pandas.core.window.rolling.Rolling.kurt
- Rolling.kurt(**kwargs)[source]
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Calculate the rolling Fisher’s definition of kurtosis without bias.
- Parameters
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- **kwargs
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For NumPy compatibility and will not have an effect on the result.
- Returns
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- Series or DataFrame
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Return type is the same as the original object.
See also
scipy.stats.kurtosis
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Reference SciPy method.
pandas.Series.rolling
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Calling rolling with Series data.
pandas.DataFrame.rolling
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Calling rolling with DataFrames.
pandas.Series.kurt
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Aggregating kurt for Series.
pandas.DataFrame.kurt
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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
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Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/1.3.4/reference/api/pandas.core.window.rolling.Rolling.kurt.html