pandas.core.window.expanding.Expanding.kurt#
- Expanding.kurt(numeric_only=False)[source]#
Calculate the expanding Fisher’s definition of kurtosis without bias.
- Parameters
- numeric_onlybool, default False
Include only float, int, boolean columns.
New in version 1.5.0.
- 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.expanding
Calling expanding with Series data.
pandas.DataFrame.expanding
Calling expanding 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, bias=False):.6f}") 4.999874 >>> s = pd.Series(arr) >>> s.expanding(4).kurt() 0 NaN 1 NaN 2 NaN 3 -1.200000 4 4.999874 dtype: float64