pandas.DataFrame.product

DataFrame.product(axis=None, skipna=None, level=None, numeric_only=None, min_count=0, **kwargs)

Return the product of the values for the requested axis.

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.

level : int or level name, default None

If the axis is a MultiIndex (hierarchical), count along a particular level, collapsing into a Series.

numeric_only : bool, default None

Include only float, int, boolean columns. If None, will attempt to use everything, then use only numeric data. Not implemented for Series.

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.

New in version 0.22.0: Added with 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.

**kwargs

Additional keyword arguments to be passed to the function.

Returns:

prod : Series or DataFrame (if level specified)

Examples

By default, the product of an empty or all-NA Series is 1

>>> pd.Series([]).prod()
1.0

This can be controlled with the min_count parameter

>>> pd.Series([]).prod(min_count=1)
nan

Thanks to the skipna parameter, min_count handles all-NA and empty series identically.

>>> pd.Series([np.nan]).prod()
1.0

>>> pd.Series([np.nan]).prod(min_count=1)
nan