> For the complete documentation index, see [llms.txt](https://docs.tabula.io/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.tabula.io/data-flows/tools-nodes/table-operations/pivot.md).

# Pivot

Creates new columns from values in the specified columns and computes aggregation functions as values for the new columns

## Overview

The Pivot Node allows you to convert rows into columns and computes aggregate functions as values for the new columns. This transformation is particularly useful for creating cross-tabular views, making comparing and contrasting different data dimensions easier. 

The reverse operation is [Unpivot](broken://pages/oI3KMyIahB4iTUGNW4CM).

<figure><img src="https://3263174655-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2Ft2TZFevDoRrOBI2rPK1p%2Fuploads%2FVQg6Sbs9PrYQJhauQBel%2FPivotNode.png?alt=media&amp;token=8bbf25f7-5675-4d88-a364-2c444f076587" alt=""><figcaption></figcaption></figure>

## Settings

#### Create columns from

Select a column from which values you want to create new columns. The Pivot node will create a distinct column for each unique value in the selected column.

#### Group rows by

Select the columns you want to group by. Column order determines group hierarchy.

#### Set values to

Select columns to perform aggregation operations. You can select multiple columns for aggregation.

There are two options for creating aggregations:

1. Predefined aggregation functions. Follow these steps:
   1. Select the column you want to use as a basis for the aggregation.
   2. Choose an aggregation function from the list.
2. Custom Formula. Enable the "Custom Formula" toggle to use a custom formula. With this option, you can define any custom expression that should return an aggregation function.

#### Place values as

Applied only if more than one aggregated column was selected. Select "Columns" to create a new column for each aggregated column, and "Rows" to create new rows for the aggregations instead of columns.