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Expanding.cov(other=None, pairwise=None, ddof=1, **kwargs)[source]

expanding sample covariance


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, where N represents the number of elements.


same type as input

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