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A ggplot2-challenged latticist needs help: What's the syntax to request variable per-facet breaks in a histogram?
library(ggplot2) d = data.frame(x=c(rnorm(100,10,0.1),rnorm(100,20,0.1)),par=rep(letters[1:2],each=100)) # Note: breaks have different length by par breaks = list(a=seq(9,11,by=0.1),b=seq(19,21,by=0.2)) ggplot(d, aes(x=x) ) + geom_histogram() + ### Here the ~breaks should be added facet_wrap(~ par, scales="free") As pointed out by jucor, here some more solutions.
On special request, and to show why I am not a great ggplot fan, the lattice version
library(lattice) d = data.frame(x=c(rnorm(100,10,0.1),rnorm(100,20,0.1)),par=rep(letters[1:2],each=100)) # Note: breaks have different length by par myBreaks = list(a=seq(8,12,by=0.1),b=seq(18,22,by=0.2)) histogram(~x|par,data=d, panel = function(x,breaks,...){ # I don't know of a generic way to get the # grouping variable with histogram, so # this is not very generic par = levels(d$par)[which.packet()] breaks = myBreaks[[par]] panel.histogram(x,breaks=breaks,...) }, breaks=NULL, # important to force per-panel compute scales=list(x=list(relation="free"))) 
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To change the number of bins in the histogram using the ggplot2 package library in the R Language, we use the bins argument of the geom_histogram() function. The bins argument of the geom_histogram() function to manually set the number of bars, cells, or bins the whole histogram will be divided into.
A facet simply breaks the data frame into subsets and draws one histogram per subset. Create a facet by adding the function facet_wrap() to the plot. You'll have to specify the faceting variable. as an argument to the facet_wrap() function.
You can also make histograms by using ggplot2 , “a plotting system for R, based on the grammar of graphics” that was created by Hadley Wickham. This post will focus on making a Histogram With ggplot2.
facet_grid() forms a matrix of panels defined by row and column faceting variables. It is most useful when you have two discrete variables, and all combinations of the variables exist in the data.
Here is one alternative:
hls <- mapply(function(x, b) geom_histogram(data = x, breaks = b), dlply(d, .(par)), myBreaks) ggplot(d, aes(x=x)) + hls + facet_wrap(~par, scales = "free_x") 
If you need to shrink the range of x, then
hls <- mapply(function(x, b) { rng <- range(x$x) bb <- c(rng[1], b[rng[1] <= b & b <= rng[2]], rng[2]) geom_histogram(data = x, breaks = bb, colour = "white") }, dlply(d, .(par)), myBreaks) ggplot(d, aes(x=x)) + hls + facet_wrap(~par, scales = "free_x") 
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I don't think that it is possible to give different break points in each facet.
As workaround you can make two plots and then with grid.arrange() function from library gridExtra put them together. To set break points in geom_histogram() use binwidth= and set one value for width of bin.
p1<-ggplot(subset(d,par=="a"), aes(x=x) ) + geom_histogram(binwidth=0.1) + facet_wrap(~ par) p2<-ggplot(subset(d,par=="b"), aes(x=x) ) + geom_histogram(binwidth=0.2) + facet_wrap(~ par) library(gridExtra) grid.arrange(p1,p2,ncol=2) 
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