Normalize Data for Analysis with Pandas

Data normalization is the act of transforming a dataset from its raw (but clean) format into a refined version with a better signal-to-noise ratio for downstream applications.

Fundamental problem: each feature has its own native distribution. If they are not normalized, features with higher nominal values will artificially take on more importance in optimization algorithms.

Without normalization, the optimization algorithm assigns disproportionate weight to features with higher nominal values (here Feature B), regardless of their actual importance.