Principal Component Analysis Explained: A Practical Example with MLB Data in Python

Introduction Principal component analysis (PCA) applied to Pete Crow-Armstrong. I am willing to bet that every data scientist in an MLB organization has thought of this pun at least once. For good reason: PCA is a powerful tool for dimensionality reduction and feature extraction. In this post, I will walk through the steps of performing PCA on a dataset of Pete Crow-Armstrong’s game-by-game…