GroupByDocs

Groups the rows of this DataFrame based on the values in one or more specified cols. Each unique value in a key column — or a unique tuple of values for multiple columns — defines the group consisting of all rows where the column(s) contain that value combination.

Returns a GroupBy — a dataframe-like structure that contains all unique combinations of key values along with the corresponding groups of rows (each represented as a DataFrame) as rows.

A GroupBy can then be:

• transformed into a new GroupBy;

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

• aggregated into a DataFrame, where each group is transformed into one or more rows of derived values;

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

Grouping keys 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 use it as a grouping key:
df.groupBy { expr("newName") { oldName.drop(5) } }

Check out Grammar.

This can include column groups and nested columns.

See Selecting Columns.

For more information: See groupBy on the documentation website.

Don't confuse this with group, which groups column into column group.

See also pivot that groups rows of DataFrame vertically.