Lab 1 · Quarto from R Markdown

Author

Workshop participant

Goal

Reconnect with Quarto by mapping it onto the R Markdown you already know. By the end you will have written a short .qmd report with headings, an inline calculation, a code chunk that produces a figure, and a cross-referenced caption.

Throughout, remember the one-line mental model: Quarto is R Markdown that grew up.

1. Open or create this file

This file is the lab. Render it now and confirm you get an HTML page.

  • In RStudio: click the Render button (or Ctrl/Cmd+Shift+K).
  • In Positron: open the Quarto preview / run render from the editor toolbar.

You should see a styled HTML document open in the Viewer.

2. Quarto vs R Markdown, in your own words

The chunk grid below is rendered statically. Experiment with the chunk options echo, eval, message, warning, fig-cap, and include.

TipSetting chunk options in Quarto

In Quarto, R chunk options are set using the #| prefix inside the chunk, rather than in the curly braces ```{r, echo=TRUE}``` as in R Markdown.

plot(cars)

From previous R Markdown experience and experimenting with Quarto below, write a short paragraph describing the differences you notice between R Markdown and Quarto using either bullet points or enumerated lists:

Your prose

3. Inline code

The mean of the numbers 1 to 10 rendered inline is produced by `r mean(1:10)` and rendered as 5.5. Below, write your own inline expression that reports the number of rows in mtcars in the following sentence:

There are ____________ rows in mtcars.

4. A figure with a caption and cross-reference

Execute the chunk below. It draws a histogram with a caption. Take note of the chunk label (#| label: fig-mpg): you reference it elsewhere with @fig-mpg.

library(ggplot2)
ggplot2::mpg |>
  ggplot(aes(hwy)) +
  geom_histogram(bins = 20, fill = "#2E7D6B", color = "white")
A histogram of the hwy column of the mpg dataset
Figure 1: Distribution of highway mileage in mtcars

A sentence that points at the figure: see Figure 1 for the distribution.

Now add a second figure (a scatter plot of hwy vs cty) below, give it a label and caption, and cross-reference it in a sentence. Render the document and confirm both figure numbers update.

5. A project-level _quarto.yml

Quarto shines with projects. Create a _quarto.yml file next to this lab (same folder) with a shared HTML theme, so every .qmd in the folder gets the same look:

project:
  type: default
output-dir: _output

format:
  html:
    toc: true
    toc-title: "On this page"
    theme: cosmo

Render again. The output should now move into _output/ and gain a table of contents.

6. Reflection

Answer these in a short paragraph (as comment lines or prose):

  1. What is the practical difference between live Shiny in a document (server: shiny in Qmd, previously runtime: shiny in R Markdown) and a Shinylive block? (Answer comes later in the workshop, but note your guess now.)
  2. Why does “rendered output is plain files” matter for the rest of the workshop?

You are done with Lab 1. Move to lab-02-shiny.qmd.