pandas.core.window.EWM.cov¶
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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