Lab 1: Welcome to Quarto!

Author

Your Name Here!

Quarto

This is a Quarto document!

Quarto is a software that allows you to interweave text and R code to create HTML, PDF, and Microsoft Word documents

There are two ways to view a Quarto document, (1) as the “Source” file, or (2) as the “Visual” file. We will only use the Visual option in this class, as it allows you to interact with Quarto similar to how you interact with Word or Google Docs.

Formatting your Document

Similar to a Word Doc, there are a variety of ways you can spice up a Quarto document! Let’s explore a few.

Question 1: Using the formatting options, make a numbered list of your top three favorite animals.

Question 2: Using the formatting options, insert an image of your favorite animal.

Question 3: Now, change the “Formatting your Document” section name to “My Favorite Animals”. Make sure your header is a level 1 – use the Header 1 formatting option!

R Code

You can differentiate the R code within a Quarto file from the body of the document, based on the gray boxes that start with an {r}.

Here is an example of an R code chunk:

Notice in the line after the {r} there are two lines that start with #| – this is the symbol that declares options for a code chunk. The #| label: allows us to specify a name for a code chunk, I typically choose a name that tells me what the code chunk does (e.g., load-packages, clean-data). The #| include: false option at the beginning of the code chunk controls how the code output looks in our final rendered document.

This code chunk has two things we want to pay attention to:

  1. The library(tidyverse) code loads in an R package called the “tidyverse”. This is code you will have in every lab assignment for this class!

  2. Code comments which are denoted by a # symbol. Code comments are a way for you (and me) to write what the code is doing, without R thinking what we are writing is code it should execute.

Running Code

In order for us to be able to use the contents of the tidyverse package (e.g., data, functions), we need to run the code chunk above! There are a few ways to do this:

  1. Clicking on the green “play” button in the upper right hand corner of the document. This will run all the code included in the code chunk.
  2. Putting your cursor in the code chunk and using a keyboard shortcut to run the code. On a PC the shortcut is Control + Enter (pressed at the same time). On a Mac the shortcut is Command + Return. This will run a single line of code, so you may need to do this multiple times is there is more than one line of code!

Question 4: Run the code in the above code chunk (load-packages) using either of these methods. What output do you see? What do you think this output is telling you?

Rendering a HTML Document

When you click the Render button a document will be generated that includes both content as well as the output of any embedded R code chunks within the document. Rendering a document is similar to running the code within the document, as Quarto performs the same action (running each chunk of code) in order to render your final document.

Question 5: Click on the “Render” button to produce an HTML file (you may need to enable popups to see the rendered document). Do you see the above code chunk (load-packages) in the rendered HTML document? Why do you think this is the case?

Including Code Output

You can include code output in your rendered document:

mpg

Question 6: Run the code above to see a preview of the mpg dataset. What are the observations (cases) in these data?

glimpse(mpg)

We can also preview a dataset using the glimpse() function.

Question 7: Run the code above and compare the output to the previous code (mpg). How is the output different? Which output do you prefer?

Including Plots

You can also embed plots in the rendered document. Here is an example of a plot:

Question 8: What do you think the echo: false option does in the above code chunk? Hint: Render the document and see what you see!

Question 9: What do you think the mapping = aes(y = manufacturer, x = hwy)) code does?

Question 10: What do you think the labs(x = "Highway Miles Per Gallon", y = "Car Manufacturer") code does?