cudf.DataFrame.prod#
- DataFrame.prod(axis=_NoDefault.no_default, skipna=True, dtype=None, numeric_only=False, min_count=0, **kwargs)[source]#
Return product of the values in the DataFrame.
- Parameters:
- axis: {index (0), columns(1)}
Axis for the function to be applied on.
- skipna: bool, default True
Exclude NA/null values when computing the result.
- dtype: data type
Data type to cast the result to.
- numeric_onlybool, default False
If True, includes only float, int, boolean columns. If False, will raise error in-case there are non-numeric columns.
- min_count: int, 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.
The default being 0. This means the sum of an all-NA or empty Series is 0, and the product of an all-NA or empty Series is 1.
- Returns:
- Series
Examples
>>> import cudf >>> df = cudf.DataFrame({'a': [1, 2, 3, 4], 'b': [7, 8, 9, 10]}) >>> df.product() a 24 b 5040 dtype: int64
Pandas Compatibility Note
pandas.DataFrame.product()
,pandas.Series.product()
Parameters currently not supported are level`, numeric_only.