code: def drop_columns(
          self, max_na_values: int = None, max_unique_values: int = None
      ):
          
          step = {}
  
          if max_na_values is not None:
              step = {
                  'data-set': self.iid,
                  'operation': 'drop-na',
                  'expression': '{"max_na_values":%s, "axis": 1}' % max_na_values
              }
          if max_unique_values is not None:
              step = {
                  'data-set': self.iid,
                  'operation': 'drop-unique',
                  'expression': '{"max_unique_values":%s}' % max_unique_values
              }
          self.attr_update(attr='steps', value=[step])
docs: When max_na_values was informed, remove columns when the proportion of
          total NA values more than max_na_values threshold.
  
          When max_unique_values was informed, remove columns when the proportion
          of the total of unique values is more than the max_unique_values
          threshold, just for columns with type as object or category.
  
          :param max_na_values: proportion threshold of max na values
          :param max_unique_values:
          :return: