pandas.core.window.Expanding.cov — pandas 0.24.0rc1 documentation (original) (raw)

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

Calculate the 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. **kwargs Keyword arguments to be passed into func.
Returns:	Series or DataFrame Return type is determined by the caller.

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.