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