How to Read Multiple .Txt Files into R

How do you read multiple .txt files into R?

Thanks for all the answers!

In the meanwhile, I also hacked a method on my own. Let me know if it is any useful:

library(foreign)

setwd("/path/to/directory")

files <-list.files()

data <- 0


for (f in files) {

tempData = scan( f, what="character")

data <- c(data,tempData)    

} 

Read multiple .txt files in R with scan()

As @MrFlick mentioned you can use list.files to get all the text files in working directory and then you can use lapply to read them in a list.

filenames <- list.files(pattern = '\\.txt$')
result <- lapply(filenames, scan, what = "character", sep=NULL)

read multiple text files into r for text mining purposes

I often have this same problem. The textreadr package that I maintain is designed to make reading .csv, .pdf, .doc, and .docx documents and directories of these documents easy. It would reduce what you're doing to:

textreadr::read_dir("../data/InauguralSpeeches/")

Your example is not reproducible so I do it below (please make your example reproducible in the future).

library(textreadr)

## Minimal working example
dir.create('delete_me')
file.copy(dir(system.file("docs/Maas2011/pos", package = "textreadr"), full.names=TRUE), 'delete_me', recursive=TRUE)
write.csv(mtcars, 'delete_me/mtcars.csv')
write.csv(CO2, 'delete_me/CO2.csv')
cat('test\n\ntesting\n\ntester', file='delete_me/00_00.txt')

## the read in of a directory
read_dir('delete_me') 

output

The output below shows the tibble output with each document registered in the document column. For every line in the document there is one row for that document. Depending on what's in the csv files this may not be fine grained enough.

##    document                                  content
## 1       0_9 Bromwell High is a cartoon comedy. It ra
## 2     00_00                                     test
## 3     00_00                                         
## 4     00_00                                  testing
## 5     00_00                                         
## 6     00_00                                   tester
## 7       1_7 If you like adult comedy cartoons, like 
## 8      10_9 I'm a male, not given to women's movies,
## 9      11_9 Liked Stanley & Iris very much. Acting w
## 10     12_9 Liked Stanley & Iris very much. Acting w
## ..      ...                                      ... 
## 141   mtcars "Ferrari Dino",19.7,6,145,175,3.62,2.77,
## 142   mtcars "Maserati Bora",15,8,301,335,3.54,3.57,1
## 143   mtcars "Volvo 142E",21.4,4,121,109,4.11,2.78,18

Read multiple .txt files and add new column identifying file name in R

This should work, if your read.table command is correct:

myData_list <- lapply(files, function(x) {
  out <- tryCatch(read.table(x, header = F, sep = ','), error = function(e) NULL)
  if (!is.null(out)) {
    out$source_file <- x
  }
  return(out)
})

myData <- data.table::rbindlist(myData_list)

In the past I found that you can spare yourself a lot of headache using data.table::fread instead of read.table. So you could consider this:

myData_list <- lapply(files, function(x) {
  out <- data.table::fread(x, header = FALSE)
  out$source_file <- x
  return(out)
})

myData <- data.table::rbindlist(myData_list)

You can add the tryCatch part back if necessary. Depending on how the files vector looks, basename() might be interesting to use on the column source_file.

Reading multiple txt files into data frames and merging them into one

The following should work well. However, without sample data or a more clear description of what you want it's hard to know for certain if this if what you are looking to accomplish.

#set working directory
setwd("C:/Users/path/to/my/files")

#read in all .txt files but skip the first 8 rows
Data.in <- lapply(list.files(pattern = "\\.txt$"),read.csv,header=T,skip=8)  

#combines all of the tables by column into one 
Data.in <- do.call(rbind,Data.in)

Read, subset and bind many .txt files in R

assign should usually be avoided and in this case we don't need to create these objects in global environment. Try using lapply.

#List all text files in the working directory
filenames <- list.files(pattern = '\\.txt$')
#Read every text file with header, skipping the 1st row. 
#Keep only the 5th column after reading the data. 
result <- lapply(filenames, function(x) read.table(x,skip = 1,header = TRUE)[,5])
result

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