DA_Project

Doctor Visit Data Analysis

IBM SkillBuild Internship DA_Project

Overview

This project aims to perform a comprehensive data analysis, summarization, and visualization of the "Doctor_visit" dataset. The dataset contains information about patients, including their gender, age, income, illness, and various other attributes collected during their visits to the hospital before going home. The goal is to gain valuable insights and identify patterns or trends related to the patients and their characteristics.

Objectives

• Conduct exploratory data analysis (EDA) to understand the distribution and relationships of the data.
• Perform data cleaning and preprocessing to handle missing values or inconsistencies.
• Summarize key statistics and metrics for different attributes in the dataset.
• Visualize the data using various charts, graphs, and plots to uncover patterns and trends.
• Identify any correlations between different attributes and their impact on patient visits.
• Provide actionable insights and recommendations based on the analysis.

Features

• Utilizes Python programming language for data analysis and visualization.
• Utilizes popular libraries like Pandas, NumPy, Matplotlib, Seaborn for data manipulation and visualization.
• Performs data cleaning and preprocessing to ensure data quality.
• Generates descriptive statistics, including mean, median, mode, standard deviation, etc.
• Creates various types of visualizations, including bar charts, line plots, scatter plots, histograms, etc.
• Identifies outliers or anomalies in the data and explores their significance.
• Applies statistical tests or machine learning techniques for deeper analysis if required.
• Ensures clear documentation and code commenting for better understanding and collaboration.

Installation

1. Clone the repository:

git clone https://github.com/your_username/doctor-visit-data-analysis.git

Data

The dataset "DoctorVisits - DA.csv" contains information about patients, including their gender, age, income, illness, and other attributes. The data is available in the / directory.

Usage

• Run the Jupyter notebook DA_Project.ipynb to perform data analysis and visualization.
• Execute the Python script for generating specific visualizations or conducting additional analysis.

Results

The project will provide valuable insights into patient characteristics, trends, and their impact on hospital visits. The visualizations will help stakeholders make informed decisions and improve patient care.

For any questions or feedback, please feel free to contact me at ronikkumarsakala@gmail.com.