This repository contains my python projects
In this project I extracted financial data like historical share price and quarterly revenue reportings from various sources using Python libraries and webscraping on popular stocks. After collecting this data I visualized it in a dashboard to identify patterns or trends. The stocks I worked with are Tesla, AMD, and GameStop.
In this course I learned the basis of data analysis and in particular:
- Develop Python code for cleaning and preparing data for analysis - including handling missing values, formatting, normalizing, and binning data
- Manipulate data using dataframes, summarize data, understand data distribution, perform correlation and create data pipelines
- Perform exploratory data analysis and apply analytical techniques to real-word datasets using libraries such as Pandas, Numpy and Scipy
- Build and evaluate regression models using machine learning scikit-learn library and use them for prediction and decision making
I collected here all my assignments, where I investigated different case-studies and practical examples.
In this projects I implement data visualization techniques and plots using Python libraries, such as Matplotlib, Seaborn, and Folium to tell a stimulating story. I create different types of charts and plots such as line, area, histograms, bar, pie, box, scatter, and bubble, but also advanced visualizations such as waffle charts, word clouds, regression plots, maps with markers, & choropleth maps. Finally, I generate interactive dashboards containing scatter, line, bar, bubble, pie, and sunburst charts using the Dash framework and Plotly library (Figure below).
