pandas.core.window.rolling.Rolling.kurt

Rolling.kurt(**kwargs)

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

Parameters

**kwargs

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

Returns

Series or DataFrame

Return type is the same as the original object.

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

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