ggplot:观察作为x轴标签的盒形图数

Question

根据我在上一篇文章中的答案,我已经成功地创建了一个非常漂亮的箱形图(按照我的目的),按因子分类并分箱:ggplot:为连续x的每组安排多个y变量的箱线图

现在,我想根据每个箱形图的观察次数来定制x轴标签.

require (ggplot2)
require (plyr)
library(reshape2)

set.seed(1234)
x<- rnorm(100)
y.1<-rnorm(100)
y.2<-rnorm(100)
y.3<-rnorm(100)
y.4<-rnorm(100)

df<- (as.data.frame(cbind(x,y.1,y.2,y.3,y.4)))
dfmelt<-melt(df, measure.vars = 2:5)

dfmelt$bin <- factor(round_any(dfmelt$x,0.5))

dfmelt.sum<-summary(dfmelt$bin)    

ggplot(dfmelt, aes(x=bin, y=value, fill=variable))+
geom_boxplot()+
facet_grid(.~bin, scales="free")+
labs(x="number of observations")+
scale_x_discrete(labels= dfmelt.sum)

dfmelt.sum只让我对每个箱不是每个箱线图观察的总数.箱线图统计给我每个箱线图观察的数量.

dfmelt.stat<-boxplot(value~variable+bin, data=dfmelt)
dfmelt.n<-dfmelt.stat$n

但我怎么添加刻度标记和标签为每个箱线图？

谢谢,新浪

UPDATE

我一直在努力.最大的问题是,在上面的代码中,每个方面只提供一个刻度标记.由于我还想绘制每个箱图的平均值,我已经使用交互分别绘制每个箱图,这也为每个箱图在x轴上添加了刻度标记:

require (ggplot2)
require (plyr)
library(reshape2)

set.seed(1234) x<- rnorm(100)
y.1<-rnorm(100)
y.2<-rnorm(100)
y.3<-rnorm(100)
y.4<-rnorm(100)

df<- (as.data.frame(cbind(x,y.1,y.2,y.3,y.4))) dfmelt<-melt(df, measure.vars = 2:5)

dfmelt$bin <- factor(round_any(dfmelt$x,0.5))

dfmelt$f2f1<-interaction(dfmelt$variable,dfmelt$bin)

dfmelt_mean<-aggregate(value~variable*bin, data=dfmelt, FUN=mean)
dfmelt_mean$f2f1<-interaction(dfmelt_mean$variable, dfmelt_mean$bin)

dfmelt_length<-aggregate(value~variable*bin, data=dfmelt, FUN=length)
dfmelt_length$f2f1<-interaction(dfmelt_length$variable, dfmelt_length$bin)

在旁边:也许有一种更优雅的方式来结合所有这些互动.我很乐意改进.

ggplot(aes(y = value, x = f2f1, fill=variable), data = dfmelt)+
geom_boxplot()+
geom_point(aes(x=f2f1, y=value),data=dfmelt_mean, color="red", shape=3)+
facet_grid(.~bin, scales="free")+
labs(x="number of observations")+
scale_x_discrete(labels=dfmelt_length$value)

这为每个可以标记的箱图提供了刻度标记.然而,使用scale_x_discrete标签只重复每个方面dfmelt_length $值的前四个值.

怎么能被规避呢？谢谢,新浪

Answer 1

看看这个答案,它不在标签上,但它有效 - 我用过这个

修改每个构面中的x轴标签

你也可以这样做,我也用过它

    library(ggplot2)
df <- data.frame(group=sample(c("a","b","c"),100,replace=T),x=rnorm(100),y=rnorm(100)*rnorm(100))
xlabs <- paste(levels(df$group),"\n(N=",table(df$group),")",sep="")
ggplot(df,aes(x=group,y=x,color=group))+geom_boxplot()+scale_x_discrete(labels=xlabs)

这也有效

library(ggplot2)library(reshape2)

df <- data.frame(group=sample(c("a","b","c"),100,replace=T),x=rnorm(100),y=rnorm(100)*rnorm(100))
df1 <- melt(df)
df2 <- ddply(df1,.(group,variable),transform,N=length(group))
df2$label <- paste0(df2$group,"\n","(n=",df2$N,")")
ggplot(df2,aes(x=label,y=value,color=group))+geom_boxplot()+facet_grid(.~variable)