code: def none_missing(df, columns=None):
      
      if columns is None:
          columns = df.columns
      try:
          assert not df[columns].isnull().any().any()
      except AssertionError as e:
          missing = df[columns].isnull()
          msg = generic.bad_locations(missing)
          e.args = msg
          raise
      return df
docs: Asserts that there are no missing values (NaNs) in the DataFrame.
  
      Parameters
      ----------
      df : DataFrame
      columns : list
        list of columns to restrict the check to
  
      Returns
      -------
      df : DataFrame
        same as the original