Pivot tables

A pivot table block summarizes and cross-tabulates a DataFrame without any code. You choose the fields to group by and the value to aggregate, and Deepnote builds the summary for you.

Adding a pivot table block

Add a pivot table block from the + (add block) menu or the block bar at the bottom of the notebook, then point it at a DataFrame produced earlier in the notebook (from a Python or SQL block).

Configuring the summary

A pivot table has three inputs:

• Rows: The field(s) whose values form the rows of the summary.
• Columns: The field(s) whose values spread across the columns. Leave this empty for a simple grouped summary.
• Aggregation: The field to aggregate, together with an aggregation: count, count unique, sum, average, median, min, or max.

Adjust any of these and the block recomputes the result.

Working with the result

The result renders as a standard data table, so you can sort, filter, and format it like any other block output and reuse it in the blocks that follow.