Convert .R files to .txt files en masse - r

I have about 56 .R files that I need to convert to .txt format--not R objects or data frames but the .R files themselves I need to convert to a text format.
Is there a package or method to do this for many files, or is doing it one by one the only option?

Base R approach:
# get list of .R files in current directory
my_r_files <- list.files(pattern = "*\\.R$")
# specify new name for each file
new_file_names <- sub(pattern="\\.R$", replacement=".txt", x=my_r_files)
# rename files
file.rename(from = my_r_files, to = new_file_names)

Related

R read multiple password protected xlsx files in directory and convert to csv

I was hoping someone could give me some pointers how to do this. I have multiple xlsx files in a directory that I'd like to convert to csv and then combine in one csv. I can do this with regular xlsx with the code below, but now I have to be able to read xlsx files that are password protected. Any ideas how I'd get around that?
library(rio)
library(plyr)
##LOAD, CONVERT AND COMBINE TO CSV
#convert all xlsx to csv
xls <- dir(pattern = "xlsx")
created <- mapply(convert, xls, gsub("xlsx", "csv", xls))
unlink(xls)
#combine csv files in directory
combined_ll <- ldply(list.files(), read.csv, header=TRUE)
They all have the same password, so in theory I should be able to read and unlock each file as it converts them. Any pointers would be so appreciated.

Read .tar.gz file in R

I have compressed file like cat.txt.tar.gz, I just need to load into R and process as follows
zip <-("cat.txt.tar.gz")
data <- read.delim(file=(untar(zip,"cat.txt")),sep="\t")
but "data" is empty while running the code.Is there any way to read a file from .tar.gz
Are you sure your file is named correctly?
Usually compressed files are named cat.tar.gz, excluding the .txt.
Second, try the following code:
tarfile <- "cat.txt.tar.gz" # Or "cat.tar.gz" if that is right
data <- read.delim(file = untar(tarfile,compressed="gzip"),sep="\t")
If this doesn't work, you might need to extract the file first, and then read the extracted file.
To read in a particular csv or txt within a gz archive without having to UNZIP it first one can use library(archive) :
library(archive)
library(readr)
read_csv(archive_read("cat.txt.tar.gz", file = 1), col_types = cols(), sep="\t")
should work.

How to convert xlsx files to csv files in RStudio? Need to convert multiple workbooks all with multiple spreadsheets

Trying to write an R script that will convert multiple xlsx workbook files within a folder while also converting the sheets within the workbook as separate csv files.
Looking for a single script to automatically apply code to all workbooks and their spreadsheets.
For reading Excel files, there are several packages.
I personally am happy with the xlsx package, which you can use to read Excel files, as well as their individual sheets. This article looks like it will give you the gist of it.
Each worksheet you read out you should then be able to export to CSV files by using R's built-in write.csv (or write.csv2) method.
Below is an example to convert a single xlsx workbook to multiple csv files.
Note that type conversions are not guaranteed to be correct.
xlsx_path <-"path_to_xlsx.xlsx"
sheet_names <- readxl::excel_sheets(xlsx_path)
# read from all sheets to a list of data frames
xlsx_data <- purrr::map(
sheet_names,
~readxl::read_excel(xlsx_path,.x,col_types = "text",col_names = FALSE)
)
# write a list of data frame to csv files
purrr::walk2(
xlsx_data,sheet_names,
~readr::write_csv(.x,paste0(xlsx_path,"-",.y,".csv"),col_names = FALSE)
)
# csv files will be saved as:
# path_to_xlsx-sheet1.xlsx, path_to_xlsx-sheet2.xlsx, ...
If you need to apply this function to many xlsx files. Use list.files() to get the path to all xlsx files. And write a for loop or use another map function to iterate this process.
If you are using Rstudio it is possible that you already have the package readxl installed. They have many workflows for common usecases explained here: https://readxl.tidyverse.org/articles/articles/readxl-workflows.html
They also provide this nice code snippet to do what you are asking for:
read_then_csv <- function(sheet, path) {
pathbase <- tools::file_path_sans_ext(basename(path))
df <- read_excel(path = path, sheet = sheet)
write.csv(df, paste0(pathbase, "-", sheet, ".csv"),
quote = FALSE, row.names = FALSE)
df
}
path <- readxl_example("datasets.xlsx")
sheets <- excel_sheets(path)
xl_list <- lapply(excel_sheets(path), read_then_csv, path = path)
names(xl_list) <- sheets
If you go to here and put "excel" and "xls" in the search bar, you 'll get a list of packages and functions which might help.

How do I zip a csv file and write that zipped file to a folder using R

I have an R script which generates a csv file of nearly 80000 KB after calculations. I want to write this csv file to folder say D:/My_Work/Output with file name result.zip as a zipped file. Please suggest is there any function or any way that i could achieve this.
Use the zip function:
zip(*path to zip*,*path to csv*)
edit: Unfortunately you cannot go from data.frame straight to zipped csv. You need to explicitly make the csv, but it wouldn't be hard to write a wrapper that deletes the csv so that you never know its there like so:
zipped.csv <- function(df, zippedfile) {
# init temp csv
temp <- tempfile(fileext=".csv")
# write temp csv
write.csv(df, file=temp)
# zip temp csv
zip(zippedfile,temp)
# delete temp csv
unlink(temp)
}
If you want just save some space on the disk then it is more convenient to use *.gz compression.
write.csv(iris, gzfile("iris.csv.gz"), row.names = FALSE)
iris2 = read.csv("iris.csv.gz")

Dynamically converting a list of Excel files to csv files in R

I currently have a folder containing all Excel (.xlsx) files, and using R I would like to automatically convert all of these files to CSV files using the "openxlsx" package (or some variation). I currently have the following code to convert one of the files and place it in the same folder:convert("team_order\\team_1.xlsx", "team_order\\team_1.csv")
I would like to automate the process so it does it to all the files in the folder, and also removes the current xlsx files, so only the csv files remain. Thanks!
You can try this using rio, since it seems like that's what you're already using:
library("rio")
xls <- dir(pattern = "xlsx")
created <- mapply(convert, xls, gsub("xlsx", "csv", xls))
unlink(xls) # delete xlsx files
library(readxl)
# Create a vector of Excel files to read
files.to.read = list.files(pattern="xlsx")
# Read each file and write it to csv
lapply(files.to.read, function(f) {
df = read_excel(f, sheet=1)
write.csv(df, gsub("xlsx", "csv", f), row.names=FALSE)
})
You can remove the files with the command below. However, this is dangerous to run automatically right after the previous code. If the previous code fails for some reason, the code below will still delete your Excel files.
lapply(files.to.read, file.remove)
You could wrap it in a try/catch block to be safe.

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