tween 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.
        bias : bool, default False
            Use a standard estimation bias correction.
        zú        >>> ser1 = pd.Series([1, 2, 3, 4])
        >>> ser2 = pd.Series([10, 11, 13, 16])
        >>> ser1.ewm(alpha=.2).cov(ser2)
        0         NaN
        1    0.500000
        2    1.524590
        3    3.408836
        dtype: float64
        z/(exponential weighted moment) sample covarianceÚ