Though Python is usually thought of over R for doing system administration tasks, R is actually quite useful in this regard. In this post we\u2019re going to talk about using R to create, delete, move, and obtain information on files.<\/p>\n\n\n\n
Before working with files, it\u2019s usually a good idea to first know what directory you\u2019re working in. The working directory is the folder that any files you create or refer to without explicitly spelling out the full path fall within. In R, you can figure this out with the getwd<\/strong> function. To change this directory, you can use the aptly named setwd<\/strong> function.<\/p>\n\n\n\n A new folder, or directory, can be created in R using the dir.create<\/strong> function, like this:<\/p>\n\n\n\n You just need to replace \u201cnew_folder\u201d with whatever name you choose. If you don\u2019t write out the full path of this new directory, it will get created into whatever the current working directory is i.e. the value of getwd()<\/strong>.<\/p>\n\n\n\n Similarly, creating a blank file can be done with file.create<\/strong>.<\/p>\n\n\n\n With this in mind, creating lots of files quickly is made easy. For example, the one-liner below will create 100 empty text files:<\/p>\n\n\n\n Copying a file can be done using file.copy<\/strong>.<\/p>\n\n\n\n With file.copy<\/strong>, the first parameter is the name of the file to be copied; the second is the destination folder that you want to copy the file to. If the file copies successfully, the function will return TRUE \u2014 otherwise, it returns FALSE.<\/p>\n\n\n\n The simplest way of listing all the files in a directory with R is by calling list.files<\/strong>.<\/p>\n\n\n\n Calling list.files<\/strong> with no additional parameters will only list the files and folders directly within the directory \u2014 i.e. it doesn\u2019t list the files within any sub-folder unless you tell it to do so. This can be done like this:<\/p>\n\n\n\n Note, adding the \u201crecursive = TRUE\u201d flag may cause the function to run for a longer period of time if the directory has a large number of sub-folders and files (e.g. running list.files(\u201cC:\/\u201d, recursive = TRUE)<\/strong>).<\/p>\n\n\n\n An additional point \u2014 running default list.files<\/strong> doesn\u2019t list the full path names of the files. We can set the parameter, full.names, to TRUE to get the full path names.<\/p>\n\n\n\n list.files<\/strong> can also apply a filter internally to the files you want to list. For instance, the R code below will list all of the CSV files in a directory (similar to \u201cls | grep .csv\u201d in Linux)<\/p>\n\n\n\n The above logic can be really useful if you want to read in all of the CSV files within a given directory. For instance, suppose you have a list of CSV\u2019s in a folder, and you want to produce a single data frame (provided they each have the same layout) from all the files. You can accomplish this in a couple lines of code:<\/p>\n\n\n\n Another way of getting the files in a directory is using the function, fileSnapshot<\/strong>. fileSnapshot<\/strong> will also give you additional details about the files. This function returns a list of objects.<\/p>\n\n\n\n fileSnapshot returns a list, which here we will just call \u201csnapshot\u201d. The most useful piece of information can be garnered from this by referencing \u201cinfo\u201d:<\/p>\n\n\n\n Here, snapshot$info is a data frame showing information about the files in the input folder parameter. Its headers include:<\/p>\n\n\n\n# get current working directory\ngetwd()\n \n# set working directory\nsetwd(\"C:\/Users\")<\/pre>\n\n\n\n
Creating Files and Directories<\/strong><\/h2>\n\n\n\n
dir.create(\"new_folder\")<\/pre>\n\n\n\n
file.create(\"new_text_file.txt\")\nfile.create(\"new_word_file.docx\")\nfile.create(\"new_csv_file.csv\")<\/pre>\n\n\n\n
sapply(paste0(\"file\", 1:100, \".txt\"), file.create)<\/pre>\n\n\n\n
Copying a file \/ folder<\/strong><\/h2>\n\n\n\n
file.copy(\"source_file.txt\", \"destination_folder\")<\/pre>\n\n\n\n
How to list all the files in a directory<\/strong><\/h2>\n\n\n\n
# list all files in current directory\nlist.files()\n \n# list all files in another directory\nlist.files(\"C:\/path\/to\/somewhere\/else\")<\/pre>\n\n\n\n
list.files(\"C:\/path\/to\/somewhere\/else\", recursive = TRUE)<\/pre>\n\n\n\n
list.files(\"C:\/path\/to\/somewhere\/else\", full.names = TRUE, recursive = TRUE)<\/pre>\n\n\n\n
# list all CSV files non-recursively\nlist.files(pattern = \".csv\")\n \n# list all CSV files recursively through each sub-folder\nlist.files(pattern = \".csv\", recursive = TRUE)<\/pre>\n\n\n\n
# read in all the CSV files\nall_data_frames <- lapply(list.files(pattern = \".csv\"), read.csv)\n \n# stack all data frames together\nsingle_data_frame <- Reduce(rbind, all_data_frames)<\/pre>\n\n\n\n
How to get created \/ modified times and other details about files<\/strong><\/h2>\n\n\n\n
fileSnapshot<\/u><\/strong><\/h4>\n\n\n\n
# get file snapshot of current directory\nsnapshot <- fileSnapshot()\n \n# or file snapshot of another directory\nsnapshot <- fileSnapshot(\"C:\/some\/other\/directory\")<\/pre>\n\n\n\n
snapshot$info<\/pre>\n\n\n\n