xorbits.pandas.window.Rolling.kurt#

Rolling.kurt(**kwargs)[source]#

Calculate the rolling Fisher’s definition of kurtosis without bias.

Parameters

  • numeric_only (bool, default False (Not supported yet)) –

    Include only float, int, boolean columns.

    New in version 1.5.0.

  • **kwargs –

    For NumPy compatibility and will not have an effect on the result.

    Deprecated since version 1.5.0.

Returns

Return type is the same as the original object with np.float64 dtype.

Return type

Series or DataFrame

See also

scipy.stats.kurtosis

Reference SciPy method.

pandas.Series.rolling

Calling rolling with Series data.

pandas.DataFrame.rolling

Calling rolling with DataFrames.

pandas.Series.kurt

Aggregating kurt for Series.

pandas.DataFrame.kurt

Aggregating kurt for DataFrame.

Notes

A minimum of four periods is required for the 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

This docstring was copied from pandas.core.window.rolling.Rolling.