bigframes.pandas.api.typing.SeriesGroupBy.kurt#
- SeriesGroupBy.kurt(*args, **kwargs) Series[source]#
Return unbiased kurtosis over requested axis.
Kurtosis obtained using Fisher’s definition of kurtosis (kurtosis of normal == 0.0). Normalized by N-1.
Examples:
>>> lst = ['a', 'a', 'a', 'a', 'b', 'b', 'b', 'b', 'b'] >>> ser = bpd.Series([0, 1, 1, 0, 0, 1, 2, 4, 5], index=lst) >>> ser.groupby(level=0).kurt() a -6.0 b -1.963223 dtype: Float64
- Parameters:
numeric_only (bool, default False) – Include only float, int or boolean data.
- Returns:
Variance of values within each group.
- Return type: