code: def load_febrl4(return_links=False):
      
  
      df_a = _febrl_load_data('dataset4a.csv')
      df_b = _febrl_load_data('dataset4b.csv')
  
      if return_links:
          links = pandas.MultiIndex.from_arrays([
              ["rec-{}-org".format(i) for i in range(0, 5000)],
              ["rec-{}-dup-0".format(i) for i in range(0, 5000)]]
          )
          return df_a, df_b, links
      else:
          return df_a, df_b
docs: Load the FEBRL 4 datasets.
  
      The Freely Extensible Biomedical Record Linkage (Febrl) package is
      distributed with a dataset generator and four datasets generated
      with the generator. This function returns the fourth Febrl dataset
      as a :class:`pandas.DataFrame`.
  
              *"Generated as one data set with 10000 records (5000
              originals and 5000  duplicates, with one duplicate per
              original), the originals have been split from the
              duplicates, into dataset4a.csv (containing the 5000
              original records) and dataset4b.csv (containing the
              5000 duplicate records) These two data sets can be
              used for testing linkage procedures."*
  
      Parameters
      ----------
      return_links: bool
          When True, the function returns also the true links.
  
      Returns
      -------
      (pandas.DataFrame, pandas.DataFrame)
          A :class:`pandas.DataFrame` with Febrl dataset4a.csv and a pandas
          dataframe with Febrl dataset4b.csv. When return_links is True,
          the function returns also the true links.