code: def column_mask(self):
          
          margin = compress_pruned(
              self._slice.margin(
                  axis=0,
                  weighted=False,
                  include_transforms_for_dims=self._hs_dims,
                  prune=self._prune,
              )
          )
          mask = margin < self._size
  
          if margin.shape == self._shape:
              # If margin shape is the same as slice's (such as in a col margin for
              # MR x CAT), don't broadcast the mask to the array shape, since
              # they're already the same.
              return mask
  
          # If the row margin is a row vector - broadcast it's mask to the array shape
          return np.logical_or(np.zeros(self._shape, dtype=bool), mask)
docs: ndarray, True where column margin <= min_base_size, same shape as slice.