olympics-data-analysis-web-app

A Streamlit web application for interactive analysis and visualization of the Olympic athletes dataset.

Live demo: https://olympic-performance-analytics.onrender.com/

Dataset Link: https://www.kaggle.com/heesoo37/120-years-of-olympic-history-athletes-and-results

Project structure

• app.py — Streamlit application entrypoint (loads athlete_events.csv).
• preprocessor.py — data cleaning and preparation utilities.
• helper.py — helper functions used by the app.
• athlete_events.csv — primary dataset (kept in repository root).
• noc_regions.csv — nation/region lookup table.
• requirements.txt — Python dependencies (includes streamlit).
• Dockerfile — container image to run the Streamlit app.
• Procfile & setup.sh — deployment helpers (used for Render/Heroku-like hosts).

Quickstart (local)

1. Create a virtual environment and activate it.

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

2. Install dependencies and run the app.

pip install -r requirements.txt
streamlit run app.py

Docker

Build and run the provided Dockerfile:

docker build -t olympics-app .
docker run -p 8501:8501 olympics-app

Notes

• The app expects athlete_events.csv to be present in the repository root. Do not remove or rename this file unless you update app.py accordingly.
• The dataset and live demo link above are preserved as-is.

Contributing

• Open issues or pull requests for improvements, bugfixes, or documentation updates.

License

• See repository root for license information (if present).