pandas.core.window.ewm.ExponentialMovingWindow.cov

ExponentialMovingWindow.cov(other=None, pairwise=None, bias=False, **kwargs)[source]

Exponential weighted sample covariance.

Parameters
otherSeries, DataFrame, or ndarray, optional

If not supplied then will default to self and produce pairwise output.

pairwisebool, 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 MultiIndex DataFrame in the case of DataFrame inputs. In the case of missing elements, only complete pairwise observations will be used.

biasbool, default False

Use a standard estimation bias correction.

**kwargs

Keyword arguments to be passed into func.

Returns
Series or DataFrame

Return type is determined by the caller.

See also

pandas.Series.ewm

Calling object with Series data.

pandas.DataFrame.ewm

Calling object with DataFrame data.

pandas.Series.cov

Similar method for Series.

pandas.DataFrame.cov

Similar method for DataFrame.