Setup

In this section we cover all of the start-up activities that you need to complete in order to use RStudio effectively: install the software, prepare your computer to hold the data that you will be using, load the tidysphere library, and download data that you will use RStudio to analyze.

1 Installing software

1.1 Install R and RStudio

Tons of resources on the Internet, both video and written, can help you install this (free) software, whether it be on a Windows, Mac, or Linux computer.

  1. You want to install R first from here.
  2. After that, install RStudio from here.
  3. Launch RStudio for the next step.

1.2 Installing software for generating shareable reports

You need to install another piece of software as well as a large package in order to generate shareable reports.

  1. Within RStudio and at the Console prompt, type install.packages("tidytex") and then hit Enter.
  2. After the above is done (and it will take a while), quit R Studio.
  3. Now, use your browser and go to Quarto’s installation page. Install the version for your operating system. This software has an open source license, so it should present minimal difficulty in getting approval (if the computer is under control of your IT group).

You should consider this software and package as integral to using R Studio as a modern user.

1.3 Installing needed libraries: tidyverse and tidylog

The tidyverse is a collection of packages (R code and tools) for data analysis. The tidylog library makes warning and status messages more helpful. You will be using these throughout this course.

  1. Use the Console, found in the lower left window after you launch RStudio.
  2. Type install.packages("tidyverse") and then hit Enter.
  3. After the above is done (and it will take a while), type install.packages("tidylog") and then hit Enter.

Installation takes a little while; just let it finish execution before continuing. This only needs to be done once on each computer.

1.4 Project Organization

One advantage of automating work with a script is that you can reuse it later. To do that, it’s helpful to have work organized so it’s easy to find in an organized folder structure.

2 Set your RStudio preferences

While working with R and RStudio, we have learned some things about how to set up RStudio that will help you enjoy your experience and be more productive.

Go through the following steps in order to accelerate your enjoyment and productivity:

  1. Open Tools/Global options in order to set your preferences.
  2. Set the following under the General/Basic tab:
    • So that you can find scripts that you create when not in a project, you can set your Default working directory to a top-level folder like the one described above. Note that, generally, you will be working in a project so R will never use this directory directly; however, set this just in case you create some files outside of the scope of a project. This is one of those “better be safe than sorry” situations.
    • When you start an R session, you can set it up so that RStudio automatically loads all that you did in your previous session. We recommend that you not do this! Why? Because it can store a lot of information, and you will lose track of exactly what it is that you have done. Better to have a bit of inconvenience while maintaining some control over your work environment. To ensure that you begin each day with an empty session, do the following:
      • Uncheck Restore .RData into workspace at startup and
      • Change Save workspace to .RData on exit to Never.
    • Keep all the other options the same under General.
    • Click the Apply button.
  3. Under Code/Editing:
    • Make sure that Use native pipe operator is checked.
    • Click the Apply button.
    • The default keyboard shortcut for the pipe is Shift+Ctrl/Cmd+M, which takes three fingers. You may prefer to pick an easier combination like Alt+M. To do that, under Code/Editing look for the keyboard shortcuts button, and use it to filter to the pipe command (type “pipe” in the filter) and change the key binding as you like.
  4. To change how RStudio looks (simply for your own work style), change any settings in Appearance (a left-menu button in this dialog box). Click the Apply button when done.
  5. For working with scripts (which you will be doing soon enough), you should set the following preference. Go to the R Markdown/Basic tab.
    • Look for the Show markdown preview in option.
    • Change it to Viewer pane. (If you have a large screen that you work on, you might change this to Window; however, on a laptop, it’s generally more convenient to use the Viewer pane.)
  6. Click the OK button.

As you gain experience with RStudio, you will want to return to your settings throughout the Global options dialog box and see if you want to change anything. The defaults are perfectly reasonable but these options are here for a reason.

3 Starting a new project

The following are the steps that you should complete when starting a new project. You might consider printing out this page as a reminder of the steps to take while you are at the beginning of your learning journey.

3.1 Preparing your computer for data

When you are doing any data analysis project, you have to have a place to put the data (we did that above) and tell RStudio where to look for data (which we’ll do now).

3.1.1 Create a new project subdirectory

Any time that you start a new project, create a folder for it within your overall folder structure. There you will store the data, scripts, and output related to the project. For all but the smallest projects, you may want to set up the project folder with subfolders called /R (for R scripts), /data (for data files), and output (for whatever gets generated). You may also want a /docs subfolder to keep documentation like notes and presentations in.

3.1.2 Create a new RStudio project

After creating the subdirectory, you need to tell RStudio that you are beginning a new project. You do this with the menu choice File/New Project...; when the dialog box comes up, choose Existing Directory and then browse to the directory that you just created.

The wonderful thing about creating this project is that now RStudio knows where to look for data—i.e., where the working directory has been set. The project will also remember which files you have open, so you can jump right back in after closing RStudio and returning to the work later on.

If you want to know what the working directory is for R, then go to the Console and type getwd().

4 Returning to an existing project

After you have gone through all of the pain of starting a new project, subsequent working sessions will be much easier. When you start RStudio, it will automatically go to the most recent project. If you are starting up RStudio after working on some other project or with a completely empty RStudio workspace, then use the menu to fine File/Recent Projects and choose the name of the project that you want to work on. The project will open, the working directory will change, and the files that you most recently were working on will be open. There’s also a project shortcut menu top right of the RStudio window.