code: def create_multiple_expectations(df, columns, expectation_type, *args, **kwargs):
      
      expectation = getattr(df, expectation_type)
      results = list()
  
      for column in columns:
          results.append(expectation(column, *args,  **kwargs))
  
      return results
docs: Creates an identical expectation for each of the given columns with the specified arguments, if any.
  
      Args:
          df (great_expectations.dataset): A great expectations dataset object.
          columns (list): A list of column names represented as strings.
          expectation_type (string): The expectation type.
  
      Raises:
          KeyError if the provided column does not exist.
          AttributeError if the provided expectation type does not exist or df is not a valid great expectations dataset.
  
      Returns:
          A list of expectation results.