Columnar Thinking

Columnar Thinking is the habit of reasoning about data one column at a time rather than one row at a time. In Brevvie Python + AI — Section 3: Data, Polars & Pair Programming, it is used to explain why dataframes, spreadsheets, and database tools care so much about schema and dtype.

In the source

• each column should represent one kind of thing
• every value in a column should share the same dtype
• operations like sum, mean, regex, and date math depend on that consistency

Why it matters

This mental shift makes dataframe operations and database queries feel natural instead of magical.