Unpivot

Spark Gem

Use the Unpivot Gem to transform your data from a wide format to a long format.

note

If you want to pivot the data, rather than unpivot, use the Aggregate Gem.

Parameters

Parameter	Description
Column(s) to use as identifiers	The column(s) that will identify to which group or entity the observation corresponds to.
Columns to unpivot	The columns (wide format) that you would like to transform into a single column (long format).
Variable column name	The name of the column that contains the names of the unpivoted columns. This helps describe the values in the value column.
Value column name	The name of the column that will contain the values from the unpivoted columns.

Example

Transforming your data into a long format can be beneficial when creating visualizations, comparing variables, handling dynamic data, and more.

Let's think about a time series example. If you have product sales data in a wide format, you may want to transform it into a long format before modeling the time series and analyzing the seasonal patterns in sales.

The image below shows sample input and output tables for this scenario.

This table describes how this transformation was achieved:

Parameter	Input
Column(s) to use as identifiers	The Product column is the identifier because it defines which product the sales correspond to.
Columns to unpivot	All of the quarterly sales columns will be unpivoted.
Variable column name	The variable column is named Quarter because it identifies the sales period.
Value column name	The value column is named UnitsSold because it contains information about number of units sold.