PivotDocs

Splits the rows of this DataFrame and groups them horizontally into new columns based on values from one or several provided columns of the original DataFrame.

Returns a Pivot — a dataframe-like structure that contains all unique combinations of key values as columns (or column groups for multiple keys) with a single row with the corresponding groups for each key combination (each represented as a DataFrame).

Works like DataFrame.groupBy but groups rows horizontally.

A Pivot can then be:

• reduced into a DataRow, where each group is collapsed into a single representative row;

• aggregated into a DataRow, where each group is transformed into a new row of derived values;

• grouped into a PivotGroupBy structure, which combines pivot and groupBy operations and then reduced or aggregated into a DataFrame.

Pivoted columns can also be created inline (i.g. by creating a new column using expr or simply renaming the old one using named):

// Create a new column "newName" based on existing "oldName" values
// and pivot it:
df.pivot { expr("newName") { oldName.drop(5) } }

Check out Grammar.

This can include column groups and nested columns.

See Selecting Columns.

For more information: See pivot on the documentation website.