pandas.core.groupby.SeriesGroupBy.skew#
- SeriesGroupBy.skew(axis=_NoDefault.no_default, skipna=True, numeric_only=False, **kwargs)[source]#
Return unbiased skew within groups.
Normalized by N-1.
- Parameters
- axis{0 or ‘index’, 1 or ‘columns’, None}, default 0
Axis for the function to be applied on. This parameter is only for compatibility with DataFrame and is unused.
- skipnabool, default True
Exclude NA/null values when computing the result.
- numeric_onlybool, default False
Include only 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