code: def hepatitis(return_X_y=True):
      
      # y is real
      # recommend LinearGAM
      hep = pd.read_csv(PATH + '/hepatitis_A_bulgaria.csv').astype(float)
      if return_X_y:
          # eliminate 0/0
          mask = (hep.total > 0).values
          hep = hep[mask]
  
          X = hep.age.values
          y = hep.hepatitis_A_positive.values / hep.total.values
          return _clean_X_y(X, y)
      return hep
docs: hepatitis in Bulgaria dataset
  
      Parameters
      ----------
      return_X_y : bool,
          if True, returns a model-ready tuple of data (X, y)
          otherwise, returns a Pandas DataFrame
  
      Returns
      -------
      model-ready tuple of data (X, y)
          OR
      Pandas DataFrame
  
      Notes
      -----
      X contains the age of each patient group.
  
      y contains the ratio of HAV positive patients to the total number for each
      age group.
  
      Groups with 0 total patients are excluded.
  
      Source:
      Keiding, N. (1991) Age-specific incidence and prevalence: a statistical perspective