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[SPARK-12184][Python] Make python api doc for pivot consistant with scala doc #10176

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[SPARK-12184][Python] Make python api doc for pivot consistant with scala doc #10176

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14 changes: 9 additions & 5 deletions python/pyspark/sql/group.py
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Original file line number Diff line number Diff line change
Expand Up @@ -169,16 +169,20 @@ def sum(self, *cols):

@since(1.6)
def pivot(self, pivot_col, values=None):
"""Pivots a column of the current DataFrame and perform the specified aggregation.
"""
Pivots a column of the current [[DataFrame]] and perform the specified aggregation.
There are two versions of pivot function: one that requires the caller to specify the list
of distinct values to pivot on, and one that does not. The latter is more concise but less
efficient, because Spark needs to first compute the list of distinct values internally.

:param pivot_col: Column to pivot
:param values: Optional list of values of pivot column that will be translated to columns in
the output DataFrame. If values are not provided the method will do an immediate call
to .distinct() on the pivot column.
:param pivot_col: Name of the column to pivot.
:param values: List of values that will be translated to columns in the output DataFrame.

// Compute the sum of earnings for each year by course with each course as a separate column
>>> df4.groupBy("year").pivot("course", ["dotNET", "Java"]).sum("earnings").collect()
[Row(year=2012, dotNET=15000, Java=20000), Row(year=2013, dotNET=48000, Java=30000)]

// Or without specifying column values (less efficient)
>>> df4.groupBy("year").pivot("course").sum("earnings").collect()
[Row(year=2012, Java=20000, dotNET=15000), Row(year=2013, Java=30000, dotNET=48000)]
"""
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