What 3.9M powerlifting records tell us about competition strategy — an EDA with Python

What 3.9M powerlifting records tell us about competition strategy — an EDA with Python

When I started this EDA project for my Data Science Master at Evolve, I picked the Open Powerlifting dataset because beyond being a gym-rat, I've always been curious about the competition strategy in powerlifting.

The dataset

Open Powerlifting is an open-source project that tracks powerlifting competition results worldwide. The full dataset has ~3.9M rows and 42 columns covering athlete info, every single lift attempt, and performance metrics.

Before any analysis I filtered it down to sanctioned, drug-tested competitions only and kept only the columns I'd actually use. The main challenge: negative values mean a failed lift, not bad data. That required building boolean columns to track success/failure before converting negatives to NaN.