pandas.api.typing.Rolling.kurt

Rolling.kurt(numeric_only=False)

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

This is equivalent to applying scipy.stats.kurtosis (with bias=False) over each rolling window. A minimum of four periods is required.

Parameters:

numeric_onlybool, default False

Include only float, int, boolean columns.

Returns:

Series or DataFrame

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

See also

scipy.stats.kurtosis

Reference SciPy method.

Series.rolling

Calling rolling with Series data.

DataFrame.rolling

Calling rolling with DataFrames.

Series.kurt

Aggregating kurt for Series.

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