pandas.core.window.rolling.Rolling.kurt¶

Rolling.kurt(self, **kwargs)[source]¶

Calculate unbiased rolling kurtosis.

This function uses Fisher’s definition of kurtosis without bias.

Parameters

**kwargs: Under Review.

Returns

Series or DataFrame: Returned object type is determined by the caller of the rolling calculation.

See also

Series.rolling: Calling object with Series data.
DataFrame.rolling: Calling object with DataFrames.
Series.kurt: Equivalent method for Series.
DataFrame.kurt: Equivalent method for DataFrame.
scipy.stats.skew: Third moment of a probability density.
scipy.stats.kurtosis: Reference SciPy method.

Notes

A minimum of 4 periods is required for the rolling calculation.

Examples

The example below will show a rolling calculation with a window size of four matching the equivalent function call using scipy.stats.

>>> arr = [1, 2, 3, 4, 999]
>>> import scipy.stats
>>> print(f"{scipy.stats.kurtosis(arr[:-1], bias=False):.6f}")
-1.200000
>>> print(f"{scipy.stats.kurtosis(arr[1:], bias=False):.6f}")
3.999946
>>> s = pd.Series(arr)
>>> s.rolling(4).kurt()
0         NaN
1         NaN
2         NaN
3   -1.200000
4    3.999946
dtype: float64