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.

def plot(self, columns=None, **errorbar_kwargs):
        """
        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.

        """
        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