docs: def transform_table(self, table, table_meta, missing=None):
          """Apply the stored transformers to `table`.
  
          Args:
              table(pandas.DataFrame):     Contents of the table to be transformed.
  
              table_meta(dict):   Metadata for the given table.
  
              missing(bool):      Wheter or not use NullTransformer to handle missing values.
  
          Returns:
              pandas.DataFrame: Transformed table.
          """
  
          if missing is None:
              missing = self.missing
  
          else:
              self.missing = missing
              warnings.warn(DEPRECATION_MESSAGE.format('transform_table'), DeprecationWarning)
  
          content = {}
          columns = []
          table_name = table_meta['name']
  
          for field in table_meta['fields']:
              column_name = field['name']
  
              if missing and table[column_name].isnull().any():
                  null_transformer = transformers.NullTransformer(field)
                  clean_column = null_transformer.fit_transform(table[column_name])
                  null_name = '?' + column_name
                  columns.append(null_name)
                  content[null_name] = clean_column[null_name].values
                  column = clean_column[column_name]
  
              else:
                  column = table[column_name].to_frame()
  
              transformer = self.transformers[(table_name, column_name)]
              content[column_name] = transformer.transform(column)[column_name].values
              columns.append(column_name)
  
          return pd.DataFrame(content, columns=columns)