pandas.core.window.rolling.Rolling.kurt#

Rolling.kurt(numeric_only=False)[source]#

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

Parameters:

numeric_onlybool, default False: Include only float, int, boolean columns.

Added in version 1.5.0.

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.
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