Meet the toolkit

Dr. D’Agostino McGowan


  • Demo: Penguin Study
  • R and RStudio
  • Quarto

A Penguin Study

Recap: What did we just do?

  • Create a project in RStudio
  • Open a .qmd file in RStudio
  • Render the analysis
  • Edit the analysis
  • Re-render the analysis

Login to RStudio Pro

RStudio Pro Setup

Step 1: Create a New Project

Click File > New Project

RStudio Pro Setup

Step 2: Click “Version Control”

Click the third option.

RStudio Pro Setup

Step 3: Click Git

Click the first option

RStudio Pro Setup

Step 4: Copy my starter files

Paste this link in the top box (Repository url):

Penguin fun!

  • Once you log on to RStudio Pro, create a new project from version control (Git)
  • Paste in the Repository url box
  • Find the file pane (on the bottom right). Click the welcome-penguins.qmd file
  • Click the “Render” button
  • Go back to the file and change your name on top (in the yaml – we’ll talk about what this means later) and render again.
  • Then, scroll to the plot chunk, below Palmer Penguins. Instead of looking at the relationship between flipper length and bill length, plot the relationship between flipper length and bill depth. Hint, look at the full dataset at the bottom of the document for variable names, update the captions to match your new plot.
  • Render again & voila!

What is R?

  • scripting language
  • statistical software
  • like a car’s “engine”

What is RStudio?

  • IDE (integrated development environment)
  • like a car’s “dashboard”

Let’s take a tour – R / RStudio

What did we learn?

  • Using the console
  • Using R as a calculator
  • Environment
  • Loading and viewing a data frame
  • Creating a Project

R essentials

A short list (for now):

  • Functions are (most often) verbs, followed by what they will be applied to in parentheses:
do_that(to_this, to_that, with_those)
  • Columns (variables) in data frames are accessed with $:
  • Packages are installed with the install.packages function and loaded with the library function, once per session:


R packages for data science

The tidyverse is an opinionated collection of R packages designed for data science. All packages share an underlying design philosophy, grammar, and data structures.



  • Fully reproducible reports – each time you render the document the analysis is run from the beginning
  • Simple markdown syntax for text
  • Code goes in chunks, defined by three backticks, narrative goes outside of chunks

Let’s take a tour - Quarto

What did we learn?

  • Creating a project
  • Creating a .qmd file
  • Rendering documents
  • Visual Editor
  • The YAML
  • Markdown and (some) R syntax


Use the Render button in the RStudio IDE to render the file and preview the output with a single click or keyboard shortcut (⇧⌘K).

If you prefer to automatically render whenever you save, you can check the Render on Save option on the editor toolbar.

YAML header

The YAML header starts and ends with three dashes

title: "This is a title"
format: html
editor: visual

Code chunks

R code chunks identified with {r} with (optional) chunk options, in YAML style, identified by #| at the beginning of the line.

#| label: load-packages
#| include: false

Would this code chunk be “included” in the final report?

Markdown text

  • Quarto uses markdown for formatting text, including section headers, hyperlinks, an embedded image, and an inline code chunk.
  • If you use the “visual” editor, you don’t need to learn much of this

Your turn

  • Log into RStudio Pro
  • Open the project you created in the last class
  • Explore the visual editor – try adding some bold text to the document


Remember this, and expect it to bite you a few times as you’re learning to work with Quarto: The workspace of your Quarto document is separate from the Console!

  • Run the following in the console
x <- 2
x * 3

All looks good, eh?

  • Then, add the following chunk in your Quarto document
x * 3

What happens? Why the error?

How will we use Quarto?

  • Every assignment / report / project / etc. is a Quarto document
  • You’ll often have a template Quarto document to start with
  • The amount of scaffolding in the template will decrease over the semester
  • You will turn in the .html file on Canvas

Lab 01

  • Lab instructions are posted on the course website under assignment
    • Let’s go find today’s!