Exploration of the Formula1 motorsport to discover trends, longest participating drivers, and best tracks.

• Formula1 Analysis
• TL;DR
• Table of contents
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Python and Pandas was used in Jupyter Notebooks to explore 13 different CSVs of motorsport data, dating back to 1950. By merging, sorting, filtering, cleaning, and visualizing the data using packages such as Seaborn, I was able to gain insight on individual driver statistics, frequency of track use, and see the progression of the sport.

Navigate to the folder you wish to use

cd Users/me/Desktop

Initialize git

git init

Clone the repo

git clone https://github.com/caly-pso/formula1_analysis.git

Move into the project root folder

cd formula1_analysis

Create virtual environment

python -m venv .venv

Activate the environment

source .venv/bin/activate

Run the application locally

jupyter notebook

Navigate to the ipynb files

MIT Public License

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