Even if you attended RStudio’s pre-convention two-day instruction past thirty day period, you could only show up at 1 workshop—and there had been extra than half a dozen. Now, nevertheless, numerous components such as slides and R code are offered cost-free on the internet. Here’s how to get them.

Most of the code and slides have been posted on GitHub. If you don’t have git version control set up on your process, you can download a zipped file of any repository. But git and GitHub do make it simpler and extra stylish. Examine out episode 33 of Do Additional with R beneath if you’d like to master about git and GitHub in RStudio:

Tidy time series and forecasting in R

Instructor Rob J. Hyndman, professor statistics at Monash University, actually wrote the reserve on time series forecasting in R — not to point out the R forecast deal. I was torn between attending this 1 and the machine-discovering workshop I finished up using. Fortunately, even nevertheless it really is not very as superior as getting in a classroom in particular person, the created components and code are on the internet.

The GitHub repository is at https://github.com/rstudio-conf-2020/time-series-forecasting and his Forecasting Rules and Exercise textbook is cost-free on the internet at  https://otexts.com/fpp3/.

Contemporary geospatial facts investigation in R

“You will master to go through, manipulate, and visualize spatial facts and you will be introduced to features that will have you stating, ‘I failed to know you could do that in R!’” touts this workshop’s overview. This is an additional 1 I desire I could have attended.

This course highlighted the sf, tmap, mapview, raster, and dplyr deals.

Most of the workshop facts is not on GitHub specifically, but there is a simple repo at https://github.com/rstudio-conf-2020/geospatial with guidelines on how to download the rest.

Workshop chief Zev Ross claimed he posted the two substantial-res slides for viewing and a PDF version for download.

See facts at the bottom of this page on how to download and put in the workshop R package with workout routines and remedies.

Equipment discovering in R

There had been two workshops on machine discovering this 12 months: an introduction to the even now-evolving tidymodels machine discovering deal ecosystem and a extra superior session with Max Kuhn, creator of the effectively-known caret deal.

Introduction to machine discovering with the tidyverse

This workshop has its personal web-site wherever you can download slides, workout routines, and remedies from Alison Hill’s classes: https://conf20-intro-ml.netlify.com/components/. There is also a GitHub repo.

Used machine discovering in R

Max Kuhn’s session has a web-site at https://rstudio-conf-2020.github.io/utilized-ml/README.html. Toward the top there are links to see sections one via six individually. There is also a GitHub repo.

Deep discovering with Keras and TensorFlow in R

Examine out the sturdy GitHub repo which consists of a range of R Markdown notebooks with code and explanations as effectively as links to slides and facts. This was taught by Brad Boehmke, director of facts science at 84.51°.

Text mining with tidy facts ideas

Julia Silge, co-creator of Text Mining with R, led this workshop. Her slides are at http://bit.ly/silge-rstudioconf-one (Working day one) and bit.ly/silge-rstudioconf-2 (Working day 2). The GitHub repo at https://github.com/rstudio-conf-2020/textual content-mining includes slides and R Markdown files with code.

Big facts investigation in R

This workshop, taught by RStudio engineer James Blair, concentrated on making use of dplyr with facts.desk, databases, and Spark for large-scale facts. It also applied the vroom, dtplyr, and DBI deals.

The GitHub repo at https://github.com/rstudio-conf-2020/major-data includes an intro, slides, and workbook listing with R Markdown files. The workshop workout routines and code are also offered as on on the internet reserve at https://rstudio-conf-2020.github.io/major-facts/introduction-to-vroom.html.

Shiny from begin to end

If you have needed to master the Shiny R interactive world wide web framework — or if you have worked with it but needed to up your sport — Macalester Faculty professor Danny Kaplan’s Shiny workshop GitHub repository features slides and undertaking code. You can also clone the undertaking with a cost-free RStudio Cloud account at https://rstudio.cloud/undertaking/865256.

JavaScript for Shiny users

Also Shiny-similar, this workshop by Garrick Aden-Buie was built to help users personalize simple Shiny applications by making use of JavaScript, HTML, and CSS to make them search greater and do extra. This is an additional workshop I desire I could have attended. I can’t wait around to dig into the code. 

In addition to the workshop GitHub repo, there is a js4shiny.com web-site that is undoubtedly worthy of a go to.

R Markdown and interactive dashboards

This two-day workshop by Yihui Xie (creator of various R deals such as knitr and DT and the co-creator of Shiny, R Markdown, and leaflet) and RStudio training director Carl Howe was aimed at assisting attendees build potent interactive files and dashboards.

The targets, according to the workshop description, included the next:

  • The complete abilities of R Markdown
  • How to parameterize and publish studies from R Markdown
  • How to build interactive dashboards making use of htmlwidgets and Shiny

The workshop GitHub repo at https://github.com/rstudio-conf-2020/rmarkdown-dashboard includes a components listing with slides, workout routines, cheat sheets, and extra.

What they forgot to teach you about R

It appears like an introductory workshop, but this was truly “designed for expert R and RStudio users who want to (re)layout their R lifestyle,” according to the session overview. “You’ll master holistic workflows that address the most frequent resources of friction in facts investigation. We’ll operate on undertaking-oriented workflows, version control for facts science (Git/GitHub), and how to system for collaboration, interaction, and iteration (such as R Markdown).” Instructors Kara Woo, Jenny Bryan, and Jim Hester are all effectively-known in the tidyverse entire world. 

Locate the GitHub repository at https://github.com/rstudio-conf-2020/what-they-forgot and “the 1 real URL that links to all the things!” at https://rstd.io/wtf-2020-rsc.

Making tidy equipment

Taught by Charlotte Wickham and Hadley Wickham, this workshop was aimed at “those who have embraced the tidyverse and now want to broaden it to meet their personal requires,” according to the workshop overview. It discusses API layout, practical programming equipment, the basic principles of object layout in Amazon S3, and the tidy eval process for non-typical evaluation.

There is a GitHub repo with slides, R Markdown files, and extra.

A realistic introduction to facts visualization with ggplot2

This workshop coated “basic ideas driving helpful facts visualizations” as effectively as discovering how to build superior graphics with ggplot2. It was taught by Duke University professor Kieran Healy, creator of Details Visualization: A Simple Introduction. The workshop repo is at https://github.com/rstudio-conf-2020/dataviz.

My organization’s 1st R deal

If you’re fascinated in generating deals at your workplace for “easier facts entry, shared features for facts transformation and investigation, and a frequent search and truly feel for reporting,” you might want to check out this workshop components by application engineer Wealthy Iannone and R developer and Ph.D. scholar Malcolm Barrett.

You can locate the GitHub repo at https://github.com/rstudio-conf-2020/my-org-1st-pkg. 

Workshops for R newcomers

R for Excel Users was, not incredibly, a workshop aimed at power Excel users who want to begin incorporating R into their workflow.

And Introduction to Details Science in the Tidyverse, taught by Hadley Wickham and Amelia McNamara, was a “two-day, palms-on workshop built for folks who are model new to R and RStudio.”