pandas.core.groupby.SeriesGroupBy.kurt#
- SeriesGroupBy.kurt(skipna=True, numeric_only=False, **kwargs)[source]#
Return unbiased kurtosis within groups.
- 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 kurtosis within groups.
See also
Series.kurt
Return unbiased kurtosis over requested axis.
Examples
>>> ser = pd.Series( ... [390.0, 350.0, 357.0, 333.0, np.nan, 22.0, 20.0, 30.0, 40.0, 41.0], ... index=[ ... "Falcon", ... "Falcon", ... "Falcon", ... "Falcon", ... "Falcon", ... "Parrot", ... "Parrot", ... "Parrot", ... "Parrot", ... "Parrot", ... ], ... name="Max Speed", ... ) >>> ser Falcon 390.0 Falcon 350.0 Falcon 357.0 Falcon 333.0 Falcon NaN Parrot 22.0 Parrot 20.0 Parrot 30.0 Parrot 40.0 Parrot 41.0 Name: Max Speed, dtype: float64 >>> ser.groupby(level=0).kurt() Falcon 1.622109 Parrot -2.878714 Name: Max Speed, dtype: float64 >>> ser.groupby(level=0).kurt(skipna=False) Falcon NaN Parrot -2.878714 Name: Max Speed, dtype: float64