pandas.core.window.EWM.cov

EWM.cov(other=None, pairwise=None, bias=False, **kwargs) [source]

exponential weighted sample covariance

Parameters:

other : Series, DataFrame, or ndarray, optional if not supplied then will default to self and produce pairwise output pairwise : bool, default None If False then only matching columns between self and other 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 MultiIndex DataFrame in the case of DataFrame inputs. In the case of missing elements, only complete pairwise observations will be used. bias : boolean, default False Use a standard estimation bias correction

Returns:

same type as input

See also

pandas.Series.ewm, pandas.DataFrame.ewm