Project Overview
This project aimed to find insights into athlete performance by analyzing race data for 50-mile and 50-kilometer races in the USA. I filtered and reconstructed a massive dataset of over 7 million entries down to the relevant athletes using the Pandas library.
A significant part of the analysis involved segregating the data by gender to provide distinct observations for men and women. I used the Seaborn library to create insightful visualizations like Violinplots, histograms, and displots to answer questions like "What season is better for running?" and "What is the optimal age for each race type?"
Visualizations & Insights
