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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 margin(self, axis):
 """Return marginal value of the current slice scaled means. This value is the the same what you would get from a single variable (constituting a 2D cube/slice), when the "non-missing" filter of the opposite variable would be applied. This behavior is consistent with what is visible in the front-end client. """

        if self._slice.ndim < 2:
            msg = (
                "Scale Means marginal cannot be calculated on 1D cubes, as"
                "the scale means already get reduced to a scalar value."
            )
            raise ValueError(msg)

        dimension_index = 1 - axis
        margin = self._slice.margin(axis=axis)
        if len(margin.shape) > 1:
            index = [
                0 if d.dimension_type == DT.MR else slice(None)
                for d in self._slice.dimensions
            ]
            margin = margin[index]
        total = np.sum(margin)
        values = self.values[dimension_index]

        if values is None:
            return None

        return np.sum(values * margin) / total