This project provides an in-depth analysis of Olympic data using Streamlit, a popular framework for creating data web applications. The analysis covers various aspects such as medal tally, overall analysis, country-wise analysis, and athlete-wise analysis.
- Medal Tally: View the medal tally for different years and countries.
- Overall Analysis: Get top statistics like number of editions, cities, sports, events, athletes, and nations. Visualize participating nations, events, and athletes over the years.
- Country-wise Analysis: Analyze the performance of a specific country over the years, including medal tally and top athletes.
- Athlete-wise Analysis: Examine the age distribution of athletes, height vs. weight distribution, and participation of men and women over the years.
-
Clone the repository:
git clone https://github.com/MohammedLike/Olympic_FData_Analysis_Streamlit.git cd Olympic_FData_Analysis_Streamlit -
Create a virtual environment and activate it:
python -m venv .venv .venv\Scripts\activate # On Windows source .venv/bin/activate # On macOS/Linux
-
Install the required packages:
pip install -r requirements.txt
-
Run the Streamlit application:
streamlit run app.py
-
Open your web browser and go to
http://localhost:8501to view the application.
- Python: The main programming language.
- Streamlit: Framework for creating the web application.
- Pandas: For data manipulation and analysis.
- Plotly: For interactive visualizations.
- Seaborn & Matplotlib: For static visualizations.
Contributions are welcome! Please follow these steps:
- Fork the repository.
- Create a new branch (
git checkout -b feature/your-feature). - Make your changes and commit them (
git commit -m 'Add some feature'). - Push to the branch (
git push origin feature/your-feature). - Open a pull request.
This project is licensed under the MIT License - see the LICENSE file for details.