pandas.core.window.ewm.ExponentialMovingWindow.cov#

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

Calculate the ewm (exponential weighted moment) sample covariance.

Parameters

otherSeries or DataFrame , 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.
numeric_onlybool, default False: Include only float, int, boolean columns.

New in version 1.5.0.
**kwargs: For NumPy compatibility and will not have an effect on the result.

Deprecated since version 1.5.0.

Returns

Series or DataFrame: Return type is the same as the original object with np.float64 dtype.