在循环[R]中绘制多个分组的条形图

Question

my challenge is to plot several bar plots at once, a plot for each of variables of different subsets. My goal is to compare regional differences for each variable. I would like to print all the resulting plots to a html file via R Markdown.

My main difficulty in making automatic grouped bar charts is that you need to tabulate the groups using table(data$Var[i], data$Region) but I don't know how to do this automatically. I would highly appreciate a hint on this.

Here is a an example of what one of my subset looks like:

# To Create this example of data:
b <- rep(matrix(c(1,2,3,2,1,3,1,1,1,1)), times=10)  
data <- matrix(b, ncol=10)
colnames(data) <- paste("Var", 1:10, sep = "")
data <- as.data.frame(data)
reg_name <- c("North", "South")
Region <- rep(reg_name, 5)
data <- cbind(data,Region)

Using beside = TRUE , I was able to create one grouped bar plot (grouped by Region for Var1 from data):

tb <- table(data$Var1,data$Region) 
barplot(tb, main="Var1", xlab="Values", legend=rownames(tb), beside=TRUE,
        col=c("green", "darkblue", "red"))

I would like to loop this process to generate for example 10 plots for Var1 to Var10:

for(i in 1:10){
     tb <- table(data[i], data$Region)
     barplot(tb, main = i, xlab = "Values", legend = rownames(tb), beside = TRUE, 
             col=c("green", "darkblue", "red"))
     }

R prefer the apply family of functions, therefore I tried to create a function to be applied:

fct <- function(i) {
      tb <- table(data[i], data$Region)
      barplot(tb, main=i, xlab="Values", legend = rownames(tb), beside = TRUE,
             col=c("green", "darkblue", "red"))
      }
sapply(data, fct)

I have tried other ways, but I was never successful. Maybe lattice or ggplot2 would offer easier way to do this. I am just starting in R, I will gladly accept any tips and suggestions. Thank you!

(I run on Windows, with the most recent Rv3.1.2 "Pumpking Helmet")

Answer 1

Given that you say "My goal is to compare regional differences for each variable", I'm not sure you've chosen the optimal plotting strategy. But yes, it is possible to do what you are asking.

Here's the default plot you get with your code above, for reference:

If you want a list with 10 plots for each variable, you can do the following (with ggplot)

many_plots <-

  # for each column name in dat (except the last one)...
  lapply(names(dat)[-ncol(dat)], function(x) {

    this_dat <- dat[, c(x, 'Region')]
    names(this_dat)[1] <- 'Var'

    ggplot(this_dat, aes(x=Var, fill=factor(Var))) +
      geom_bar(binwidth=1) + facet_grid(~Region) +
      theme_classic()
  })

Sample output, for many_plots[[1]] :

If you wanted all the plots in one image, you can do this (using reshape and data.table)

library(data.table)
library(reshape2)
dat2 <- 
  data.table(melt(dat, id.var='Region'))[, .N, by=list(value, variable, Region)]

ggplot(dat2, aes(y=N, x=value, fill=factor(value))) +
  geom_bar(stat='identity') + facet_grid(variable~Region) +
  theme_classic()

...but that's not a great plot.