pandas.core.window.rolling.Rolling.var

Rolling.var(ddof=1, *args, **kwargs)

Calculate the rolling variance.

Parameters

ddofint, default 1

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

*args

For NumPy compatibility and will not have an effect on the result.

**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.

See also

numpy.var

Equivalent method for NumPy array.

pandas.Series.rolling

Calling rolling with Series data.

pandas.DataFrame.rolling

Calling rolling with DataFrames.

pandas.Series.var

Aggregating var for Series.

pandas.DataFrame.var

Aggregating var for DataFrame.

Notes

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

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

The implementation is susceptible to floating point imprecision as shown in the example below.

Examples

>>> s = pd.Series([5, 5, 6, 7, 5, 5, 5])
>>> s.rolling(3).var()
0             NaN
1             NaN
2    3.333333e-01
3    1.000000e+00
4    1.000000e+00
5    1.333333e+00
6    6.661338e-16
dtype: float64

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