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 expanding Fisher's definition of kurtosis without bias.
pandas.DataFrame.expanding
Calling expanding with DataFrames.
pandas.DataFrame.kurt
Aggregating kurt for DataFrame.
pandas.Series.expanding
Calling expanding with Series data.
pandas.Series.kurt
Aggregating kurt for Series.
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, bias=False):.6f}") 4.999874This example is valid syntax, but we were not able to check execution
>>> s = pd.Series(arr)See :
... s.expanding(4).kurt() 0 NaN 1 NaN 2 NaN 3 -1.200000 4 4.999874 dtype: float64
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