GR Cup Lap Insight

Inspiration

Toyota Gazoo Racing is all about performance, precision and data. I was inspired to use real race telemetry to build something that could help drivers and teams understand lap performance in a simple, visual, and meaningful way.

The idea was to turn complex raw CSV data into clear insights that anyone could read and use.

What it does

GR Cup Lap Insight is a lap time analysis and leaderboard application for Toyota GR Cup racing data.

The app allows users to upload official race CSV files and instantly view: • Driver lap time analysis
• Lap consistency graphs
• Leaderboard ranking
• Fastest driver and best lap
• Session-based comparison

Everything is displayed in a clean, interactive dashboard.

How I built it

The application is built using:

• Python for logic and data handling
  
• Pandas for CSV processing
  
• Streamlit for the web interface
  
• Matplotlib for charts and visualizations
  

The system reads raw telemetry data, cleans it, structures it, and then generates insights in real-time.

Challenges I ran into

The biggest challenges were:

• Understanding complex race telemetry structure
  
• Cleaning inconsistent data formats
  
• Eliminating duplicates and noise
  
• Turning large datasets into something simple and visual
  

Solving these taught me a lot about real-world data processing and analytics.

Built With

• github
• matplotlib
• pandas
• python
• streamlit