# [R] Labeling a range of bars in barplot?

Gabor Grothendieck ggrothendieck at gmail.com
Wed Dec 14 22:00:28 CET 2005

```Note that if I follow this correctly then you could remove the loop.   In
particular note that 1. st is just the cumulative sum of new.break.points
but summed from the end:

st <- rev(cumsum(rev(my.new.breaks)))

2. segments and text both take vector arguments and 3. averaging over the
groups can be done by defining a factor g whose levels are the groups
using cut and then performing the averaging with tapply:

g <- cut(seq(mp), c(1, st.), include.lowest = TRUE)
tapply(mp, g, mean)

On 12/14/05, Dan Bolser <dmb at mrc-dunn.cam.ac.uk> wrote:
> Marc Schwartz (via MN) wrote:
> > On Tue, 2005-12-13 at 10:53 +0000, Dan Bolser wrote:
> >
> >>Hi, I am plotting a distribution of (ordered) values as a barplot. I
> >>would like to label groups of bars together to highlight aspects of the
> >>distribution. The label for the group should be the range of values in
> >>those bars.
> >>
> >>As this is hard to describe, here is an example;
> >>
> >>
> >>x <- rlnorm(50)*2
> >>
> >>barplot(sort(x,decreasing=T))
> >>
> >>y <- quantile(x, seq(0, 1, 0.2))
> >>
> >>y
> >>
> >>plot(diff(y))
> >>
> >>
> >>
> >>That last plot is to highlight that I want to label lots of the small
> >>columns together, and have a few more labels for the bigger columns
> >>(more densely labeled). I guess I will have to turn out my own labels
> >>using low level plotting functions, but I am stumped as to how to
> >>perform the calculation for label placement.
> >>
> >>I imagine drawing several line segments, one for each group of bars to
> >>be labeled together, and putting the range under each line segment as
> >>the label. Each line segment will sit under the group of bars that it
> >>covers.
> >>
> >>Thanks for any help with the above!
> >>
> >>Cheers,
> >>Dan.
> >
> >
> > Dan,
> >
> > Here is a hint.
> >
> > barplot() returns the bar midpoints:
> >
> > mp <- barplot(sort(x, decreasing = TRUE))
> >
> >
> >
> >      [,1]
> > [1,]  0.7
> > [2,]  1.9
> > [3,]  3.1
> > [4,]  4.3
> > [5,]  5.5
> > [6,]  6.7
> >
> > There will be one value in 'mp' for each bar in your series.
> >
> > You can then use those values along the x axis to draw your line
> > segments under the bars as you require, based upon the cut points you
> > want to highlight.
> >
> > To get the center of a given group of bars, you can use:
> >
> >   mean(mp[start:end])
> >
> > where 'start' and 'end' are the extreme bars in each of your groups.
> >
> > Two other things that might be helpful. See ?cut and ?hist, noting the
> > output in the latter when 'plot = FALSE'.
> >
> > HTH,
>
> Thanks all for help on this question, including those who emailed me off
> list.
>
> I went with the suggestion of Marc above, because I could follow through
> how to implement the code (other more complete solutions were hard for
> me to 'reverse engineer').
>
> Here is my solution in full, which I feel gives rather nice output :)
>
> ## Approximate my data for you to try
> x <- sort((runif(70)*100)^3,decreasing=T)
>
> ## Plot the barplot
> mp <-
>   barplot(x,
>           # Remove default label names
>           names.arg=rep('',70)
>           )
>
> ## Break data range, and count bars per break
> my.hist <-
>   hist(x,plot=F,
>        ## Pick the (approximate) number of labels
>        ## NB: using quantiles is incorrect here
>        breaks=4
>        )
>
> ## Check for sanity
> ## points(mp[length(mp)],x[length(mp)],col=2)
>
> ## Counts become new 'breaks'
> my.new.breaks <-
>   my.hist\$counts
>
> ## Some formating stuff
> my.names <-
>   sprintf("%.1d",my.hist\$breaks)
>
> # Prepare to add labels
> op<-par(xpd=TRUE)
>
> i <- length(mp)             # Note we label from right to left
> q <- 1
> #
> for(j in my.new.breaks){
>   st <- i                   #
>   en <- i-j+1               #
>   ##
>   segments(mp[st],-50000,
>            mp[en],-50000,lwd=2,col=2)
>   ##
>   text(mean(mp[st:en]),-100000,pos=1,
>        paste(paste(my.names[q],"-",sep=" "),
>              my.names[q+1],sep="\n"),cex=0.6)
>   ##
>   i <- i-j                  #
>   q <- q+1
> }
>
>
> You should see that the density of labels corresponds to the range of
> data (hopefully not too dense), giving more labels to regions of the
> plot with bigger ranges.
>
>
> > Marc Schwartz
> >
> >
>
>
> Cheers,
> Dan.
>
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