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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 data(self):
 """list of mean numeric values of categorical responses."""

        means = []
        table = self._slice.as_array()
        products = self._inner_prods(table, self.values)

        for axis, product in enumerate(products):
            if product is None:
                means.append(product)
                continue

            # Calculate means
            valid_indices = self._valid_indices(axis)
            num = np.sum(product[valid_indices], axis)
            den = np.sum(table[valid_indices], axis)
            mean = num / den
            if not isinstance(mean, np.ndarray):
                mean = np.array([mean])
            means.append(mean)
        return means