Rolling.var(self, ddof=1, *args, **kwargs)
[source]
Calculate unbiased rolling variance.
Normalized by N-1 by default. This can be changed using the ddof
argument.
Parameters: |
|
---|---|
Returns: |
|
See also
Series.rolling
DataFrame.rolling
Series.var
DataFrame.var
numpy.var
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.
>>> 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
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Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/0.25.0/reference/api/pandas.core.window.Rolling.var.html