pandas.core.window.rolling.Rolling.kurt¶
- Rolling.kurt(**kwargs)[source]¶
Calculate the rolling Fisher’s definition of kurtosis without bias.
- Parameters
- **kwargs
For NumPy compatibility and will not have an effect on the result.
- 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