How can I label the points of a quantile-quantile plot composed with ggplot2?

Question

I am building a quantile-quantile plot out of an variable called x from a data frame called df in the working example provided below. I would like to label the points with the name variable of my df dataset.

Is it possible to do this in ggplot2 without resorting to the painful solution (coding the theoretical distribution by hand and then plotting it against the empirical one)?

Edit: it happens that yes, thanks to a user who posted and then deleted his answer. See the comments after Arun's answer below. Thanks to Didzis for his otherwise clever solution with ggbuild.

# MWE
df <- structure(list(name = structure(c(1L, 2L, 3L, 4L, 5L, 7L, 9L, 
10L, 6L, 12L, 13L, 14L, 15L, 16L, 17L, 19L, 18L, 20L, 21L, 22L, 
8L, 23L, 11L, 24L), .Label = c("AUS", "AUT", "BEL", "CAN", "CYP", 
"DEU", "DNK", "ESP", "FIN", "FRA", "GBR", "GRC", "IRL", "ITA", 
"JPN", "MLT", "NLD", "NOR", "NZL", "PRT", "SVK", "SVN", "SWE", 
"USA"), class = "factor"), x = c(-0.739390016757746, 0.358177826874146, 
1.10474523846099, -0.250589535389937, -0.423112615445571, -0.862144579740376, 
0.823039669834058, 0.079521521937704, 1.08173649722493, -2.03962942823921, 
1.05571087029737, 0.187147291278723, -0.144770773941437, 0.957990771847331, 
-0.0546549555439176, -2.70142550075757, -0.391588386498849, -0.23855544527369, 
-0.242781575907386, -0.176765072121165, 0.105155860923456, 2.69031085872414, 
-0.158320176671995, -0.564560815972446)), .Names = c("name", 
"x"), row.names = c(NA, -24L), class = "data.frame")

library(ggplot2)
qplot(sample = x, data = df) + geom_abline(linetype = "dotted") + theme_bw()

# ... using names instead of points would allow to spot the outliers

I am working on an adaptation of this gist, and will consider sending other questions to CrossValidated if I have questions about the regression diagnostics, which might be of interest to CV users.

Answer 1

You can save your original QQ plot as object (used function ggplot() and stat_qq() instead of qplot())

g<-ggplot(df, aes(sample = x)) + stat_qq()

Then with function ggplot_build() you can extract data used for plotting. They are stored in element data[[1]]. Saved those data as new data frame.

df.new<-ggplot_build(g)$data[[1]]
head(df.new)
           x          y     sample theoretical PANEL group
1 -2.0368341 -2.7014255 -2.7014255  -2.0368341     1     1
2 -1.5341205 -2.0396294 -2.0396294  -1.5341205     1     1
3 -1.2581616 -0.8621446 -0.8621446  -1.2581616     1     1
4 -1.0544725 -0.7393900 -0.7393900  -1.0544725     1     1
5 -0.8871466 -0.5645608 -0.5645608  -0.8871466     1     1
6 -0.7415940 -0.4231126 -0.4231126  -0.7415940     1     1

Now you can add to hew data frame names of observations. Important is to use order() as data in new data frame are ordered.

df.new$name<-df$name[order(df$x)]

Now plot new data frame as usual and instead of geom_point() provide geom_text().

ggplot(df.new,aes(theoretical,sample,label=name))+geom_text()+ 
  geom_abline(linetype = "dotted") + theme_bw()

Answer 2

The points are too close by. I would do something like this:

df <- df[with(df, order(x)), ]
df$t <- quantile(rnorm(1000), seq(0, 100, length.out = nrow(df))/100)

p <- ggplot(data = df, aes(x=t, y=x)) + geom_point(aes(colour=df$name))

This gives:

If you insist on having labels inside the plot, then, you could try something like:

df <- df[with(df, order(x)), ]
df$t <- quantile(rnorm(1000), seq(0, 100, length.out = nrow(df))/100)

p <- ggplot(data = df, aes(x=t, y=x)) + geom_point(aes(colour=df$name))
p <- p + geom_text(aes(x=t-0.05, y=x-0.15, label=df$name, size=1, colour=df$name))

p

You can play around with the x and y coordinates and if you want you can always remove the colour aesthetics.