pandas.core.groupby.SeriesGroupBy.prod — pandas 2.2.3 documentation (original) (raw)

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