R: iterate over columns and plot - r

Question

My data looks like this:
Group Feature_A Feature_B Feature_C Feature_D
1 1 0 3 2 4
2 1 5 2 2 8
3 1 9 8 6 5
4 2 5 7 8 8
5 2 2 6 8 1
6 2 3 8 6 4
7 3 1 5 3 5
8 3 1 4 3 4
df <- structure(list(Group = c(1L, 1L, 1L, 2L, 2L, 2L, 3L, 3L), Feature_A = c(0L,
5L, 9L, 5L, 2L, 3L, 1L, 1L), Feature_B = c(3L, 2L, 8L, 7L, 6L,
8L, 5L, 4L), Feature_C = c(2L, 2L, 6L, 8L, 8L, 6L, 3L, 3L), Feature_D = c(4L,
8L, 5L, 8L, 1L, 4L, 5L, 4L)), .Names = c("Group", "Feature_A",
"Feature_B", "Feature_C", "Feature_D"), class = "data.frame", row.names = c(NA,
-8L))
For every Feature I want to generate a plot (e.g., boxplot) that would higlight difference between Groups.
# Get unique Feature and Group
Features<-unique(colnames(df[,-1]))
Group<-unique(colnames(df$Group))
But how can I do the rest?
Pseudo-code might look like this:
Select Feature from Data
Split Data according Group
Boxplot
for (i in 1:levels(df$Features)){
for (o in 1:length(Group)){
}}
How can I achieve this? Hope someone can help me.

Answer 1

I would put py data in the long format. Then Using ggplot2 you can do some nice things.
library(reshape2)
library(ggplot2)
library(gridExtra)
## long format using Group as id
dat.m <- melt(dat,id='Group')
## bar plot
p1 <- ggplot(dat.m) +
geom_bar(aes(x=Group,y=value,fill=variable),stat='identity')
## box plot
p2 <- ggplot(dat.m) +
geom_boxplot(aes(x=factor(Group),y=value,fill=variable))
## aggregate the 2 plots
grid.arrange(p1,p2)

Answer 2

This is easy to do. I do this all the time
The code below will generate the charts using ggplot and save them as ch_Feature_A ....
you can wrap the answer in a pdf statement to send them to pdf as well
library(ggplot2)
df$Group <- as.factor(df$Group)
for (i in 2:dim(df)[2]) {
ch <- ggplot(df,aes_string(x="Group",y=names(df)[i],fill="Group"))+geom_boxplot()
assign(paste0("ch_",names(df)[i]),ch)
}
or even simpler, if you do not want separate charts
library(reshape2)
df1 <- melt(df)
ggplot(df1,aes(x=Group,y=value,fill=Group))+geom_boxplot()+facet_grid(.~variable)