xorbits.pandas.window.ExponentialMovingWindow.var#

ExponentialMovingWindow.var()#

Calculate the ewm (exponential weighted moment) variance.

Parameters

  • bias (bool, default False (Not supported yet)) – Use a standard estimation bias correction.

  • numeric_only (bool, default False (Not supported yet)) –

    Include only float, int, boolean columns.

    New in version 1.5.0(pandas).

Returns

Return type is the same as the original object with np.float64 dtype.

Return type

Series or DataFrame

See also

pandas.Series.ewm

Calling ewm with Series data.

pandas.DataFrame.ewm

Calling ewm with DataFrames.

pandas.Series.var

Aggregating var for Series.

pandas.DataFrame.var

Aggregating var for DataFrame.

Examples

>>> ser = pd.Series([1, 2, 3, 4])  
>>> ser.ewm(alpha=.2).var()  
0         NaN
1    0.500000
2    0.991803
3    1.631547
dtype: float64

This docstring was copied from pandas.core.window.ewm.ExponentialMovingWindow.