code: def data(self):
          
          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
docs: list of mean numeric values of categorical responses.