Explore and visualize FIFA21 player data with an interactive Jupyter Notebook that combines powerful data analysis and geographic mapping.
This project provides a comprehensive Exploratory Data Analysis (EDA) of FIFA21 player statistics. It includes data cleaning, transformation, global summaries, top performer rankings, position-based analysis, and an interactive choropleth map of player distribution by country.
| Section | Description |
|---|---|
| 1. Introduction | Load dataset and overview of data structure. |
| 2. Data Cleaning & Transformation | Handle missing values, convert height/weight to metric, calculate BMI & age. |
| 3. Global Statistics | Summary statistics (mean, median, quartiles) for key metrics. |
| 4. Top Performers | Lists of top 10 players by rating and potential. |
| 5. Position Analysis | Aggregated statistics by primary playing position. |
| 6. Geospatial Analysis | Folium choropleth map showing number of players per country with interactive tooltips. |
| 7. Additional Insights | Further explorations and potential next steps. |
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Clone the repository:
git clone https://github.com/Vinicius-Mangueira/fifa21-eda-dashboard.git cd fifa21-eda-dashboard -
Create and activate a virtual environment (recommended):
python -m venv venv # Linux/Mac source venv/bin/activate # Windows venv\Scripts\activate
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Install requirements:
pip install -r requirements.txt
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Launch the notebook:
jupyter notebook notebooks/fifa21_eda_dashboard.ipynb
Interact with the notebook cells to explore data tables, charts, and the world map.
Contributions are welcome! To contribute:
- Fork the repository
- Create a new branch:
git checkout -b feature/my-new-feature - Commit your changes:
git commit -m 'Add my new feature' - Push to your branch:
git push origin feature/my-new-feature - Open a Pull Request
This project is licensed under the MIT License.
Developed by Vinícius Mangueira — Student of Data Science & Artificial Intelligence @ UFPB 🇧🇷