# 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)}

  skipna : boolean, 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 : boolean, 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 1. This means the sum or product of an all-NA or empty series is `NaN`.

  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]).sum(min_count=1)
      nan

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