pandas.core.groupby.SeriesGroupBy.kurt — pandas 3.0.0.dev0+2098.g9c5b9ee823 documentation (original) (raw)

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