Stock Market Analysis & Visualization 📈 (Lab from uni course)

This tool fetches, analyzes, and visualizes stock data for your favorite tickers using Python, async APIs, and (probably) beautiful plots.

Features

• Async Data Fetching: Fast, efficient download of daily stock data using Polygon.io.
• Custom Ticker Selection: Analyze only the stocks you care about.
• Powerful Visualizations: Trend lines, cumulative returns, and top performer charts.
• Easy to Use: Run everything in a Jupyter notebook.

Extra Materials

You can learn the following topics by going throw the project and visiting the links below:

Click to expand extra learning materials

• about AIOHTTP
• about asyncio
• about async/await
• using jupyter notebooks via vscode
• quickstart — how to use jupyter notebooks
• matplotlib plotting guide

Setup Instructions 🛠️

1. Clone the repository

   git clone https://github.com/undeluro/uni-plotting-stocks.git
   cd uni-plotting-stocks

2. Create a virtual environment

   python -m venv .venv
   # On Windows:
   .venv\Scripts\activate
   # On macOS/Linux:
   source .venv/bin/activate

3. Install requirements

   pip install -r requirements.txt

4. Get your free Polygon.io API key

   • Sign up at polygon.io
   • Go to your dashboard and copy your API key

5. Create a .env file

   echo API_KEY=your_api_key_here > .env

How to Use

• Open main.ipynb in VS Code or Jupyter Lab.
• Set your desired date range and tickers.
• Run the notebook cells to fetch data, analyze, and visualize!

Project Structure

.
├── main.ipynb            # Main Jupyter notebook for analysis and visualization
├── requirements.txt      # List of Python dependencies
├── .env                  # API key for Polygon.io (not included in repo)
├── src/                  # Source code directory
│   ├── fetch_data.py     # Functions for fetching stock data (async)
│   └── analyze_data.py   # Functions for preprocessing and analyzing data
├── README.md             # Project documentation (this file)
└── LICENSE               # License file

Contributing

Contributions are welcome! Feel free to submit issues or pull requests to improve the project.

License

This project is licensed under the MIT License. See LICENSE for details.