pandas.core.groupby.SeriesGroupBy.prod#

SeriesGroupBy.prod(numeric_only=False, min_count=0)[source] #

Compute prod of group values.

Parameters:

numeric_onlybool, default False

Include only float, int, boolean columns.

Changed in version 2.0.0: numeric_only no longer accepts None.

min_countint, default 0

The required number of valid values to perform the operation. If fewer than min_count non-NA values are present the result will be NA.

Returns:

Series or DataFrame

Computed prod of values within each group.

Examples

For SeriesGroupBy:

>>> lst = ['a', 'a', 'b', 'b']
>>> ser = pd.Series([1, 2, 3, 4], index=lst)
>>> ser
a 1
a 2
b 3
b 4
dtype: int64
>>> ser.groupby(level=0).prod()
a 2
b 12
dtype: int64

For DataFrameGroupBy:

>>> data = [[1, 8, 2], [1, 2, 5], [2, 5, 8], [2, 6, 9]]
>>> df = pd.DataFrame(data, columns=["a", "b", "c"],
...  index=["tiger", "leopard", "cheetah", "lion"])
>>> df
 a b c
 tiger 1 8 2
leopard 1 2 5
cheetah 2 5 8
 lion 2 6 9
>>> df.groupby("a").prod()
 b c
a
1 16 10
2 30 72