向ggplot2栏添加垂直线图

Question

我正在对银行业的非违约者和违约者进行一些研究。在这种情况下，我将他们的分布相对于条形图中的某个分数进行绘图。评分越高，信用评级越高。

由于与非默认值的数量相比，默认值的数量非常有限，因此绘制默认值和非默认值在同一条形图上并不是很给力，因为您几乎看不到默认值。然后，我根据违纪者的分数创建第二个条形图，但是与违纪者和非违约者的分数的完整条形图相同。然后，我想向第一个条形图添加垂直线，指示最高违规者得分位置以及最低违规者得分所在的位置。那就是要弄清楚违约者的分布在哪里适合违约者和非违约者的整体分配。

下面是我正在使用的代码替换（种子）随机数据。

library(ggplot2) 

#NDS represents non-defaults and DS defaults on the same scale 
#although here being just some random normals for the sake of simplicity. 
set.seed(10) 
NDS<-rnorm(10000,sd=1)-2 
DS<-rnorm(100,sd=2)-5 

#Cutoffs are constructed such that intervals of size 0.3 
#contain all values of NDS & DS 
minCutoff<--9.3 
maxCutoff<-2.1 

#Generate the actual interval "bins" 
NDS_CUT<-cut(NDS,breaks=seq(minCutoff, maxCutoff, by = 0.3)) 
DS_CUT<-cut(DS,breaks=seq(minCutoff, maxCutoff, by = 0.3)) 

#Manually generate where to put the vertical lines for min(DS) and max(DS) 
minDS_bar<-levels(cut(NDS,breaks=seq(minCutoff, maxCutoff, by = 0.3)))[1] 
maxDS_bar<-levels(cut(NDS,breaks=seq(minCutoff, maxCutoff, by = 0.3)))[32] 

#Generate data frame - seems stupid, but makes sense 
#when the "real" data is used :-) 
NDSdataframe<-cbind(as.data.frame(NDS_CUT),rep(factor("State-1"),length(NDS_CUT))) 
colnames(NDSdataframe)<-c("Score","Action") 
DSdataframe<-cbind(as.data.frame(DS_CUT),rep(factor("State-2"),length(DS_CUT))) 
colnames(DSdataframe)<-c("Score","Action") 
fulldataframe<-rbind(NDSdataframe,DSdataframe) 
attach(fulldataframe) 

#Plot the full distribution of NDS & DS 
# with geom_vline(xintercept = minDS_bar) + geom_vline(xintercept = maxDS_bar) 
# that unfortunately does not show :-(
fullplot<-ggplot(fulldataframe, aes(Score, fill=factor(Action,levels=c("State-2","State-1")))) +  geom_bar(position="stack") + opts(axis.text.x = theme_text(angle = 45)) + opts (legend.position = "none") + xlab("Scoreinterval") + ylab("Antal pr. interval") + geom_vline(xintercept = minDS_bar) + geom_vline(xintercept = maxDS_bar) 

#Generate dataframe for DS only 
#It might seem stupid, but again makes sense 
#when using the original data :-) 
DSdataframe2<-cbind(as.data.frame(DS_CUT),rep(factor("State-2"),length(DS_CUT))) 
colnames(DSdataframe2)<-c("theScore","theAction") 

#Calucate max number of observations to adjust bar plot of DS only 
myMax<-max(table(DSdataframe2))+1 
attach(DSdataframe2) 

#Generate bar plot of DS only 
subplot<-ggplot(fulldataframe, aes(theScore, fill=factor(theAction))) + geom_bar  (position="stack") + opts(axis.text.x = theme_text(angle = 45)) + opts(legend.position = "none") +  ylim(0, myMax) + xlab("Scoreinterval") + ylab("Antal pr. interval") 

#plot on a grid 
grid.newpage() 
pushViewport(viewport(layout = grid.layout(2, 1))) 
vplayout <- function(x, y) 
viewport(layout.pos.row = x, layout.pos.col = y) 
print(fullplot, vp = vplayout(1, 1)) 
print(subplot, vp = vplayout(2, 1)) 

#detach dataframes 
detach(DSdataframe2) 
detach(fulldataframe) 

此外，如果有人有我如何对齐一个想法绘制，使正确的时间间隔仅仅低于/高于对方的网格划分

希望有人能够帮助！

由于提前，

基督教

Answer 1

裹aes在geom_vline层的xintercept周围：

... + geom_vline(aes(xintercept = minDS_bar)) + geom_vline(aes(xintercept = maxDS_bar)) 

Answer 2

问题1：

由于您提供的垂直线的数据，你必须首先映射美学，使用aes（）

fullplot <-ggplot(
     fulldataframe, 
     aes(Score, fill=factor(Action,levels=c("State-2","State-1")))) +  
     geom_bar(position="stack") + 
     opts(axis.text.x = theme_text(angle = 45)) + 
     opts (legend.position = "none") + 
     xlab("Scoreinterval") + 
     ylab("Antal pr. interval") + 
     geom_vline(aes(xintercept = minDS_bar)) + 
     geom_vline(aes(xintercept = maxDS_bar)) 

第二个问题：

要对齐图，你可以使用align.plots（）函数封装ggExtra

install.packages("dichromat") 
install.packages("ggExtra", repos="http://R-Forge.R-project.org") 
library(ggExtra) 

ggExtra::align.plots(fullplot, subplot)