Different breaks per facet in ggplot2 histogram

Question

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(         


        

Answer 1

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)

Answer 2

Following on from Didzis example:

ggplot(dat=d, aes(x=x, y=..ncount..)) +
  geom_histogram(data = d[d$par == "a",], binwidth=0.1) +
  geom_histogram(data = d[d$par == "b",], binwidth=0.01) +  
  facet_grid(.~ par, scales="free")

EDIT: This works for more levels but of course there are already better solutions

# More facets
d <- data.frame(x=c(rnorm(200,10,0.1),rnorm(200,20,0.1)),par=rep(letters[1:4],each=100))

# vector of binwidths same length as number of facets - need a nicer way to calculate these
my.width=c(0.5,0.25,0.1,0.01)

out<-lapply(1:length(my.width),function(.i) data.frame(par=levels(d$par)[.i],ggplot2:::bin(d$x[d$par==levels(d$par)[.i]],binwidth=my.width[.i])))

my.df<-do.call(rbind , out)

ggplot(my.df) + geom_histogram(aes(x, y = density, width = width), stat =  "identity") + facet_wrap(~par,scales="free")

from https://groups.google.com/forum/?fromgroups=#!searchin/ggplot2/bin$20histogram$20by$20facet/ggplot2/xlqRIFPP-zE/CgfigIkgAAkJ

Answer 3

It is not, strictly speaking, possible to give different breaks in the different facets. But you can get the same effect by having a different layer for each facet (much as in user20650's answer), but mostly automating the multiple geom_histogram calls:

d <- data.frame(x=c(rnorm(100,10,0.1),rnorm(100,20,0.1)),
                par=rep(letters[1:2],each=100))
breaks <- list(a=seq(9,11,by=0.1),b=seq(19,21,by=0.2))

ggplot(d, aes(x=x)) +
  mapply(function(d, b) {geom_histogram(data=d, breaks=b)}, 
         split(d, d$par), breaks) +
  facet_wrap(~ par,  scales="free_x")

The mapply call creates a list of geom_histograms which can be added to the plot. The tricky part is that you have to manually split the data (split(d, d$par)) into the data that goes into each facet.

Answer 4

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")