Schema Inspection

Schema Inspection is the habit of checking a dataset’s shape, column names, null counts, and dtypes before doing analysis. In Brevvie Python + AI — Section 3: Data, Polars & Pair Programming, this is one of the first recommended steps after loading data.

Why it matters

• reveals whether columns were typed correctly
• catches missing values early
• prevents invalid aggregations or time-series mistakes

In the source

Typical checks include shape, schema, and null counts.

See also dtypes and Columnar Thinking.