pandas.core.groupby.DataFrameGroupBy.prod

DataFrameGroupBy.prod(numeric_only=False, min_count=0)

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.

See also

Series.prod

Return the product of the values over the requested axis.

DataFrame.prod

Return the product of the values over the requested axis.

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