Calculate the rolling Fisher’s definition of kurtosis without bias.
Include only float, int, boolean columns.
Added in version 1.5.0.
Return type is the same as the original object with np.float64 dtype.
See also
scipy.stats.kurtosisReference SciPy method.
pandas.Series.rollingCalling rolling with Series data.
pandas.DataFrame.rollingCalling rolling with DataFrames.
pandas.Series.kurtAggregating kurt for Series.
pandas.DataFrame.kurtAggregating 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
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https://pandas.pydata.org/pandas-docs/version/2.3.0/reference/api/pandas.core.window.rolling.Rolling.kurt.html