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https://github.com/nehul1149/olympic-data-analysis


https://github.com/nehul1149/olympic-data-analysis

analysis data-analysis data-science data-visualization matplotlib python streamlit

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# 🏅 Olympic Data Analysis



This project is an interactive data visualization and analytics platform for exploring historical Olympic Games data. Built with Python and Streamlit, it offers an in-depth analysis of medal tallies, athlete statistics, and country-wise performance trends, providing users with powerful insights into the world's biggest sporting event.



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## 📌 Features



- **Medal Tally Analysis:**

  - Explore medal tallies by year, country, or both.

  - Compare the performance of nations and athletes across Olympic editions.



- **Overall Analysis:**

  - Visualize participation growth in terms of nations, events, and athletes.

  - Examine trends in sports, events, and athlete demographics.



- **Country-Wise Analysis:**

  - Delve into the medal-winning history of specific countries.

  - Identify sports where countries excel using heatmaps.



- **Athlete-Wise Analysis:**

  - Analyze age distributions of medalists across gold, silver, and bronze categories.

  - Study the physical attributes (height, weight) of athletes by sport and gender.

  - Explore the historical participation trends of male and female athletes.



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## 🚀 Technologies Used



- **Python** for data processing and analysis.

- **Streamlit** for creating the interactive web app.

- **Pandas** for data manipulation and cleaning.

- **Matplotlib**, **Seaborn**, and **Plotly** for visualizing trends and distributions.

- **Scipy** for generating statistical plots.



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## 📂 Data Sources



1. **Athlete Events Dataset**: Contains details of athletes, their events, and medal outcomes.

2. **NOC Regions Dataset**: Maps National Olympic Committees (NOCs) to their respective regions.



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## 🛠️ How It Works



1. **Data Preprocessing**:

   - Filtered for Summer Olympics data to ensure relevance.

   - Merged datasets to include regional information.

   - Applied one-hot encoding for medal types for detailed analysis.



2. **Interactive Dashboard**:

   - Users can explore trends via dropdowns and dynamic visualizations.

   - Options to analyze data by year, sport, athlete, or nation.



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## 📊 Visual Highlights



- **Line Charts**:

  - Growth of participating nations, athletes, and events over time.

- **Heatmaps**:

  - Sports performance trends of countries.

- **Scatter Plots**:

  - Height vs. weight distribution of athletes, categorized by gender and medal type.

- **Distribution Plots**:

  - Age trends among gold, silver, and bronze medalists.



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## 🖥️ How to Run the Project



1. Visit the live application hosted on Streamlit:  

   [Olympic Data Analysis](https://olympic-data-analysis-bynehul.streamlit.app/)



2. Alternatively, you can run it locally:

   - Clone the repository:

     ```bash

     git clone https://github.com/yourusername/Olympic-Data-Analysis.git

     cd Olympic-Data-Analysis

     ```

   - Install required packages:

     ```bash

     pip install -r requirements.txt

     ```

   - Run the Streamlit app:

     ```bash

     streamlit run app.py

     ```

   - Open the app in your browser at `http://localhost:8501`.



## 📢 Contributions



- Contributions, issues, and feature requests are welcome! Feel free to open an issue or submit a pull request for improvements.



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## 📧 Contact



- For any queries or suggestions, reach out at [email protected].