This blog post is part of a series on new features in RStudio 1.3, currently available as a preview release.
We’re excited to announce that RStudio v1.3 will gain a newly-minted pane: the Tutorial pane, used to host tutorials powered by the learnr package.
A learnr tutorial can include any of the following:
With the Tutorial pane, it is now possible to work through a learnr tutorial directly from the comfort of the RStudio IDE. You can use the RStudio IDE to learn, reflect, and tinker as you work through your running tutorial.
RStudio will automatically index and display the tutorials provided by the installed R packages in your R library paths:
You can use this list to browse and run tutorials at your convenience.
The learnr package bundles a selection of tutorials that will introduce users to R, RStudio and the Tidyverse, but we hope the R community at large will find this a useful medium for creating and sharing their own R tutorials. If you’re interesting in authoring your own learnr tutorials, please see the Publishing article on the learnr website.
The Tutorial pane is available in the latest iteration of the RStudio v1.3 preview release. You can download the latest preview release here:
We’d also like to take this time to highlight a small selection of R packages developed and shared by members of the R community that provide their own learnr tutorials:
sortable includes a tutorial showing how sortable widgets can be included in your own learnr tutorials;
sur includes a tutorial that (quite comprehensively!) explores the manipulation of R data frames, including how missing data can be handled.
If you’d like to try out the tutorials bundled in these packages, you can install the packages from CRAN with:
install.packages(c("vegawidget", "sortable", "sur"))
and their associated tutorials will automatically become available in the Tutorial pane.
Questions? Comments? Please share your feedback with us on the RStudio community forums.
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We’d like to highlight and answer some of the great audience questions asked during the "MLOps with vetiver in Python and R" webinar.