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# pandas.stats.moments.rolling_corr

`pandas.stats.moments.``rolling_corr`(arg1, arg2=None, window=None, min_periods=None, freq=None, center=False, pairwise=None, how=None)

  Moving sample correlation.

  Parameters : | arg1 : Series, DataFrame, or ndarray arg2 : Series, DataFrame, or ndarray, optional if not supplied then will default to arg1 and produce pairwise output 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 pairwise : bool, default False If False then only matching columns between arg1 and arg2 will be used and the output will be a DataFrame. If True then all pairwise combinations will be calculated and the output will be a Panel in the case of DataFrame inputs. In the case of missing elements, only complete pairwise observations will be used.
  Returns : | y : type depends on inputs DataFrame / DataFrame -> DataFrame (matches on columns) or Panel (pairwise) DataFrame / Series -> Computes result for each column Series / Series -> Series

  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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