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Question

I want to plot some data and then add a regression line and horizontal lines for the mean and mean +/- the standard deviation, each in a different colour. I have managed to do this but I can't get the legend right. It shows labels for the first two but says nothing about the three horizontal lines. How can I get the legend to have a label for each of these three lines too?

Another post mentioned show_guide = TRUE, but this didn't work for me. I've also been looking at the documentation for scale_colour_manual but that didn't help me.

My code is this:

p <- qplot(mpg, wt, data = mtcars, colour="1")
p <- p + geom_smooth(method='lm',aes(x=mpg,y=wt,colour="2"),formula=y~x)
p <- p + geom_hline(yintercept = mean(mtcars$wt), colour = "3")
p <- p + geom_hline(yintercept = mean(mtcars$wt) + sd(mtcars$wt), colour = "3",    linetype="dashed")
p <- p + geom_hline(yintercept = mean(mtcars$wt) - sd(mtcars$wt), colour = "3", linetype="dashed")      
p <- p + labs(colour="")    
p <- p + scale_colour_manual(values = c("red","blue", "green","green","green"),labels=c("Data","Regression","Mean","Mean + SD","Mean - SD"))
p <- p + guides(colour = guide_legend())
print(p)

Any help will be much appreciated, cheers!

Answer 1

I think this is probably closer to what you want:

d <- data.frame(yint = c(mean(mtcars$wt) - sd(mtcars$wt),
                mean(mtcars$wt),
                mean(mtcars$wt) + sd(mtcars$wt)),
                grp = c('dashed','solid','dashed'))

p <- ggplot(data = mtcars,aes(mpg, wt)) + 
    geom_point(aes(color = "Data")) +
    geom_smooth(method='lm',aes(x=mpg,y=wt,color = "Regression"),formula=y~x) + 
    geom_hline(data = d,aes(yintercept = yint,linetype = grp,color = "Mean +/- SD")) + 
    scale_linetype_manual(values = c('dashed' = 'dashed','solid' = 'solid')) + 
    labs(color = "")
print(p)

As to the question about labeling each of the horizontal lines separately, my answer is that that doesn't belong in the legend at all. Those should be labeled with geom_text() :

d <- data.frame(yint = c(mean(mtcars$wt) - sd(mtcars$wt),
                         mean(mtcars$wt),
                         mean(mtcars$wt) + sd(mtcars$wt)),
                         grp = c('dashed','solid','dashed'),
                         lab = c('-SD','Mean','+SD'))

p <- ggplot(data = mtcars,aes(mpg, wt)) + 
    geom_point(aes(color = "Data")) +
    geom_smooth(method='lm',aes(x=mpg,y=wt,color = "Regression"),formula=y~x) + 
    geom_hline(data = d,aes(yintercept = yint,linetype = grp),color = "green") + 
    geom_text(data = d,aes(y = yint,label = lab),
              vjust = -0.5,hjust = 1,x = Inf,size = 3) +
    scale_linetype_manual(values = c('dashed' = 'dashed','solid' = 'solid')) + 
    labs(color = "")
print(p)

Answer 2

Joran's answer inspired me to make some changes and now I have managed to write some code that gives me the plot and legend I was looking for:

n <- ncol(mtcars)
mtcars[,n+1] <- mean(mtcars$wt)
mtcars[,n+2] <- mean(mtcars$wt) + sd(mtcars$wt)
mtcars[,n+3] <- mean(mtcars$wt) - sd(mtcars$wt)
p <- qplot(mpg,wt,data = mtcars, colour="1")
p <- p + geom_smooth(method='lm',aes(x=mpg,y=wt,colour="2"),formula=y~x)
p <- p + geom_line(aes(x=mpg,y=mtcars[,n+1],colour="3"))
p <- p + geom_line(aes(x=mpg,y=mtcars[,n+2],colour="4"),linetype="dashed")
p <- p + geom_line(aes(x=mpg,y=mtcars[,n+3],colour="5"),linetype="dashed")
p <- p + labs(colour="")    
p <- p + scale_colour_manual(values = c("red","blue",  "green","green","green"),labels=c("Data","Regression","Mean","Mean + SD","Mean - SD"))
p <- p + guides(colour = guide_legend())
print(p)