pandas.core.groupby.DataFrameGroupBy.cumprod#

DataFrameGroupBy.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