ggplot Extension Course: Instructor Notes

Dataset

The data used for this lesson are in the figshare repository at: https://figshare.com/articles/SAFI_Survey_Results/6262019.

This lesson uses SAFI_clean.csv. The direct download link for this file is: https://ndownloader.figshare.com/files/11492171.

When time comes in the lesson to use this file, we recommend that the instructors, place the download.file() command in the Etherpad, and that the learners copy and paste it in their scripts to download the file directly from figshare in their working directory. . If the learners haven’t created the data/ directory and/or are not in the correct working directory, the download.file command will produce an error. Therefore, it is important to use the stickies at this point.

RStudio and Multiple R Installs

Some learners may have previous R installations. On Mac, if a new install is performed, the learner’s system will create a symbolic link, pointing to the new install as ‘Current.’ Sometimes this process does not occur, and, even though a new R is installed and can be accessed via the R console, RStudio does not find it. The net result of this is that the learner’s RStudio will be running an older R install. This will cause package installations to fail. This can be fixed at the terminal. First, check for the appropriate R installation in the library;

ls -l /Library/Frameworks/R.framework/Versions/

We are currently using R 3.x.y If it isn’t there, they will need to install it. If it is present, you will need to set the symbolic link to Current to point to the 3.x.y directory:

ln -s /Library/Frameworks/R.framework/Versions/3.x.y /Library/Frameworks/R.framework/Version/Current

Then restart RStudio.

Narrative

Before we start

• The main goal here is to help the learners be comfortable with the RStudio interface. We use RStudio because it helps make using R more organized and user friendly.
• Go very slowly in the “Getting setup section”. Make sure everyone is following along (remind learners to use the stickies). Plan with the helpers at this point to go around the room, and be available to help. It’s important to make sure that learners are in the correct working directory, and that they create a data (all lowercase) subfolder.

Intro to R

• When going over the section on assignments, make sure to pause for at least 30 seconds when asking “What do you think is the current content of the object area_acres? 123.5 or 6.175?”. For learners with no programming experience, this is a new and important concept.
• Given that the concept of missing data is an important feature of the R language, it is worth spending enough time on it.

Starting with data

The two main goals for this lessons are:

• To make sure that learners are comfortable with working with data frames, and can use the bracket notation to select slices/columns
• To expose learners to factors. Their behavior is not necessarily intuitive, and so it is important that they are guided through it the first time they are exposed to it. The content of the lesson should be enough for learners to avoid common mistakes with them.

Manipulating data with dplyr

• For this lesson make sure that learners are comfortable using pipes.
• There is also sometimes some confusion on what the arguments of group_by should be, and when to use filter() and select().

Visualizing data with ggplot2

• This lesson is a broad overview of ggplot2 and focuses on (1) getting familiar with the layering system of ggplot2, (2) using the argument group in the aes() function, (3) basic customization of the plots.

Using databases from R

• Ideally this lesson is best taught at the end of the workshop (as a capstone example) to illustrate how the tools covered can integrate with each others. Depending on the audience, and the pace of the workshop, it can be shown as a demonstration rather than a typically lesson.
• The explanation of how dplyr’s verb syntax is translated into SQL statements, and the section on laziness are optional and don’t need to be taught in detail during a workshop. They can be useful after a workshop for learners interested in learning more about the topics or for instructors to answer questions from the workshop participants.

Technical Tips and Tricks

Show how to use the ‘zoom’ button to blow up graphs without constantly resizing windows

Sometimes a package will not install, try a different CRAN mirror

• Tools > Global Options > Packages > CRAN Mirror

Alternatively you can go to CRAN and download the package and install from ZIP file

• Tools > Install Packages > set to ‘from Zip/TAR’

It is important that R, and the R packages be installed locally, not on a network drive. If a learner is using a machine with multiple users where their account is not based locally this can create a variety of issues (This often happens on university computers). Hopefully the learner will realize these issues before hand, but depending on the machine and how the IT folks that service the computer have things set up, it may be very difficult to impossible to make R work without their help.

If learners are having issues with one package, they may have issues with another. It’s often easier to make sure they have all the needed packages installed at one time, rather then deal with these issues over and over. Here is a list of all necessary packages for these lessons.

Other Resources

If you encounter a problem during a workshop, feel free to contact the maintainers by email or open an issue.

For a more in-depth coverage of topics of the workshops, you may want to read “R for Data Science” by Hadley Wickham and Garrett Grolemund.