Data Cleaning & Wrangling

Summary

Fixing inconsistent types, formatting, duplicates and outliers before a dataset is usable — the unglamorous work that determines model quality more than any algorithm choice.

• 1Take a genuinely messy public dataset and clean it end-to-end.
• 2Build a checklist: dtypes, duplicates, outliers, inconsistent categories, invalid values.
• 3Document every cleaning decision so it's reproducible.