pandas.core.groupby.SeriesGroupBy.skew#

SeriesGroupBy.skew(skipna=True, numeric_only=False, **kwargs)[source]#

Return unbiased skew within groups.

Normalized by N-1.

Parameters:

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: Unbiased skew within groups.

See also

Series.skew: Return unbiased skew over requested axis.

Examples

>>> ser = pd.Series(
...     [390.0, 350.0, 357.0, np.nan, 22.0, 20.0, 30.0],
...     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