https://github.com/akhi07rx/f1-statistics-dashboard
A comprehensive command-line tool for analyzing Formula 1 race data using the FastF1 library.
https://github.com/akhi07rx/f1-statistics-dashboard
akhi07rx cli cli-tools data f1 f1-score f1cli f1dashboard f1stats fastf1 formula1 opensource race race-analytics
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A comprehensive command-line tool for analyzing Formula 1 race data using the FastF1 library.
- Host: GitHub
- URL: https://github.com/akhi07rx/f1-statistics-dashboard
- Owner: akhi07rx
- License: mit
- Created: 2025-04-10T11:05:14.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2025-04-10T12:03:04.000Z (about 1 year ago)
- Last Synced: 2025-04-10T13:42:39.796Z (about 1 year ago)
- Topics: akhi07rx, cli, cli-tools, data, f1, f1-score, f1cli, f1dashboard, f1stats, fastf1, formula1, opensource, race, race-analytics
- Language: Python
- Homepage:
- Size: 44.9 KB
- Stars: 1
- Watchers: 1
- Forks: 1
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
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README
# F1 Statistics Dashboard
A comprehensive command-line tool for analyzing Formula 1 race data using the FastF1 library.
## Overview
F1 Statistics Dashboard is a Python application that provides detailed statistics, visualizations, and analysis of Formula 1 race data. From viewing race schedules to comparing driver performances across seasons, this tool offers F1 fans and data enthusiasts a powerful way to explore the world of Formula 1 racing.
## Features
### Race Information
- **Race Schedules**: View full season calendars for any F1 season
- **Race Results**: Get detailed results from specific races
- **Grand Prix Summaries**: Comprehensive information about each race including winners, podiums, fastest laps, and team points
### Driver Statistics
- **Podium Counts**: Track podium finishes for each driver in a season
- **DNF Analysis**: Analyze driver retirements and non-finishes
- **Driver Comparisons**: Compare two drivers' performances across multiple seasons
### Data Visualization
- **Driver Points Charts**: Visualize points distribution for each race
- **Performance Trends**: Track drivers and teams across a season
### Data Export
- **Season Details Export**: Export complete season data to CSV files
- **Historical Data Export**: Compile data across multiple seasons
- **Race Result Exports**: Save individual race results
## Installation
### Prerequisites
- Python 3.7 or higher
- pip package manager
### Required Libraries
```bash
pip install fastf1 pandas matplotlib tabulate
```
### Installing F1 Statistics Dashboard
```bash
# Clone the repository
git clone https://github.com/akhi07rx/F1-Statistics-Dashboard.git
cd f1-statistics-dashboard
# Install required dependencies
pip install -r requirements.txt
```
## Usage
### Interactive Menu
The easiest way to use the dashboard is through its interactive menu:
```bash
python f1_dashboard.py --menu
```
This opens a user-friendly interface organized into the following sections:
1. View Race Schedule
2. Race Results & Analysis
3. Driver Statistics
4. Season Analysis
5. Historical Data
6. Export Options
### Command-Line Arguments
You can also access specific features directly through command-line arguments:
```bash
# Display current season schedule
python f1_dashboard.py
# Show race schedule for a specific year
python f1_dashboard.py --schedule 2023
# Get race results and generate points chart
python f1_dashboard.py --results 2023 5
# Get fastest lap information
python f1_dashboard.py --fastest 2023 22
# Count podiums for each driver in a season
python f1_dashboard.py --podiums 2023
# Count DNFs for each driver in a season
python f1_dashboard.py --dnfs 2023
# Compare two drivers across seasons
python f1_dashboard.py --compare VER HAM 2021 2023
# Generate a Grand Prix summary
python f1_dashboard.py --summary 2023 22
# Export full season details to CSV
python f1_dashboard.py --export-season 2023
# Export race data for a date range
python f1_dashboard.py --export-history 2010 2023
```
### Help
For a full list of available commands:
```bash
python f1_dashboard.py --help
```
## Examples
### Viewing the Current Season Schedule
```python
from f1_dashboard import F1Dashboard
dashboard = F1Dashboard()
dashboard.display_race_schedule()
```
### Analyzing a Specific Grand Prix
```python
dashboard = F1Dashboard()
dashboard.grand_prix_summary(2023, 5) # Monaco Grand Prix 2023
```
### Comparing Two Drivers
```python
dashboard = F1Dashboard()
dashboard.compare_drivers('VER', 'HAM', range(2021, 2024)) # Compare Verstappen and Hamilton from 2021-2023
```
### Exporting Full Season Data
```python
dashboard = F1Dashboard()
results, drivers, teams = dashboard.export_full_season_details(2023)
```
## Data Files
The dashboard creates the following data files:
| File | Description |
|------|-------------|
| `race{N}_results_{YEAR}.csv` | Results for a specific race |
| `race{N}_points_{YEAR}.png` | Points visualization for a specific race |
| `podiums_{YEAR}.csv` | Podium counts for a season |
| `dnfs_{YEAR}.csv` | DNF counts for a season |
| `full_season_{YEAR}_results.csv` | Complete race-by-race results for a season |
| `driver_standings_{YEAR}.csv` | Driver championship standings |
| `team_standings_{YEAR}.csv` | Team/constructor championship standings |
| `all_f1_races_{START}_to_{END}.csv` | Historical race data for a date range |
## Cache System
The dashboard uses FastF1's cache system to improve performance and reduce API calls. The cache is stored in the `f1_cache` directory, which is created automatically.
## Troubleshooting
### Common Issues
#### Data Loading Errors
```
Error getting race results for {year} round {race_round}: ...
```
Check your internet connection. The FastF1 library requires internet access to load data.
#### Missing Cache Directory
If you encounter this error:
```
NotADirectoryError: Cache directory does not exist!
```
The application should create this directory automatically, but you can manually create an `f1_cache` directory in the same location as the script.
#### Matplotlib Display Issues
If charts don't display properly, ensure you have a working display server or try exporting to image files instead.
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request.
1. Fork the repository
2. Create your feature branch (`git checkout -b feature/amazing-feature`)
3. Commit your changes (`git commit -m 'Add some amazing feature'`)
4. Push to the branch (`git push origin feature/amazing-feature`)
5. Open a Pull Request
## License
This project is licensed under the MIT License - see the LICENSE file for details.
## Acknowledgments
- [FastF1](https://github.com/theOehrly/Fast-F1) - The amazing library that makes this dashboard possible
- Formula 1 - For providing the data through their API
- All the contributors to Pandas, Matplotlib, and other libraries used in this project
---
*Disclaimer: This is an unofficial application and is not associated with, endorsed by, or affiliated with Formula 1 or the FIA Formula One World Championship.*