CODEWITHSUNDEEP
rggplot2geom-hline
Jesper.Lindberg
Jesper.Lindberg

Reputation: 341

Add geom_hline to legend

After searching the web both yesterday and today, the only way I get a legend working was to follow the solution by 'Brian Diggs' in this post: Add legend to ggplot2 line plot

Which gives me the following code:

library(ggplot2)
ggplot()+
  geom_line(data=myDf, aes(x=count, y=mean, color="TrueMean"))+
  geom_hline(yintercept = myTrueMean, color="SampleMean")+
  scale_colour_manual("",breaks=c("SampleMean", "TrueMean"),values=c("red","blue"))+
  labs(title = "Plot showing convergens of Mean", x="Index", y="Mean")+
  theme_minimal()

Everything works just fine if I remove the color of the hline, but if I add a value in the color of hline that is not an actual color (like "SampleMean") I get an error that it's not a color (only for the hline). How can adding a such common thing as a legend big such a big problem? There much be an easier way?

To create the original data:

#Initial variables
myAlpha=2
myBeta=2
successes=14
n=20
fails=n-successes

#Posterior values
postAlpha=myAlpha+successes
postBeta=myBeta+fails

#Calculating the mean and SD
myTrueMean=(myAlpha+successes)/(myAlpha+successes+myBeta+fails)
myTrueSD=sqrt(((myAlpha+successes)*(myBeta+fails))/((myAlpha+successes+myBeta+fails)^2*(myAlpha+successes+myBeta+fails+1)))

#Simulate the data
simulateBeta=function(n,tmpAlpha,tmpBeta){
  tmpValues=rbeta(n, tmpAlpha, tmpBeta)
  tmpMean=mean(tmpValues)
  tmpSD=sd(tmpValues)
  returnVector=c(count=n, mean=tmpMean, sd=tmpSD)
  return(returnVector)
}

#Make a df for the data
myDf=data.frame(t(sapply(2:10000, simulateBeta, postAlpha, postBeta)))

Upvotes: 3

Views: 7440

Answers (1)

pogibas
pogibas

Reputation: 28379

Given solution works in most of the cases, but not for geom_hline (vline). For them you usually don't have to use aes, but when you need to generate a legend then you have to wrap them within aes:

library(ggplot2)
ggplot() +
  geom_line(aes(count, mean, color = "TrueMean"), myDf) +
  geom_hline(aes(yintercept = myTrueMean, color = "SampleMean")) +
  scale_colour_manual(values = c("red", "blue")) +
  labs(title = "Plot showing convergens of Mean",
       x = "Index",
       y = "Mean",
       color = NULL) +
  theme_minimal()

enter image description here

Seeing original data you can use geom_point for better visualisation (also added some theme changes):

ggplot() +
  geom_point(aes(count, mean, color = "Observed"), myDf,
             alpha = 0.3, size = 0.7) +
  geom_hline(aes(yintercept = myTrueMean, color = "Expected"),
             linetype = 2, size = 0.5) +
  scale_colour_manual(values = c("blue", "red")) +
  labs(title = "Plot showing convergens of Mean",
       x = "Index",
       y = "Mean",
       color = "Mean type") +
  theme_minimal() +
  guides(color = guide_legend(override.aes = list(
    linetype = 0, size = 4, shape = 15, alpha = 1))
  )

enter image description here

Upvotes: 5

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