pandas.core.window.rolling.Window.var

Window.var(self, ddof=1, *args, **kwargs)

Calculate unbiased window variance.

New in version 1.0.0.

Normalized by N-1 by default. This can be changed using the ddof argument.

Parameters

ddofint, default 1

Delta Degrees of Freedom. The divisor used in calculations is N - ddof, where N represents the number of elements.

*args, **kwargs

For NumPy compatibility. No additional arguments are used.

Returns

Series or DataFrame

Returns the same object type as the caller of the window calculation.

See also

pandas.Series.window

Calling object with Series data.

pandas.DataFrame.window

Calling object with DataFrames.

pandas.Series.var

Equivalent method for Series.

pandas.DataFrame.var

Equivalent method for DataFrame.

numpy.var

Equivalent method for Numpy array.

Notes

The default ddof of 1 used in Series.var() is different than the default ddof of 0 in numpy.var().

A minimum of 1 period is required for the rolling calculation.

Examples

>>> s = pd.Series([5, 5, 6, 7, 5, 5, 5])
>>> s.rolling(3).var()
0         NaN
1         NaN
2    0.333333
3    1.000000
4    1.000000
5    1.333333
6    0.000000
dtype: float64

>>> s.expanding(3).var()
0         NaN
1         NaN
2    0.333333
3    0.916667
4    0.800000
5    0.700000
6    0.619048
dtype: float64

pandas.core.window.rolling.Window.sum pandas.core.window.rolling.Window.std