pandas.core.window.Rolling.kurt

Rolling.kurt(**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]
>>> fmt = "{0:.6f}"  # limit the printed precision to 6 digits
>>> import scipy.stats
>>> print(fmt.format(scipy.stats.kurtosis(arr[:-1], bias=False)))
-1.200000
>>> print(fmt.format(scipy.stats.kurtosis(arr[1:], bias=False)))
3.999946
>>> s = pd.Series(arr)
>>> s.rolling(4).kurt()
0         NaN
1         NaN
2         NaN
3   -1.200000
4    3.999946
dtype: float64