bigframes.pandas.api.typing.SeriesGroupBy.skew

SeriesGroupBy.skew(*args, **kwargs) → Series

Return unbiased skew within groups.

Normalized by N-1.

Examples:

For SeriesGroupBy:

>>> ser = bpd.Series([390., 350., 357., np.nan, 22., 20., 30.],
...                  index=['Falcon', 'Falcon', 'Falcon', 'Falcon',
...                         'Parrot', 'Parrot', 'Parrot'],
...                  name="Max Speed")
>>> ser.groupby(level=0).skew()
Falcon    1.525174
Parrot    1.457863
Name: Max Speed, dtype: Float64

Parameters:

numeric_only (bool, default False) – Include only float, int or boolean data.

Returns:

Variance of values within each group.

Return type:

bigframes.pandas.DataFrame or bigframes.pandas.Series