https://github.com/ttaannnyyya/olympics_analysis
Olympics Data Analysis Web App An interactive Streamlit app to explore and visualize Olympic Games data — including medal tallies, country-wise trends, athlete statistics, and participation insights.
https://github.com/ttaannnyyya/olympics_analysis
matplotlib pandas plotly pycharm python render seaborn streamlit
Last synced: 3 months ago
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Olympics Data Analysis Web App An interactive Streamlit app to explore and visualize Olympic Games data — including medal tallies, country-wise trends, athlete statistics, and participation insights.
- Host: GitHub
- URL: https://github.com/ttaannnyyya/olympics_analysis
- Owner: ttaannnyyya
- Created: 2025-06-22T12:33:17.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-06-22T13:21:51.000Z (about 1 year ago)
- Last Synced: 2025-06-22T14:26:21.932Z (about 1 year ago)
- Topics: matplotlib, pandas, plotly, pycharm, python, render, seaborn, streamlit
- Language: Jupyter Notebook
- Homepage: https://olympics-analysis-y7p2.onrender.com
- Size: 555 KB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# 🏅 Olympics Data Analysis Web App
An interactive Streamlit web app to explore and visualize Olympic Games data — including medal tallies, country-wise performance, athlete insights, and participation trends over the years.
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## 📌 Features
- **Medal Tally:** Filter by country and year to see detailed medal counts.
- **Overall Analysis:** View key stats like editions, host cities, sports, events, nations, and athletes, with trends visualized over time.
- **Country-wise Analysis:** Track a specific country’s medal performance year by year.
- **Athlete-wise Analysis:** Analyze athlete age distributions, weight vs. height comparisons across sports, and trends in male vs. female participation.
Built using **Streamlit**, **pandas**, **Plotly**, **Seaborn**, and **Matplotlib**.
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## 🚀 Live Demo
👉 [Open the App](https://olympics-analysis-y7p2.onrender.com/)
⚠️ **Note:** This app runs on a free Render server.
It may take **15–30 seconds** to load or require refreshing once or twice if idle for a while.
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