Data Cleaning

Data Cleaning is the process of fixing data so analysis can proceed correctly. In Brevvie Python + AI — Section 3: Data, Polars & Pair Programming, it appears mainly through dtype correction: strings that should be numbers, strings that should be dates, and other small schema mismatches.

Typical issues from the source

• numeric values loaded as strings
• date columns still stored as text
• missing values that affect aggregations

Why it matters

Most analysis problems begin as data-cleaning problems. The lesson teaches learners to inspect and repair the dataset before trusting any metric.