code: def table_mask(self):
          
          margin = compress_pruned(
              self._slice.margin(
                  axis=None,
                  weighted=False,
                  include_transforms_for_dims=self._hs_dims,
                  prune=self._prune,
              )
          )
          mask = margin < self._size
  
          if margin.shape == self._shape:
              return mask
  
          if self._slice.dim_types[0] == DT.MR:
              # If the margin is a column vector - broadcast it's mask to the array shape
              return np.logical_or(np.zeros(self._shape, dtype=bool), mask[:, None])
  
          return np.logical_or(np.zeros(self._shape, dtype=bool), mask)
docs: ndarray, True where table margin <= min_base_size, same shape as slice.