Tool to download data from the Nasdaq Data Link API, implemented primarily in Jupyter Notebooks and Python scripts.
Features
- Simple interface to read API keys and fetch data from Nasdaq Data Link.
- Example usage with financial and freight rail datasets.
- Modular codebase separating initialization, data fetching, and main execution.
Tech Stack
- Python 3.9+
- Jupyter Notebook for exploratory data analysis and demonstration
- nasdaqdatalink Python package for API interaction
Getting Started
Prerequisites
- Python 3.9 or higher
- Install dependencies:
pip install nasdaqdatalink
Setup
- Obtain an API key from Nasdaq Data Link.
- Save the key in a file named
.keyin the project root.
Running the project
- Run the main script to fetch data for a sample ticker:
python main.py
- Alternatively, explore the Jupyter Notebooks for domain-specific analyses:
Capital-Markets.ipynbFreightRailEasyRead.ipynbRail-Freight-Energy-Usage.ipynb
Project Structure
├── Capital-Markets.ipynb # Notebook for capital markets data analysis
├── FreightRailEasyRead.ipynb # Notebook focused on freight rail data
├── Rail-Freight-Energy-Usage.ipynb # Notebook analyzing energy usage in rail freight
├── Untitled.ipynb # Example code for API key reading and data fetching
├── Untitled1.ipynb # Additional exploratory notebook
├── data.py # Function to fetch data given a link and ticker
├── initialize.py # Function to read API key into link
├── main.py # Main execution script demonstrating usage
Future Work / Roadmap
- Enhance error handling and input validation for API calls.
- Add support for more Nasdaq Data Link datasets and tickers.
- Develop a command-line interface for flexible data queries.
- Implement caching or local storage of fetched data for efficiency.
- Expand documentation and usage examples.
For questions or contributions, please open an issue or pull request on the GitHub repository.
Repository URL: https://github.com/justin-napolitano/data-link