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https://github.com/zeynepcol/data-analysis-visualization
Data visualization and interactive analytics - Olympics Dataset
https://github.com/zeynepcol/data-analysis-visualization
data-analysis data-science data-visualization matplotlib pandas plotly python scipy seaborn streamlit
Last synced: 2 days ago
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Data visualization and interactive analytics - Olympics Dataset
- Host: GitHub
- URL: https://github.com/zeynepcol/data-analysis-visualization
- Owner: zeynepcol
- Created: 2025-01-31T13:48:01.000Z (21 days ago)
- Default Branch: main
- Last Pushed: 2025-02-18T14:16:14.000Z (3 days ago)
- Last Synced: 2025-02-18T15:27:19.832Z (3 days ago)
- Topics: data-analysis, data-science, data-visualization, matplotlib, pandas, plotly, python, scipy, seaborn, streamlit
- Language: Python
- Homepage:
- Size: 8.22 MB
- Stars: 1
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
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README
⚽️ OLYMPICS: DATA ANALYSIS 🏅
## ✨ Overview
**"Olympics: Data Analysis"** is an interactive dashboard that explores the history of the Olympic Games from **1896 to 2016** using a comprehensive dataset. The project provides deep insights into **medal tallies, athlete achievements, country performances, and the evolution of sports**. Users can explore trends in **medals, sports growth, and athlete participation** with dynamic visualizations and data-driven insights.
---
## 🌟 Features
- ⭐ **Medal Tally:** Analyze gold, silver, and bronze medal distributions by year and country.
- 🏆 **Country-wise Analysis:** Explore a nation's performance over the years and identify dominant sports.
- 🏏 **Athlete-wise Analysis:** Dive into athlete demographics, including **age, height, weight**, and **gender** trends.
- 🌟 **Overall Analysis:** Visualize historical trends in **participating nations, events, and athletes**.
- 🔄 **Interactive Visualizations:** Dynamic charts and graphs for an engaging data exploration experience.
---
## 💻 Tech Stack
| Tool/Library | Purpose |
|--------------|---------|
| **Python** | Data processing & backend logic |
| **Pandas, NumPy** | Data cleaning & manipulation |
| **Matplotlib, Seaborn** | Data visualization |
| **Plotly** | Interactive visualizations |
| **Streamlit** | Dashboard & UI development |
| **Scipy** | Scientific computations |
| **Kaggle Dataset** | Source of Olympic data |
---
## 📝 Dataset
The dataset is sourced from Kaggle:
[120 Years of Olympic History: Athletes and Results](https://www.kaggle.com/datasets/heesoo37/120-years-of-olympic-history-athletes-and-results)
It includes **206 nations, 116000+ athletes, 52 sports, and 651 events** across **28 Olympic editions** in **23 host cities**.
---
## 🚀 Installation & Usage
1. **Clone the Repository**
2. **Create a Virtual Environment**
```bash
python -m venv venv
source venv/bin/activate # On Windows use: venv\Scripts\activate
```
3. **Install Dependencies**
4. **Run the Dashboard**
```bash
streamlit run app.py
```
---
## 🎓 Learnings & Experience
This project provided hands-on experience in:
- Working with **large datasets** for data analysis and visualization.
- Extracting **meaningful insights** from historical sports data.
- Optimizing **code performance** and improving data-processing efficiency.
- Creating **interactive dashboards** for intuitive data exploration.
---
## 📚 References
- D. Yamunathangam, G. Kirthicka, and S. Parveen, *"Performance analysis in Olympic Games using exploratory data analysis techniques"*, International Journal of Recent Technology and Engineering, vol. 7, pp. 251-253, 2019.
- Kaggle Dataset: [120 Years of Olympic History](https://www.kaggle.com/datasets/heesoo37/120-years-of-olympic-history-athletes-and-results)
---
## 🤝 Contributing
Contributions are welcome!
---
## 📡 Contact
For any queries or collaborations, feel free to reach out!
🌐 GitHub: [zeynepcol](https://github.com/zeynepcol)
👤 LinkedIn: [zeynep-col](https://linkedin.com/in/zeynep-col/)