positron.tutorials is a collection of tutorials for working with Positron. Covers scripts, Quarto documents, git, Github, and Quarto websites. Makes extensive use of the tools in the tutorial.helpers package.
To install the package from CRAN:
install.packages("positron.tutorials")However, the CRAN package does not include the data necessary for running the tutorials. The best solution is to install the development version from GitHub with:
remotes::install_github("PPBDS/positron.tutorials")However, if you want to use the CRAN version, then, when you first
load the library, you will be prompted to run
setup_tutorial_data() at the Console in order to download
the necessary data.
There are many tutorials in the package. To run a tutorial, use
learnr::run_tutorial(), providing the short name of the
tutorial and the package name.
learnr::run_tutorial(name = "01-code",
package = "positron.tutorials")The core tutorials introduce students to the Positron integrated development environment.
Positron and Code (“01-code”). Introduce students to Positron and to writing R code in simple scripts.
Positron and Quarto (“02-quarto”). Demonstrate more tricks for working with R code using Positron, and also explain Quarto documents.
Terminal (“03-terminal”). Teach the command line.
Positron and GitHub Introduction (“04-github-1”). Explain the basics of Git and GitHub, mostly in the context of Positron.
Positron and GitHub Advanced (“05-github-2”). Provide more practice in working with Git/GitHub, including more details on the use of GitHub Pages.
Quarto Websites Introduction (“06-websites-1”). Demonstrate the basics of website construction using Quarto projects.
Quarto Websites Advanced (“07-websites-2”). Practice Quarto websites, with a focus on splitting data analysis tasks into separate files.
These tutorials cover material from R for Data Science (2e)
(R4DS) by Hadley Wickham, Mine Çetinkaya-Rundel, and Garrett Grolemund.
There are five related tutorials in the package: r4ds-1,
r4ds-2, r4ds-3, r4ds-4, and
r4ds-5. Different tutorials cover different chapters from
the book as follows.
Data import
Data visualization
Data transformations
Data tidying
Spreadsheets
Layers
Exploratory data analysis
Communication
Databases
Logical vectors
Numbers
Strings
Regular expressions
Arrow
Factors
Dates and times
Missing values
Joins
Hierarchical-data
Web scraping
Functions
Iterations
The organization of the tutorials is not the same as the organization of R4DS. Instead, each tutorial begins by sourcing data from a different sort of storage technology and then working with that data.
We have one tutorial, tidycensus-1, covering material
from Analyzing
US Census Data: Methods, Maps, and Models in R by Kyle
Walker.