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2x4 Lattice Barchart minimally in R?

Two data files of two different measurement sessions: ECG and B ECG. Each data file contains male and female. I want to do 2 column x 4 row Lattice Barchart minimally in R where the following is a draft of the interface. I can do 2x2 barchart, see code below. There must be some more minimal way than manually just adding more and more lines to the end of the code, which is difficult to control.

                     ECG    B.ECG
                     female female
  Sinus
  Arr/AHB
  Digoxin arr
  Furosemide arr
                     ECG    B.ECG
                     male   male
  Sinus
  Arr/AHB
  Digoxin arr
  Furosemide arr

Data ecg.csv 

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 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

Data b.ecg.csv

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
,,,,,,,,
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

Code which can do 2x2 barchart but difficult to expand to 2 col x 4 row barchart about 1) read data, and 2) apply Lattice barchart

library("gridExtra")
library("lattice")
library("reshape2")

data.n <- read.csv("ecg.csv", sep=",", header = TRUE)[1:2,1:7] 
rownames(data.n) <- read.csv("ecg.csv", sep=",", header = TRUE)[1:2,1] 
data.n.female <- read.csv("ecg.csv", sep=",", header = TRUE)[1:2,1:7] 
rownames(data.n.female) <- read.csv("ecg.csv", sep=",", header = TRUE)[1:2,1] 
data.n.male <- read.csv("ecg.csv", sep=",", header = TRUE)[1:2,1:7] 
rownames(data.n.male) <- read.csv("ecg.csv", sep=",", header = TRUE)[1:2,1] 

data.b <- read.csv("b.ecg.csv", sep=",", header = TRUE)[1:2,1:7] 
rownames(data.b) <- read.csv("b.ecg.csv", sep=",", header = TRUE)[1:2,1] 
data.b.female <- read.csv("b.ecg.csv", sep=",", header = TRUE)[1:2,1:7] 
rownames(data.b.female) <- read.csv("b.ecg.csv", sep=",", header = TRUE)[1:2,1] 
data.b.male <- read.csv("b.ecg.csv", sep=",", header = TRUE)[1:2,1:7] 
rownames(data.b.male) <- read.csv("b.ecg.csv", sep=",", header = TRUE)[1:2,1] 

# https://stackoverflow.com/a/40693458/54964
#1
data.n[] <- lapply(data.n, function(x) as.numeric(as.character(x)))
data.n$type <- "ecg"
data.n$ID <- rownames(data.n)

data.b[] <- lapply(data.b, function(x) as.numeric(as.character(x)))
data.b$type <- "b ecg"
data.b$ID <- rownames(data.b)

dat <- rbind(data.n[names(data.b)], data.b)
# Arrange data for plotting
dat.m <- melt(dat)

barchart(variable ~ value|ID, groups=type, data=dat.m,
                               auto.key=list(space='right'), 
                   origin=0
)

#2
data.n.female[] <- lapply(data.n.female, function(x) as.numeric(as.character(x)))
data.n.female$gender <- "female"
data.n.female$ID <- rownames(data.n.female)

data.n.male[] <- lapply(data.n.male, function(x) as.numeric(as.character(x)))
data.n.male$gender <- "male"
data.n.male$ID <- rownames(data.n.male)

data.b.female[] <- lapply(data.b.female, function(x) as.numeric(as.character(x)))
data.b.female$gender <- "female"
data.b.female$ID <- rownames(data.b.female)

data.b.male[] <- lapply(data.b.male, function(x) as.numeric(as.character(x)))
data.b.male$gender <- "male"
data.b.male$ID <- rownames(data.b.male)

dat.2 <- rbind(data.n.female[names(data.n.male)], 
  data.b.female[names(data.b.male)], 
  data.n.male, 
  data.b.male) 
dat.2$type <- rep(c("ECG", "B ECG"), each=2) 
dat.2.m <- melt(dat.2, id=c("ID", "gender", "type")) 
barchart(variable ~ value|ID+type, groups=gender, data=dat.2.m, auto.key=list(space='right'), 
  origin=0)

Fig. 1 Output of 2x2 Lattice barchart code

enter image description here

Troubleshooting the answer here for my system

Output with the code 1 in the answer

Using male.Nij, gender, group as id variables Error in
layout_base(data, rows, drop = drop) : At least one layer must contain
all variables used for facetting Calls: <Anonymous> ...
facet_train_layout.grid -> layout_grid -> layout_base Execution halted

Output 2 with the code

Error in +geom_bar(stat = "identity", position = position_dodge()) : 
  invalid argument to unary operator
Execution halted

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

System info

> library(ggplot2)
> sessionInfo()
R version 3.3.2 (2016-10-31)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Debian GNU/Linux 8 (jessie)

locale:
 [1] LC_CTYPE=en_US.UTF-8       LC_NUMERIC=C              
 [3] LC_TIME=en_US.UTF-8        LC_COLLATE=en_US.UTF-8    
 [5] LC_MONETARY=en_US.UTF-8    LC_MESSAGES=en_US.UTF-8   
 [7] LC_PAPER=en_US.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C            
[11] LC_MEASUREMENT=en_US.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] ggplot2_2.1.0

loaded via a namespace (and not attached):
[1] colorspace_1.3-0 scales_0.4.1     plyr_1.8.4       gtable_0.2.0    
[5] Rcpp_0.12.7      grid_3.3.2       munsell_0.4.3

We noticed there is some differences in the handling + by ggplot2 versions. Final line to get the code work in the described system

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

R: 3.3.2 backports
OS: Debian 8.5

Solution

  • I think the best approach is to combine the data, and reshape for plotting

    # 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"

    Combine data and reshape 

    # 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)

    Lattice plot

    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)

    ggplot2 plot 

    library(ggplot2) # v2.1.0.9001

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

    For earlier ggplot2 (v2.1.0) versions you may need to set the factor levels outside of facet_grid

    datm$male.Nij <- factor(datm$male.Nij, levels=lvs)

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

    enter image description here

    and the full code for easy copy-pasting here.