xorbits.pandas.groupby.DataFrameGroupBy.prod#
- DataFrameGroupBy.prod(**kw)#
Compute prod of group values.
- Parameters
numeric_only (bool, default False (Not supported yet)) –
Include only float, int, boolean columns.
Changed in version 2.0.0(pandas): numeric_only no longer accepts
None
.min_count (int, default 0 (Not supported yet)) – 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
Computed prod of values within each group.
- Return type
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
This docstring was copied from pandas.core.groupby.generic.DataFrameGroupBy.