code: def _compute_baseline_survival(self):
          
          survival_df = np.exp(-self.baseline_cumulative_hazard_)
          if self.strata is None:
              survival_df.columns = ["baseline survival"]
          return survival_df
docs: Importantly, this agrees with what the KaplanMeierFitter produces. Ex:
  
          Example
          -------
          >>> from lifelines.datasets import load_rossi
          >>> from lifelines import CoxPHFitter, KaplanMeierFitter
          >>> rossi = load_rossi()
          >>> kmf = KaplanMeierFitter()
          >>> kmf.fit(rossi['week'], rossi['arrest'])
          >>> rossi2 = rossi[['week', 'arrest']].copy()
          >>> rossi2['var1'] = np.random.randn(432)
          >>> cph = CoxPHFitter()
          >>> cph.fit(rossi2, 'week', 'arrest')
          >>> ax = cph.baseline_survival_.plot()
          >>> kmf.plot(ax=ax)