Northwestern IT Research Computing Services
NOTE: Workshop materials may be updated before the next workshop date. You may want to wait to download materials until close to the workshop date (or the morning of) to get the most current version.
This workshop assumes you have recent versions of R and RStudio - R 3.4 or 3.5 and RStudio 1.1. R and RStudio installation instructions.
How to get the materials depends on how you plan to access R and RStudio for the workshop.
If you installed R and RStudio on your laptop, download all of the materials to your laptop. Click on the green Clone or Download button above, then download the repository as a ZIP file.
Find the downloaded .zip file on your computer, likely in your Downloads folder. Unzip it - usually by double-clicking. This will create a directory called r_intro_june2018-master. Move this somewhere on your computer where you'll be able to find it, like your Documents folder.
You should open the file r_intro_june2018.Rproj in this folder to open the materials as an RStudio project. Double-click on it from your Finder/File Explorer, or from RStudio, File menu > Open Project..., then navigate to the location of the file.
If you're using RStudio Cloud, go to https://rstudio.cloud and log in (or create an account if needed). Click on Your Workspace in the left Menu. Then make sure you are on the Projects tab, and click down arrow in the blue button for New Project. Choose the option of New Project from a Git Repo. The repo address is https://github.com/nuitrcs/r_intro_june2018.
This will copy all of the files from this repository into your new project. This will take a few moments to copy files from this repository. You'll then need to install packages. Open packagelist.r and run the code. The tidyverse package will take a while to install.
You can use this space like you would your RStudio on own computer, except you can only access the files that are part of the project and save files within the project.
If you're familiar with git, you can log in to Quest and clone the repository. Then connect to RStudio on the Quest Analytics Nodes and navigate to the directory. It's easier to find directories in /home than in /projects
Alternatively, you can download the files to your laptop, as in option 1 above, then transfer them to Quest via SFTP; save them somewhere in your /home directory, which is where you'll be by default when you connect to Quest via SFTP. Then navigate to the directory after you connect to RStudio on the Quest Analytics Nodes.
Open the workshops materials as a project in RStudio: File menu > Open Project..., then navigate to the location of the file.
The main materials are slides. Keynote and Powerpoint versions are available:
Exercises we do during the workshop are either in the slides or in .R files in the exercises directory.
Reference materials and independent practice exercises are written in RMarkdown (*.Rmd). You can open these files directly in RStudio and run the code chunks. The RMarkdown files have also been converted to html files for easy viewing. Exercise files have one RMarkdown file (with answers) and two html files (one with and one without answers). Links to the html files are in the coreexercises directory.
RMarkdown files can be previewed in GitHub, but they won't include the output of the code cells. HTML files generated from the RMarkdown generally can't be previewed directly in the GitHub repository view, but they can be viewed online through GitHub Pages; links are provided for that where relevant. HTML files are self-contained; this means they are on the large side, but they can be downloaded and viewed locally as a single file.
REMEMBER: if downloading individual files from GitHub, you want to download the RAW version of a file. Otherwise, it's often better to download everything together by using the green clone/download button for the entire repository. Downloading from GitHub reference.
An extensive list of good R resources can be found in the main R workshop repository.
The handouts for this workshop are from:
R Reference Card: lists many commonly used functions
RStudio Base R Cheat Sheet: syntax reference
Online reference for plotting for this workshop:
Base R Examples by David Gerard
R Base Graphics Cheat Sheet by Joyce Robbins