在绘图上用多行添加图例到ggplot2

Question

我真的很感激这方面的一些帮助.我完全不明白ggplot2是如何思考传说的!

该图表基于以下数据框架,称为"meltdf":

        xval       variable  value
1   0.000000 Shortfall Risk 100.00
2   4.624457 Shortfall Risk  99.83
3   9.179656 Shortfall Risk  60.96
4  13.742579 Shortfall Risk  36.29
5  18.620338 Shortfall Risk  27.71
6  22.947704 Shortfall Risk  22.52
7  27.690638 Shortfall Risk  19.72
8  32.174379 Shortfall Risk  17.89
9  36.637940 Shortfall Risk  15.79
10 41.107962 Shortfall Risk  15.96
11 45.644065 Shortfall Risk  15.97

该图表如下:

ggplot(data=meltdf,aes(x=xval,y=value))+
  geom_line(size=1,colour=rgb(69,99,111,max=255))+
  geom_vline(xintercept = 22 ,colour="darkgray")+
  geom_vline(xintercept = 30 ,colour="darkred")+
  theme_bw()+
  labs(title="Shortfall Risk versus Investment Risk, Meeting Expenditure Only")+
  theme(legend.position="bottom",
    legend.text = element_text(size=9),
    axis.text = element_text(size=9),
    axis.title = element_text(size=9),
    plot.title=element_text(size = 9),
    legend.title=element_text(size=9))+
  labs(x="Largest Historical Decline (%)", y="Probability of Shortfall (%)")+
  scale_y_continuous(limits = c(0, 100))

我想在底部有一个图例,其中图表中的所有三行(蓝色,红色和灰色)都被命名.

Answer 1

ggplot将自动生成在aes()调用中映射的元素(颜色,线型等)的图例.这意味着当您手动指定元素的颜色时,您将无法获得图例,就像您在此处所做的那样(所有colour语句都不在内部aes).

我建议您将垂直线的坐标存储在自己的数据框中,在这些数据框中,它们可以映射到给出颜色的变量.在这里,我创建了这样一个dataframe(summ)并重写了你的代码geom_vline().我也被映射meltdf$variable到colour在geom_vline所以它出现在传奇.最后,我添加scale_colour_manual()了选择颜色.您可能希望调整其值,summ$colour以便它们在图例中有意义.

summ <- data.frame(x=c(22,30),
                   colour=c("gray","red"))

ggplot(data=meltdf,aes(x=xval,y=value))+
  geom_line(size=1,aes(colour=variable))+
  geom_vline(data=summ,aes(xintercept = x,colour=colour))+
  scale_color_manual(values = c(rgb(69,99,111,max=255),"darkgray","darkred")) +
  theme_bw()+
  labs(title="Shortfall Risk versus Investment Risk, Meeting Expenditure Only")+
  theme(legend.position="bottom",
        legend.text = element_text(size=9),
        axis.text = element_text(size=9),
        axis.title = element_text(size=9),
        plot.title=element_text(size = 9),
        legend.title=element_text(size=9))+
  labs(x="Largest Historical Decline (%)", y="Probability of Shortfall (%)")+
  scale_y_continuous(limits = c(0, 100))