# Your data
# ECG
fem <- read.csv( text=
"female Nij,N11,N22,N33,N44,N21,N31,N32,N123
Sinus,1.0,0.0,0.0,0.0,0.0,0.0,12.0,0.0
Arr/AHB,1.0,0.0,0.0,0.1,0.0,0.0,20.9,0.0
Digoxin arr,1.0,0.0,0.0,0.2,0.0,0.0,10.8,0.0
Furosemide arr,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0")

male <- read.csv( text=
"male Nij,N11,N22,N33,N44,N21,N31,N32,N123
Sinus,1.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0
Arr/AHB,1.0,0.0,0.0,0.0,0.0,0.0,24.0,0.0
Digoxin arr,1.0,0.0,0.0,0.0,0.0,0.0,11.0,0.0
Furosemide arr,1.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0")

# Add gender grouping variable
fem$gender <- "female"
male$gender <- "male"
fem$group <- male$group <- "ECG"

# ECG  b
fem2 <- read.csv( text=
"female Nij,N11,N22,N33,N44,N21,N31,N32,N123
Sinus,1.0,0.2,0.2,0.0,0.0,0.0,11.7,0.0
Arr/AHB,1.2,0.0,1.8,3.8,0.0,0.0,15.1,0.1
Digoxin arr,0.5,0.2,0.0,1.0,0.0,0.0,4.3,0.0
Furosemide arr,0.0,0.0,0.0,0.0,0.0,0.0,0.0,0.0")

male2 <- read.csv( text=
"male Nij,N11,N22,N33,N44,N21,N31,N32,N123
Sinus,1.0,0.0,0.0,0.0,0.0,0.0,4.0,0.0
Arr/AHB,1.0,3.2,0.0,4.3,0.0,0.0,16.5,0.0
Digoxin arr,1.0,0.0,0.7,0.8,0.0,0.0,9.5,0.0
Furosemide arr,1.0,0.0,0.0,0.0,0.0,0.0,3.0,0.0")

fem2$gender <- "female"
male2$gender <- "male"
fem2$group <- male2$group <- "ECG b"




# you will need to check they are in the right order
dat <- rbind(setNames(fem, names(male)), male,
                          setNames(fem2, names(male)), male2)

# reshape data for plotting
library(reshape2)
datm <- melt(dat)




library(lattice)

lvs = unique(dat$male.Nij) # for ordering facets
barchart(variable ~ value|group + factor(male.Nij, levels=lvs), groups=gender, data=datm, auto.key=list(space='right'), origin=0)

library(ggplot2)

ggplot(datm, aes(variable, value, fill=gender)) + geom_bar(stat="identity", position = position_dodge()) + facet_grid(factor(male.Nij, levels=lvs) ~ group) + coord_flip()