📊 Stock Market Data Analysis

Explore stock price trends using Python, web scraping, and financial APIs. Originally created as a capstone assignment in the IBM Data Science Professional Certificate on Coursera.

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🎯 Project Objective

• Collect and analyze real-world stock data using Python
• Visualize market movement trends for select companies
• Apply EDA techniques using public datasets
• Build readable, accessible charts for interpretation

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📁 Project Structure

Stock-Data-Analysis/
├── README.md
├── Final_Assignment.ipynb
├── visuals/
│   ├── stock_price_plot.png
│   └── trend_analysis_chart.png
└── data/
    └── collected_stocks.csv

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🧰 Tools & Technologies

• Python
• Pandas
• Matplotlib & Seaborn
• yfinance
• BeautifulSoup
• Jupyter Notebook

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🔎 Ethical Considerations

• Data sourced from open/public APIs (Yahoo Finance)
• Visuals are made for human-readability, avoiding black-box charts
• Interpretations are kept neutral — no investment advice
• Encourages ethical modeling and human-centered presentation

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📘 About the Dataset

• Yahoo Finance stock data via yfinance
• Data includes: historical prices, volume, and trend indicators
• Additional scraping was performed using BeautifulSoup for metadata

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🤝 Reusability

You may adapt this notebook for:

• Financial time series forecasting
• Teaching basic market analysis
• Feature engineering demos

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📃 License

MIT License. Feel free to fork and build on it.