code: def drop_dimension(self, dimensions):
          
          dimensions = [dimensions] if np.isscalar(dimensions) else dimensions
          dims = [d for d in self.kdims if d not in dimensions]
          dim_inds = [self.get_dimension_index(d) for d in dims]
          key_getter = itemgetter(*dim_inds)
          return self.clone([(key_getter(k), v) for k, v in self.data.items()],
                            kdims=dims)
docs: Drops dimension(s) from keys
  
          Args:
              dimensions: Dimension(s) to drop
  
          Returns:
              Clone of object with with dropped dimension(s)