Search results
This tutorial demonstrates how to visualize Formula 1 race strategies using Python, Fastf1, Pandas, and Matplotlib. Abstract. The tutorial focuses on visualizing pitstop and tyre strategies in Formula 1 races using Python libraries such as Fastf1, Pandas, and Matplotlib.
2 sie 2023 · In this article, we will learn how to analyze the data of the 2022 Bahrain Grand Prix using Python. Step 1: Data Collection. Firstly, we will use the ergast API to access the results and race...
"f1-analysis" is a GitHub repository dedicated to harnessing the power of the FastF1 library in Python for comprehensive analysis of Formula 1 data, facilitating in-depth insights into race performance and strategies.
8 gru 2023 · FastF1 is a simple yet powerful tool for anyone interested in Formula 1. It's a Python library that lets you easily access and analyse F1 data. The library grants you access to a wide range of F1 data, including lap timing, car telemetry, position, tyre data, weather data, event schedules, and session results.
1 paź 2021 · Step 1: Set up the basics. First of all, we load all the packages that are required for this analysis. After that, we enable the plotting functionality, enable the cache and change a small...
25 lip 2024 · FastF1 is a python package for accessing and analyzing Formula 1 results, schedules, timing data and telemetry. Main Features. Access to F1 timing data, telemetry, sessions results and more. Full support for Ergast to access current and historical F1 data.
29 sty 2022 · This tutorial will show you how you can visualize the pitstop- and tyre strategies of a race, like in the following figure: Doing this will learn you how reshape the raw data to the format we...