Python-Project-for-Data-Science

Tesla & GameStop Revenue Analysis

This project explores Tesla (TSLA) and GameStop (GME) financial data using a mix of APIs and web scraping.
It combines Python libraries such as yfinance, pandas, numpy, matplotlib, and BeautifulSoup to gather, clean, and visualize revenue data.

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📌 Project Overview

• Yahoo Finance API (yfinance) → Download stock price history.
• Web Scraping (BeautifulSoup) → Extract Tesla and GameStop revenue tables from web pages.
• Data Cleaning (pandas, numpy) → Parse dates, clean revenue values, handle missing data.
• Data Visualization (matplotlib) → Plot revenue trends and stock prices over time.

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⚙️ Libraries Used

• pandas
• numpy
• matplotlib
• yfinance
• BeautifulSoup (bs4)
• requests

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📊 Key Steps

1. Scraping Revenue Data from company financial tables.
2. Fetching Stock Prices from Yahoo Finance API.
3. Merging & Cleaning Data: date parsing, revenue formatting, handling nulls.
4. Visualization: plotting stock performance vs. revenue.

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🚀 How to Run

1. Clone this repository:

   git clone https://github.com/your-username/tesla-gme-revenue-analysis.git
   cd tesla-gme-revenue-analysis