Merging a large number of files from one directory into a data frame in R

I have a large number of data files (>1000) in a single directory. I would like to merge them all in a single data frame in R. They all have the same number and types of columns. So far what I have is:

setwd("directory")
files <- list.files()
for (i in 1:length(files)) assign(files[i], read.csv(files[i]))

This creates data frames for each of the 1000+ files. Is there any way to merge them, without having to type out a list of all 1000+ file names?

Any help would be appreciated!

Solved

The standard way to do this with data.table (recommended because of its speed) is:

library(data.table)
data <- rbindlist(lapply(list.files(), fread))

From 1.9.5+ rbindlist has additional functionalities, e.g.

rbindlist(lapply(list.files(), fread), fill = TRUE)

Will take care of the possibility that some or many of your files have different column names--any non-overlap will be filled with NA in those files lacking that column.

---

EDIT: as @nicola mentioned, using assign is to be avoided in general.

See this post for further reference to that end.

One good way to do that is to utilize data.table. This library has two benefits that will work in your case: a) it has a fast way of reading .csv files, and b) a fast way of combining data.tables (which are an extension of data.frame) into one. So in this spirit, let me propose the following alternative:

# if you don't have data.table installed, run install.packages('data.table') first
library(data.table)
files <- list.files('directory', full.names = TRUE)
#create a list to manage the individual files, only used to merge them in the end
FILES_LIST=vector("list",length(files)) 
for (i in 1:length(files)) {
    FILES_LIST[[i]]<-fread(files[i]) #this reads your .csv file
}
FILES_LIST = rbindlist(FILES_LIST) #this merges all of your files in a big data.table

The variable you are interested in, in the end is FILES_LIST.

I hope this helps.