code: def _denominator(self, weighted, include_transforms_for_dims, axis):
          
  
          table = self._measure(weighted).raw_cube_array
          new_axis = self._adjust_axis(axis)
          index = tuple(
              None if i in new_axis else slice(None) for i, _ in enumerate(table.shape)
          )
          hs_dims = self._hs_dims_for_den(include_transforms_for_dims, axis)
          den = self._apply_subtotals(self._apply_missings(table), hs_dims)
          return np.sum(den, axis=new_axis)[index]
docs: Calculate denominator for percentages.
  
          Only include those H&S dimensions, across which we DON'T sum. These H&S
          are needed because of the shape, when dividing. Those across dims
          which are summed across MUST NOT be included, because they would
          change the result.