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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def cov(self, other, min_periods=None):
 """ Compute covariance with Series, excluding missing values. Parameters other : Series Series with which to compute the covariance. min_periods : int, optional Minimum number of observations needed to have a valid result. Returns ------- float Covariance between Series and other normalized by N-1 (unbiased estimator). Examples -------- -0.01685762652715874 """

        this, other = self.align(other, join='inner', copy=False)
        if len(this) == 0:
            return np.nan
        return nanops.nancov(this.values, other.values,
                             min_periods=min_periods)