pandas.Series.kurt#

Series.kurt(*, axis=0, skipna=True, numeric_only=False, **kwargs)[source]#

Return unbiased kurtosis over requested axis.

Kurtosis obtained using Fisher’s definition of kurtosis (kurtosis of normal == 0.0). Normalized by N-1.

Parameters:
axis{index (0)}

Axis for the function to be applied on. For Series this parameter is unused and defaults to 0.

For DataFrames, specifying axis=None will apply the aggregation across both axes.

Added in version 2.0.0.

skipnabool, default True

Exclude NA/null values when computing the result.

numeric_onlybool, default False

Include only float, int, boolean columns.

**kwargs

Additional keyword arguments to be passed to the function.

Returns:
scalar

Unbiased kurtosis.

See also

Series.skew

Return unbiased skew over requested axis.

Series.var

Return unbiased variance over requested axis.

Series.std

Return unbiased standard deviation over requested axis.

Examples

>>> s = pd.Series([1, 2, 2, 3], index=["cat", "dog", "dog", "mouse"])
>>> s
cat    1
dog    2
dog    2
mouse  3
dtype: int64
>>> s.kurt()
1.5