The video is missing a part installing R.
I have also added “reprex” to the installation and should include “gramr”
I should take a look here he has a better breakdown than I do.
This is, in my opinion, by far the most frustrating part about learning R. Getting setup is a bit of a pain. But once you are setup things work very well. I am going to do my best to walk you through all the things you need. This should take you about 2 hours to complete. It sucks, but just do it and then were off to the races.
I will be going through some of the steps within this document but I would recommend checking out this video, which was part of a recent workshop. You can watch it at 1.5X speed or browse along to the specific spot where you run into a problem.
There’s some documentation over on my GitHub which should help a bit. I would download
MyProjectName somewhere on your computer. If you believe you have these components installed you can go to Already have R and RStudio installed. Otherwise go to the Installing R+RStudio for the first time
For OSX users, you need to be running at least OSX High Sierra v13.0 or higher.
- R 4.x.x
- RStudio 4.
Some of you might already have R+RStudio installed. This section is for you. We need to make sure you are running the correct versions of both programs, otherwise parts of the workshop will not work for you.
To check which version of R you are running simply type
version in the Console
To check your version of RStudio
Another method is to use the
rstudioapi package which allows you to do this via the Console. We need to run at least RStudio 1.4. If not proceed to update RStudio.
With some packages it is possible that you will need to update R and/or RStudio (notice that these are different). RStudio is the GUI which runs R.
If you are using Windows I would highly recommend using the
if (!require('remotes')) install.packages('remotes'); # make sure you have Rtools installed first! if not, then run: #install.packages('installr') #install.Rtools() ::install_github('talgalili/installr')remotes
Launch RGui and then run the following code
if(!require("installr")) install.packages('installr') library("installr") updateR() # this will open dialog boxes to take you through the steps.
There is apparently a version in development for this to work with OSX
install.packages('devtools') #assuming it is not already installed library(devtools) install_github('andreacirilloac/updateR') library(updateR) updateR(admin_password = 'Admin user password')
This might be the most frustrating part. It can be a bit tricky and takes time to setup. It should take about an hour to accomplish (assuming you have decent internet speeds)
We need to run at least RStudio 1.4.
- Install R
- Install RStudio
- Install RTools
- Make sure to set
.REnvironwhich you can read about here
- Make sure to set
- Install Git
These tools are required for the workshop, for those who wish to knit to PDF you will need to install
tiny_tex which I will not cover in the workshop since we knit to
docx. The installation process is a bit troublesome. But definitely possible.
“packages” include a list of functions that can be used in your code. One of the most widely used packages is the
tidyverse. In order to use the package we would normally use the
library(packageName)which in this case would be
However, before you can “load” a library for the first time it must be installed on your computer. Packages are traditionally downloaded from CRAN, which is an RStudio curated list of packages. Packages on CRAN are tested for stability. You can also download packages directly from GitHub. Packages from GitHub can be (but are rarely) unstable. They can be packages created by anyone, which is one of the main strengths of R. In order to install packages from GitHub we are going to create an authentication key, otherwise there is a limit on how much you can download.
You are going to be installing packages from multiple sources. When installing a package for the first time you might need to install it from GitHub. It’s a great source for packages that have not yet been released on CRAN. Under normal circumstances your ability to install packages from GitHub is limited. However you can create an authentication key which will give you unlimited power.
First, go ahead and make yourself a GitHub account and install Git. Once that is complete I would run the following code in your console
# Creating a GitHub Personal Token Key ::p_load(credentials) pacman::set_github_pat()credentials
This will prompt you for your login, at which time you will no longer have a limit.
Install from CRAN you would use the following code
install.packages("package1", dependencies = TRUE) # This will install 'package1' on your computer
install.packages("package2", dependencies = TRUE) # This will install 'package1' on your computer
To install from GitHub the
devtools package is required. Here is a GitHub package called
easystats which can be found here on GitHub.
install.packages("devtools") # This will install devtools on your computer library(devtools) # load the 'devtools' library ::install_github("easystats/easystats") # install a package off GitHub using 'devtools'devtools
Personally, I find that this approach to installing/loading packages is quite cumbersome. If you have 5 packages here is what your script would look like
install.packages("package1", dependencies = TRUE) # This will install 'package1' on your computer install.packages("package2", dependencies = TRUE) # This will install 'package2' on your computer install.packages("package3", dependencies = TRUE) # This will install 'package3' on your computer install.packages("package4", dependencies = TRUE) # This will install 'package4' on your computer install.packages("package5", dependencies = TRUE) # This will install 'package5' on your computer library(package1) # This will load 'package1' in your workspace library(package2) # This will load 'package2' in your workspace library(package3) # This will load 'package3' in your workspace library(package4) # This will load 'package4' in your workspace library(package5) # This will load 'package5' in your workspace
An alternative to this would be use the
pacman package which I fell in love with when I was learning R. Here is the code I have at the top of my scripts.
p_load This function is a wrapper for library and require. It checks to see if a package is installed, if not it attempts to install the package from CRAN and/or any other repository in the pacman repository list.
For a list of
pacman functions here:
<- 'https://i.imgur.com/T8xl8Bi.png' png_url <- 'https://i.imgur.com/T8xl8Bi.png' gif_url ::include_graphics2(png_url, gif_url)linguisticsdown
if (!require("pacman")) install.packages("pacman") ::p_load(package1, package2, package3, package4, package5) #p_load - This function is a wrapper for library and require. It checks to see if a package is installed, if not it attempts to install the package from CRAN and/or any other repository in the pacman repository list.pacman
if (!require("pacman")) install.packages("pacman") # This will install/load the 'pacman' package ::p_load(package1, package2) # This will check to see if 'package1' and 'package2' is installed on your computer, otherwise it will install it and then load it.pacman
I have made this as easy as possible. Go into your
MyProjectName directory, under
scripts. You will find
install.R. Open this file. We are going to run through each line one by one. This way if an error occurs, we can troubleshoot that specific line.
At times you can have issues installing new packages, this can be for a variety of reasons.
- Try closing and re-opening RStudio. At times packages can conflict with each other. Some packages depend on other packages to work. For example the
psychpackage which requires or depends on the
mnormtpackage. My first test is to
unloadpackage which can be done using the code below
::p_unload(all) # detaches all packages. Very useful when you need to update a package OR install a packages which has dependencies that are already loaded in your R Sessionpacman
This is amongst the most common reasons for an installation failing. The package you are trying to install has dependencies loaded in your R Session. You can either use the code a provided to unload all packages or start a new session in RStudio.
- You are using a very old version of R This is rather unlikely, but make sure you are using at least version 4.0 or newer.
If you have conflicting packages see here
::conflict_prefer("tidy", "broom") # for a given function e.g., tidy(lm) it will prefer the function from tidy before broomconflicted
I typically do a few other small things to setup. The first is I install a dark theme. There are plenty of default themes available but I prefer using one from GitHub called
rscodeio. It’s not perfect but its my personal favorite at the moment. I change the color of the cursor to a bright pink as well as the color of syntax highlighting.
::install_github("anthonynorth/rscodeio") # install the package remotes::install_theme() # install the themerscodeio
Ctrl+Alt+L for Clear Workspace this is a shortcut I use a lot to reset my environment
- Insert an animation showing how to fold code.
Code sections allow you to break a larger source file into a set of discrete regions for easy navigation between them. Code sections are automatically foldable—for example, the following source file has three sections (one expanded and the other two folded):
To insert a new code section you can use the
Code -> Insert Section command. Alternatively, any comment line which includes at least four trailing dashes (-), equal signs (=), or pound signs (#) automatically creates a code section. For example, all of the following lines create code sections:
# Section One --------------------------------- # Section Two ================================= ### Section Three #############################
There’s a couple more examples on StackOverflow here
Note that as illustrated above the line can start with any number of pound signs (#) so long as it ends with four or more -, =, or # characters.
# Header 1 ---------- # ▐ Header 1.1 -------- # ▐ ▬ Header 1.1.1 -------- # Section 1 ---------- # ▐ Subsection 1.1 -------- # ▐ ▬ Sub-subsection 1.1.1 --------
There is a massive library of add-ins you can browse and find packages that fit your specific needs. You can browse within RStudio or head on over to GitHub and see the rstudio-addin tag.
Now that you have your environment setup, we can finally start with some coding. I would suggest you take a look at my optional chapter on “Project Environment” where we break down where things should be stored in a typical research project. This will come into play if you decide to create a reproducible document using RMarkdown in later chapters. Its also just a good idea to keep things organized so you can find stuff within your project.
In order to make things a tad easier…your first time deploying R I suggest your run the following lines of code, then go grab a coffee. Below is the
install.R file from the Workshop repo
# DESCRIPTION: As part of the workshop you will need to install some packages. # This script is meant to be run on your first install. You can delete it after you run it without errors options(repos = getOption("repos")["CRAN"]) install.packages(c("devtools", "BiocManager", "pacman", "remotes", "ggstatsplot", "rmarkdown", "credentials"), dependencies = TRUE) # rest omitted # Creating a GitHub Personal Token Key ::set_github_pat() credentials # if you want a dark theme then run the following code ::install_github("anthonynorth/rscodeio") # install the package remotes::install_theme() # install the theme rscodeio # remotes installation ::install_github("easystats/easystats") # installs the whole easystats suite remotes::install_github("davidgohel/officedown") remotes::install_github('achetverikov/apastats', subdir='apastats') devtools::install_github("benmarwick/wordcountaddin", type = "source", dependencies = TRUE) devtools::install_github("dcomtois/pathToClip") remotes::install_github("nevrome/wellspell.addin") #github.com/nevrome/wellspell.addin devtools::install_github("nevrome/LanguageToolR") devtools::install_github("fkeck/quickview") devtools::install_github("gadenbuie/shrtcts") remotes ::lato_quick_setup() LanguageToolR::easystats_update() # updates easystats packages easystats # Other Package Installation if (!require("pacman")) install.packages("pacman") # if pacman is not installed, the install it. # load/install required packages ::p_load(addinslist, arsenal, cgwtools, colourpicker, easystats, esquisse, ggpubr, ggstatsplot, pacman ggThemeAssist, googlesheets4, hablar, Hmisc, janitor, jtools, officer, parameters, rio, Rmisc, rstatix, see, sjmisc, sjPlot, tidyverse) ::install_formats() # will install packages required by rio to function rio# pacman::p_unload(all) # detaches all packages. Very useful when you need to update a package OR install a packages which has dependencies that are already loaded in your R Session
# tinytex installation install.packages('tinytex') ::install_tinytex() tinytex:::is_tinytex() # This will return "TRUE" if it is installed. tinytex::pdflatex('test.tex') # to confirm run this line. If it fails, then there's a problem tinytex
Here we will go through an example on how to install and setup Zotero. This is critical if you want to write your own reproducible document. For the sake of brevity our goal is to create a
*.bib file which contains our references. This
*.bib file is called within our
YAML at the very top of our RMarkdown document. In the example directory I gave you, I created one but Zotero is going to be required for inserting reference. There are 2 things to install
If you do plan on being able to write documents then I suggest using Zotero. Our goal is to create a
*.bib file which is the filetype needed for RStudio. There might be ways to export a
*.bib file from EndNote but I am cheap and Zotero is free. The biggest issue going the EndNote route is that everytime you update your resources, you will need to re-export your
*.bib file. This may not be an issue for some people but it was for me.
Here are some resources for EndNote
Check a few of the websites I have bookmarked on this subject
Here is an example from a project where folder structures were not followed. It is an unmitigated disaster.
If you plan on importing
.mat files into R, I would recommend using the
R.matlab package rather than the
rio package based on evidence found here
Michael Culshaw-Maurer has a nice page with some of his favorite shortcuts in R.
If you want to make noise at the end of your scripts check this out.