⚽ Football Data Pipeline Dashboard

A complete Data Engineering & Data Visualization project built with Python.
It demonstrates how to fetch, process, store, and visualize real football league data using modern Python libraries.

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🧩 Overview

This project connects to the API-Football service to collect live league data.
The data is processed into structured tables, stored locally in SQLite, and visualized using an interactive Streamlit dashboard.

Data Flow:
API → Fetch → Transform → Load → Streamlit Dashboard

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🏗️ Project Structure

project_fotball/
│
├── football_data_fetcher.py
├── process_leagues.py
├── db_utils.py
├── football_dashboard.py
├── requirements.txt
├── .env.example
└── README.md

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🚀 How to Run

1. Clone the repository

git clone https://github.com/ohad2406/project_fotball
cd project_fotball

2. Install dependencies

pip install -r requirements.txt

3. Set up your API key

APISPORTS_KEY=your_api_key_here

4. Run the ETL process

python process/process_leagues.py

5. Launch the Streamlit dashboard

streamlit run dashboard/football_dashboard.py

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📊 Features

✅ Fetches football league data via API-Football
✅ Cleans and transforms the data into structured tables
✅ Saves the data to an SQLite database
✅ Displays KPIs, charts, and tables in an interactive Streamlit dashboard
✅ Supports dynamic filtering and CSV export

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🧠 Technologies

• Python
• Pandas
• Requests
• SQLite3
• Streamlit
• Plotly
• dotenv

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👨‍💻 Author

Ohad Shmuel
Data Analyst & Software Developer