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

Series or DataFrame

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.