,797,France,Male,45,8,0,1,0,0,125110.02,0 +8799,15630349,Hollis,543,Spain,Male,23,5,0,2,1,0,117832.39,0 +8800,15803801,Jamieson,454,France,Male,34,4,0,2,1,0,198817.72,0 +8801,15647890,Su,691,France,Male,37,9,149405.18,1,1,1,146411.6,0 +8802,15606115,P'eng,510,France,Female,52,6,191665.21,1,1,1,131312.56,1 +8803,15714642,Hawkins,792,Spain,Female,40,7,0,1,1,0,141652.2,0 +8804,15741181,Ndubuagha,721,France,Male,41,6,135071.12,1,1,1,64477.25,0 +8805,15773973,Hill,765,France,Male,41,2,0,2,0,1,191215.61,0 +8806,15758546,Norton,850,Spain,Male,39,8,0,2,1,1,37090.44,0 +8807,15598940,Achebe,681,Germany,Male,38,6,181804.34,2,1,1,57517.71,0 +8808,15669783,Simpson,586,France,Female,60,3,47020.65,2,0,1,63241.21,1 +8809,15624993,Chiang,753,France,Female,36,7,128518.98,1,1,1,44567.83,1 +8810,15760568,Dalrymple,593,Germany,Female,38,5,142658.04,2,0,1,135337.11,0 +8811,15699047,Chukwuemeka,674,France,Female,21,9,120150.39,2,1,1,33964.03,0 +8812,15616168,Ojiofor,610,France,Female,35,7,81905.95,1,1,1,61623.19,0 +8813,15773146,Rubeo,652,France,Male,26,3,137998.2,2,0,1,168989.77,0 +8814,15770375,Fanucci,850,Germany,Female,26,8,123126.29,1,1,0,74425.41,0 +8815,15589725,Zubarev,740,France,Female,51,4,0,2,1,1,178929.84,0 +8816,15710034,T'ao,637,Germany,Male,43,1,135645.29,2,0,1,101382.86,1 +8817,15800806,Pai,685,Spain,Male,31,7,122449.31,2,1,1,180769.55,0 +8818,15570485,Udegbunam,558,Spain,Male,40,4,161766.87,1,0,0,92378.54,0 +8819,15575391,Claypool,677,France,Female,37,3,0,2,1,1,38252.25,0 +8820,15790750,Manfrin,592,Germany,Male,36,10,123187.51,1,0,1,146111.35,0 +8821,15714832,Baker,652,Germany,Male,36,9,150956.71,1,0,0,72350.17,0 +8822,15619953,Efremov,662,Spain,Female,42,6,105021.28,1,1,0,48242.38,0 +8823,15673929,Chin,543,France,Male,64,4,0,2,1,1,148305.82,0 +8824,15578835,Brookes,675,Spain,Female,50,1,133204.91,1,0,1,8270.06,0 +8825,15752388,Doyle,643,Spain,Female,35,6,0,2,1,1,41549.64,0 +8826,15797081,Ajuluchukwu,611,Germany,Female,49,9,115488.52,2,1,1,138656.81,1 +8827,15570194,Ikemefuna,412,France,Male,29,5,0,2,0,0,12510.53,0 +8828,15580149,Fowler,638,Spain,Male,41,7,0,2,1,0,43889.41,0 +8829,15777708,Liao,824,Spain,Female,38,3,0,2,1,0,192800.25,0 +8830,15769955,Onuora,683,France,Female,40,1,0,2,0,0,75762,0 +8831,15810444,Aksenov,562,Germany,Female,39,6,130565.02,1,1,0,9854.72,1 +8832,15645593,Trevisani,599,France,Female,41,2,91328.71,1,1,0,115724.78,0 +8833,15765345,Wood,753,France,Male,35,4,0,2,1,1,106303.4,0 +8834,15760873,Lombardo,594,France,Male,50,7,81310.34,1,1,1,183868.01,0 +8835,15794178,Walpole,657,France,Male,34,3,107136.6,1,1,0,153895.46,0 +8836,15589361,Chikwendu,716,Spain,Male,34,9,0,1,1,1,66695.71,0 +8837,15662483,Ko,850,France,Male,43,7,0,2,1,1,173851.11,0 +8838,15809736,Steigrad,664,France,Male,46,2,0,1,1,1,177423.02,1 +8839,15731148,Isayeva,558,France,Male,33,0,108477.49,1,1,1,109096.71,1 +8840,15774328,Boni,606,Germany,Male,40,1,144757.97,2,1,1,166656.18,0 +8841,15646969,Anayolisa,776,Spain,Male,33,2,0,2,1,1,176921,0 +8842,15718769,Fallaci,557,Spain,Male,36,1,113110.26,1,1,0,98413.1,0 +8843,15610226,Fenton,614,France,Female,27,9,106414.57,2,0,0,77500.81,0 +8844,15616270,Chao,620,Spain,Male,42,4,106920.91,1,0,1,119747.08,0 +8845,15790717,Osinachi,695,Spain,Male,35,7,0,2,1,0,160387.98,0 +8846,15635703,Chu,729,Germany,Female,39,1,131513.26,1,1,1,193715,0 +8847,15616365,Obiuto,571,France,Female,53,2,0,2,1,0,28045.77,0 +8848,15630244,Chu,457,France,Male,40,10,134320.23,2,1,0,150757.35,0 +8849,15734714,Nash,559,France,Female,29,3,79715.36,1,1,0,82252.28,0 +8850,15721433,Hixson,664,France,Female,38,4,74306.19,2,1,0,154395.56,0 +8851,15590201,Fiorentini,500,Spain,Female,50,5,0,4,1,1,83866.35,1 +8852,15590828,Chidimma,782,Germany,Male,42,7,126428.38,1,1,0,39830.1,0 +8853,15752097,Chiazagomekpere,708,Spain,Male,38,8,99640.89,1,1,0,12429.22,0 +8854,15800031,Laura,681,France,Male,43,3,66338.68,1,1,1,18772.5,1 +8855,15630857,Wu,674,Spain,Female,39,6,0,2,1,1,9574.83,0 +8856,15689953,Toscani,697,Spain,Male,43,10,128226.37,1,0,0,188486.94,0 +8857,15759733,McMillan,774,France,Female,26,5,0,2,1,1,64716.08,0 +8858,15810826,Chiekwugo,624,France,Male,36,6,0,2,0,0,84749.96,0 +8859,15668009,Hendley,747,Spain,Male,37,1,0,2,0,1,180551.76,0 +8860,15743456,Birnie,715,France,Female,32,10,0,2,1,0,60907.49,0 +8861,15725762,Kemp,808,France,Male,24,4,122168.65,1,1,0,174107.04,0 +8862,15761713,Johnstone,678,France,Female,43,7,178074.33,1,0,0,110405.9,0 +8863,15769246,Lo Duca,813,Germany,Male,59,2,135078.41,1,1,0,187636.06,1 +8864,15781129,Montgomery,687,Spain,Male,38,8,69434.4,2,1,1,66580.13,1 +8865,15599124,Miller,832,France,Female,29,5,0,2,1,0,178779.52,0 +8866,15639004,Chiemezie,668,France,Male,72,2,0,2,1,1,70783.61,0 +8867,15810995,Wright,526,Germany,Male,34,3,122726.56,1,1,1,46772.36,0 +8868,15653773,Shaw,457,France,Female,38,7,164496.99,1,1,1,163327.27,0 +8869,15708357,Chapman,649,Spain,Female,38,8,0,1,1,0,103760.53,0 +8870,15733597,Y?an,669,France,Female,41,0,150219.41,2,0,0,107839.03,0 +8871,15789560,Clark,668,France,Male,42,8,187534.79,1,1,1,32900.41,1 +8872,15699524,Howells,466,France,Female,30,3,0,1,1,0,193984.6,0 +8873,15626475,Gamble,685,France,Male,30,2,0,2,1,1,140889.32,0 +8874,15810839,Rogers,610,France,Male,34,0,103108.17,1,0,0,125646.82,0 +8875,15684318,McMillan,582,Germany,Female,50,6,96486.57,2,1,1,20344.02,0 +8876,15768120,Brown,702,Germany,Male,36,9,90560.48,2,1,0,174268.87,0 +8877,15712807,Robertson,556,Spain,Male,46,3,131764.96,1,1,1,108500.66,1 +8878,15696371,Thomas,812,Spain,Female,24,1,92476.88,1,0,0,83247.14,0 +8879,15675794,Hsing,645,Germany,Male,47,9,152076.93,1,1,0,121840.2,1 +8880,15774277,Chiu,809,France,Male,43,2,0,2,1,1,132908.07,0 +8881,15603764,Chang,560,France,Male,49,4,0,1,1,1,100075.1,1 +8882,15618647,Kornilova,744,France,Male,29,1,43504.42,1,1,1,119327.75,0 +8883,15614643,Chifo,731,Spain,Female,39,2,0,2,1,0,136737.13,0 +8884,15707696,Lu,471,Spain,Female,28,5,0,2,1,1,22356.97,0 +8885,15749583,Bellucci,686,Germany,Female,38,2,93569.86,3,0,0,10137.34,1 +8886,15815125,Michael,668,Spain,Male,45,4,102486.21,2,1,1,158379.25,0 +8887,15779620,Sinclair,575,France,Male,36,1,0,1,0,1,94570.56,0 +8888,15768233,Chukwuebuka,435,Germany,Male,37,8,114346.3,1,0,1,980.93,1 +8889,15637788,Schmidt,743,France,Male,23,3,110203.77,1,1,0,95583.45,0 +8890,15777046,Parry,580,France,Female,39,9,128362.59,1,1,0,86044.98,0 +8891,15788723,McIntyre,599,Germany,Female,49,10,143888.22,2,1,1,166236.38,1 +8892,15790489,Lo Duca,534,Spain,Male,34,5,170600.78,1,0,1,5240.53,0 +8893,15739476,Ferrari,680,France,Female,32,5,0,1,1,1,150684.23,0 +8894,15612670,Berry,631,Spain,Female,46,10,0,2,1,1,129508.96,0 +8895,15631222,Cattaneo,485,France,Female,39,2,75339.64,1,1,1,70665.16,0 +8896,15658972,Foster,699,France,Female,40,8,122038.34,1,1,0,102085.35,0 +8897,15724691,Gordon,712,France,Male,34,1,0,2,1,1,195052.12,0 +8898,15740442,May,603,France,Male,51,8,186825.57,1,1,0,93739.71,1 +8899,15760427,Cameron,850,France,Male,40,6,124788.18,1,1,0,65612.12,0 +8900,15677939,Ch'eng,584,France,Female,41,3,0,2,1,1,160095.48,0 +8901,15611599,Curtis,604,France,Female,71,2,0,2,1,1,49506.82,0 +8902,15633474,Whitehead,586,France,Male,51,2,138553.57,1,1,1,92406.22,0 +8903,15671973,Chukwuemeka,467,Spain,Male,39,5,0,2,1,1,7415.96,0 +8904,15790019,Onwughara,520,France,Male,35,9,105387.89,1,1,1,25059.06,0 +8905,15737735,Grant,683,Spain,Male,40,4,95053.1,1,1,1,116816.54,1 +8906,15661745,Browne,557,France,Male,36,3,0,1,0,1,144078.02,0 +8907,15797065,Goloubev,613,Spain,Female,32,0,0,2,0,1,126675.62,0 +8908,15710671,Gordon,786,France,Male,34,3,137361.96,1,0,0,183682.09,0 +8909,15656522,Sutherland,593,Spain,Male,32,10,158537.42,1,1,0,166850.57,0 +8910,15705085,Quesada,670,Spain,Female,29,9,0,2,1,0,27359.19,0 +8911,15744873,Wright,657,Germany,Female,48,5,143595.87,1,0,0,101314.65,1 +8912,15781914,Simmons,718,Germany,Male,32,9,169947.41,2,1,1,27979.16,0 +8913,15637354,Yobachukwu,623,France,Female,24,7,148167.83,2,1,1,109470.34,0 +8914,15717307,Read,496,France,Male,31,5,0,2,1,0,93713.13,0 +8915,15746695,Wunder,429,France,Female,39,6,48023.83,1,1,0,74870.99,0 +8916,15804962,Nnaife,606,France,Male,36,1,155655.46,1,1,1,192387.51,1 +8917,15665378,Shen,499,France,Female,46,6,0,2,1,0,73457.55,0 +8918,15757865,Powell,642,France,Male,62,7,0,2,1,1,61120.75,0 +8919,15578787,Goddard,641,France,Female,52,4,0,1,1,0,90964.54,1 +8920,15794323,Buckley,673,France,Male,32,8,121240.76,1,1,0,116969.73,0 +8921,15697546,McIntyre,570,France,Female,36,3,0,2,1,0,92118.75,0 +8922,15629519,Yen,472,France,Female,37,1,0,2,1,1,48357.9,0 +8923,15624703,Okonkwo,550,Germany,Male,35,9,129847.75,2,1,0,197325.4,0 +8924,15570002,Burlingame,625,Germany,Female,55,8,118772.71,4,0,0,135853.62,1 +8925,15808566,Hs?,516,France,Male,46,2,0,2,1,1,169122.54,0 +8926,15805463,Board,682,Germany,Male,32,2,105163.88,2,1,1,164170.46,0 +8927,15709136,Adams,620,France,Male,28,8,0,2,1,1,199909.32,0 +8928,15801605,Rizzo,626,France,Female,39,0,0,2,1,1,83295.09,0 +8929,15567855,Chukwufumnanya,623,France,Female,29,1,0,2,0,0,39382.06,0 +8930,15675141,Fraser,569,France,Female,35,4,93934.63,1,1,0,184748.23,0 +8931,15665759,Russell,724,France,Female,69,5,117866.92,1,1,1,62280.91,0 +8932,15761487,Yefimova,678,France,Female,55,5,0,1,0,1,196794.11,1 +8933,15700394,Palermo,713,Spain,Female,26,4,122857.46,2,1,0,144682.17,1 +8934,15631162,Bergamaschi,631,France,Male,32,10,0,2,0,1,196342.66,0 +8935,15630641,Shao,846,France,Female,37,6,127103.97,1,1,1,41516.44,0 +8936,15585066,Chimaraoke,660,France,Female,43,1,0,1,0,1,112026.1,1 +8937,15722991,McGregor,567,France,Male,54,9,96402.96,1,0,0,52035.29,1 +8938,15737404,Kesteven,731,France,Male,31,1,132512.26,1,1,1,185466.85,0 +8939,15722409,Ritchie,693,Spain,Male,47,8,107604.66,1,1,1,80149.27,0 +8940,15806420,Jenks,772,France,Male,34,9,0,2,1,0,170980.86,0 +8941,15658148,Udokamma,657,France,Male,38,7,0,2,1,0,185827.74,0 +8942,15810660,Boyle,774,Germany,Male,34,4,120875.23,2,0,1,113407.26,0 +8943,15709780,Azuka,667,France,Female,37,9,71786.9,2,1,1,67734.79,0 +8944,15727350,Pai,516,France,Female,37,8,113143.12,1,0,0,3363.36,0 +8945,15752312,Howells,551,Spain,Male,49,1,150777.72,2,1,1,135757.27,0 +8946,15616745,Hs?,542,Spain,Male,35,2,174894.53,1,1,1,22314.55,0 +8947,15572294,Kelly,623,France,Male,28,7,0,1,0,0,129526.57,0 +8948,15674110,Walton,701,France,Female,43,2,160416.56,1,0,1,37266.43,0 +8949,15662501,Ebelechukwu,583,France,Male,48,3,91246.53,1,1,0,60017.46,1 +8950,15649239,Vasilieva,731,Spain,Male,46,10,0,2,1,0,153015.42,0 +8951,15700424,Hsiao,461,France,Female,35,5,0,1,1,1,54209.02,0 +8952,15636388,Abrego,702,Germany,Female,23,7,98775.23,1,1,0,114603.96,0 +8953,15713975,Gibson,565,Germany,Female,47,10,139756.12,1,1,0,165849.49,1 +8954,15592925,Giordano,711,Spain,Male,42,3,177626.77,3,0,1,16392.72,1 +8955,15581626,Mancini,664,France,Male,54,8,0,1,1,1,162719.69,1 +8956,15641319,Afanasyeva,518,Spain,Male,50,4,0,1,0,0,107112.25,1 +8957,15723481,Wright,728,Spain,Male,42,8,0,2,0,1,41823.22,0 +8958,15787825,Okwudiliolisa,585,Germany,Male,37,6,152496.82,1,1,1,99907.29,0 +8959,15710726,Hughes,573,France,Male,52,8,0,2,0,1,178229.04,0 +8960,15627195,Parrott,568,Germany,Male,26,1,112930.28,2,1,0,22095.73,0 +8961,15657957,Hughes,602,Germany,Female,26,8,113674.2,1,1,0,197861.16,1 +8962,15676117,Zinachukwudi,603,France,Male,44,9,0,1,1,0,138328.24,0 +8963,15607874,Keane,687,France,Male,38,0,144450.58,1,0,1,137276.83,0 +8964,15796993,McCollum,741,France,Male,52,1,171236.3,2,0,0,21834.4,1 +8965,15649858,Simpson,469,Spain,Male,37,9,96776.49,1,1,1,119890.86,0 +8966,15811032,Gambrell,477,Germany,Female,58,8,145984.92,1,1,1,24564.7,0 +8967,15679963,Moretti,737,Germany,Male,43,8,96353.8,1,0,0,10209.8,0 +8968,15579131,Ricci,835,France,Male,25,7,0,2,1,1,83449.65,0 +8969,15572428,Rieke,717,Germany,Female,33,0,115777.23,1,1,1,81508.1,0 +8970,15622461,Ndubuagha,562,France,Female,51,7,122822,2,0,0,32626.21,0 +8971,15636105,Chung,758,Spain,Male,61,2,0,2,1,1,43982.41,0 +8972,15583849,Ts'ai,408,France,Male,40,3,0,2,0,0,124874.23,0 +8973,15718780,Cox,650,Spain,Female,32,4,79450.09,1,1,1,118324.75,0 +8974,15739271,Lei,582,Germany,Male,33,2,122394,1,1,1,22113.93,0 +8975,15697129,Ulyanova,706,Spain,Female,43,1,0,2,1,0,31962.77,0 +8976,15763415,Gray,567,Germany,Male,41,0,134378.89,1,1,1,105746.94,0 +8977,15796617,McGregor,720,France,Male,29,2,0,2,1,0,39925.52,0 +8978,15626628,Tretiakova,631,Spain,Female,31,2,88161.85,2,1,0,127630.88,0 +8979,15765857,Genovesi,623,Spain,Male,41,2,142412.13,1,1,0,28778.98,0 +8980,15742511,Gordon,514,France,Male,35,3,121030.9,1,1,0,10008.68,0 +8981,15786433,Aitken,650,Germany,Female,35,3,165982.43,2,1,1,24482.16,0 +8982,15685805,Ginikanwa,673,Spain,Female,35,6,0,2,1,0,98618.79,0 +8983,15627971,Coates,504,France,Female,32,8,206663.75,1,0,0,16281.94,0 +8984,15783025,Piazza,723,Germany,Male,37,3,94661.53,2,1,0,121239.65,0 +8985,15726289,Cawood,645,France,Male,25,0,174400.36,1,1,0,42669.37,0 +8986,15802118,Ignatieff,664,Spain,Male,41,7,123428.69,1,1,1,164924.11,0 +8987,15607990,Gallo,760,Spain,Male,43,6,175735.5,1,1,1,157337.29,0 +8988,15695932,Yelverton,766,Spain,Male,36,5,78381.13,1,0,1,153831.6,0 +8989,15812279,William,634,France,Male,37,5,115345.86,2,0,0,168781.8,0 +8990,15687558,Mault,640,Germany,Female,31,10,118613.34,1,1,0,168469.65,0 +8991,15729065,Mackay,784,Germany,Male,28,2,109960.06,2,1,1,170829.87,0 +8992,15698902,McIntyre,547,Germany,Female,42,1,142703.4,1,1,0,86207.49,1 +8993,15570192,Henry,608,Germany,Female,40,8,121729.42,1,0,0,61164.45,0 +8994,15809265,Kao,547,France,Female,35,4,0,1,1,1,133287.73,0 +8995,15745201,Frewin,612,France,Female,43,4,139496.35,2,1,1,77128.23,0 +8996,15580623,Yefremova,573,Spain,Male,28,8,0,2,0,0,77660.03,0 +8997,15578156,Anenechukwu,615,Spain,Male,32,5,138521.83,1,1,1,56897.1,0 +8998,15631063,Trentino,710,France,Female,33,2,0,2,1,0,72945.32,0 +8999,15692577,Tomlinson,674,Germany,Female,38,10,83727.68,1,1,0,45418.12,0 +9000,15810910,Royston,702,Spain,Female,38,9,0,2,1,1,158527.45,0 +9001,15723217,Cremonesi,616,France,Male,37,9,0,1,1,0,111312.96,0 +9002,15733111,Yeh,688,Spain,Male,32,6,124179.3,1,1,1,138759.15,0 +9003,15610727,Ch'in,605,France,Male,36,7,128829.25,1,1,0,190588.59,0 +9004,15792720,Martinez,676,France,Male,33,6,171490.78,1,0,0,79099.64,0 +9005,15723153,Wearing,708,Spain,Male,33,3,0,2,1,0,138613.21,0 +9006,15802823,Maclean,745,Spain,Female,38,7,0,2,1,1,194230.82,0 +9007,15756118,T'ao,661,Spain,Male,20,8,0,1,1,0,110252.53,0 +9008,15684934,Rose,726,France,Male,31,9,0,2,1,1,106117.3,0 +9009,15776936,Whitworth,475,France,Male,40,7,160818.08,1,0,1,169642.13,1 +9010,15729087,Suttor,751,Germany,Male,54,9,156367.6,2,0,1,116179.92,0 +9011,15786463,Hsing,645,Germany,Female,59,8,121669.93,2,0,0,91.75,1 +9012,15717498,Boni,775,France,Male,42,6,133970.22,2,0,1,187839.9,0 +9013,15718406,Marshall,540,France,Male,41,3,0,2,1,0,121098.65,0 +9014,15799468,Catchpole,591,France,Female,34,3,96127.27,1,0,0,30972.06,0 +9015,15626383,Tang,596,Spain,Male,60,7,121907.97,1,0,1,30314.04,0 +9016,15597385,Siddons,573,Spain,Male,41,5,0,2,0,1,14479.29,0 +9017,15570271,Wan,577,Spain,Male,31,6,0,1,1,1,196395.25,0 +9018,15690330,Efimov,830,Germany,Female,40,8,77701.64,1,0,1,19512.38,0 +9019,15680611,Rose,663,France,Male,67,9,0,3,1,1,72318.77,0 +9020,15810227,Fanucci,421,France,Male,34,2,0,2,1,1,96615.23,0 +9021,15807194,Iweobiegbulam,718,Spain,Male,34,5,113922.44,2,1,0,30772.22,0 +9022,15712199,Ijendu,655,Germany,Female,61,2,183997.7,2,1,1,161217.18,0 +9023,15694995,O'Sullivan,712,France,Male,23,2,0,2,0,1,66795.78,0 +9024,15723400,Hutchinson,663,France,Male,28,4,0,2,1,1,123969.64,0 +9025,15654772,Kwemto,640,France,Female,47,6,89799.46,2,0,1,13783.77,1 +9026,15574743,Chiu,577,Spain,Male,29,2,0,1,1,1,168924.41,0 +9027,15807593,Berry,546,Spain,Female,36,7,85660.96,1,0,0,134778.01,0 +9028,15686718,Hung,802,Germany,Male,37,9,115569.21,1,0,1,119782.89,0 +9029,15695299,Mordvinova,590,France,Female,45,2,81828.22,1,1,0,52167.97,0 +9030,15722701,Bruno,594,Germany,Male,18,1,132694.73,1,1,0,167689.56,0 +9031,15799635,Arbour,577,Spain,Male,51,2,108867,1,0,0,140800.66,1 +9032,15742323,Barese,541,France,Male,39,7,0,2,1,0,19823.02,0 +9033,15658435,Hingston,781,France,Female,27,5,0,2,0,0,72969.9,0 +9034,15586029,Davis,806,Germany,Male,34,2,96152.68,2,1,0,143711.02,0 +9035,15772337,Lawrence,723,Germany,Female,49,0,153855.52,1,1,1,180862.26,1 +9036,15807555,Chung,535,France,Male,45,2,0,2,1,0,125658.28,0 +9037,15603378,Padovano,768,France,Female,36,3,141334.95,1,0,1,125870.5,0 +9038,15792862,Blinova,653,Germany,Male,41,1,104584.11,1,1,0,15126.32,1 +9039,15657349,Carter,803,Germany,Female,50,8,98173.02,1,0,0,22457.25,1 +9040,15777614,Webb,545,Spain,Female,44,1,0,2,1,1,82614.89,0 +9041,15653952,T'an,581,Germany,Female,38,3,135157.05,1,1,1,32919.42,0 +9042,15724336,Yates,513,Germany,Female,49,5,171601.27,1,1,0,126223.84,0 +9043,15689594,Su,731,France,Male,29,5,179539.2,1,0,0,112010.02,0 +9044,15801920,Christian,727,Germany,Male,39,5,80615.46,2,0,0,180962.32,0 +9045,15653347,Chiu,560,Spain,Male,47,1,0,1,0,0,128882.66,1 +9046,15749951,Sacco,766,Germany,Male,27,5,126285.73,1,1,0,177614.17,1 +9047,15648178,Lettiere,630,Germany,Female,23,4,137964.51,1,0,1,174570.55,0 +9048,15738662,Daluchi,652,Germany,Male,41,9,159434.03,1,1,0,178373.93,0 +9049,15640855,T'ien,729,Germany,Male,40,5,113574.61,2,1,0,103396.08,0 +9050,15584288,Hung,629,France,Female,33,6,0,2,1,1,59129.72,0 +9051,15760988,Liu,667,Germany,Male,33,9,124573.33,2,0,0,683.37,0 +9052,15569624,Feng,671,Germany,Female,31,6,105864.6,2,1,0,145567.34,0 +9053,15597949,Gilbert,768,Germany,Female,47,5,104552.61,1,1,0,48137.08,1 +9054,15604551,Robb,732,France,Female,35,3,0,2,1,0,90876.95,0 +9055,15617476,Manfrin,546,France,Female,30,5,0,2,0,1,198543.09,0 +9056,15645323,Chinwenma,630,France,Male,55,2,0,1,1,1,106202.07,1 +9057,15793311,Smith,765,Germany,Female,46,8,119492.88,2,0,1,166896.01,1 +9058,15764153,Rowe,704,France,Female,33,0,130499.09,2,1,1,74804.36,0 +9059,15802560,Moran,470,Spain,Female,48,6,140576.11,1,1,1,116971.05,0 +9060,15728608,Walker,688,Germany,Female,34,9,91025.58,2,0,1,163783,0 +9061,15770474,Myers,685,France,Female,33,1,0,3,0,1,70221.13,1 +9062,15724444,Wall,567,France,Female,38,1,125877.65,2,1,1,107841.77,0 +9063,15753110,McKay,720,Spain,Male,64,3,45752.78,2,1,0,79623.28,1 +9064,15711521,Egobudike,609,France,Male,39,3,121778.71,1,1,1,138399.67,0 +9065,15632816,Williams,521,Germany,Female,49,2,127948.57,1,1,1,182765.14,0 +9066,15693637,Ochoa,556,France,Female,30,7,0,2,1,1,186648.19,0 +9067,15725509,Otutodilinna,662,Germany,Male,30,5,115286.68,2,1,1,149587.92,0 +9068,15684645,Ajuluchukwu,704,Germany,Male,41,9,62078.21,2,1,0,129050.67,0 +9069,15692235,Bellucci,750,France,Female,38,1,0,2,1,0,47764.99,0 +9070,15777459,Gordon,619,Spain,Female,32,4,175406.13,2,1,1,172792.43,1 +9071,15656937,Johnston,468,Spain,Male,26,1,131643.25,1,1,0,64436.16,0 +9072,15610643,De Luca,435,Germany,Male,44,3,151739.65,1,1,0,167461.5,0 +9073,15777315,Hill,529,France,Male,43,6,93616.35,2,0,0,98348.66,0 +9074,15611058,Eluemuno,702,Germany,Female,60,5,138597.54,2,1,1,41536.59,1 +9075,15630413,Howarth,608,France,Female,41,5,0,2,1,1,72462.25,0 +9076,15635942,Thomson,576,France,Male,40,9,0,2,1,0,112465.19,1 +9077,15648858,King,666,France,Female,27,1,85225.21,1,0,1,64511.44,0 +9078,15810732,Grant,730,France,Female,36,8,148749.29,2,1,0,91830.75,0 +9079,15705448,Gilbert,647,Germany,Male,52,7,130013.12,1,1,1,190806.36,1 +9080,15730488,Richmond,516,Spain,Female,27,1,0,1,0,1,112311.15,0 +9081,15620443,Fiorentino,711,France,Female,81,6,0,2,1,1,72276.24,0 +9082,15741078,Greece,736,France,Male,54,7,111729.47,2,0,1,84920.49,0 +9083,15753161,Dickson,768,France,Female,36,5,180169.44,2,1,0,17348.56,0 +9084,15711396,Henderson,427,Spain,Male,40,8,0,2,1,1,82870.75,0 +9085,15593499,Stevens,686,Spain,Female,47,6,0,1,1,0,32080.69,1 +9086,15579189,Mitchell,690,France,Female,42,5,0,2,0,1,120512.08,0 +9087,15743545,Nworie,647,Spain,Female,29,2,0,2,1,0,179032.68,0 +9088,15791316,Boni,714,France,Male,35,3,0,2,1,1,95623.28,0 +9089,15608246,Wentcher,736,Germany,Female,36,8,103914.17,1,1,1,110035.88,1 +9090,15676526,Bentley,608,France,Female,34,4,88772.87,1,1,1,168822.01,0 +9091,15813911,Hayes-Williams,809,France,Female,39,5,0,1,1,0,77705.75,0 +9092,15630195,Johnstone,745,France,Female,40,6,131184.67,1,1,1,49815.62,0 +9093,15736250,Johnstone,781,France,Male,38,2,117810.79,1,0,1,65632.33,1 +9094,15671334,Nixon,527,France,Male,31,4,0,1,1,0,169361.89,0 +9095,15574169,Trevisano,595,Germany,Female,32,0,92466.21,1,1,0,4721.3,0 +9096,15718839,Tsui,850,Germany,Female,38,2,102741.15,2,0,1,23974.85,0 +9097,15762331,Moss,569,France,Male,37,9,178755.84,1,1,0,199929.17,0 +9098,15606901,Graham,728,France,Male,43,7,0,2,1,0,40023.7,0 +9099,15713559,Onyemauchechukwu,473,Germany,Female,32,5,146602.25,2,1,1,72946.95,0 +9100,15768881,Saunders,738,France,Male,29,2,0,2,1,1,170421.13,0 +9101,15743075,Ko,659,France,Male,35,6,0,2,1,1,58879.11,0 +9102,15660980,Cairns,597,Spain,Male,38,6,115702.67,2,1,1,25059.05,0 +9103,15810942,Chiemela,445,Germany,Female,61,2,137655.31,1,0,1,29909.84,0 +9104,15728362,Robertson,671,France,Female,29,3,0,2,1,0,158043.11,0 +9105,15683339,P'eng,656,Spain,Female,34,6,59877.33,1,1,0,14032.62,1 +9106,15685476,Tseng,658,France,Male,31,5,100082.14,1,0,1,49809.88,0 +9107,15663650,Russell,698,Germany,Male,52,10,107304.39,3,1,0,28806.32,1 +9108,15617434,Yen,655,Spain,Male,38,9,0,1,0,1,90490.33,0 +9109,15622470,Yeh,772,Spain,Male,41,10,96032.22,1,1,1,75825.57,0 +9110,15703682,Kalinina,681,Spain,Male,33,10,0,1,0,0,158336.36,0 +9111,15727391,Collier,688,Germany,Male,29,9,144553.5,2,1,0,143454.95,0 +9112,15711062,Thomas,633,Germany,Male,40,5,86172.81,2,1,1,117279.49,0 +9113,15567339,Shaw,735,France,Male,73,9,0,1,1,1,114283.33,0 +9114,15760662,Francis,521,Germany,Female,29,2,87212.8,1,1,1,994.86,0 +9115,15605737,George,541,France,Male,36,5,0,2,1,0,124795.84,0 +9116,15692977,Ikenna,612,Germany,Female,36,2,130700.92,2,0,0,77592.8,0 +9117,15672082,Schatz,562,France,Male,62,3,0,2,1,0,105986.01,0 +9118,15600280,Tao,703,France,Female,32,6,0,2,0,0,33606.52,0 +9119,15804052,Scott,710,Spain,Male,23,6,0,2,1,1,134188.11,0 +9120,15576065,Sims,731,Spain,Female,40,5,171325.98,1,1,1,159718.27,1 +9121,15796838,Chibugo,703,Spain,Male,58,4,92930.92,1,0,1,85148.78,0 +9122,15693526,Ku,618,France,Female,40,0,0,1,1,0,119059.13,0 +9123,15748595,Stanton,689,France,Female,29,1,77556.79,2,1,1,122998.26,0 +9124,15679029,Kung,718,France,Male,33,7,102874.28,1,0,0,117841.06,0 +9125,15753639,Gibson,608,France,Male,37,5,146093.39,2,0,0,160593.41,0 +9126,15604138,Iheanacho,749,Spain,Male,34,2,0,1,0,0,174189.04,1 +9127,15666095,Costa,753,Spain,Male,51,4,79811.72,2,0,1,68260.27,1 +9128,15643487,Sal,630,Spain,Male,39,10,105473.74,1,0,0,58854.88,1 +9129,15764033,Lin,693,Germany,Female,43,1,121927.92,1,1,0,87994.95,1 +9130,15747288,Ferri,838,Spain,Female,40,6,61671.19,1,0,1,150659.35,1 +9131,15790599,Yin,756,Germany,Female,39,5,149363.12,2,1,1,109098.39,0 +9132,15737705,Avdeyeva,775,France,Female,27,4,152309.37,1,1,0,104112,0 +9133,15737194,Tu,635,France,Female,33,5,0,2,1,0,122949.71,0 +9134,15726776,Donnelly,705,Spain,Male,36,1,111629.29,1,1,1,21807.16,0 +9135,15804357,Loggia,481,France,Male,40,3,0,1,1,1,32319.93,0 +9136,15664432,Chao,727,Spain,Female,49,7,96296.78,1,1,0,190457.87,1 +9137,15688984,Belonwu,595,France,Male,20,4,95830.43,1,1,0,177738.98,0 +9138,15583026,Welch,535,France,Female,38,0,135919.33,1,1,0,80425.65,0 +9139,15771668,Henderson,578,France,Male,59,10,185966.64,1,0,0,9445.42,1 +9140,15779904,Yobanna,597,France,Female,29,5,0,2,1,1,174825.57,0 +9141,15784323,Gallo,449,France,Female,21,7,0,2,0,0,175743.92,0 +9142,15756277,Wilson,850,Germany,Female,43,8,92244.83,2,1,0,54949.73,0 +9143,15663312,Marino,494,France,Female,35,9,112727.06,2,1,0,183752.91,0 +9144,15793197,Bailey,676,France,Female,34,8,100359.54,1,0,0,46038.28,0 +9145,15731463,Gboliwe,818,Germany,Male,43,10,105301.5,1,1,1,78941.59,0 +9146,15621768,Chukwuhaenye,712,Spain,Male,45,6,112994.65,1,0,0,198398.68,0 +9147,15691323,Bianchi,672,Germany,Male,40,4,89025.88,2,1,0,188892.19,0 +9148,15781326,Ford,636,France,Male,35,9,95478.17,1,0,0,169286.74,0 +9149,15595640,Rizzo,698,France,Male,37,8,0,2,0,0,145004.39,0 +9150,15814331,Lung,597,Germany,Female,43,7,119127.46,2,1,0,55809.92,0 +9151,15602030,Ramirez,717,France,Male,28,4,128206.79,1,1,1,54272.12,0 +9152,15747974,Sabbatini,614,France,Male,49,1,0,2,1,0,192440.54,0 +9153,15611315,Ts'ao,708,Germany,Female,23,4,71433.08,1,1,0,103697.57,0 +9154,15636977,Trevisan,507,Germany,Male,36,9,118214.32,3,1,0,119110.03,1 +9155,15690337,Chinwenma,581,France,Female,27,5,102258.11,2,1,0,194681.6,0 +9156,15680666,Berry,579,Spain,Female,39,2,151963.26,2,1,0,158948.63,0 +9157,15679551,Colombo,504,Spain,Female,46,2,163764.84,1,1,1,165122.55,1 +9158,15778915,Harris,737,France,Female,32,7,128551.36,2,0,1,189402.71,0 +9159,15568849,Bryan,540,Spain,Female,31,10,118158.74,1,1,1,158027.57,0 +9160,15747762,Chigozie,609,France,Male,32,7,118520.41,1,0,0,3815.48,0 +9161,15753679,Mullawirraburka,778,France,Male,24,4,0,2,1,1,162809.2,0 +9162,15750049,Steele,621,France,Male,40,10,163823.37,1,0,0,89519.47,0 +9163,15606097,Zakharov,665,Germany,Male,63,7,104469.58,1,1,1,25165.36,1 +9164,15802368,Ch'eng,608,France,Female,47,6,0,1,1,1,126012.57,0 +9165,15767488,Berry,680,Spain,Male,36,7,0,2,1,0,20109.21,0 +9166,15669946,Jen,663,Germany,Female,46,2,141726.88,1,1,1,58257.23,0 +9167,15612103,Wang,627,Germany,Female,35,2,137852.96,1,1,1,172269.21,1 +9168,15645353,Chubb,607,France,Male,26,1,0,1,1,0,29818.2,0 +9169,15650018,Chen,681,France,Female,43,8,154100.3,1,0,0,114659.81,0 +9170,15659002,Mazzanti,766,France,Female,45,6,0,2,0,0,147184.74,0 +9171,15616028,T'ao,694,France,Male,30,2,0,3,0,1,15039.41,0 +9172,15660475,Ndubueze,411,France,Female,54,9,0,1,0,1,76621.49,0 +9173,15652615,Ferri,742,France,Male,39,8,140004.96,1,1,1,92985.78,0 +9174,15653572,Thornton,673,Spain,Male,43,8,127132.96,1,0,1,6009.27,1 +9175,15628059,DeRose,529,France,Male,61,1,0,2,1,1,191370.97,0 +9176,15703413,Montes,519,France,Female,38,7,125328.56,1,1,0,188225.67,0 +9177,15610433,Kwemto,573,France,Male,35,9,0,2,1,0,11743.89,0 +9178,15770548,Lucchese,453,Germany,Female,28,3,139986.65,1,1,0,136846.75,0 +9179,15645637,Huggins,798,Germany,Female,39,6,119787.76,1,1,1,164248.33,0 +9180,15590888,Wade,693,Spain,Female,34,10,107556.06,2,0,0,154631.35,0 +9181,15568326,Kenenna,637,France,Female,44,2,0,2,1,0,149665.65,0 +9182,15655368,Wheeler,672,France,Male,47,1,0,1,0,0,91574.92,0 +9183,15665579,Cartwright,597,France,Female,28,0,142705.95,1,1,0,127233.39,0 +9184,15676091,Iloerika,543,France,Male,42,7,0,1,1,1,56650.47,0 +9185,15716984,Palermo,695,Spain,Female,56,4,0,2,1,0,84644.76,0 +9186,15715078,Nkemakolam,584,France,Male,35,6,161613.94,2,1,1,148238.16,0 +9187,15569452,Butler,652,Germany,Female,58,3,116353.2,2,0,1,193502.9,0 +9188,15628863,Calabresi,601,France,Male,38,4,60013.81,1,1,1,38020.05,0 +9189,15778192,Nkemdilim,628,Spain,Male,28,4,0,2,1,1,176750.81,0 +9190,15793723,Ch'iu,607,Germany,Male,32,9,144272.07,2,1,0,176580.63,0 +9191,15798943,Alexander,646,France,Female,46,8,0,2,1,0,133059.15,0 +9192,15764708,Chiabuotu,572,France,Male,30,6,117696.67,1,1,0,100843.82,0 +9193,15791040,Vasilyeva,801,Spain,Male,58,1,79954.61,2,1,1,30484.19,0 +9194,15631512,Schneider,597,France,Female,26,8,149989.39,1,1,0,42330.58,0 +9195,15640106,Mason,613,France,Male,40,7,124339.9,1,0,0,193309.58,0 +9196,15710315,Chukwukadibia,529,Germany,Male,29,4,135759.4,1,0,0,112813.79,1 +9197,15771535,Tsui,794,Spain,Female,37,9,0,2,1,0,68008.85,0 +9198,15611947,Banks,557,France,Male,34,3,83074,1,1,0,132673.22,0 +9199,15670266,Shih,499,France,Female,28,4,141792.61,1,1,1,22001.91,0 +9200,15609083,Tretiakova,544,France,Female,26,6,0,1,1,0,100200.4,1 +9201,15567923,Barese,739,France,Female,30,6,0,1,0,0,122604.44,0 +9202,15788183,Longo,458,Germany,Female,43,1,106870.12,2,1,0,100564.37,0 +9203,15735782,MacDonald,528,France,Male,31,9,120962.59,1,1,0,5419.31,0 +9204,15774401,Chambers,773,Spain,Male,51,4,0,2,0,0,123587.83,1 +9205,15737971,Cowen,646,France,Female,30,5,0,2,1,0,13935.32,0 +9206,15758750,Iweobiegbunam,564,France,Male,31,0,110527.17,1,1,1,87060.77,0 +9207,15611767,Mai,624,Germany,Female,52,0,133723.43,1,0,0,4859.59,1 +9208,15643770,Yu,682,France,Female,52,5,112670.48,1,1,0,21085.17,1 +9209,15744717,Duffy,726,France,Female,44,2,0,2,1,1,26733.86,0 +9210,15570681,Chiang,560,France,Male,24,1,116084.32,1,1,0,89734.7,0 +9211,15792650,Watts,382,Spain,Male,36,0,0,1,1,1,179540.73,1 +9212,15605531,Daly,457,Spain,Female,38,6,0,2,1,0,173219.09,0 +9213,15605339,Baker,673,France,Female,37,10,0,2,1,1,37411.35,0 +9214,15672216,Uvarov,584,France,Female,40,4,82441.75,1,0,0,80852.11,0 +9215,15812893,Costa,629,France,Female,39,10,0,2,1,1,43174.49,1 +9216,15624180,Genovesi,584,Germany,Female,37,10,134171.8,4,1,1,70927.11,1 +9217,15701364,Doherty,724,France,Male,30,10,0,2,1,1,54265.55,0 +9218,15762588,Kaleski,644,France,Male,31,5,0,2,1,1,41872.17,0 +9219,15806318,Wright,676,Germany,Female,48,2,124442.38,1,1,0,15068.53,1 +9220,15712596,Huang,499,France,Male,31,4,0,1,1,0,25950.49,0 +9221,15600399,Trentino,598,France,Male,60,4,0,1,1,0,197727.14,1 +9222,15576216,Chienezie,655,Germany,Female,37,4,108862.76,1,1,0,79555.08,1 +9223,15620750,Sugden,559,France,Male,28,3,141099.43,1,1,1,15607.27,0 +9224,15623489,Tu,543,France,Female,67,0,128843.67,1,1,1,134612.48,0 +9225,15667944,Onuchukwu,679,France,Male,39,0,86843.61,1,0,1,159830.58,0 +9226,15584928,Ugochukwutubelum,594,Germany,Female,32,4,120074.97,2,1,1,162961.79,0 +9227,15779913,Davidson,586,France,Male,27,5,130231.8,2,1,1,192427.16,0 +9228,15644977,Goddard,776,France,Female,31,5,0,2,1,0,92647.94,0 +9229,15749679,Beck,699,France,Male,39,2,109724.38,1,1,1,180022.39,0 +9230,15629010,Beam,847,Germany,Female,35,5,111743.43,1,1,1,183584.14,0 +9231,15768465,Sheppard,582,Germany,Male,35,8,121309.17,2,1,1,28750.67,0 +9232,15767781,Godfrey,648,France,Male,38,10,82697.28,1,1,0,74846.67,0 +9233,15635364,Gray,618,France,Female,49,9,44301.43,3,1,1,89729.3,1 +9234,15722004,Hsiung,543,France,Female,31,4,138317.94,1,0,0,61843.73,0 +9235,15766044,Cameron,642,Germany,Male,49,4,120688.61,1,1,0,24770.22,1 +9236,15586680,Fleming,462,France,Male,27,4,176913.52,1,1,0,80587.27,0 +9237,15635388,Austin,640,Spain,Male,47,6,89047.14,1,1,0,116286.25,0 +9238,15655175,Wallace,740,Germany,Male,40,4,114318.78,2,1,0,129333.69,1 +9239,15639133,Ku,773,France,Female,50,4,0,2,1,0,129372.94,0 +9240,15799653,Fiorentino,583,Germany,Female,32,7,94753.55,2,1,1,18149.03,0 +9241,15723872,Buccho,589,Spain,Female,46,10,0,2,0,1,168369.37,0 +9242,15775627,Gordon,509,France,Male,35,8,0,2,0,1,67431.28,0 +9243,15630704,Haworth,612,Germany,Male,32,9,106520.73,2,1,0,177092.16,0 +9244,15815534,Guidry,505,Spain,Male,37,0,134006.39,1,1,1,93736.69,0 +9245,15697249,Lettiere,546,Germany,Female,25,3,132837.7,1,1,0,131647.31,0 +9246,15681316,Tai,681,France,Female,41,0,120549.29,2,1,0,175722.31,0 +9247,15682523,Chigozie,762,France,Male,20,1,139432.55,1,1,1,85606.83,0 +9248,15650244,Bezrukov,786,Spain,Male,29,7,80895.44,2,1,0,64945.57,0 +9249,15648638,Chia,629,Spain,Male,34,6,0,2,1,0,190347.72,0 +9250,15795747,Sheppard,787,Spain,Female,39,7,171646.76,1,0,1,100791.36,0 +9251,15607330,Vasilyev,713,Spain,Male,42,0,109121.71,1,0,1,167873.49,0 +9252,15624013,Maxwell,541,France,Female,39,6,109844.81,1,1,0,25289.23,0 +9253,15800805,Maher,451,France,Female,31,7,140931.82,1,0,1,20388.77,0 +9254,15667321,Cocci,644,Spain,Male,49,10,0,2,1,1,145089.64,0 +9255,15601116,P'an,686,France,Male,32,6,0,2,1,1,179093.26,0 +9256,15622033,Rapuluchukwu,847,Germany,Female,41,3,101543.51,4,1,0,16025.17,1 +9257,15758451,Azuka,765,Germany,Male,37,7,102708.77,1,1,0,9087.81,0 +9258,15688689,Esposito,678,Germany,Female,37,8,149000.91,2,1,1,21472.42,0 +9259,15652674,Hou,539,France,Male,20,0,83459.86,1,1,1,146752.67,0 +9260,15806327,Cyril,800,France,Female,40,3,75893.11,2,1,0,132562.23,0 +9261,15649618,Tomlinson,799,Germany,Female,39,7,167395.6,2,0,1,139537.43,0 +9262,15677117,Crawford,629,France,Female,61,6,0,2,1,1,133672.61,0 +9263,15751445,Chikwado,734,Germany,Female,52,6,71283.09,2,0,1,38984.37,0 +9264,15749669,Hargreaves,542,France,Female,31,3,0,2,1,1,115217.59,0 +9265,15656351,Laidley,414,Spain,Male,60,3,0,2,1,1,93844.82,0 +9266,15667438,Ferguson,675,France,Female,38,1,104016.88,1,0,0,22068.83,1 +9267,15682273,Burns,683,France,Female,38,5,127616.56,1,1,0,123846.07,0 +9268,15580912,McNeill,748,France,Male,32,5,154737.88,2,1,1,172638.13,0 +9269,15785183,Chukwuebuka,596,Spain,Male,29,2,0,2,1,1,1591.19,0 +9270,15705383,Shen,642,France,Male,35,4,125476.31,1,1,1,91775.51,0 +9271,15712903,Diaz,499,France,Female,21,3,176511.08,1,1,1,153920.22,0 +9272,15774285,Kentish,649,Spain,Female,47,8,110783.28,1,1,1,71420.16,0 +9273,15583138,Persse,739,France,Male,42,2,141642.92,2,1,0,172149.76,0 +9274,15740160,Okwukwe,616,France,Male,31,1,0,2,1,1,54706.75,0 +9275,15793425,Watt,560,Spain,Female,33,9,0,1,0,1,183358.21,0 +9276,15749265,Carslaw,427,Germany,Male,42,1,75681.52,1,1,1,57098,0 +9277,15623989,Griffin,435,France,Male,54,3,0,1,1,0,156910.46,1 +9278,15604832,Hsia,633,France,Male,29,7,0,1,1,1,130224.73,0 +9279,15584580,Fyodorova,443,France,Male,35,6,161111.45,1,0,0,13946.66,0 +9280,15573854,Chukwujekwu,727,France,Male,62,5,0,2,0,1,38652.96,0 +9281,15614847,Townsend,674,France,Female,45,6,72494.69,1,0,1,140041.78,0 +9282,15679966,Marsh,661,France,Female,31,3,133964.3,1,1,1,166187.1,0 +9283,15799435,Hayes,619,Spain,Male,34,1,0,1,1,0,139919.38,0 +9284,15752186,Padovano,562,France,Female,27,3,0,2,1,0,28137.03,0 +9285,15705544,Ma,633,France,Male,61,3,157201.48,1,0,1,50368.63,0 +9286,15713632,Ham,551,Spain,Female,48,5,95679.29,1,0,0,94978.1,0 +9287,15586523,Paten,720,Germany,Female,29,7,106230.92,1,1,1,69903.93,1 +9288,15609176,Cawthorne,688,France,Female,32,5,0,2,0,1,177607.77,0 +9289,15769308,Herbert,635,Germany,Female,36,9,81231.85,2,1,0,196731.08,0 +9290,15676810,Jen,561,France,Female,31,1,81480.27,2,1,1,65234.6,0 +9291,15634591,Saunders,850,France,Male,33,8,73059.38,1,1,1,186281,0 +9292,15679804,Esquivel,636,France,Male,36,5,117559.05,2,1,1,111573.3,0 +9293,15677764,Chao,461,Germany,Female,74,1,186445.31,2,1,1,196767.83,0 +9294,15571917,Eluemuno,771,Germany,Female,38,5,137657.71,2,1,0,72985.61,0 +9295,15574608,Sidorova,713,France,Male,36,8,133889.35,1,1,1,143265.65,0 +9296,15740868,Pirogova,658,Germany,Female,45,9,134562.8,1,1,1,159268.67,0 +9297,15702442,Benson,586,Germany,Female,56,9,100781.75,2,1,1,54448.41,0 +9298,15699797,Santana,737,France,Male,30,8,174356.13,1,0,0,31928.5,0 +9299,15648047,Williamson,742,Germany,Male,27,5,190125.43,2,0,0,21793.59,0 +9300,15766826,North,824,France,Male,26,7,146266,1,1,0,21903.62,1 +9301,15591628,Davies,701,Germany,Male,41,9,164046.1,1,1,0,49405.93,0 +9302,15583857,Siciliano,623,Spain,Female,43,4,123536.52,2,0,0,154908.52,0 +9303,15752534,Mironov,744,France,Male,36,10,0,2,1,1,182867.84,0 +9304,15741403,Amechi,698,Spain,Female,38,1,171848.38,1,0,0,16957.45,0 +9305,15783589,Toscano,616,France,Male,40,9,0,2,0,0,93717.55,0 +9306,15598046,Su,662,France,Female,39,5,139562.05,2,1,0,61636.22,0 +9307,15643330,Chukwuemeka,594,France,Male,37,2,0,2,0,1,95864.5,0 +9308,15680405,P'eng,685,France,Male,40,2,168001.34,2,1,1,167400.29,0 +9309,15728683,Lombardo,742,France,Male,27,0,0,2,0,1,131534.96,0 +9310,15621644,Lombardi,678,Germany,Male,83,6,123356.63,1,0,1,92934.41,0 +9311,15733032,Butler,651,Spain,Male,47,2,0,2,1,1,119808.64,0 +9312,15608381,Dean,585,Germany,Male,50,2,125845.66,1,1,0,9439.31,1 +9313,15658946,Piccio,579,Germany,Male,40,10,45408.85,2,1,0,18732.91,0 +9314,15757912,Bradley,722,Germany,Female,37,0,125977.81,1,0,0,160162.42,0 +9315,15645371,Cameron,613,Germany,Female,51,7,147262.11,1,1,1,53630.9,1 +9316,15653110,Chan,694,France,Male,42,8,133767.19,1,1,0,36405.21,0 +9317,15766355,Lettiere,550,Germany,Male,49,0,108806.96,3,1,0,61446.92,1 +9318,15585249,Mironova,741,France,Male,42,6,106036.52,1,1,0,194686.78,1 +9319,15611786,Tsui,668,Spain,Female,69,9,0,1,0,1,134483.07,0 +9320,15575486,Okoli,529,France,Female,27,1,0,2,1,1,37769.98,0 +9321,15780215,Berry,636,France,Male,31,6,0,2,1,1,2382.61,0 +9322,15686099,Ruse,563,Spain,Male,61,1,82182.1,1,1,0,106826.92,1 +9323,15739042,Bogolyubov,767,France,Female,35,9,0,2,1,0,39511.61,0 +9324,15815316,Kennedy,644,France,Male,50,9,76817,4,1,0,196371.13,1 +9325,15778489,Bolton,780,Germany,Male,71,9,142550.25,2,1,1,122506.78,0 +9326,15786389,Chuang,635,Spain,Female,41,10,0,2,1,1,61994.2,0 +9327,15601787,Greco,641,Germany,Male,35,2,103711.56,1,0,1,192464.21,1 +9328,15624715,Ma,593,Spain,Female,40,2,0,1,1,1,5194.95,0 +9329,15763093,Nucci,540,Germany,Female,35,7,128369.75,2,1,0,198256.15,0 +9330,15572073,Yao,663,Spain,Male,35,5,0,2,1,1,62634.94,0 +9331,15780256,Palfreyman,630,France,Male,34,9,0,2,1,1,114006.35,0 +9332,15659305,Webster,605,Germany,Male,19,8,166133.28,1,1,1,107994.99,0 +9333,15638882,Cardell,710,Germany,Female,62,9,148214.36,1,1,0,48571.14,1 +9334,15714680,Bianchi,755,France,Female,78,5,121206.96,1,1,1,76016.49,0 +9335,15777217,Somadina,641,Spain,Male,25,10,0,2,1,1,180808.39,0 +9336,15739123,Mellor,737,Germany,Male,50,4,127552.85,2,1,0,4225.11,0 +9337,15594450,Tomlinson,695,France,Male,49,9,159458.53,1,1,0,135841.35,0 +9338,15797751,Pai,466,Germany,Female,47,5,102085.72,1,1,1,183536.24,1 +9339,15691543,Lennox,558,Germany,Male,58,2,142537.18,1,1,1,88791.83,0 +9340,15722845,Meldrum,665,Spain,Male,29,1,182781.74,2,1,1,63732.9,0 +9341,15605804,Watson,737,France,Male,45,10,0,2,1,0,1364.54,0 +9342,15702061,Findlay,654,France,Male,29,7,0,2,1,1,149184.15,0 +9343,15694321,Su,619,France,Female,28,3,0,2,1,0,53394.12,0 +9344,15798749,Davidson,845,Germany,Female,43,3,152063.59,2,1,0,97910.06,0 +9345,15720050,Barrett,727,France,Female,28,2,110997.76,1,1,0,101433.76,0 +9346,15758048,Miah,582,France,Male,50,2,148942,1,1,1,116944.3,0 +9347,15805681,Chamberlain,716,France,Male,41,9,0,1,1,1,113267.48,0 +9348,15802809,Vidal,660,Spain,Female,36,0,84438.57,1,1,1,181449.51,0 +9349,15807239,Lung,664,France,Female,34,7,93920.47,1,0,0,179913.98,0 +9350,15749093,Tretyakova,801,France,Male,43,4,158713.08,2,0,0,98586.14,0 +9351,15689344,Montgomery,615,Spain,Male,42,4,0,3,0,1,120321.09,0 +9352,15606076,Golubev,718,Germany,Male,63,7,123204.88,1,1,1,100538.8,0 +9353,15610090,Han,667,France,Male,40,8,72945.29,2,1,0,98931.5,0 +9354,15693926,Pan,670,Spain,Male,37,0,178742.71,1,1,1,194493.57,0 +9355,15791501,Carroll,590,France,Male,43,8,0,2,1,1,143628.31,0 +9356,15621870,Hawkins,739,Spain,Female,40,8,0,1,1,0,167030.51,0 +9357,15734711,Loggia,373,France,Male,42,7,0,1,1,0,77786.37,1 +9358,15814405,Chesnokova,418,France,Female,46,9,0,1,1,1,81014.5,1 +9359,15729359,Chambers,837,France,Female,29,9,0,2,1,1,41866.26,0 +9360,15606944,Fleming,645,Germany,Male,43,9,140121.17,1,1,0,11302.7,1 +9361,15671934,Veale,552,Germany,Male,39,2,132906.88,1,0,1,149384.43,0 +9362,15641773,Browne,580,Germany,Male,45,2,179334.83,2,1,1,169303.65,0 +9363,15701972,Parsons,684,France,Male,35,3,137179.39,1,1,1,37264.11,0 +9364,15749114,Bailey,634,Spain,Male,35,3,0,2,1,1,19515.48,0 +9365,15780362,Ferrari,607,France,Female,49,9,119960.29,2,1,0,103068.22,0 +9366,15753229,Genovese,802,France,Male,29,9,127414.55,1,1,1,134459.12,0 +9367,15656009,McIntyre,736,France,Female,36,6,0,1,1,0,70496.66,0 +9368,15785024,Warner,629,France,Female,40,9,137409.19,1,1,0,175877.7,1 +9369,15670492,Gordon,737,France,Male,28,8,0,2,1,0,106390.01,0 +9370,15795458,McMillan,718,Spain,Female,39,2,0,1,1,1,52138.49,0 +9371,15732438,Cheng,561,France,Male,43,4,0,4,0,0,18522.91,1 +9372,15781987,Akhtar,641,France,Male,31,9,112494.99,1,1,1,32231.6,0 +9373,15775826,Iadanza,677,France,Male,30,1,78133.15,1,0,1,174225.88,0 +9374,15807457,Abernathy,641,Spain,Female,36,1,0,2,1,0,102021.39,0 +9375,15632538,Watson,658,Spain,Female,32,5,145553.07,1,1,1,31484.76,0 +9376,15641389,Shen,659,Germany,Male,48,4,123593.22,2,1,0,82469.06,1 +9377,15657306,Kershaw,567,France,Female,47,2,0,1,0,0,110900.43,1 +9378,15709447,Reed,584,France,Female,26,0,146286.22,1,1,0,105105.35,0 +9379,15762682,Mitchell,709,Spain,Female,35,1,111827.27,2,1,0,12674.68,0 +9380,15626042,Webb,690,Spain,Female,26,2,0,2,1,1,93255.85,0 +9381,15597109,Vanzetti,627,France,Male,70,1,94416.78,1,0,1,145299.5,0 +9382,15756148,Nnanna,765,Spain,Male,45,2,91549.78,1,1,1,47139.44,0 +9383,15665634,Campbell,645,France,Female,38,7,59568.57,1,1,1,167723.25,0 +9384,15739997,Capon,716,France,Female,23,2,94464.81,2,0,1,185900.88,0 +9385,15686242,Otutodilichukwu,771,France,Female,57,4,0,1,0,0,85876.67,1 +9386,15759244,Boone,687,Germany,Male,44,8,95368.14,2,1,1,1787.85,0 +9387,15672027,McIntyre,717,Germany,Female,33,10,102185.42,2,1,0,23231.93,0 +9388,15594576,Zhdanov,524,France,Male,32,1,144875.71,1,0,0,187740.04,0 +9389,15707138,Nagy,679,Spain,Male,39,5,0,2,1,1,100060.54,0 +9390,15756954,Lombardo,538,France,Female,32,2,0,1,1,1,80130.54,0 +9391,15619130,Simpson,752,Germany,Female,37,5,113291.05,2,1,1,132467.54,0 +9392,15639665,Herbert,846,Spain,Male,61,0,0,2,1,1,96202.44,0 +9393,15571065,Lehr,532,Spain,Female,39,0,0,2,1,0,94977.3,0 +9394,15686060,Chou,670,Germany,Male,43,9,111677.88,1,1,0,178827.3,1 +9395,15615753,Upchurch,597,Germany,Female,35,8,131101.04,1,1,1,192852.67,0 +9396,15800961,Ugorji,627,Germany,Male,52,1,76101.81,2,0,1,177238.35,0 +9397,15763065,Palerma,700,Spain,Female,40,2,0,2,1,0,199753.97,0 +9398,15672467,Coles,766,France,Female,52,7,92510.9,2,0,1,66193.61,0 +9399,15752915,Hsueh,488,France,Female,34,2,0,2,1,1,181270.84,0 +9400,15744695,Tu,694,France,Male,39,5,77652.4,1,1,1,25407.59,0 +9401,15584897,Kuo,639,France,Female,31,3,98360.03,1,0,0,20973.8,0 +9402,15601857,Woodhouse,705,Germany,Female,46,4,115518.07,1,0,0,76544.9,1 +9403,15674156,Tretiakova,810,Germany,Male,69,3,27288.43,1,1,1,110509.9,0 +9404,15695465,Gibson,638,France,Female,36,6,0,1,1,0,164247.51,0 +9405,15792232,Moss,595,Spain,Female,43,5,0,2,0,0,105149.8,0 +9406,15807900,Chineze,575,France,Male,36,7,0,1,1,1,55868.97,1 +9407,15743760,Davidson,850,France,Male,31,6,131996.66,2,1,1,178747.43,0 +9408,15652835,Liang,419,Spain,Female,27,2,121580.42,1,0,1,134720.51,0 +9409,15767818,Graham,640,France,Male,55,10,132436.34,1,1,0,978.66,0 +9410,15591150,Nwebube,570,Spain,Male,34,10,0,2,0,1,183387.12,0 +9411,15734659,Sozonov,640,Germany,Female,46,5,107978.4,2,1,0,155876.06,0 +9412,15796115,Forbes,689,Germany,Female,40,4,78119.59,4,1,0,119259.34,1 +9413,15724648,Chikezie,725,France,Male,26,6,98684.15,1,0,0,133720.57,0 +9414,15737732,Onwuemelie,751,France,Female,44,10,0,2,1,0,170634.49,0 +9415,15632280,Toth,544,Spain,Female,53,9,0,1,1,0,125692.07,1 +9416,15750407,Hunt,768,Germany,Female,43,2,129264.05,2,0,0,19150.14,0 +9417,15795370,Mazure,648,Germany,Male,37,6,131753.41,1,1,0,86894.67,0 +9418,15656829,Hughes,577,Spain,Female,33,6,0,2,1,0,57975.8,0 +9419,15643794,Bennett,639,Spain,Female,27,2,0,1,1,1,82938.99,0 +9420,15798605,Tien,686,Germany,Male,26,1,57422.62,1,1,1,79189.4,0 +9421,15637324,Kay,657,France,Female,28,7,0,2,0,1,5177.62,0 +9422,15589589,Bryan,613,France,Male,34,5,144094.2,1,1,0,44510.26,0 +9423,15778936,Ingamells,701,France,Male,33,9,147510.34,1,1,0,190611.92,0 +9424,15757385,Milne,578,Spain,Female,28,8,161592.76,1,1,0,177834.79,0 +9425,15666200,Lombardo,689,France,Female,40,1,0,2,1,1,119446.64,0 +9426,15683977,Owens,687,Spain,Female,72,4,0,2,1,1,50267.69,0 +9427,15675518,Charlton,499,Spain,Female,53,1,75225.53,2,0,0,144849.1,1 +9428,15584812,Overby,693,Spain,Female,39,0,0,2,0,0,81901.6,0 +9429,15752984,Chifley,737,France,Female,70,9,87542.89,2,1,1,42576.86,0 +9430,15577913,Oliver,651,France,Female,32,8,144581.96,1,1,1,87609.5,0 +9431,15591980,Hill,753,France,Male,33,5,122568.05,2,1,1,82820.85,0 +9432,15598948,DeRose,523,Spain,Female,24,5,172231.93,1,0,1,155144.12,0 +9433,15574142,Chuang,458,Germany,Female,28,2,171932.26,2,1,1,9578.24,0 +9434,15582903,Edwards,643,France,Male,39,7,0,2,1,1,170392.59,0 +9435,15733229,Rodriguez,638,Spain,Female,34,7,0,2,0,0,3946.29,0 +9436,15635752,Lo,685,Germany,Male,38,4,111798.06,2,1,1,102184.66,0 +9437,15771000,Powell,684,France,Male,38,4,0,3,1,0,75609.84,0 +9438,15804864,Chu,670,France,Female,27,5,79336.61,1,1,1,26170.08,0 +9439,15641175,Munro,701,Germany,Male,63,3,120916.52,3,0,0,144727.45,1 +9440,15692226,Onwumelu,705,France,Female,31,3,142905.51,1,1,1,58134.97,0 +9441,15584156,Siciliani,593,Spain,Male,27,10,0,3,0,0,94620,1 +9442,15702656,Yobachi,651,France,Female,33,1,96834.78,1,1,0,108764.69,0 +9443,15606552,Akabueze,741,France,Male,37,9,105261.76,2,1,1,149503.54,0 +9444,15687001,Chiemenam,596,Germany,Male,54,1,123544,1,1,1,120314.75,1 +9445,15781903,Odinakachukwu,581,Germany,Male,41,2,127913.71,2,1,1,44205.95,0 +9446,15731951,Reilly,689,Spain,Female,28,5,95328.6,1,1,0,6129.61,1 +9447,15580953,Forbes,544,France,Male,30,4,73218.89,1,0,1,126796.69,0 +9448,15810390,Amadi,718,France,Female,41,1,0,2,0,1,27509.52,1 +9449,15628274,Ferri,583,Germany,Male,35,8,149995.72,2,1,0,42143.55,0 +9450,15615444,Y?an,663,Germany,Male,28,8,123674.28,2,1,1,87985.2,0 +9451,15784010,Williamson,666,Germany,Male,33,2,124125.26,1,1,0,81884.8,0 +9452,15571586,Briggs,524,Spain,Male,29,3,159035.45,1,1,0,2705.31,1 +9453,15748616,Napolitani,599,France,Male,27,5,0,2,1,0,30546.4,0 +9454,15769402,Carpenter,667,France,Male,27,7,156811.74,1,1,1,149402.59,0 +9455,15739248,Lin,727,France,Male,52,4,0,2,1,1,118429.02,0 +9456,15603481,Robinson,689,Spain,Female,55,4,0,2,1,1,58442.25,0 +9457,15723604,Collins,639,France,Male,39,6,150555.83,1,1,0,30414.17,0 +9458,15797822,Kingsley,678,France,Male,28,2,109137.12,1,1,1,58814.41,0 +9459,15665064,Harvey,523,France,Male,36,8,158351.02,2,1,0,155304.53,0 +9460,15640580,Obiora,650,France,Female,47,9,0,1,1,0,187943.6,0 +9461,15581089,Knight,744,Spain,Male,35,7,0,2,1,1,43036.6,0 +9462,15728605,Hung,697,France,Male,40,4,0,2,0,1,26543.28,0 +9463,15737385,Curtis,800,Spain,Female,46,6,0,2,1,0,171928.04,0 +9464,15714789,Perez,664,France,Male,24,7,0,1,0,1,35611.35,0 +9465,15786035,Gosnell,740,France,Male,39,9,0,2,1,0,19047.23,0 +9466,15815259,Fang,835,France,Female,56,2,0,2,1,1,39820.13,0 +9467,15592716,Clarke,559,France,Male,52,2,0,1,1,0,129013.59,1 +9468,15734850,Milanesi,676,Spain,Male,36,1,82729.49,1,1,0,113810.12,0 +9469,15638047,Chia,613,Germany,Female,45,9,142765.24,2,1,0,34749.65,0 +9470,15674573,Gearhart,713,France,Female,25,4,121172.97,1,1,1,56268.98,0 +9471,15694859,McLean,751,Germany,Female,28,10,132932.14,2,1,1,46630.47,0 +9472,15776404,Williamson,523,France,Male,22,8,123374.46,1,1,1,124906.59,0 +9473,15579345,Murphy,775,Germany,Female,74,0,161371.5,1,1,1,134869.93,0 +9474,15690733,Angelo,608,Spain,Male,45,4,0,2,0,0,36697.48,1 +9475,15631481,Thomson,673,France,Male,51,8,79563.36,2,1,1,172200.91,0 +9476,15620988,Murray,616,France,Male,46,2,0,2,1,0,137136.46,0 +9477,15571529,Kirby,650,Germany,Female,48,7,138232.24,1,1,0,57594.78,0 +9478,15592104,Lane,655,France,Female,41,5,0,1,0,0,36548,1 +9479,15651900,Bergamaschi,782,Germany,Female,53,1,81571.05,1,1,0,182960.46,1 +9480,15596212,Yang,781,Spain,Male,35,1,0,2,0,0,42117.9,0 +9481,15710687,Mills,593,France,Female,33,0,95927.04,1,1,0,199478.05,0 +9482,15613787,Chidubem,505,Spain,Male,35,8,116932.59,1,1,0,91092.84,0 +9483,15599211,Findlay,707,France,Male,40,1,0,2,1,0,14090.4,1 +9484,15675983,Wood,692,France,Female,36,3,79551.12,1,0,1,178267.07,0 +9485,15622370,Boyle,813,Germany,Male,30,1,116416.94,1,0,1,85808.22,0 +9486,15656319,Toscano,850,Spain,Male,37,4,88141.1,1,1,0,109659.12,0 +9487,15605130,Seccombe,753,France,Male,32,6,177729.13,1,1,1,161642.08,0 +9488,15672574,Uspenskaya,850,Spain,Female,32,5,0,1,1,1,3830.59,0 +9489,15659355,McKenzie,671,Spain,Male,32,6,123912.78,2,1,1,146636.44,0 +9490,15777907,Liang,791,France,Female,33,3,0,1,1,1,144413.92,1 +9491,15655171,Yermakova,624,France,Male,80,3,0,1,1,1,65801.44,0 +9492,15619674,White,649,France,Female,35,4,108306.44,1,1,1,192486.24,0 +9493,15775192,Rounsevell,732,Germany,Female,48,4,102962.62,1,1,0,120852.85,1 +9494,15617657,Ts'ai,664,France,Female,36,0,103502.22,1,1,1,146191.82,0 +9495,15688951,Stoneman,789,Germany,Male,43,8,119654.44,2,0,1,148412.24,1 +9496,15763460,Yao,680,France,Male,33,10,183768.47,1,1,0,164119.35,0 +9497,15756992,Chukwukere,701,France,Male,37,1,0,2,1,0,163457.55,0 +9498,15617454,Ifeatu,684,France,Female,25,1,0,2,0,1,144978.47,0 +9499,15701932,Millar,586,France,Female,52,6,140900.97,1,1,1,67288.89,0 +9500,15700813,Igwebuike,522,Germany,Female,25,5,94049.92,2,1,0,103269,0 +9501,15645600,Obidimkpa,739,Spain,Female,27,8,98926.4,1,1,1,106969.98,0 +9502,15634146,Hou,835,Germany,Male,18,2,142872.36,1,1,1,117632.63,0 +9503,15686743,Moody,790,Spain,Male,29,3,46057.96,2,1,1,189777.66,0 +9504,15698792,Keldie,671,France,Female,48,6,119769.77,1,0,1,66032.65,0 +9505,15591724,Liu,560,France,Female,44,5,143244.97,1,1,0,98661.27,0 +9506,15571281,Ts'ao,651,France,Male,28,10,79562.98,1,1,1,74687.37,0 +9507,15661380,Walker,682,France,Male,69,6,0,2,0,1,149604.18,0 +9508,15728885,Defalco,808,France,Male,41,0,0,1,1,1,79888.78,0 +9509,15618950,Lo Duca,644,Spain,Male,26,8,96659.64,2,1,1,138775.69,0 +9510,15609804,Hyde,688,France,Male,29,1,0,2,1,0,154695.57,0 +9511,15735849,Kanayochukwu,617,France,Female,26,2,165947.99,2,0,1,168834.38,0 +9512,15652948,Yen,738,France,Male,33,4,92676.3,1,1,0,105817.63,0 +9513,15618155,Ts'ui,663,France,Male,45,5,83195.12,1,1,1,48682.1,0 +9514,15566378,Tillman,515,France,Male,48,5,129387.94,1,0,1,147955.91,1 +9515,15565879,Riley,845,France,Female,28,9,0,2,1,1,56185.98,0 +9516,15792922,Tu,639,Spain,Male,38,9,130233.14,1,1,1,81861.1,0 +9517,15770567,Ruiz,557,France,Female,32,3,123502.53,1,1,1,69826.8,0 +9518,15738042,Goliwe,543,Germany,Male,37,8,140894.06,2,1,1,118059.19,0 +9519,15714920,Balashov,585,Germany,Male,44,7,163867.86,1,1,1,112333.22,0 +9520,15782121,Leonard,610,France,Female,27,2,0,2,1,0,14546.76,0 +9521,15673180,Onyekaozulu,727,Germany,Female,18,2,93816.7,2,1,0,126172.11,0 +9522,15660636,Carpenter,540,Spain,Female,40,8,0,2,1,0,3560,0 +9523,15664504,Beede,418,France,Male,35,7,0,2,1,1,88878.15,0 +9524,15790322,Beneventi,660,France,Female,32,0,114668.89,1,1,0,84605,0 +9525,15739847,Sadlier,850,Germany,Male,38,5,146756.68,1,1,0,78268.61,0 +9526,15699415,Lewis,618,France,Female,46,6,150213.71,1,1,0,120668.46,1 +9527,15665521,Chiazagomekpele,642,Germany,Male,18,5,111183.53,2,0,1,10063.75,0 +9528,15682868,Elliott,850,France,Female,40,9,99816.46,1,1,1,163989.66,1 +9529,15584462,Liang,739,France,Male,34,9,0,1,1,0,60584.33,0 +9530,15661708,She,508,France,Female,41,5,0,2,1,1,94170.84,0 +9531,15584452,Bozeman,667,France,Male,41,6,0,2,0,0,167181.77,0 +9532,15717010,Yu,741,France,Female,60,5,0,1,1,1,38914.51,0 +9533,15643828,Teng,592,France,Male,29,7,0,2,1,1,91196.67,0 +9534,15733361,Davide,651,Germany,Female,45,6,86714.06,1,1,0,85869.89,1 +9535,15795488,Beneventi,773,Spain,Male,52,2,0,2,1,0,57337.79,0 +9536,15581551,Yobachukwu,850,Spain,Male,41,8,132838.07,1,1,1,175347.28,0 +9537,15632051,Douglas,550,Germany,Female,42,10,128707.31,1,1,0,63092.65,1 +9538,15780409,Egobudike,783,France,Male,40,6,0,2,1,0,109742.55,0 +9539,15572767,Shelby,777,France,Male,29,2,0,2,1,0,124489.88,0 +9540,15590337,Golubov,659,France,Male,29,6,123192.12,1,1,1,56971.41,1 +9541,15634551,Williamson,727,Germany,Male,46,3,115248.11,4,1,0,130752.01,1 +9542,15669290,Fan,603,France,Male,38,8,59360.77,1,1,1,191457.06,0 +9543,15621140,Nwebube,644,Spain,Male,37,9,0,2,1,1,96442.86,0 +9544,15613518,Bellucci,647,France,Female,35,6,112668.7,1,0,1,122584.29,0 +9545,15728043,Udinese,648,Germany,Female,37,7,138503.51,2,1,0,57215.85,0 +9546,15570073,Marian,721,Spain,Male,57,1,0,1,1,1,195940.96,0 +9547,15777033,Chizoba,524,France,Male,29,7,0,2,1,1,105448.74,0 +9548,15682454,McFarland,626,France,Female,34,3,0,2,1,1,37870.29,0 +9549,15758513,McDonald,569,France,Male,43,7,0,2,1,0,52534.81,0 +9550,15772604,Chiemezie,578,Spain,Male,36,1,157267.95,2,1,0,141533.19,0 +9551,15721715,Fane,769,France,Female,40,9,133871.05,1,1,1,50568.02,0 +9552,15688563,Marchesi,694,Germany,Male,31,4,141989.27,2,1,0,26116.82,0 +9553,15772009,Scott,664,France,Female,41,5,0,1,1,1,152054.33,0 +9554,15809585,H?,646,France,Male,38,7,0,2,1,0,1528.4,0 +9555,15593778,Craig,779,France,Female,29,3,46388.16,3,1,0,127939.26,1 +9556,15655360,Chikelu,782,Germany,Female,72,5,148666.99,1,1,0,2605.65,1 +9557,15780909,Caffyn,769,Germany,Male,34,7,115101.5,1,0,0,57841.89,1 +9558,15757310,Otitodilichukwu,655,Germany,Male,67,6,148363.38,1,1,1,186995.17,0 +9559,15801411,Green,623,Spain,Male,46,4,0,1,1,0,5549.11,1 +9560,15761706,Y?an,705,Spain,Female,39,8,144102.32,1,1,1,11682.36,0 +9561,15658409,Mao,686,France,Male,41,5,128876.71,3,1,1,106939.34,1 +9562,15810010,Dahlenburg,678,Germany,Male,36,6,118448.15,2,1,0,53172.02,0 +9563,15627027,Shih,738,France,Male,39,5,0,2,1,1,114388.98,0 +9564,15624374,Maclean,703,France,Male,28,9,0,2,0,1,2151.17,0 +9565,15720083,Fiorentino,554,Spain,Male,42,1,0,2,0,1,183492.9,0 +9566,15752294,Long,582,France,Female,38,9,135979.01,4,1,1,76582.95,1 +9567,15743193,Olson,644,France,Male,37,6,117271.8,2,1,0,104217.96,1 +9568,15696733,McKenzie,724,France,Male,29,4,0,1,1,0,8982.75,0 +9569,15677522,Rossi,593,France,Male,33,1,0,2,0,0,9984.4,0 +9570,15643523,Power,710,Spain,Female,30,10,0,2,1,0,19500.1,0 +9571,15624936,Yen,631,France,Male,35,8,129205.49,1,1,1,79146.36,0 +9572,15716085,Norris,739,Spain,Female,41,8,0,1,1,0,191694.77,1 +9573,15641688,Collier,644,Spain,Male,18,7,0,1,0,1,59645.24,1 +9574,15796834,Rivers,652,Germany,Male,35,7,104015.54,2,1,1,55207.88,0 +9575,15720123,Hudson,554,Spain,Male,37,3,0,2,1,0,166177.3,0 +9576,15604732,Milani,483,France,Female,30,9,0,2,0,0,136356.97,0 +9577,15723484,Hunt,669,Germany,Female,42,1,103873.39,1,1,0,148611.52,0 +9578,15807120,Oluchukwu,841,Germany,Female,52,3,112383.03,1,1,0,85516.37,1 +9579,15810891,Lorenzo,662,France,Male,34,2,117731.79,2,0,1,55120.79,0 +9580,15640407,Chidiegwu,821,Germany,Male,45,0,135827.33,2,1,1,131778.58,0 +9581,15778838,Warren,783,France,Male,38,9,114135.17,1,1,0,153269.98,0 +9582,15709256,Glover,850,France,Female,28,9,0,2,1,1,164864.67,0 +9583,15742285,Andersen,559,France,Male,62,6,118756.62,1,1,1,20367.68,0 +9584,15729019,Arcuri,602,Spain,Male,34,8,98382.72,1,1,0,39542,0 +9585,15608588,Mackinlay,563,Germany,Male,41,2,100520.92,1,1,1,19412.8,1 +9586,15610557,McCarthy,695,Spain,Female,35,7,79858.13,2,1,1,127977.66,0 +9587,15786418,Chiu,546,France,Female,20,6,0,1,0,1,20508.85,0 +9588,15653050,Norriss,719,Germany,Female,76,10,95052.29,1,1,0,176244.87,0 +9589,15744914,Moore,539,Germany,Male,42,1,177728.55,1,1,0,105013.63,0 +9590,15669611,Mott,632,France,Male,71,3,83116.68,1,1,1,27597.76,0 +9591,15594786,Ts'ai,772,Germany,Male,34,7,111565.91,1,1,1,121073.23,0 +9592,15649211,Fokina,708,Spain,Male,40,8,83015.71,1,1,0,101089.76,0 +9593,15766066,Nikitina,668,Germany,Female,28,1,124511.01,1,0,0,114258.18,0 +9594,15772216,Henry,738,France,Female,67,1,130652.52,1,0,1,22762.23,0 +9595,15619898,Chiefo,785,France,Male,55,5,0,2,1,1,7008.65,0 +9596,15724543,Mao,597,France,Male,61,5,0,2,1,1,81299.17,0 +9597,15755084,Bezrukova,531,France,Male,37,7,121854.45,1,1,0,147521.35,0 +9598,15730441,Dodd,509,France,Male,26,10,0,2,1,1,6177.83,0 +9599,15666767,Lori,508,France,Male,35,1,86893.28,1,0,0,59374.82,0 +9600,15690456,Yudina,749,Germany,Female,32,7,79523.13,1,0,1,157648.12,0 +9601,15570533,Conti,621,Germany,Female,55,7,131033.76,1,0,1,75685.59,1 +9602,15797692,Volkova,659,France,Female,33,7,89939.62,1,1,0,136540.09,0 +9603,15603135,Boni,634,Germany,Female,59,3,95727.05,1,0,0,97939.4,1 +9604,15698927,Ritchie,675,France,Male,39,7,0,2,0,1,36267.21,0 +9605,15687363,McMillan,770,France,Male,31,3,155047.56,2,1,1,186064.34,0 +9606,15733444,Phillips,736,France,Female,29,9,0,2,0,0,176152.7,0 +9607,15678057,Lombardi,524,France,Male,44,10,118569.03,2,0,0,82117.2,0 +9608,15806918,Ireland,674,France,Male,28,5,0,1,1,1,151925.25,0 +9609,15638247,Boan,700,Spain,Male,44,9,0,2,1,0,142287.65,0 +9610,15674833,Shao,741,France,Female,35,1,0,2,1,0,36557.55,0 +9611,15812534,Chiemenam,455,France,Male,40,1,0,3,0,1,129975.34,0 +9612,15586522,Hunter,608,Spain,Male,37,2,130461.02,1,1,0,21967.15,0 +9613,15794297,McKay,776,France,Male,36,1,0,2,1,0,53477.76,0 +9614,15737025,Roberts,635,France,Male,33,1,0,3,0,0,178067.33,1 +9615,15615931,Aitken,746,France,Female,37,4,0,2,0,1,171039.56,0 +9616,15664860,Chao,692,Spain,Female,47,3,0,2,1,0,150802.41,1 +9617,15664539,Bruce,683,Spain,Male,35,9,61172.04,1,0,0,82951.12,0 +9618,15583692,Chan,591,Germany,Female,35,2,90194.34,2,1,0,57064.57,0 +9619,15693131,Watts,581,France,Female,24,3,95508.2,1,1,1,45755,0 +9620,15779973,Gibbons,684,Germany,Male,35,3,99967.76,1,1,1,176882.08,0 +9621,15620557,Ni,561,Spain,Male,37,4,101470.29,1,0,1,88838.14,0 +9622,15639549,Jen,718,Germany,Female,33,4,70541.06,1,0,0,88592.8,0 +9623,15618750,Phillips,590,France,Male,31,8,112211.61,1,1,0,26261.42,0 +9624,15796790,Amaechi,573,France,Female,47,8,154543.98,1,1,0,29586.73,0 +9625,15668309,Maslow,350,France,Female,40,0,111098.85,1,1,1,172321.21,1 +9626,15732437,Rowley,504,Germany,Female,44,0,131873.07,2,1,1,158036.72,1 +9627,15665158,Chukwuemeka,813,Spain,Male,27,1,137275.36,1,0,1,115733.16,0 +9628,15689322,Bevan,641,Spain,Male,31,3,153316.14,1,1,0,59927.99,0 +9629,15596624,Topp,662,France,Female,22,9,0,2,1,1,44377.65,0 +9630,15601977,Burgoyne,497,Spain,Male,44,2,121250.04,1,0,1,79691.4,0 +9631,15801462,Yermakov,716,France,Male,31,8,109578.04,2,1,1,51503.51,0 +9632,15566139,Ts'ui,526,France,Female,37,5,53573.18,1,1,0,62830.97,0 +9633,15791006,Kodilinyechukwu,760,Germany,Female,34,6,58003.41,1,1,0,90346.1,0 +9634,15668057,K?,669,France,Female,31,6,113000.66,1,1,0,40467.82,0 +9635,15580805,Marino,655,France,Male,27,10,0,2,1,0,51620.94,0 +9636,15658768,Lucas,547,France,Female,49,2,0,1,0,0,65466.93,1 +9637,15613048,Anderson,648,Germany,Female,40,5,139973.65,1,1,1,667.66,1 +9638,15803654,Wei,790,France,Female,31,2,151290.16,1,1,1,172437.12,0 +9639,15662337,Baldwin,744,Germany,Female,50,1,121498.11,2,0,1,106061.47,1 +9640,15650924,Foster,761,Spain,Female,32,4,103515.39,2,1,1,177622.38,0 +9641,15647203,Gebhart,750,France,Female,35,3,0,1,1,0,191520.5,0 +9642,15682778,Fedorov,680,France,Male,34,9,0,2,1,1,95686.6,0 +9643,15579820,Robertson,704,Spain,Male,38,6,106687.76,1,1,0,173776.5,0 +9644,15709354,Tudawali,521,France,Female,41,2,0,2,1,1,113089.43,0 +9645,15728480,Iloerika,452,France,Female,35,8,0,2,1,1,149614.81,0 +9646,15641091,Onyemauchechukwu,695,France,Female,31,5,106089.2,1,0,0,99537.68,0 +9647,15603111,Muir,850,Spain,Male,71,10,69608.14,1,1,0,97893.4,1 +9648,15679693,Walker,625,France,Male,31,5,0,2,0,1,90.07,0 +9649,15797190,Charlton,608,Germany,Female,40,7,96202.32,1,0,0,161154.85,0 +9650,15788025,Tseng,715,France,Female,38,0,0,2,1,1,332.81,0 +9651,15646168,Ifeatu,834,Spain,Male,33,5,0,2,1,0,66285.18,0 +9652,15580493,Chin,469,France,Male,33,1,127818.52,1,1,0,163477.22,0 +9653,15726720,Blinova,480,France,Female,40,7,0,1,1,0,170332.67,1 +9654,15735799,Maconochie,527,Germany,Male,58,3,137318.42,1,1,1,126144.96,0 +9655,15773098,Ch'in,834,Spain,Male,34,5,0,2,0,0,53437.1,0 +9656,15668971,Nicholson,583,France,Female,40,4,55776.39,2,1,0,26920.43,0 +9657,15603221,Burgess,696,Germany,Male,32,4,84421.62,1,0,1,52314.71,0 +9658,15740043,Young,606,France,Male,32,5,83161.65,1,1,1,116885.59,0 +9659,15712264,Plumb,713,France,Female,39,10,0,2,1,1,126263.97,0 +9660,15751926,Trentino,821,Germany,Male,42,3,87807.29,2,1,1,64613.81,0 +9661,15589401,Allen,550,France,Female,30,4,0,2,1,0,89216.29,0 +9662,15742019,Benford,675,France,Female,39,6,0,2,0,0,83419.15,0 +9663,15660611,Gallo,748,Spain,Male,39,3,0,2,1,1,123998.52,0 +9664,15607634,Cobb,606,Germany,Male,40,9,95293.86,2,0,1,96985.58,0 +9665,15595036,Doherty,726,Germany,Male,30,7,92847.59,1,1,0,146154.06,0 +9666,15745794,Cocci,547,France,Male,30,6,0,2,1,1,18471.86,0 +9667,15781689,Macadam,758,Spain,Male,35,5,0,2,1,0,95009.6,0 +9668,15696054,Tychonoff,596,France,Male,37,2,0,1,0,1,121175.86,0 +9669,15752467,Johnson,720,Spain,Male,34,3,0,2,1,1,77047.78,0 +9670,15597739,Tu,674,France,Male,37,3,0,1,1,0,158049.9,0 +9671,15651336,Chidiebere,756,France,Female,32,4,0,2,1,0,147040.25,0 +9672,15636061,Pope,649,Germany,Male,78,4,68345.86,2,1,1,142566.75,0 +9673,15723013,Sutherland,613,Germany,Male,28,7,76656.4,2,1,1,185483.24,0 +9674,15784148,Beneventi,643,France,Male,62,9,0,2,0,0,155870.82,0 +9675,15578098,Jamieson,600,France,Male,31,8,0,2,1,1,121555.51,0 +9676,15638621,Simmons,735,Spain,Male,39,1,60374.98,1,1,0,40223.74,0 +9677,15720924,Chijioke,585,France,Female,34,1,0,1,1,1,75503.6,0 +9678,15566531,Iloerika,724,Germany,Male,33,4,88046.88,1,0,1,186942.49,1 +9679,15718064,Chia,635,Spain,Male,29,2,0,2,0,0,117173.8,0 +9680,15605067,Nwachinemelu,472,France,Male,19,9,0,2,1,0,3453.4,0 +9681,15655335,Becher,590,France,Male,36,1,0,2,1,0,48876.84,0 +9682,15607301,Romano,651,Spain,Female,63,8,129968.67,1,1,1,11830.53,0 +9683,15694628,Walker,686,Germany,Female,39,4,157731.6,2,1,0,162820.6,0 +9684,15607112,Chiawuotu,606,France,Male,32,6,0,2,0,1,36540.63,0 +9685,15635775,Watt,781,France,Male,33,3,89276.48,1,1,0,6959,0 +9686,15644280,Udegbunam,593,France,Male,45,4,138825.19,1,0,0,10828.78,0 +9687,15708362,Watson,793,France,Male,63,4,103729.79,2,1,1,80272.06,0 +9688,15771997,Bryant,791,France,Female,31,10,75499.24,1,1,0,22184.14,0 +9689,15730579,Ward,850,France,Male,68,5,169445.4,1,1,1,186335.07,0 +9690,15728005,Urban,698,France,Female,57,9,111359.55,2,1,0,105715.01,0 +9691,15791674,Sutherland,846,France,Female,34,10,142388.61,2,0,1,68393.64,1 +9692,15754599,K'ung,765,France,Male,42,4,123311.39,2,1,1,82868.34,0 +9693,15693690,Iweobiegbunam,574,Spain,Male,52,7,115532.52,1,1,0,196257.67,0 +9694,15728963,Wei,617,Germany,Female,51,10,167273.71,1,0,0,93439.75,1 +9695,15659710,Lascelles,581,France,Male,25,5,77886.53,2,1,0,150319.49,0 +9696,15658675,Ts'ao,710,Germany,Male,37,6,135795.63,1,0,1,46523.6,0 +9697,15638788,Mack,550,France,Male,32,8,97514.07,1,1,1,199138.84,0 +9698,15609735,Campbell,533,Germany,Male,51,6,127545.56,2,0,0,79559.02,1 +9699,15771477,Fiorentini,779,France,Male,49,9,106160.37,1,0,0,116893.87,0 +9700,15570145,Long,763,France,Female,23,2,0,2,1,0,153983.99,0 +9701,15797149,Lloyd,563,Spain,Female,36,4,143680.47,2,1,1,63531.19,0 +9702,15636912,Sneddon,678,Spain,Male,38,3,124483.53,1,1,0,126253.31,0 +9703,15687828,Gorshkov,644,Spain,Female,31,5,86006.3,1,1,1,73922.95,0 +9704,15667424,Forbes,682,Germany,Female,43,7,111094.05,2,1,1,64679.3,0 +9705,15759872,L?,625,France,Male,22,9,0,2,1,0,157072.91,0 +9706,15572374,Hopetoun,733,Spain,Male,36,1,0,2,0,1,108377.82,0 +9707,15754926,Lucchesi,512,France,Female,30,6,0,2,1,0,88827.31,0 +9708,15687431,Faria,642,France,Female,41,7,115171.71,1,1,1,37674.47,0 +9709,15604515,Yefremov,737,Germany,Female,22,10,111543.26,2,0,0,106327.85,0 +9710,15682839,Genovesi,575,France,Female,57,8,137936.94,1,1,1,84475.13,0 +9711,15624677,Marquez,543,Germany,Female,37,3,122304.65,2,0,0,33998.7,0 +9712,15646366,Trevisani,521,Germany,Male,41,8,120586.54,1,0,1,20491.15,0 +9713,15701768,Tung,637,France,Male,32,3,0,2,1,1,197827.06,0 +9714,15623566,Barnhill,714,France,Male,40,9,46520.69,1,1,1,96687.25,0 +9715,15681274,Marshall,726,Spain,Female,56,2,105473.74,1,1,1,46044.7,0 +9716,15762573,Bednall,680,Spain,Female,34,7,0,2,1,0,98949.85,0 +9717,15706458,Pan,812,Germany,Male,39,5,115730.71,3,1,1,185599.34,1 +9718,15654222,Ogg,757,Spain,Male,30,3,145396.49,1,0,1,198341.15,0 +9719,15704053,T'ang,710,Spain,Male,62,3,131078.42,2,1,0,119348.76,1 +9720,15724321,Baresi,516,Germany,Female,47,9,128298.74,1,0,0,149614.17,1 +9721,15621815,Obiajulu,803,France,Female,40,6,165526.71,1,1,0,12328.08,0 +9722,15724876,McGregor,560,France,Female,38,5,83714.41,1,1,1,33245.97,0 +9723,15696588,Lung,679,France,Female,36,3,0,2,1,1,2243.41,0 +9724,15612832,Jamieson,526,France,Male,32,7,125540.05,1,0,0,86786.41,0 +9725,15804295,Pinto,485,France,Male,41,2,100254.76,2,1,1,12706.67,0 +9726,15712536,Fallaci,625,France,Female,36,3,0,2,1,0,41295.1,1 +9727,15662494,Goliwe,773,Spain,Male,43,7,138150.57,1,1,1,177357.16,0 +9728,15807728,Ferri,530,France,Female,45,1,0,1,0,1,190663.89,1 +9729,15764916,Rowley,616,Germany,Female,43,7,95984.21,1,0,1,115262.54,1 +9730,15615330,Tretiakova,651,France,Male,23,10,0,2,1,1,170099.23,0 +9731,15638487,She,586,Germany,Male,38,2,136858.42,1,0,1,189143.94,0 +9732,15627859,Nebeolisa,607,Germany,Male,29,7,102609,1,1,0,163257.44,0 +9733,15622192,Young,724,Spain,Male,39,3,0,2,0,1,95562.81,0 +9734,15789413,Fitzgerald,733,France,Male,64,3,0,2,1,1,75272.63,0 +9735,15583221,Arnold,667,Germany,Male,70,3,77356.92,2,1,1,20881.96,0 +9736,15768495,Chidimma,700,France,Female,32,8,110923.15,2,1,1,161845.81,1 +9737,15644103,Wells,659,Spain,Male,78,2,151675.65,1,0,1,49978.67,0 +9738,15741197,Calzada,710,Spain,Male,22,8,0,3,1,0,107292.91,0 +9739,15664547,Black,760,France,Male,37,7,0,1,0,0,32863.24,1 +9740,15797293,Sopuluchukwu,677,France,Female,25,3,0,2,1,0,179608.96,0 +9741,15572021,Ts'ao,798,Germany,Female,29,8,80204.11,2,1,0,70223.22,0 +9742,15637461,Ukaegbunam,758,France,Male,35,7,0,2,1,0,77951.84,0 +9743,15620577,Wood,715,France,Male,45,4,0,2,1,1,55043.93,0 +9744,15609643,Furneaux,752,Germany,Male,32,9,115587.49,2,0,1,101677.46,0 +9745,15785358,Gresswell,586,Germany,Male,46,8,106968.96,1,1,1,79366.98,1 +9746,15603883,Ch'in,818,France,Male,36,4,0,2,1,1,8037.03,0 +9747,15782550,Ma,490,Germany,Female,41,0,139659.04,1,1,1,176254.12,0 +9748,15775761,Iweobiegbunam,610,Germany,Female,69,5,86038.21,3,0,0,192743.06,1 +9749,15680201,Marcelo,627,Germany,Male,24,5,102773.2,2,1,0,56793.02,1 +9750,15767594,Azubuike,533,France,Female,35,8,0,2,1,1,187900.12,0 +9751,15591985,Stewart,708,France,Female,51,8,70754.18,1,1,1,92920.04,1 +9752,15789339,Yen,681,France,Male,59,4,122781.51,1,0,1,140166.95,0 +9753,15781530,Hsieh,690,France,Male,21,8,0,2,1,1,155782.89,0 +9754,15705174,Chiedozie,656,Germany,Male,68,7,153545.11,1,1,1,186574.68,0 +9755,15572114,Shih,673,Spain,Male,40,1,121629.22,1,1,1,3258.6,0 +9756,15804009,Amechi,806,Germany,Male,36,8,167983.17,2,1,1,106714.28,0 +9757,15662698,Ko,648,Spain,Female,43,7,81153.82,1,1,1,144532.85,1 +9758,15696047,Chimezie,501,France,Male,35,6,99760.84,1,1,1,13591.52,0 +9759,15701160,Azubuike,556,Germany,Female,43,4,125890.72,1,1,1,74854.97,0 +9760,15790093,Aguirre,627,France,Female,27,2,0,2,1,0,125451.01,0 +9761,15632143,Lung,652,France,Male,31,2,119148.55,1,0,0,149740.22,0 +9762,15736778,Adams,807,Germany,Female,60,1,72948.58,2,1,1,17355.36,0 +9763,15734917,Castiglione,708,Germany,Male,21,8,133974.36,2,1,0,50294.09,0 +9764,15643903,Yao,619,France,Male,27,1,154483.98,1,1,0,156394.74,0 +9765,15569526,Morales,601,France,Male,40,10,98627.13,2,0,0,77977.69,0 +9766,15777067,Thomas,445,France,Male,64,2,136770.67,1,0,1,43678.06,0 +9767,15795511,Vasiliev,800,Germany,Male,39,4,95252.72,1,1,0,13906.34,0 +9768,15610419,Chukwueloka,554,France,Male,33,3,117413.95,1,1,1,12766.74,0 +9769,15644994,Ko,714,Germany,Male,54,4,137986.58,2,0,1,51308.54,1 +9770,15703707,Atkins,656,France,Male,44,10,143571.52,1,0,0,127444.14,0 +9771,15659327,Moffitt,520,France,Male,49,5,121197.64,1,1,0,72577.33,1 +9772,15771323,Panicucci,480,Spain,Male,39,5,121626.9,1,1,1,82438.13,0 +9773,15750549,Akobundu,660,Germany,Male,30,1,84440.1,2,1,1,60485.98,0 +9774,15698462,Chiu,532,France,Male,36,4,0,2,1,1,132798.78,0 +9775,15739692,Tsui,679,France,Male,42,1,0,2,0,0,71823.15,0 +9776,15744041,Yobanna,780,France,Female,26,3,140356.7,1,1,0,117144.15,0 +9777,15700714,Hollis,747,France,Male,29,7,0,2,1,1,141706.43,0 +9778,15777743,Cattaneo,705,France,Female,39,3,92224.56,1,1,1,54517.25,0 +9779,15623143,Lung,732,France,Female,43,9,0,2,1,0,183147.17,0 +9780,15712568,Angelo,515,Spain,Male,40,10,121355.99,1,1,0,138360.29,0 +9781,15617432,Folliero,816,Germany,Female,40,9,109003.26,1,1,1,79580.56,0 +9782,15650424,Bryant,641,France,Female,48,3,147341.43,1,1,1,157458.61,1 +9783,15728829,Weigel,509,France,Male,18,7,102983.91,1,1,0,171770.58,0 +9784,15680430,Ajuluchukwu,601,Germany,Female,49,4,96252.98,2,1,0,104263.82,0 +9785,15687626,Zhirov,527,France,Male,39,4,0,2,1,0,167183.07,1 +9786,15609187,Cox,455,France,Female,27,5,155879.09,2,0,0,70774.97,0 +9787,15609521,Chimaraoke,803,Germany,Male,34,4,142929.16,2,1,1,114869.56,0 +9788,15752626,Genovese,553,France,Male,32,7,64082.09,1,0,1,109159.58,0 +9789,15571756,Ohearn,724,France,Female,28,5,0,1,1,0,59351.68,0 +9790,15814040,Munroe,610,France,Female,45,1,0,2,1,1,199657.46,0 +9791,15658211,Morrison,559,Spain,Female,39,2,0,2,1,1,121151.1,0 +9792,15742091,Parkhill,825,Germany,Female,35,6,118336.95,1,1,0,26342.33,1 +9793,15787168,Y?,819,Spain,Female,28,8,168253.21,1,1,1,102799.14,0 +9794,15772363,Hilton,772,Germany,Female,42,0,101979.16,1,1,0,90928.48,0 +9795,15659364,Thompson,685,Spain,Male,23,5,164902.43,1,0,0,141152.28,0 +9796,15738980,Yobanna,506,France,Male,43,2,0,2,1,0,105568.6,0 +9797,15794236,Thorpe,642,Germany,Male,22,10,111812.52,2,1,1,183045.46,0 +9798,15721383,Harvey,627,Spain,Male,40,10,0,2,1,1,194792.42,0 +9799,15652981,Robinson,600,Germany,Male,30,2,119755,1,1,1,21852.91,0 +9800,15722731,Manna,653,France,Male,46,0,119556.1,1,1,0,78250.13,1 +9801,15640507,Li,762,Spain,Female,35,3,119349.69,3,1,1,47114.18,1 +9802,15578878,Hancock,569,Spain,Female,30,3,139528.23,1,1,1,33230.37,0 +9803,15744295,Hao,756,France,Male,40,1,94773.11,1,1,0,114279.63,0 +9804,15776558,Nicholls,673,France,Male,31,1,108345.22,1,0,1,38802.03,0 +9805,15596136,Folliero,637,France,Female,36,9,166939.88,1,1,1,72504.76,0 +9806,15704597,Trumbull,644,France,Male,33,7,174571.36,1,0,1,43943.09,0 +9807,15648272,Medvedeva,658,Spain,Male,35,9,71829.34,1,1,1,68141.92,0 +9808,15594915,Crist,649,France,Female,36,8,0,2,0,1,109179.89,0 +9809,15581115,Middleton,603,France,Female,39,9,76769.68,1,0,0,48224.72,0 +9810,15763907,Watts,820,France,Female,39,1,104614.29,1,1,0,61538.43,1 +9811,15705994,Udinese,712,Spain,Male,27,10,0,1,1,0,94544.88,0 +9812,15772421,Tretiakov,645,Germany,Female,31,1,128927.93,1,1,1,2850.01,0 +9813,15711572,O'Kane,705,Germany,Female,31,9,110941.93,2,1,0,163484.8,0 +9814,15691170,Vasilyeva,590,Spain,Female,29,10,99250.08,1,1,1,129629.41,0 +9815,15600106,Wei,631,France,Male,36,1,0,2,0,0,133141.34,0 +9816,15745431,Chinonyelum,604,France,Male,34,7,0,2,1,1,188078.55,0 +9817,15649508,Chin,643,Spain,Male,48,8,0,2,1,0,174729.3,0 +9818,15812611,Lorimer,690,Spain,Female,30,5,0,2,0,1,78700.03,0 +9819,15619699,Yeh,558,France,Male,31,7,0,1,1,0,198269.08,0 +9820,15813946,Duffy,637,Germany,Male,51,1,104682.83,1,1,0,55266.96,1 +9821,15762762,Onyekachukwu,648,Germany,Female,45,5,118886.55,1,0,0,51636.7,0 +9822,15629793,Banks,652,Spain,Male,28,8,156823.7,2,1,0,198251.52,0 +9823,15781298,Hughes,808,Germany,Male,39,3,124216.93,1,0,1,171442.36,0 +9824,15622658,Lai,551,France,Female,26,2,144258.52,1,1,0,49778.79,0 +9825,15658980,Matthews,711,Germany,Male,26,9,128793.63,1,1,0,19262.05,0 +9826,15701936,Bell,467,Germany,Male,28,10,126315.26,1,1,0,32349.29,1 +9827,15686917,Tu,789,Spain,Female,40,4,0,2,1,0,137402.27,0 +9828,15807312,Hsia,602,Spain,Male,33,5,0,2,0,1,64038.34,0 +9829,15574523,Cheng,576,France,Male,39,1,0,2,1,1,68814.23,0 +9830,15724200,Cheng,584,France,Male,38,1,115341.55,1,0,1,173632.92,0 +9831,15738224,Lin,593,France,Male,32,6,99162.29,1,1,0,128384.11,0 +9832,15593283,Higgins,705,Germany,Female,48,1,156848.13,2,1,1,99475.95,1 +9833,15814690,Chukwujekwu,595,Germany,Female,64,2,105736.32,1,1,1,89935.73,1 +9834,15807245,McKay,699,Germany,Female,41,1,200117.76,2,1,0,94142.35,0 +9835,15799358,Vincent,516,France,Female,46,6,62212.29,1,0,1,171681.86,1 +9836,15616172,Ubanwa,838,France,Male,31,2,0,2,1,0,8222.96,0 +9837,15777958,Ch'ien,587,France,Male,39,10,0,2,1,1,170409.45,0 +9838,15809124,T'ien,750,France,Male,38,5,151532.4,1,1,1,46555.15,0 +9839,15616367,Ricci,581,Germany,Male,39,1,121523.51,1,0,0,161655.55,1 +9840,15687385,McDowell,484,France,Male,41,5,0,1,1,1,74267.35,0 +9841,15607877,Maclean,576,Spain,Male,26,8,0,2,0,1,34101.06,0 +9842,15736327,Manna,567,Germany,Female,46,1,68238.51,2,1,1,109572.58,0 +9843,15746704,Jibunoh,638,Spain,Male,30,9,136808.53,2,1,1,106642.97,0 +9844,15778304,Fan,646,Germany,Male,24,0,92398.08,1,1,1,18897.29,0 +9845,15588456,Hsieh,658,France,Female,40,5,143566.12,1,1,1,189607.71,0 +9846,15664035,Parsons,590,Spain,Female,38,9,0,2,1,1,148750.16,0 +9847,15596405,Udinese,546,Spain,Male,25,7,127728.24,2,1,1,105279.74,0 +9848,15815097,Root,603,France,Female,34,9,0,2,1,0,167916.35,0 +9849,15762708,Chiemezie,619,Spain,Female,38,10,119658.49,1,1,1,8646.58,0 +9850,15776211,Toscani,678,France,Female,34,6,0,2,1,1,124592.84,0 +9851,15626012,Obidimkpa,459,France,Male,26,4,149879.66,1,0,0,50016.17,0 +9852,15792077,Degtyaryov,671,Germany,Male,28,8,119859.52,2,1,0,125422.66,0 +9853,15718765,Maclean,501,Spain,Male,43,6,104533.24,1,0,0,81123.59,1 +9854,15576615,Giordano,719,Spain,Male,37,10,145382.61,1,1,0,80408.59,0 +9855,15752650,Saad,681,Spain,Female,37,6,121231.39,1,1,1,146366.08,0 +9856,15797502,Lord,706,Spain,Male,24,2,141078.57,1,1,1,24402.87,0 +9857,15687329,Hope,763,Germany,Female,32,1,108465.65,2,1,0,60552.44,1 +9858,15779423,K?,716,France,Male,39,1,70657.61,2,1,1,76476.05,0 +9859,15619514,Bull,507,Germany,Male,40,3,120105.43,1,1,0,92075.01,1 +9860,15615430,Adams,678,Germany,Male,55,4,129646.91,1,1,1,184125.1,1 +9861,15716431,Brookes,775,France,Female,30,10,191091.74,2,1,1,96170.38,0 +9862,15798341,Victor,544,France,Male,38,8,0,1,1,1,98208.62,0 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+9878,15572182,Onwuamaeze,505,Germany,Female,33,3,106506.77,3,1,0,45445.78,1 +9879,15770041,Manna,728,Spain,Female,43,8,128412.61,1,0,1,139024.31,0 +9880,15669414,Pisano,486,Germany,Male,62,9,118356.89,2,1,0,168034.83,1 +9881,15777054,Thorpe,584,Germany,Male,42,3,137479.13,1,1,0,25669.1,0 +9882,15621021,Dwyer,687,Spain,Female,40,1,0,2,1,0,8207.36,0 +9883,15785490,Okeke,771,France,Male,50,3,105229.72,1,1,1,16281.68,1 +9884,15577695,Zito,678,France,Male,41,2,148088.11,1,1,0,14083.12,0 +9885,15686974,Sergeyeva,751,France,Female,48,4,0,1,0,1,30165.06,1 +9886,15574584,Fang,670,France,Male,33,8,126679.69,1,1,1,39451.09,0 +9887,15719541,Flannagan,675,Spain,Male,31,2,90826.27,2,1,0,60270.87,0 +9888,15646310,Mao,684,Spain,Male,24,8,143582.89,1,1,1,22527.27,0 +9889,15697606,Sturdee,637,France,Female,21,10,125712.2,1,0,0,175072.47,0 +9890,15711489,Azikiwe,760,Spain,Female,32,2,0,1,1,1,114565.35,0 +9891,15670427,Chidi,662,Spain,Male,37,4,155187.3,1,1,0,48930.8,0 +9892,15731755,Hull,680,France,Male,49,10,0,2,1,0,187008.45,0 +9893,15796370,Shah,604,Spain,Male,40,5,155455.43,1,0,1,113581.85,0 +9894,15598331,Morgan,764,France,Female,40,9,100480.53,1,1,0,124095.69,0 +9895,15704795,Vagin,521,France,Female,77,6,0,2,1,1,49054.1,0 +9896,15796764,Bruno,684,Germany,Female,56,3,127585.98,3,1,1,80593.49,1 +9897,15589420,Osinachi,795,France,Female,40,2,101891.1,1,1,1,183044.86,0 +9898,15810563,Ho,678,Spain,Female,61,8,0,2,1,1,159938.82,0 +9899,15746569,Tsui,589,France,Male,38,4,0,1,1,0,95483.48,1 +9900,15811594,Gordon,660,Spain,Female,28,3,128929.88,1,1,1,198069.71,0 +9901,15645896,Duncan,646,Germany,Male,39,6,121681.91,2,0,1,61793.47,0 +9902,15802909,Hu,706,Germany,Female,56,3,139603.22,1,1,1,86383.61,0 +9903,15797665,Docherty,730,France,Female,27,7,0,2,1,0,144099.48,0 +9904,15778959,Brookes,606,France,Female,36,10,0,2,0,1,155641.46,0 +9905,15722532,Angelo,690,Spain,Female,36,10,91760.11,1,1,1,135784.94,0 +9906,15784124,Emenike,645,Germany,Male,41,2,93925.3,1,1,0,123982.14,1 +9907,15776518,Pugh,579,France,Female,38,4,175739.36,1,1,1,193130.55,0 +9908,15611247,McKenzie,481,France,Female,28,10,0,2,1,0,145215.96,0 +9909,15721469,Mach,492,Germany,Male,45,9,170295.04,2,0,0,164741.81,0 +9910,15773338,Endrizzi,739,France,Male,58,2,101579.28,1,1,1,72168.53,0 +9911,15784042,L?,624,France,Male,55,7,118793.6,1,1,1,95022.02,1 +9912,15776229,MacPherson,682,France,Male,44,3,115282.3,1,0,0,23766.4,0 +9913,15655903,Michael,701,Spain,Female,34,6,107980.37,1,1,1,119374.74,0 +9914,15590177,Chiedozie,718,France,Female,44,1,133866.22,1,0,1,139049.24,0 +9915,15568876,Hughes,496,France,Female,34,1,102723.35,2,1,0,180844.81,0 +9916,15813140,Taylor,543,Spain,Male,41,5,0,2,0,1,143980.29,0 +9917,15770516,Evdokimov,616,Spain,Female,44,7,193213.02,2,1,1,137392.77,0 +9918,15755731,Davis,635,Germany,Male,53,8,117005.55,1,0,1,123646.57,1 +9919,15574480,Ubanwa,652,Spain,Male,31,1,132862.59,1,0,0,158054.49,0 +9920,15798084,Murray,688,France,Male,26,0,0,2,1,0,105784.85,0 +9921,15673020,Smith,678,France,Female,49,3,204510.94,1,0,1,738.88,1 +9922,15643575,Evseev,757,Germany,Male,36,1,65349.71,1,0,0,64539.64,0 +9923,15596811,Mitchell,667,France,Male,36,8,139753.35,1,1,0,79871.16,0 +9924,15786789,Ni,725,France,Female,29,6,0,2,1,1,190776.83,0 +9925,15578865,Palerma,632,Germany,Female,50,5,107959.39,1,1,1,6985.34,1 +9926,15605672,Yuan,694,France,Female,38,5,195926.39,1,1,1,85522.84,0 +9927,15603674,Knight,803,France,Male,36,1,0,2,1,1,149370.93,0 +9928,15759915,Rapuokwu,814,France,Female,31,6,87772.52,1,1,0,188516.45,0 +9929,15686219,Wan,611,France,Male,38,4,71018.6,2,1,0,2444.29,0 +9930,15696388,Artamonova,755,Germany,Male,38,4,111096.91,1,1,1,19762.88,0 +9931,15713604,Rossi,425,Germany,Male,40,9,166776.6,2,0,1,172646.88,0 +9932,15647800,Greco,850,France,Female,34,6,101266.51,1,1,0,33501.98,0 +9933,15813451,Fleetwood-Smith,677,Spain,Male,18,8,134796.87,2,1,1,114858.9,0 +9934,15765375,Butusov,797,France,Female,46,8,0,1,0,0,162668.33,0 +9935,15774586,West,692,Germany,Female,43,10,118588.83,1,1,1,161241.65,1 +9936,15603454,Sanders,735,Germany,Male,28,5,160454.15,2,0,1,114957.22,0 +9937,15653037,Parks,609,France,Male,77,1,0,1,0,1,18708.76,0 +9938,15782475,Edith,700,France,Female,42,8,0,2,1,1,105305.72,0 +9939,15593496,Korovin,526,Spain,Female,36,5,91132.18,1,0,0,58111.71,0 +9940,15808971,Lajoie,693,Spain,Female,57,9,0,2,1,1,135502.77,0 +9941,15791972,Bergamaschi,748,France,Female,20,7,0,2,0,0,10792.42,0 +9942,15676869,T'ien,657,Spain,Male,36,8,0,2,0,1,123866.43,0 +9943,15683007,Torode,739,Germany,Female,25,5,113113.12,1,1,0,129181.27,0 +9944,15659495,Fu,784,Spain,Male,23,2,0,1,1,1,6847.73,0 +9945,15703923,Cameron,744,Germany,Male,41,7,190409.34,2,1,1,138361.48,0 +9946,15674000,Cattaneo,645,France,Male,44,10,0,2,0,1,166707.22,0 +9947,15618171,James,669,France,Female,33,9,0,2,0,1,107221.03,0 +9948,15732202,Abramovich,615,France,Male,34,1,83503.11,2,1,1,73124.53,1 +9949,15735078,Onwughara,724,Germany,Female,53,1,139687.66,2,1,1,12913.92,0 +9950,15798615,Wan,850,France,Female,47,9,137301.87,1,1,0,44351.77,0 +9951,15638494,Salinas,625,Germany,Female,39,10,129845.26,1,1,1,96444.88,0 +9952,15763874,Ho,635,Spain,Male,46,8,0,2,1,1,60739.16,0 +9953,15696355,Cleveland,724,Germany,Male,37,6,125489.4,1,1,0,118570.53,0 +9954,15655952,Burke,550,France,Male,47,2,0,2,1,1,97057.28,0 +9955,15739850,Trentino,645,France,Male,45,6,155417.61,1,0,1,3449.22,0 +9956,15611338,Kashiwagi,714,Spain,Male,29,4,0,2,1,1,37605.9,0 +9957,15707861,Nucci,520,France,Female,46,10,85216.61,1,1,0,117369.52,1 +9958,15672237,Oluchi,633,France,Male,25,1,0,1,1,0,100598.98,0 +9959,15657771,Ts'ui,537,France,Male,37,6,0,1,1,1,17802.42,0 +9960,15677783,Graham,764,Spain,Male,38,4,113607.47,1,1,0,91094.46,0 +9961,15681026,Lucciano,795,Germany,Female,33,9,104552.72,1,1,1,120853.83,1 +9962,15566543,Aldridge,573,Spain,Male,44,9,0,2,1,0,107124.17,0 +9963,15594612,Flynn,702,Spain,Male,44,9,0,1,0,0,59207.41,1 +9964,15814664,Scott,740,Germany,Male,33,2,126524.11,1,1,0,136869.31,0 +9965,15642785,Douglas,479,France,Male,34,5,117593.48,2,0,0,113308.29,0 +9966,15690164,Shao,627,Germany,Female,33,4,83199.05,1,0,0,159334.93,0 +9967,15590213,Ch'en,479,Spain,Male,35,4,125920.98,1,1,1,20393.44,0 +9968,15603794,Pugliesi,623,France,Male,48,5,118469.38,1,1,1,158590.25,0 +9969,15733491,McGregor,512,Germany,Female,40,8,153537.57,2,0,0,23101.13,0 +9970,15806360,Hou,609,France,Male,41,6,0,1,0,1,112585.19,0 +9971,15587133,Thompson,518,France,Male,42,7,151027.05,2,1,0,119377.36,0 +9972,15721377,Chou,833,France,Female,34,3,144751.81,1,0,0,166472.81,0 +9973,15747927,Ch'in,758,France,Male,26,4,155739.76,1,1,0,171552.02,0 +9974,15806455,Miller,611,France,Male,27,7,0,2,1,1,157474.1,0 +9975,15695474,Barker,583,France,Male,33,7,122531.86,1,1,0,13549.24,0 +9976,15666295,Smith,610,Germany,Male,50,1,113957.01,2,1,0,196526.55,1 +9977,15656062,Azikiwe,637,France,Female,33,7,103377.81,1,1,0,84419.78,0 +9978,15579969,Mancini,683,France,Female,32,9,0,2,1,1,24991.92,0 +9979,15703563,P'eng,774,France,Male,40,9,93017.47,2,1,0,191608.97,0 +9980,15692664,Diribe,677,France,Female,58,1,90022.85,1,0,1,2988.28,0 +9981,15719276,T'ao,741,Spain,Male,35,6,74371.49,1,0,0,99595.67,0 +9982,15672754,Burbidge,498,Germany,Male,42,3,152039.7,1,1,1,53445.17,1 +9983,15768163,Griffin,655,Germany,Female,46,7,137145.12,1,1,0,115146.4,1 +9984,15656710,Cocci,613,France,Male,40,4,0,1,0,0,151325.24,0 +9985,15696175,Echezonachukwu,602,Germany,Male,35,7,90602.42,2,1,1,51695.41,0 +9986,15586914,Nepean,659,France,Male,36,6,123841.49,2,1,0,96833,0 +9987,15581736,Bartlett,673,Germany,Male,47,1,183579.54,2,0,1,34047.54,0 +9988,15588839,Mancini,606,Spain,Male,30,8,180307.73,2,1,1,1914.41,0 +9989,15589329,Pirozzi,775,France,Male,30,4,0,2,1,0,49337.84,0 +9990,15605622,McMillan,841,Spain,Male,28,4,0,2,1,1,179436.6,0 +9991,15798964,Nkemakonam,714,Germany,Male,33,3,35016.6,1,1,0,53667.08,0 +9992,15769959,Ajuluchukwu,597,France,Female,53,4,88381.21,1,1,0,69384.71,1 +9993,15657105,Chukwualuka,726,Spain,Male,36,2,0,1,1,0,195192.4,0 +9994,15569266,Rahman,644,France,Male,28,7,155060.41,1,1,0,29179.52,0 +9995,15719294,Wood,800,France,Female,29,2,0,2,0,0,167773.55,0 +9996,15606229,Obijiaku,771,France,Male,39,5,0,2,1,0,96270.64,0 +9997,15569892,Johnstone,516,France,Male,35,10,57369.61,1,1,1,101699.77,0 +9998,15584532,Liu,709,France,Female,36,7,0,1,0,1,42085.58,1 +9999,15682355,Sabbatini,772,Germany,Male,42,3,75075.31,2,1,0,92888.52,1 +10000,15628319,Walker,792,France,Female,28,4,130142.79,1,1,0,38190.78,0 diff --git a/models/model.pk b/models/model.pk index 62552a2f469d2dcf40e712a4591748b34c5ed872..1da145eb95b71b4ec8f69a008c7bf622dcfe872d 100644 GIT binary patch literal 369831 zcmb5%1zZ(N|M+q2#<+F|c6U1}Hg-26V4OOR&tNoy{u8w08esCY+Fv^+zMvimy 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+ " 4815\n", + " 0.850\n", + " 0.5\n", " 0.0\n", - " 1.0\n", - " 0.567568\n", - " 0.8\n", - " 0.739936\n", + " 0.797297\n", + " 0.6\n", + " 0.538548\n", " 0.000000\n", + " 1.0\n", " 0.0\n", + " 0.189143\n", " 0.0\n", - " 0.960817\n", - " 1.0\n", " \n", " \n", - " 4508\n", - " 0.498\n", - " 0.0\n", - " 0.0\n", - " 0.310811\n", - " 0.1\n", - " 0.000000\n", - " 0.333333\n", + " 4500\n", + " 0.842\n", + " 0.5\n", " 1.0\n", + " 0.189189\n", + " 0.9\n", + " 0.308839\n", + " 0.000000\n", " 0.0\n", - " 0.480337\n", + " 0.0\n", + " 0.165673\n", " 0.0\n", " \n", " \n", - " 5379\n", - " 0.554\n", - " 0.0\n", + " 5068\n", + " 0.724\n", + " 1.0\n", " 0.0\n", - " 0.040541\n", - " 0.7\n", - " 0.394555\n", + " 0.824324\n", + " 0.5\n", + " 0.430767\n", " 0.000000\n", " 1.0\n", " 1.0\n", - " 0.845806\n", + " 0.870620\n", " 0.0\n", " \n", " \n", - " 4091\n", - " 0.498\n", - " 0.5\n", + " 7282\n", + " 0.462\n", " 1.0\n", - " 0.283784\n", - " 0.2\n", - " 0.753202\n", - " 0.333333\n", " 0.0\n", + " 0.351351\n", + " 0.7\n", + " 0.754562\n", + " 0.333333\n", " 1.0\n", - " 0.880737\n", " 0.0\n", + " 0.225095\n", + " 1.0\n", " \n", " \n", - " 1831\n", - " 0.564\n", - " 0.0\n", + " 185\n", + " 0.328\n", " 0.0\n", - " 0.243243\n", - " 0.7\n", + " 1.0\n", + " 0.189189\n", + " 0.8\n", " 0.000000\n", " 0.333333\n", " 1.0\n", - " 1.0\n", - " 0.262600\n", + " 0.0\n", + " 0.479274\n", " 0.0\n", " \n", " \n", - " 8254\n", - " 0.574\n", + " 7301\n", + " 0.834\n", " 0.5\n", - " 1.0\n", - " 0.135135\n", - " 0.3\n", - " 0.492932\n", + " 0.0\n", + " 0.202703\n", + " 0.1\n", + " 0.576940\n", " 0.000000\n", " 1.0\n", " 1.0\n", - " 0.832314\n", + " 0.662409\n", " 0.0\n", " \n", " \n", @@ -572,28 +572,28 @@ ], "text/plain": [ " CreditScore Geography Gender Age Tenure Balance \\\n", - "4335 0.716 1.0 0.0 0.621622 0.5 0.000000 \n", - "3186 0.574 0.5 0.0 0.243243 1.0 0.580915 \n", - "40 0.244 1.0 1.0 0.297297 0.4 0.000000 \n", - "4404 0.508 1.0 1.0 0.337838 0.2 0.578250 \n", - "5114 0.656 0.0 1.0 0.567568 0.8 0.739936 \n", - "4508 0.498 0.0 0.0 0.310811 0.1 0.000000 \n", - "5379 0.554 0.0 0.0 0.040541 0.7 0.394555 \n", - "4091 0.498 0.5 1.0 0.283784 0.2 0.753202 \n", - "1831 0.564 0.0 0.0 0.243243 0.7 0.000000 \n", - "8254 0.574 0.5 1.0 0.135135 0.3 0.492932 \n", + "9355 0.778 1.0 0.0 0.297297 0.8 0.000000 \n", + "4272 0.580 1.0 0.0 0.216216 0.3 0.310193 \n", + "89 0.570 0.5 0.0 0.135135 0.3 0.325326 \n", + "4424 0.502 0.5 0.0 0.391892 0.1 0.569163 \n", + "4815 0.850 0.5 0.0 0.797297 0.6 0.538548 \n", + "4500 0.842 0.5 1.0 0.189189 0.9 0.308839 \n", + "5068 0.724 1.0 0.0 0.824324 0.5 0.430767 \n", + "7282 0.462 1.0 0.0 0.351351 0.7 0.754562 \n", + "185 0.328 0.0 1.0 0.189189 0.8 0.000000 \n", + "7301 0.834 0.5 0.0 0.202703 0.1 0.576940 \n", "\n", " NumOfProducts HasCrCard IsActiveMember EstimatedSalary Exited \n", - "4335 0.666667 0.0 1.0 0.562596 1.0 \n", - "3186 0.333333 1.0 1.0 0.483292 0.0 \n", - "40 0.000000 1.0 0.0 0.350747 0.0 \n", - "4404 0.000000 1.0 1.0 0.119362 0.0 \n", - "5114 0.000000 0.0 0.0 0.960817 1.0 \n", - "4508 0.333333 1.0 0.0 0.480337 0.0 \n", - "5379 0.000000 1.0 1.0 0.845806 0.0 \n", - "4091 0.333333 0.0 1.0 0.880737 0.0 \n", - "1831 0.333333 1.0 1.0 0.262600 0.0 \n", - "8254 0.000000 1.0 1.0 0.832314 0.0 " + "9355 0.000000 1.0 0.0 0.835174 0.0 \n", + "4272 0.000000 1.0 1.0 0.842747 0.0 \n", + "89 0.333333 1.0 1.0 0.783974 0.0 \n", + "4424 0.000000 1.0 1.0 0.287735 0.0 \n", + "4815 0.000000 1.0 0.0 0.189143 0.0 \n", + "4500 0.000000 0.0 0.0 0.165673 0.0 \n", + "5068 0.000000 1.0 1.0 0.870620 0.0 \n", + "7282 0.333333 1.0 0.0 0.225095 1.0 \n", + "185 0.333333 1.0 0.0 0.479274 0.0 \n", + "7301 0.000000 1.0 1.0 0.662409 0.0 " ] }, "execution_count": 11, @@ -627,7 +627,8 @@ "source": [ "# Vamos a crear un modelo de regresion logistica\n", "from sklearn.model_selection import train_test_split\n", - "from sklearn.linear_model import LogisticRegression\n" + "from sklearn.svm import SVC\n", + "seed=42" ] }, { @@ -644,7 +645,7 @@ }, { "cell_type": "code", - "execution_count": 28, + "execution_count": 14, "id": "8721e498", "metadata": {}, "outputs": [], @@ -658,262 +659,87 @@ }, { "cell_type": "code", - "execution_count": 29, + "execution_count": 15, "id": "8a6ee78f-7c8b-4810-a763-c8b20155ec28", "metadata": {}, "outputs": [], "source": [ "# Separar los datos en datos de entrenamiento y testing\n", - "X_train, X_test, y_train, y_test = train_test_split( X, y, test_size=0.33, random_state=42)" + "X_train, X_test, y_train, y_test = train_test_split( X, y, test_size=0.33, random_state=42)\n", + "# Crear el modelo base\n", + "svm = SVC(random_state=seed)" ] }, { "cell_type": "code", - "execution_count": 30, + "execution_count": 16, "id": "8cd168ca", "metadata": {}, "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "Fitting 5 folds for each of 100 candidates, totalling 500 fits\n" - ] - }, - { - "name": "stderr", - "output_type": "stream", - "text": [ - "/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py:425: FitFailedWarning: \n", - "335 fits failed out of a total of 500.\n", - "The score on these train-test partitions for these parameters will be set to 0.\n", - "If these failures are not expected, you can try to debug them by setting error_score='raise'.\n", - "\n", - "Below are more details about the failures:\n", - "--------------------------------------------------------------------------------\n", - "35 fits failed with the following error:\n", - "Traceback (most recent call last):\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", - " estimator.fit(X_train, y_train, **fit_params)\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1151, in wrapper\n", - " return fit_method(estimator, *args, **kwargs)\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 1168, in fit\n", - " solver = _check_solver(self.solver, self.penalty, self.dual)\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 56, in _check_solver\n", - " raise ValueError(\n", - "ValueError: Solver newton-cg supports only 'l2' or 'none' penalties, got elasticnet penalty.\n", - "\n", - "--------------------------------------------------------------------------------\n", - "25 fits failed with the following error:\n", - "Traceback (most recent call last):\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", - " estimator.fit(X_train, y_train, **fit_params)\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1151, in wrapper\n", - " return fit_method(estimator, *args, **kwargs)\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 1168, in fit\n", - " solver = _check_solver(self.solver, self.penalty, self.dual)\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 56, in _check_solver\n", - " raise ValueError(\n", - "ValueError: Solver sag supports only 'l2' or 'none' penalties, got l1 penalty.\n", - "\n", - "--------------------------------------------------------------------------------\n", - "20 fits failed with the following error:\n", - "Traceback (most recent call last):\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", - " estimator.fit(X_train, y_train, **fit_params)\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1151, in wrapper\n", - " return fit_method(estimator, *args, **kwargs)\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 1168, in fit\n", - " solver = _check_solver(self.solver, self.penalty, self.dual)\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 56, in _check_solver\n", - " raise ValueError(\n", - "ValueError: Solver lbfgs supports only 'l2' or 'none' penalties, got elasticnet penalty.\n", - "\n", - "--------------------------------------------------------------------------------\n", - "52 fits failed with the following error:\n", - "Traceback (most recent call last):\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", - " estimator.fit(X_train, y_train, **fit_params)\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1144, in wrapper\n", - " estimator._validate_params()\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 637, in _validate_params\n", - " validate_parameter_constraints(\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/utils/_param_validation.py\", line 95, in validate_parameter_constraints\n", - " raise InvalidParameterError(\n", - "sklearn.utils._param_validation.InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'l1', 'none' (deprecated), 'l2', 'elasticnet'} or None. Got 'None' instead.\n", - "\n", - "--------------------------------------------------------------------------------\n", - "33 fits failed with the following error:\n", - "Traceback (most recent call last):\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", - " estimator.fit(X_train, y_train, **fit_params)\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1144, in wrapper\n", - " estimator._validate_params()\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 637, in _validate_params\n", - " validate_parameter_constraints(\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/utils/_param_validation.py\", line 95, in validate_parameter_constraints\n", - " raise InvalidParameterError(\n", - "sklearn.utils._param_validation.InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'none' (deprecated), 'l1', 'elasticnet', 'l2'} or None. Got 'None' instead.\n", - "\n", - "--------------------------------------------------------------------------------\n", - "25 fits failed with the following error:\n", - "Traceback (most recent call last):\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", - " estimator.fit(X_train, y_train, **fit_params)\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1144, in wrapper\n", - " estimator._validate_params()\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 637, in _validate_params\n", - " validate_parameter_constraints(\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/utils/_param_validation.py\", line 95, in validate_parameter_constraints\n", - " raise InvalidParameterError(\n", - "sklearn.utils._param_validation.InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'elasticnet', 'none' (deprecated), 'l2', 'l1'} or None. Got 'None' instead.\n", - "\n", - "--------------------------------------------------------------------------------\n", - "40 fits failed with the following error:\n", - "Traceback (most recent call last):\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", - " estimator.fit(X_train, y_train, **fit_params)\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1144, in wrapper\n", - " estimator._validate_params()\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 637, in _validate_params\n", - " validate_parameter_constraints(\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/utils/_param_validation.py\", line 95, in validate_parameter_constraints\n", - " raise InvalidParameterError(\n", - "sklearn.utils._param_validation.InvalidParameterError: The 'penalty' parameter of LogisticRegression must be a str among {'l1', 'l2', 'none' (deprecated), 'elasticnet'} or None. Got 'None' instead.\n", - "\n", - "--------------------------------------------------------------------------------\n", - "25 fits failed with the following error:\n", - "Traceback (most recent call last):\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", - " estimator.fit(X_train, y_train, **fit_params)\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1151, in wrapper\n", - " return fit_method(estimator, *args, **kwargs)\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 1178, in fit\n", - " raise ValueError(\"l1_ratio must be specified when penalty is elasticnet.\")\n", - "ValueError: l1_ratio must be specified when penalty is elasticnet.\n", - "\n", - "--------------------------------------------------------------------------------\n", - "10 fits failed with the following error:\n", - "Traceback (most recent call last):\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", - " estimator.fit(X_train, y_train, **fit_params)\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1151, in wrapper\n", - " return fit_method(estimator, *args, **kwargs)\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 1168, in fit\n", - " solver = _check_solver(self.solver, self.penalty, self.dual)\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 56, in _check_solver\n", - " raise ValueError(\n", - "ValueError: Solver lbfgs supports only 'l2' or 'none' penalties, got l1 penalty.\n", - "\n", - "--------------------------------------------------------------------------------\n", - "15 fits failed with the following error:\n", - "Traceback (most recent call last):\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", - " estimator.fit(X_train, y_train, **fit_params)\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1151, in wrapper\n", - " return fit_method(estimator, *args, **kwargs)\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 1168, in fit\n", - " solver = _check_solver(self.solver, self.penalty, self.dual)\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 56, in _check_solver\n", - " raise ValueError(\n", - "ValueError: Solver sag supports only 'l2' or 'none' penalties, got elasticnet penalty.\n", - "\n", - "--------------------------------------------------------------------------------\n", - "25 fits failed with the following error:\n", - "Traceback (most recent call last):\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", - " estimator.fit(X_train, y_train, **fit_params)\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1151, in wrapper\n", - " return fit_method(estimator, *args, **kwargs)\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 1168, in fit\n", - " solver = _check_solver(self.solver, self.penalty, self.dual)\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 56, in _check_solver\n", - " raise ValueError(\n", - "ValueError: Solver newton-cg supports only 'l2' or 'none' penalties, got l1 penalty.\n", - "\n", - "--------------------------------------------------------------------------------\n", - "30 fits failed with the following error:\n", - "Traceback (most recent call last):\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/model_selection/_validation.py\", line 732, in _fit_and_score\n", - " estimator.fit(X_train, y_train, **fit_params)\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/base.py\", line 1151, in wrapper\n", - " return fit_method(estimator, *args, **kwargs)\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 1168, in fit\n", - " solver = _check_solver(self.solver, self.penalty, self.dual)\n", - " ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n", - " File \"/usr/local/python/3.12.1/lib/python3.12/site-packages/sklearn/linear_model/_logistic.py\", line 66, in _check_solver\n", - " raise ValueError(\n", - "ValueError: Only 'saga' solver supports elasticnet penalty, got solver=liblinear.\n", - "\n", - " warnings.warn(some_fits_failed_message, FitFailedWarning)\n" - ] - }, { "data": { "text/html": [ - "

RandomizedSearchCV(error_score=0,\n",
-       "                   estimator=LogisticRegression(multi_class='ovr',\n",
-       "                                                random_state=42),\n",
-       "                   n_iter=100, n_jobs=-1,\n",
-       "                   param_distributions={'C': array([1.00000000e-04, 2.63665090e-04, 6.95192796e-04, 1.83298071e-03,\n",
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-       "       2.33572147e-01, 6.15848211e-01, 1.62377674e+00, 4.28133240e+00,\n",
-       "       1.12883789e+01, 2.976...\n",
-       "                                                   'liblinear', 'sag', 'saga'],\n",
-       "                                        'tol': array([1.00000000e-04, 1.83298071e-04, 3.35981829e-04, 6.15848211e-04,\n",
-       "       1.12883789e-03, 2.06913808e-03, 3.79269019e-03, 6.95192796e-03,\n",
-       "       1.27427499e-02, 2.33572147e-02, 4.28133240e-02, 7.84759970e-02,\n",
-       "       1.43844989e-01, 2.63665090e-01, 4.83293024e-01, 8.85866790e-01,\n",
-       "       1.62377674e+00, 2.97635144e+00, 5.45559478e+00, 1.00000000e+01])},\n",
-       "                   random_state=42, verbose=1)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" + "
RandomizedSearchCV(estimator=SVC(random_state=42), n_iter=50, n_jobs=-1,\n",
+       "                   param_distributions=[{'C': [1.0, 2.0, 5.0, 10.0, 25.0, 100.0,\n",
+       "                                               500.0, 1000.0],\n",
+       "                                         'kernel': ['linear'],\n",
+       "                                         'tol': [0.01, 0.001, 0.0001, 1e-05]},\n",
+       "                                        {'C': [1.0, 2.0, 5.0, 10.0, 25.0, 100.0,\n",
+       "                                               500.0, 1000.0],\n",
+       "                                         'gamma': [0.1, 0.2, 0.3, 0.4, 0.5, 0.6,\n",
+       "                                                   0.7, 0.8, 0.9],\n",
+       "                                         'kernel': ['rbf'],\n",
+       "                                         'tol': [0.01, 0.001, 0.0001, 1e-05]},\n",
+       "                                        {'C': [1.0, 2.0, 5.0, 10.0, 25.0, 100.0,\n",
+       "                                               500.0, 1000.0],\n",
+       "                                         'degree': [2, 3, 4, 5, 6],\n",
+       "                                         'gamma': [0.01, 0.02, 0.03, 0.04,\n",
+       "                                                   0.05],\n",
+       "                                         'kernel': ['poly'],\n",
+       "                                         'tol': [0.01, 0.001, 0.0001, 1e-05]}],\n",
+       "                   random_state=42)
In a Jupyter environment, please rerun this cell to show the HTML representation or trust the notebook.
On GitHub, the HTML representation is unable to render, please try loading this page with nbviewer.org.
" ], "text/plain": [ - "RandomizedSearchCV(error_score=0,\n", - " estimator=LogisticRegression(multi_class='ovr',\n", - " random_state=42),\n", - " n_iter=100, n_jobs=-1,\n", - " param_distributions={'C': array([1.00000000e-04, 2.63665090e-04, 6.95192796e-04, 1.83298071e-03,\n", - " 4.83293024e-03, 1.27427499e-02, 3.35981829e-02, 8.85866790e-02,\n", - " 2.33572147e-01, 6.15848211e-01, 1.62377674e+00, 4.28133240e+00,\n", - " 1.12883789e+01, 2.976...\n", - " 'liblinear', 'sag', 'saga'],\n", - " 'tol': array([1.00000000e-04, 1.83298071e-04, 3.35981829e-04, 6.15848211e-04,\n", - " 1.12883789e-03, 2.06913808e-03, 3.79269019e-03, 6.95192796e-03,\n", - " 1.27427499e-02, 2.33572147e-02, 4.28133240e-02, 7.84759970e-02,\n", - " 1.43844989e-01, 2.63665090e-01, 4.83293024e-01, 8.85866790e-01,\n", - " 1.62377674e+00, 2.97635144e+00, 5.45559478e+00, 1.00000000e+01])},\n", - " random_state=42, verbose=1)" + "RandomizedSearchCV(estimator=SVC(random_state=42), n_iter=50, n_jobs=-1,\n", + " param_distributions=[{'C': [1.0, 2.0, 5.0, 10.0, 25.0, 100.0,\n", + " 500.0, 1000.0],\n", + " 'kernel': ['linear'],\n", + " 'tol': [0.01, 0.001, 0.0001, 1e-05]},\n", + " {'C': [1.0, 2.0, 5.0, 10.0, 25.0, 100.0,\n", + " 500.0, 1000.0],\n", + " 'gamma': [0.1, 0.2, 0.3, 0.4, 0.5, 0.6,\n", + " 0.7, 0.8, 0.9],\n", + " 'kernel': ['rbf'],\n", + " 'tol': [0.01, 0.001, 0.0001, 1e-05]},\n", + " {'C': [1.0, 2.0, 5.0, 10.0, 25.0, 100.0,\n", + " 500.0, 1000.0],\n", + " 'degree': [2, 3, 4, 5, 6],\n", + " 'gamma': [0.01, 0.02, 0.03, 0.04,\n", + " 0.05],\n", + " 'kernel': ['poly'],\n", + " 'tol': [0.01, 0.001, 0.0001, 1e-05]}],\n", + " random_state=42)" ] }, - "execution_count": 30, + "execution_count": 16, "metadata": {}, "output_type": "execute_result" } @@ -923,28 +749,24 @@ "from sklearn.model_selection import RandomizedSearchCV\n", "\n", "# Definir el espacio de búsqueda de hiperparámetros\n", - "param_dist = {\n", - " 'solver': ['newton-cg', 'lbfgs', 'liblinear', 'sag', 'saga'],\n", - " 'penalty': ['l1', 'l2', 'elasticnet', 'None'], \n", - " 'C': np.logspace(-4, 4, 20),\n", - " 'tol': np.logspace(-4, 1, 20)\n", - "}\n", - "\n", - "# Crear el modelo base\n", - "log_reg = LogisticRegression(random_state=42, multi_class='ovr')\n", + "param_distribution = [ {'C':[1.0,2.0,5.0,10.0,25.0,100.0,500.0,1000.0], 'kernel':['linear'],'tol':[1e-2,1e-3,1e-4,1e-5]},\n", + " {'C':[1.0,2.0,5.0,10.0,25.0,100.0,500.0,1000.0], 'kernel':['rbf'], 'gamma':[0.1, 0.2, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9],'tol':[1e-2,1e-3,1e-4,1e-5]},\n", + " {'C':[1.0,2.0,5.0,10.0,25.0,100.0,500.0,1000.0], 'kernel':['poly'], 'degree': [2,3,4,5,6] ,'gamma':[0.01,0.02,0.03,0.04,0.05],'tol':[1e-2,1e-3,1e-4,1e-5]}]\n", "\n", - "# Configurar la búsqueda aleatoria\n", - "\n", - "random_search = RandomizedSearchCV(log_reg, param_distributions=param_dist, n_iter=100, verbose=1, n_jobs=-1, random_state=42, error_score=0)\n", + "#Usamos RandomizedSearchCV teniendo en cuenta que este módelo no explora todas las combinaciones sino solo las que se indiquen en n_iter de forma aleatoria\n", + "random_search = RandomizedSearchCV(estimator=svm,\n", + " param_distributions=param_distribution,\n", + " n_iter=50,\n", + " random_state=seed,\n", + " n_jobs=-1)\n", "\n", "# Ejecutar la búsqueda aleatoria\n", - "random_search.fit(X_train, y_train)\n", - "#Tener en cuenta que algunas combinaciones de hiperparametros pueden no ser posible" + "random_search.fit(X_train, y_train)" ] }, { "cell_type": "code", - "execution_count": 31, + "execution_count": 17, "id": "64b64908", "metadata": {}, "outputs": [ @@ -953,11 +775,11 @@ "output_type": "stream", "text": [ "Las 5 mejores combinaciones de hiperparámetros:\n", - "Combinación 82: {'tol': 0.04281332398719392, 'solver': 'saga', 'penalty': 'l1', 'C': 0.23357214690901212}, Puntuación: 0.711\n", - "Combinación 99: {'tol': 0.8858667904100823, 'solver': 'saga', 'penalty': 'l2', 'C': 545.5594781168514}, Puntuación: 0.709\n", - "Combinación 37: {'tol': 5.455594781168514, 'solver': 'newton-cg', 'penalty': 'l2', 'C': 29.763514416313132}, Puntuación: 0.708\n", - "Combinación 43: {'tol': 0.0006158482110660267, 'solver': 'sag', 'penalty': 'l2', 'C': 29.763514416313132}, Puntuación: 0.708\n", - "Combinación 64: {'tol': 0.0003359818286283781, 'solver': 'saga', 'penalty': 'l1', 'C': 0.08858667904100823}, Puntuación: 0.708\n" + "Combinación 8: {'tol': 0.001, 'kernel': 'rbf', 'gamma': 0.5, 'C': 500.0}, Puntuación: 0.822\n", + "Combinación 1: {'tol': 1e-05, 'kernel': 'rbf', 'gamma': 0.8, 'C': 100.0}, Puntuación: 0.822\n", + "Combinación 10: {'tol': 0.01, 'kernel': 'rbf', 'gamma': 0.4, 'C': 1000.0}, Puntuación: 0.822\n", + "Combinación 9: {'tol': 0.01, 'kernel': 'rbf', 'gamma': 0.7, 'C': 5.0}, Puntuación: 0.796\n", + "Combinación 2: {'tol': 0.001, 'kernel': 'rbf', 'gamma': 0.9, 'C': 2.0}, Puntuación: 0.794\n" ] } ], @@ -978,7 +800,7 @@ }, { "cell_type": "code", - "execution_count": 41, + "execution_count": 18, "id": "d0ee8400", "metadata": {}, "outputs": [ @@ -986,9 +808,15 @@ "name": "stdout", "output_type": "stream", "text": [ - "Fitting 5 folds for each of 1200 candidates, totalling 6000 fits\n", - "Mejores hiperparámetros: {'C': 0.3, 'penalty': 'l1', 'solver': 'saga', 'tol': 0.1}\n", - "Mejor puntuación: 0.712\n" + "Fitting 3 folds for each of 63 candidates, totalling 189 fits\n" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "Mejores hiperparámetros: {'C': 1000.0, 'gamma': 0.9, 'kernel': 'rbf', 'tol': 0.0001}\n", + "Mejor puntuación: 0.837\n" ] } ], @@ -996,27 +824,13 @@ "from sklearn.model_selection import GridSearchCV\n", "\n", "# Definir el espacio de búsqueda de hiperparámetros alrededor de los mejores encontrados\n", - "\n", - "param_grid = [\n", - " {\n", - " 'solver': ['saga'], # saga soporta tanto l1 como l2\n", - " 'penalty': ['l1', 'l2'],\n", - " 'C': np.linspace(0.01, 0.3, 30),\n", - " 'tol': np.logspace(-4, -1, 10)\n", - " },\n", - " {\n", - " 'solver': ['sag','newton-cg'], # sag y newton-cg solo soportan l2\n", - " 'penalty': ['l2'],\n", - " 'C': np.linspace(0.01, 0.3, 30),\n", - " 'tol': np.logspace(-4, -1, 10)\n", - " }\n", - "]\n", - "\n", - "# Crear el modelo base\n", - "log_reg = LogisticRegression(random_state=42, multi_class='ovr')\n", + "param_grid = {'C':np.logspace(1, 3, 3),\n", + " 'kernel':['rbf'], \n", + " 'gamma':np.linspace(0.6,0.9,7),\n", + " 'tol':np.logspace(-4, -2, 3)}\n", "\n", "# Configurar la búsqueda en cuadrícula\n", - "grid_search = GridSearchCV(log_reg, param_grid=param_grid, cv=5, verbose=1, n_jobs=-1)\n", + "grid_search = GridSearchCV(estimator=svm, param_grid=param_grid, cv=3, verbose=1, n_jobs=-1)\n", "\n", "# Ejecutar la búsqueda en cuadrícula\n", "grid_search.fit(X_train, y_train)\n", @@ -1028,13 +842,13 @@ }, { "cell_type": "code", - "execution_count": 42, + "execution_count": 19, "id": "409f0391-4500-41fd-85a9-e501ecdd9329", "metadata": {}, "outputs": [], "source": [ "# Entrenar el modelo con los mejores hiperparametros\n", - "clf_lin = LogisticRegression(random_state=42, multi_class='ovr', **grid_search.best_params_).fit(X_train, y_train)" + "svm = SVC(random_state=42, **grid_search.best_params_).fit(X_train, y_train)" ] }, { @@ -1047,13 +861,13 @@ }, { "cell_type": "code", - "execution_count": 43, + "execution_count": 20, "id": "753ab797-0b07-4e27-a497-9518034451a9", "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", 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" ] @@ -1067,7 +881,7 @@ "import matplotlib.pyplot as plt\n", "import seaborn as sns\n", "from sklearn.metrics import confusion_matrix\n", - "cm = confusion_matrix(y_test, clf_lin.predict(X_test))\n", + "cm = confusion_matrix(y_test, svm.predict(X_test))\n", "\n", "#Visualizar la matriz de confusión\n", "plt.figure(figsize=(9,9))\n", @@ -1080,7 +894,7 @@ }, { "cell_type": "code", - "execution_count": 44, + "execution_count": 22, "id": "1e21c8b3", "metadata": {}, "outputs": [ @@ -1088,10 +902,10 @@ "name": "stdout", "output_type": "stream", "text": [ - "Accuracy model: 0.698\n", - "Exited Churn='NO': 0.626\n", - "Exited Churn='YES': 0.772\n", - "F1 Score: 0.716\n" + "Accuracy model: 0.853\n", + "Exited Churn='NO': 0.814\n", + "Exited Churn='YES': 0.892\n", + "F1 Score: 0.857\n" ] } ], @@ -1100,7 +914,7 @@ "from sklearn.metrics import accuracy_score, recall_score, f1_score\n", "\n", "# Predecir resultados con los datos de prueba\n", - "prediction_test = clf_lin.predict(X_test)\n", + "prediction_test = svm.predict(X_test)\n", "\n", "# Exactitud: proporción de predicciones correctas.\n", "print(f\"Accuracy model: {accuracy_score(y_test, prediction_test):.3f}\")\n", @@ -1124,7 +938,7 @@ }, { "cell_type": "code", - "execution_count": 45, + "execution_count": 23, "id": "20f25624-4ba7-4c0d-a79a-590d1884b7d0", "metadata": {}, "outputs": [], @@ -1134,7 +948,7 @@ "#Tener en cuenta esta nota de la documentación de Python\n", "#\"Warning: The pickle module is not secure. Only unpickle data you trust.\"\n", "\n", - "pickle.dump(clf_lin, open(\"models/model.pk\", \"wb\"))\n", + "pickle.dump(svm, open(\"models/model.pk\", \"wb\"))\n", "pickle.dump(column_equivalence, open(\"models/column_equivalence.pk\", \"wb\"))\n", "pickle.dump(features, open(\"models/features.pk\", \"wb\"))" ]