[R] Labeling a range of bars in barplot?

Dan Bolser dmb at mrc-dunn.cam.ac.uk
Wed Dec 14 18:16:12 CET 2005

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
>>y <- quantile(x, seq(0, 1, 0.2))
>>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 
>>Thanks for any help with the above!
> 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 

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 <-
           # Remove default label names

## Break data range, and count bars per break
my.hist <-
        ## Pick the (approximate) number of labels
        ## NB: using quantiles is incorrect here

## Check for sanity
## points(mp[length(mp)],x[length(mp)],col=2)

## Counts become new 'breaks'
my.new.breaks <-

## Some formating stuff
my.names <-

# Prepare to add labels

i <- length(mp)             # Note we label from right to left
q <- 1
for(j in my.new.breaks){
   st <- i                   #
   en <- i-j+1               #
        paste(paste(my.names[q],"-",sep=" "),
   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


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