code: def _as_array(
          self,
          include_missing=False,
          get_non_selected=False,
          weighted=True,
          include_transforms_for_dims=False,
      ):
          
          return self._apply_subtotals(
              self._apply_missings(
                  self._measure(weighted).raw_cube_array, include_missing=include_missing
              ),
              include_transforms_for_dims,
          )
docs: Get crunch cube as ndarray.
  
          Args
              include_missing (bool): Include rows/cols for missing values.
              get_non_selected (bool): Get non-selected slices for MR vars.
              weighted (bool): Take weighted or unweighted counts.
              include_transforms_for_dims (list): For which dims to
                  include headings & subtotals (H&S) transformations.
          Returns
              res (ndarray): Tabular representation of crunch cube