pandas.core.groupby.SeriesGroupBy.skew — pandas 2.2.3 documentation (original) (raw)

SeriesGroupBy.skew(axis=<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.

Deprecated since version 2.1.0: For axis=1, operate on the underlying object instead. Otherwise the axis keyword is not necessary.

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