pandas.stats.moments.rolling_cov¶
- pandas.stats.moments.rolling_cov(arg1, arg2=None, window=None, min_periods=None, freq=None, center=False, pairwise=None, how=None, ddof=1)¶
Unbiased moving covariance.
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.
ddof : int, default 1
Delta Degrees of Freedom. The divisor used in calculations is N - ddof, where N represents the number of elements.
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).