docs: def fit_transform(
              self, tables=None, transformer_dict=None, transformer_list=None, missing=None):
          """Create, apply and store the specified transformers for the given tables.
  
          Args:
              tables(dict):   Mapping of table names to `tuple` where each tuple is on the form
                              (`pandas.DataFrame`, `dict`). The `DataFrame` contains the table data
                              and the `dict` the corresponding meta information.
                              If not specified, the tables will be retrieved using the meta_file.
  
              transformer_dict(dict):     Mapping  `tuple(str, str)` -> `str` where the tuple is
                                          (table_name, column_name).
  
              transformer_list(list):     List of transformers to use. Overrides the transformers in
                                          the meta_file.
  
              missing(bool):      Wheter or not use NullTransformer to handle missing values.
  
          Returns:
              dict: Map from `str` (table_names) to `pandas.DataFrame` (transformed data).
          """
  
          if missing is None:
              missing = self.missing
  
          else:
              self.missing = missing
              warnings.warn(DEPRECATION_MESSAGE.format('fit_transform'), DeprecationWarning)
  
          transformed = {}
  
          if tables is None:
              tables = self.table_dict
  
          if transformer_dict is None and transformer_list is None:
              transformer_dict = self.transformer_dict
  
          for table_name in tables:
              table, table_meta = tables[table_name]
              transformed_table = self.fit_transform_table(
                  table, table_meta, transformer_dict, transformer_list)
  
              transformed[table_name] = transformed_table
  
          return transformed