kurt(self, **kwargs)
A minimum of four periods is required for the calculation.
For NumPy compatibility and will not have an effect on the result.
Return type is the same as the original object with np.float64
dtype.
Calculate the rolling Fisher's definition of kurtosis without bias.
pandas.DataFrame.kurt
Aggregating kurt for DataFrame.
pandas.DataFrame.rolling
Calling rolling with DataFrames.
pandas.Series.kurt
Aggregating kurt for Series.
pandas.Series.rolling
Calling rolling with Series data.
scipy.stats.kurtosis
Reference SciPy method.
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]This example is valid syntax, but we were not able to check execution
... 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}") 3.999946This example is valid syntax, but we were not able to check execution
>>> s = pd.Series(arr)See :
... s.rolling(4).kurt() 0 NaN 1 NaN 2 NaN 3 -1.200000 4 3.999946 dtype: float64
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