pandas.core.window.expanding.Expanding.kurt

Expanding.kurt(numeric_only=False, **kwargs)[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.

**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.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