Add count and labels to stacked bar plot with facet_wrap - r

Question

I want to use ggplo2 to analyse likert scale variables. I would like to get this kind of graphic (below) but I don't know how to add labels on stacked bars and insert different counts and means for each grouping variable and facet variable (for facet_wrap).
I would be grateful for any help!
Data can be obtained from here
My code:
library(ggplot2)
library(scales)
library(RColorBrewer)
ggplot(example,aes(GroupungVar,fill=VarOfInterest)) + geom_bar(position='fill') +
scale_fill_manual(values = (brewer.pal(5, "Greens"))) +
facet_wrap(~FacetVar,ncol=1) + coord_flip() +
scale_y_continuous(labels=percent) + ylab('Percent')
What I get...
..and what I want to achieve (numbers ale not the same as in dataset). I want to have count (N) in labels of each group, percentage labels on bars and mean value on the right side (for each group of course). Percentages and mean values should be for all bars in the plot, I only add them to the first few, just to show what I mean.

Answer 1

I spend night with R and ggplot2 and I get what I wanted :)
library('ggplot2')
library('plyr')
library('RColorBrewer')
library(scales)
label_positions<- function(x) {
n<-length(x)
wynik<-numeric(n)
for (i in 1:n){
if (i==1) {
wynik[i]<-0+x[i]/2
}
else {
wynik[i]<-x[i]-(x[i]-x[i-1])/2
}
}
return(wynik)
}
exam1<-ddply(example,.(GroupingVar,FacetVar,VarOfInterest), 'nrow')
exam1.1<-ddply(example,.(GroupingVar,FacetVar),summarise, sr=mean(as.numeric(VarOfInterest),na.rm=T),
odch=sd(as.numeric(VarOfInterest,na.rm=T)))
exam1<-merge(exam1,exam1.1,by.x=c('GroupingVar','FacetVar'),by.y=c('GroupingVar','FacetVar'))
names(exam1)[4]<-'Count'
exam2<-mutate(exam1,cumul=ave(Count,list(GroupingVar,FacetVar),FUN=cumsum),
N=ave(cumul, list(GroupingVar,FacetVar),FUN=max),
CumSumPercent=cumul/N*100,
Freq=Count/N*100)
exam2<-mutate(exam2,cfrq = ave(CumSumPercent, list(GroupingVar,FacetVar), FUN = label_positions))
exam2$XLabel<-paste(exam2$GroupingVar,' (N=',exam2$N,')',sep='')
exam2$PosMean<-105
p<-ggplot(exam2, aes(x = Etykieta, y = Freq, fill = VarOfInterest)) +
geom_bar(stat = 'identity',colour="black") +
labs (x = "", y = "Percentage", fill=" ") +
scale_fill_brewer(name="Rating", palette="Greens", breaks = rev(levels(exam2$VarOfInterest))) +
geom_text(aes(y = cfrq, label=paste(sprintf("%.01f",Freq), "%", sep='')), size=5) +
geom_text(aes(y=PosMean,label=paste(sprintf("%.02f",sr),' (',sprintf("%.02f",odch),')',sep='')),size=5)+
facet_wrap(~FacetVar,ncol=1) +
coord_flip() + ylab('Procent odpowiedzi') +
guides(fill=guide_legend(title=NULL)) + theme_bw() +
theme(legend.position="bottom",strip.text.x=element_text(size=15,face='bold'),
axis.text.x =element_text(size=12,face='bold'), axis.text.y =element_text(size=12,face='bold'),
axis.title.x=element_text(size=15,face='bold'), axis.title.y=element_text(size=15,face='bold'),
strip.background=element_rect(colour='black'))
plot(p)
And result

Answer 2

For the sample sizes, I would probably just put them in the axis labels, rather than on the graph itself:
library(plyr)
example <- ddply(example,.(FacetVar,GroupungVar),
transform,
GroupingVar = paste(as.character(GroupungVar)," - (n=",length(GroupungVar),")",sep = ""))
ggplot(example,aes(GroupingVar,fill=VarOfInterest)) +
geom_bar(position='fill') +
scale_fill_manual(values = (brewer.pal(5, "Greens"))) +
facet_wrap(~FacetVar,ncol=1) +
coord_flip() +
scale_y_continuous(labels=percent) +
ylab('Percent')