Second devlog!

Worked on analyze.py which for now has 5 functions as the core of the project:

get_clean_lap which filters out sc, vsc laps, track limits and such
get_race_pace calculates the average race pace per stint
get_head_to_head combines 2 drivers’ laps into one table for comparison get_consistency_score uses standard deviation to measure the consistency
get_h2h_summary compares 2 drivers’ pace and tells which one was faster

• I’ve also started working on charts.py to set up the dark F1 color theme and pulled the official team colors from the session data.
• I tested everything in the terminal, VER vs LEC in Australia 2023 showed that Verstappen’s pace was 1.667 seconds per laps faster on average.

• This here is Max Verstappen’s race pace in Mexico, 2024:

Day 1 of working on PitWall (temporary name)

As an f1 fan and motosports fan in general, I wanted
to create something that I’m going to use myself pretty often and work with data that genuinely interests me which is why I’m creating PitWall, a website that analyses data using FastF1, an open source F1 data library. The main idea is to pull real F1 data and let people analyze race pace, quali laps, driver mistakes, simulate alternate race strategies. I’m also going to be using NASA atmospheric data to correlate weather conditions with lap time performance.

I started off by setting up my project structure in VS Code and install all the necessary libraries then, I wrote fetch.py which is a file from where I pull the data itself. Although, I faced an error on the way, a NotADirectoryError because FastF1 needed a cache folder that didn’t exist yet, fixed that by creating the folder manually. In the end I got it to work

The screenshot shows Verstappen’s first 5 laps from the 2023 Monaco GP