spotify_confidence/analysis/bayesian/bayesian_models.py [345:375]:
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        )
        # ch.callout.text(
        #     '{0:.2f}%'.format(posterior_mean * 100), posterior_mean, 0)
        ch.callout.text(
            f"Expected change: {posterior_mean:{format_str_precision(posterior_mean, absolute=False)}}",
            posterior_mean,
            0,
            angle=90,
        )

        # ch.callout.line(
        #     potential_loss,
        #     orientation='height',
        #     line_color=ch.style.color_palette._colors[1])
        # ch.callout.text(
        #     'Potential Loss: {0:.2f}%'.format(potential_loss * 100),
        #     potential_loss,
        #     1.5,
        #     angle=90)
        # ch.callout.text(
        #     '{0:.2f}%'.format(potential_loss * 100), potential_loss, 1.)

        ch.set_source_label("")
        ch.axes.set_yaxis_range(0)
        ch.axes.set_xaxis_label(self.get_difference_plot_label(absolute))
        ch.axes.set_yaxis_label("Probability Density")
        ch.axes.hide_yaxis()
        axis_format = axis_format_precision(df["values"].max() * 10, df["values"].min() * 10, absolute)
        ch.axes.set_xaxis_tick_format(axis_format)

        return ch
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spotify_confidence/analysis/bayesian/bayesian_models.py [681:710]:
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            )

            ch.callout.text(
                f"Expected change: {posterior_mean:{format_str_precision(posterior_mean, absolute=False)}}",
                posterior_mean,
                0,
                angle=90,
            )

        # ch.callout.line(
        #     potential_loss,
        #     orientation='height',
        #     line_color=ch.style.color_palette._colors[1])
        # ch.callout.text(
        #     'Potential Loss: {0:.2f}%'.format(potential_loss * 100),
        #     potential_loss,
        #     1.5,
        #     angle=90)
        # ch.callout.text(
        #     '{0:.2f}%'.format(potential_loss * 100), potential_loss, 1.)

        ch.set_source_label("")
        ch.axes.set_yaxis_range(0)
        ch.axes.set_xaxis_label(self.get_difference_plot_label(absolute))
        ch.axes.set_yaxis_label("Probability Density")
        ch.axes.hide_yaxis()
        axis_format = axis_format_precision(df["values"].max() * 10, df["values"].min() * 10, absolute)
        ch.axes.set_xaxis_tick_format(axis_format)

        return ch
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