 float, int, boolean columns. Not implemented for Series.

        **kwargs
            Additional keyword arguments to be passed to the function.

        Returns
        -------
        Series

        See Also
        --------
        Series.skew : Return unbiased skew over requested axis.

        Examples
        --------
        >>> ser = pd.Series([390., 350., 357., np.nan, 22., 20., 30.],
        ...                 index=['Falcon', 'Falcon', 'Falcon', 'Falcon',
        ...                        'Parrot', 'Parrot', 'Parrot'],
        ...                 name="Max Speed")
        >>> ser
        Falcon    390.0
        Falcon    350.0
        Falcon    357.0
        Falcon      NaN
        Parrot     22.0
        Parrot     20.0
        Parrot     30.0
        Name: Max Speed, dtype: float64
        >>> ser.groupby(level=0).skew()
        Falcon    1.525174
        Parrot    1.457863
        Name: Max Speed, dtype: float64
        >>> ser.groupby(level=0).skew(skipna=False)
        Falcon         NaN
        Parrot    1.457863
        Name: Max Speed, dtype: float64
        r