pyspark.pandas.groupby.GroupBy.max¶

GroupBy.max(numeric_only: Optional[bool] = False) → FrameLike¶

Compute max of group values.

Parameters

numeric_onlybool, default False: Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data.

See also

Examples

>>> df = ps.DataFrame({"A": [1, 2, 1, 2], "B": [True, False, False, True],
...                    "C": [3, 4, 3, 4], "D": ["a", "b", "b", "a"]})

>>> df.groupby("A").max().sort_index()
      B  C  D
A
1  True  3  b
2  True  4  b

Include only float, int, boolean columns when set numeric_only True.

>>> df.groupby("A").max(numeric_only=True).sort_index()
      B  C
A
1  True  3
2  True  4

pyspark.pandas.groupby.GroupBy.last

pyspark.pandas.groupby.GroupBy.mean