Create a Working Directory

Overview

Teaching: 20 min
Exercises: 20 min

Questions

• How to create a working directory?

Objectives

• Successfully set up a working directory in RStudio

Getting set up

You will need to create and set up your working directory in RStudio for this lesson. The working directory is very important, as it is the place where you will store, save, and retrieve your files. RStudio projects makes it easy to set up your working directory.

For this lesson we’ll create a new project.

• Under the File menu, click on New project, choose New directory, then New project

• Enter a name for this new project library-carpentry, and choose your desktop as the location.

• Click on Create project

If for some reason your working directory is not set up correctly you can change it in the RStudio interface by navigating in the file browser where your working directory should be, and clicking on the blue gear icon “More”, and select “Set As Working Directory”.

If you haven’t already, download the workshop files, unzip or decompress the folder and place it into your new library-carpentry project directory by dragging and dropping file.

Make sure the files you downloaded from the zip folder are organized correctly before continuing on.

If you need to reorganize your files the instructions are below:

Create three folders on your computer desktop and name them data, anderson_naive, and search_results

Add the following files you downloaded at the beginning of the lesson to the data folder.

• anderson_refs.csv
• anderson_refs.rda
• andersosn_studies.rda
• suggested_keywords_grouped

Add the three downloaded files from the anderson_naive zip folder to the anderson_naive folder.

• MEDLINE_1-500
• MEDLINE_501-603
• PsycINFO

Add the three downloaded savedrecs files to the search_results folder.

• savedrecs(1)
• savedrecs(2)
• savedrecs(3)

Add your three new folders, data, anderson_naive, and search_results to the library-carpentry folder you just created.

Set your working directory

The working directory is the location on your computer R will use for reading and writing files. Use getwd() to print your current working directory to the console. Use setwd() to set your working directory.

# Determine which directory your R session is using as its current working directory using getwd().
getwd()

To set your new working directory go to:

1. Under Session at the top
2. Scroll down to Set Working Directory
3. Select Choose Directory
4. Choose the folder lc_litsearchr on your desktop

Organize your working directory

Using consistent filing naming and folder structure across your projects will help keep things organized. It will also make it easy to find things in the future since systematic reviews typically take months to complete. This can be especially helpful when you are working on multiple reviews or checking in with a review team months after running the initial search. In general, you can create directories or folders for scripts, data, and documents.

For this lesson, we will create the following in your working directory:

• search_results_data/ Use this folder to store your raw data or the original files you export from a bibliographic database. For the sake of transparency and provenance, you should always keep a copy of your raw data accessible and do as much of your data cleanup and preprocessing programmatically (i.e., with scripts, rather than manually) as possible.

• search_results_data_output/ When you need to modify your raw data for your analyses, it might be useful to store the modified versions of the datasets generated by your scripts in a different folder.

• documents/ This would be a place to keep outlines, drafts, and other text.

• scripts/ This would be the location to keep your R scripts for different analyses or plotting.

You may want additional directories or subdirectories depending on your project needs, but these should form the backbone of your working directory for this lesson.

We can create these folders using the RStudio interface by clicking on the “New Folder” button in the file pane (bottom right), or directly from R by typing in the console.

# Use dir.create() to create directories in the current working directory called "search_results_data", "search_results_data_output", "documents", and "scripts".

dir.create("search_results_data")
dir.create("search_results_data_output")
dir.create("documents")
dir.create("scripts")

Exploring your working directory

Create a new object by assigning 8 to x using x <- 8.

x <- 8

You can list all the objects in your local workspace using ls(). See if the object x is listed.

ls()

Now, list all the files in your working directory using list.files() or dir().

dir()

As we go through this lesson, you should be examining the help page for each new function. Check out the help page for list.files with the command ?list.files.

?list.files

One of the most helpful parts of any R help file is the See Also section. Read that section for list.files.

Using the args() function on a function name is also a handy way to see what arguments a function can take. Use the args() function to determine the arguments to list.files().

args(list.files)

function (path = ".", pattern = NULL, all.files = FALSE, 
    full.names = FALSE, recursive = FALSE, ignore.case = FALSE, 
    include.dirs = FALSE, no.. = FALSE) 
NULL

Create a file in your working directory called “mylesson.R” by using the file.create() function.

file.create("mylesson.R")

Typing in list.files() shows that the directory contains mylesson.R.

list.files()

You can check to see if “mylesson.R” exists in the working directory by using the file.exists() function.

file.exists("mylesson.R")

You can change the name of the file “mylesson.R” to “myscript.R” by using file.rename().

file.rename("mylesson.R", "myscript.R")

You can make a copy of “myscript.R” called “myscript2.R” by using file.copy().

file.copy("myscript.R", "myscript2.R")

Key Points

• The working directory is very important, as it is the place where you will store, save, and retrieve your files.

• Using consistent filing naming and folder structure across your projects will help keep things organized.

• Download the file for this lesson if you haven’t done so already.