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pandas.core.window.Rolling.cov

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

Calculate the 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.

**kwargs

Keyword arguments to be passed into func.

Returns:
Series or DataFrame

Return type is determined by the caller.

See also

Series.rolling
Series rolling.
DataFrame.rolling
DataFrame rolling.

© 2008–2012, AQR Capital Management, LLC, Lambda Foundry, Inc. and PyData Development Team
Licensed under the 3-clause BSD License.
https://pandas.pydata.org/pandas-docs/version/0.25.0/reference/api/pandas.core.window.Rolling.cov.html