pandas.core.groupby.SeriesGroupBy.cumprod#

SeriesGroupBy.cumprod(axis=<no_default>, *args, **kwargs)[source]#

Cumulative product 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', 'b']
>>> ser = pd.Series([6, 2, 0], index=lst)
>>> ser
a    6
a    2
b    0
dtype: int64
>>> ser.groupby(level=0).cumprod()
a    6
a   12
b    0
dtype: int64

For DataFrameGroupBy:

>>> data = [[1, 8, 2], [1, 2, 5], [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   2   5
bull    2   6   9
>>> df.groupby("a").groups
{1: ['cow', 'horse'], 2: ['bull']}
>>> df.groupby("a").cumprod()
        b   c
cow     8   2
horse  16  10
bull    6   9