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Rolling.cov(other=None, pairwise=None, ddof=1, **kwargs)
[source] -
rolling 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 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
, whereN
represents the number of elements.Returns: same type as input
Rolling.cov()
2017-01-12 04:53:01
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