This post is a quick tip on how to use the paste( ) function to read and write multiple files. First, let’s create some data.

dataset = data.frame(expand.grid(Trt=c(rep("Low",10),rep("High",10)), Sex=c(rep("Male",10),rep("Female",10))),Response=rnorm(400))

The next step is not necessary, but makes the subsequent code more readable.

trt = levels(dataset$Trt)
sex = levels(dataset$Sex)

The following example is silly because you would rarely want to split your data as shown in this example, but (hopefully) it clearly illustrates the general idea of using paste( ) to create dynamic file names when writing files.

for (i in 1:length(trt)){
	for (j in 1:length(sex)){
		write.csv(subset(dataset, Trt==trt[i] & Sex==sex[j]), paste(trt[i],sex[j],".csv",sep=""), row.names=F)
	}
}

The result of this loop is four CSV files: HighFemale.csv, HighMale.csv, LowFemale.csv, and LowMale.csv.

We can use the same basic idea to read those same four files into a single data frame. The key is to initialize an empty data frame and then append, via rbind( ), the data from each of the four files.

dataset2 = data.frame()
for (i in 1:length(trt)){
	for (j in 1:length(sex)){
		dataset2 = rbind(dataset2,read.csv(paste(trt[i],sex[j],".csv",sep="")))
	}
}

I found this approach useful when I used a supercomputer to conduct many, many runs of an agent-based model. My jobs were queued more quickly on the supercomputer if they were small, so I broke my simulation experiments into many small jobs. This produced many files that I needed to combine into one data frame for analysis in R.