Skip to main content

Pivot cells

Use pivot cells to interactively aggregate and pivot your data in a UI-first way.

info
  • Users need Can Edit permissions to create pivot cells.
tip

Pivot cells got a glow-up in August 2025. Pivot cells created before this change are considered legacy and don't have some of the features mentioned in this doc, like pivot totals and drilling. See below for info on how to upgrade legacy pivot cells.

A pivot cell can accept dataframes, semantic models, or warehouse tables as input. Pivots aggregate data based on your configurations, and return a dataframe that can be displayed in an app or used downstream in your notebook.

Using pivot cells​

  1. Create a pivot cell by selecting "Pivot" in the Add cell bar.
Creating a pivot cell

  1. From the data selector in the upper left of the cell, select a dataframe, semantic model, or warehouse table. All of the fields from the selected data source will appear in the field picker on the left.

  2. Drag columns from the field picker into the drop zones to render your pivot table.

    • Rows: The field(s) you want to aggregate by, rendered vertically.
    • Columns: The field(s) you want to aggregated by, rendered horizontally
    • Values: The field(s) you want to aggregate. The aggregate type and formatting of the value can be changed per value.

As you configure the cell, the pivot table will update with the results. The resulting pivot table can be added to a published app.

Configuration settings​

Click on the column header in the pivot, or use the Edit pivot panel on the right, to change the aggregation type, formatting, truncate time units, and update labels.

To transpose the pivot values and visualize them as rows, use the Edit pivot panel on the and click the icon next to the values, as shown in the screenshot below. This config option only appears when multiple values are included in the pivot.

Transpose values in the Edit pivot panel

Row and column totals are enabled in pivot cells by default, and can be disabled in the Edit pivot panel. Conditional formatting on pivot values can also be applied in the Edit pivot panel.

Output dataframes​

Click Create output below the pivot cell to generate a dataframe that can be referenced downstream in the project.

Return a dataframe from a pivot cell

The returned dataframe will hold the grouped, aggregated data represented in the pivot.

Calculations​

Click the + next to the Dimension or Measure lists in the field picker to add custom calculations.

Add a custom field via the field picker

This will open the calculation editor and prompt you to define a custom field. Read more about calculations here.

Drilling and viewing data​

Click on any pivot value to view underlying data or drill down. This is possible by users with Can Edit access in a notebook, and by users with Can Explore access in a published app.

Drill or view data when clicking on a pivot value

Read more about drilling here and viewing underlying data here.

Legacy pivots​

tip

We upgraded our pivot cell in August 2025. Pivot cells created before this upgrade are considered legacy.

Pivot cells created before August 2025 will still run, but are considered legacy and have a "Legacy" tag that is visible in the notebook.

Upgrade legacy pivot cells​

It's encouraged to upgrade legacy pivot cells to take advantage of new features that only exist in the new cell, like pivot totals and drilling. To do so, hover over the "Legacy" tag to see an option to duplicate the legacy cell as a new pivot cell.

Duplicating a legacy pivot as a new pivot.

The remainder of the doc describes legacy behavior specific to the legacy pivot cell.

[Legacy] Using pivot objects in downstream cells​

Legacy pivot cells returned a custom pivot object (HexPivotTable), named pivot_result by default. The custom pivot object is not a dataframe itself, rather it contains two different dataframe representations of the data, .pivoted and .aggregated.

  1. HexPivotTable.pivoted returns the pivoted object as a dataframe that uses the same indexing and pivoting that is rendered in your original pivot cell.

  2. HexPivotTable.aggregated returns the aggregated data without any pivoting. For those familiar with SQL, this is the result of writing a statement that groups by all the fields rendered as rows and columns, before the data is pivoted.

On this page