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pandas.core.window.Rolling.cov

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 MultiIndexed DataFrame 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:
same type as input

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Licensed under the 3-clause BSD License.
http://pandas.pydata.org/pandas-docs/version/0.23.4/generated/pandas.core.window.Rolling.cov.html