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# pandas.stats.moments.rolling_var

`pandas.stats.moments.``rolling_var`(arg, window, min_periods=None, freq=None, center=False, how=None, **kwargs)

  Numerically stable implementation using Welford’s method.

  Unbiased moving variance.

  Parameters : | arg : Series, DataFrame window : int Size of the moving window. This is the number of observations used for calculating the statistic. min_periods : int, default None Minimum number of observations in window required to have a value (otherwise result is NA). freq : string or DateOffset object, optional (default None) Frequency to conform the data to before computing the statistic. Specified as a frequency string or DateOffset object. center : boolean, default False Set the labels at the center of the window. how : string, default ‘None’ Method for down- or re-sampling
  Returns : | y : type of input argument

  Notes

  By default, the result is set to the right edge of the window. This can be changed to the center of the window by setting `center=True`.

  The freq keyword is used to conform time series data to a specified frequency by resampling the data. This is done with the default parameters of `resample()` (i.e. using the mean).

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