ggplot2直方图中每个面的不同中断

Question

ggplot2-challenged latticist需要帮助：在直方图中请求变量per-facet中断的语法是什么？

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")

正如jucor所指出，here还有更多解决方案。

根据特殊要求，并说明为什么我不是一个伟大的ggplot粉丝，lattice版本

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")))

Answer 1

这是另一种选择：

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")

如果你需要缩小x的范围，那么

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")

Answer 2

我认为不可能在每个方面给出不同的断点。

作为解决方法，您可以创建两个图，然后使用库grid.arrange()中的gridExtra函数将它们组合在一起。要在geom_histogram()中设置断点，请使用binwidth=并为bin的宽度设置一个值。

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 3

继Didzis之后的例子：

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")

编辑：这适用于更多级别，但当然已有更好的解决方案

# 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")

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

Answer 4

严格地说，不可能在不同方面给出不同的中断。但是，您可以通过为每个方面设置不同的图层来获得相同的效果（与user20650's answer中一样），但主要是自动执行多个geom_histogram调用：

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")

mapply调用会创建一个geom_histogram列表，可以将其添加到绘图中。棘手的部分是您必须手动将数据（split(d, d$par)）拆分为进入每个方面的数据。