Analysis of Tesla and GameStop

This project analyzes the stock prices and quarterly revenue data of Tesla (TSLA) and GameStop (GME). The analysis is performed using Python in a Jupyter Notebook, with data fetched via the yfinance library and web scraping techniques.

Project Overview

This analysis covers the following key steps:

1. Data Retrieval:

   • Use yfinance to fetch historical stock data for Tesla and GameStop.
   • Web scraping to extract quarterly revenue data for both companies.

2. Data Processing:

   • Cleaning and preparing the data for analysis, including resetting indices and converting date formats.

3. Data Visualization:

   • Generate visualizations comparing stock prices and revenue over time to observe trends and anomalies.

Files in this Repository

• Analysis of Tesla and GameStop.ipynb: The Jupyter Notebook containing all the code and analysis.
• README.md: This file, providing an overview of the project.

Prerequisites

To run this notebook, you'll need to have the following installed:

• Python 3.x
• Jupyter Notebook
• Required Python libraries: yfinance, pandas, matplotlib, beautifulsoup4, requests

You can install the required libraries using pip:

pip install yfinance pandas matplotlib beautifulsoup4 requests