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"F1 Analysis" is a data-centric dive into Formula 1. Through statistical analysis and visualization, this project uncovers driver performances, team strategies, race dynamics, and fan engagement trends. Experience the thrill of F1 with data-driven exploration.

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🏎️ Formula 1 Data Analysis Dashboard

Streamlit Python Pandas

An interactive dashboard for analyzing Formula 1 historical data with driver/constructor performance metrics and race visualizations.

✨ Features

  • Driver/constructor performance analytics
  • Circuit speed comparisons
  • Interactive race telemetry
  • Pit stop efficiency analysis

🛠️ Tech Stack

  • Frontend: Streamlit
  • Data Processing: Pandas, NumPy
  • Visualization: Plotly, Matplotlib, Seaborn

📂 Data Structure

data/
├── drivers.csv
├── constructors.csv
├── races.csv
├── results.csv
├── qualifying.csv
└── lap_times.csv

🚀 Quick Start

# Clone repo
git clone https://github.com/yourusername/f1-dashboard.git
cd f1-dashboard

# Install dependencies
pip install -r requirements.txt

# Launch app
streamlit run app.py

📊 Example Query

# Get top 10 winning drivers
winners = results[results['position'] == 1]
top_drivers = winners['driverId'].value_counts().head(10)

📜 License

MIT License - See LICENSE for details.

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"F1 Analysis" is a data-centric dive into Formula 1. Through statistical analysis and visualization, this project uncovers driver performances, team strategies, race dynamics, and fan engagement trends. Experience the thrill of F1 with data-driven exploration.

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