bigframes.pandas.api.typing.SeriesGroupBy.cummax

SeriesGroupBy.cummax(*args, **kwargs) → Series

Cumulative max for each group.

Examples:

For SeriesGroupBy:

>>> lst = ['a', 'a', 'b']
>>> ser = bpd.Series([6, 2, 0], index=lst)
>>> ser.groupby(level=0).cummax()
a    6
a    6
b    0
dtype: Int64

For DataFrameGroupBy:

>>> data = [[1, 8, 2], [1, 2, 5], [2, 6, 9]]
>>> df = bpd.DataFrame(data, columns=["a", "b", "c"],
...                   index=["fox", "gorilla", "lion"])
>>> df.groupby("a").cummax()
         b  c
fox      8  2
gorilla  8  5
lion     6  9

[3 rows x 2 columns]

Returns:

Cumulative max for each group.

Return type:

bigframes.pandas.DataFrame or bigframes.pandas.Series