pandas.core.window.rolling.Rolling.kurt

Rolling.kurt(**kwargs)

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

pandas.Series.rolling

Calling object with Series data.

pandas.DataFrame.rolling

Calling object with DataFrames.

pandas.Series.kurt

Equivalent method for Series.

pandas.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

pandas.core.window.rolling.Rolling.skew pandas.core.window.rolling.Rolling.apply