Ho to color specific values in scatter plot in R

January 19, 2023

A sample of my data is:

df<-read.table (text=" No   value
1   -1.25
2   -0.9
3   0.91
4   2.39
5   1.54
6   1.87
7   -2.5
8   -1.73
9   1.26
10  -2.1

", header=TRUE)

The numbers outside of -2 and +2 should be coloured, let’s say, red. In this example, the number are 4,7 and 10, Here is my effort :

ggplot(df, aes(x=No, y=value)) +
  theme_bw()+geom_text(aes(label=No))+
  geom_hline(yintercept=2, linetype="dashed", color = "red")+
  geom_hline(yintercept=-2, linetype="dashed", color = "red")

>Solution :

Use ggplot2’s aesthetics for color= (and a manual color scale).

ggplot(df, aes(x=No, y=value)) +
  theme_bw() + geom_text(aes(label=No, color=abs(value)>2))+
  geom_hline(yintercept=2, linetype="dashed", color = "red")+
  geom_hline(yintercept=-2, linetype="dashed", color = "red")+
  scale_color_manual(values = c("FALSE" = "black", "TRUE" = "red"))

Reduction: you can combine your geom_hline‘s if you’d like,

ggplot(df, aes(x=No, y=value)) +
  theme_bw() + geom_text(aes(label=No, color=abs(value)>2))+
  geom_hline(yintercept=c(-2,2), linetype="dashed", color = "red")+
  scale_color_manual(values = c("FALSE" = "black", "TRUE" = "red"))

In general, I prefer to use as few geom_*s as strictly required, relying more in ggplot2’s internal grouping and aesthetic handling: it is robust, elegant, and at times more flexible when the data changes. There are certainly times when I use multiple geom_* calls and bespoke subsets of the data for each, so it’s not a broken paradigm.

The naming of the legend is unlikely to be satisfactory in the long term. You can remove it entirely with ... + guides(color="none"), or you can pre-process the variable in as Tom’s answer demonstrates, providing a way to control the name of the group and its apparent levels.