code: def plot(self, columns=None, **errorbar_kwargs):
          
          from matplotlib import pyplot as plt
  
          ax = errorbar_kwargs.pop("ax", None) or plt.figure().add_subplot(111)
  
          errorbar_kwargs.setdefault("c", "k")
          errorbar_kwargs.setdefault("fmt", "s")
          errorbar_kwargs.setdefault("markerfacecolor", "white")
          errorbar_kwargs.setdefault("markeredgewidth", 1.25)
          errorbar_kwargs.setdefault("elinewidth", 1.25)
          errorbar_kwargs.setdefault("capsize", 3)
  
          z = inv_normal_cdf(1 - self.alpha / 2)
  
          if columns is None:
              columns = self.hazards_.index
  
          yaxis_locations = list(range(len(columns)))
          symmetric_errors = z * self.standard_errors_[columns].to_frame().squeeze(axis=1).values.copy()
          hazards = self.hazards_[columns].values.copy()
  
          order = np.argsort(hazards)
  
          ax.errorbar(hazards[order], yaxis_locations, xerr=symmetric_errors[order], **errorbar_kwargs)
          best_ylim = ax.get_ylim()
          ax.vlines(0, -2, len(columns) + 1, linestyles="dashed", linewidths=1, alpha=0.65)
          ax.set_ylim(best_ylim)
  
          tick_labels = [columns[i] for i in order]
  
          ax.set_yticks(yaxis_locations)
          ax.set_yticklabels(tick_labels)
          ax.set_xlabel("log(HR) (%g%% CI)" % ((1 - self.alpha) * 100))
  
          return ax
docs: Produces a visual representation of the coefficients, including their standard errors and magnitudes.
  
          Parameters
          ----------
          columns : list, optional
              specify a subset of the columns to plot
          errorbar_kwargs:
              pass in additional plotting commands to matplotlib errorbar command
  
          Returns
          -------
          ax: matplotlib axis
              the matplotlib axis that be edited.