pandas.core.window.Expanding.cov

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

expanding 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

See also

pandas.Series.expanding, pandas.DataFrame.expanding