pandas.core.groupby.SeriesGroupBy.cummax#

SeriesGroupBy.cummax(axis=<no_default>, numeric_only=False, **kwargs)[source] #

Cumulative max for each group.

Returns:

Series or DataFrame

See also

Series.groupby

Apply a function groupby to a Series.

DataFrame.groupby

Apply a function groupby to each row or column of a DataFrame.

Examples

For SeriesGroupBy:

>>> lst = ['a', 'a', 'a', 'b', 'b', 'b']
>>> ser = pd.Series([1, 6, 2, 3, 1, 4], index=lst)
>>> ser
a 1
a 6
a 2
b 3
b 1
b 4
dtype: int64
>>> ser.groupby(level=0).cummax()
a 1
a 6
a 6
b 3
b 3
b 4
dtype: int64

For DataFrameGroupBy:

>>> data = [[1, 8, 2], [1, 1, 0], [2, 6, 9]]
>>> df = pd.DataFrame(data, columns=["a", "b", "c"],
...  index=["cow", "horse", "bull"])
>>> df
 a b c
cow 1 8 2
horse 1 1 0
bull 2 6 9
>>> df.groupby("a").groups
{1: ['cow', 'horse'], 2: ['bull']}
>>> df.groupby("a").cummax()
 b c
cow 8 2
horse 8 2
bull 6 9