Even if you attended RStudio’s pre-meeting two-working day education final thirty day period, you could only attend one workshop—and there had been a lot more than half a dozen. Now, however, a lot of products such as slides and R code are available no cost online. Here’s how to get them.
Most of the code and slides have been posted on GitHub. If you don’t have git model management set up on your procedure, you can obtain a zipped file of any repository. But git and GitHub do make it easier and a lot more tasteful. Test out episode 33 of Do Much more with R down below if you’d like to learn about git and GitHub in RStudio:
Tidy time collection and forecasting in R
Teacher Rob J. Hyndman, professor stats at Monash College, virtually wrote the book on time collection forecasting in R — not to mention the R forecast bundle. I was torn between attending this one and the machine-discovering workshop I ended up getting. Happily, even however it really is not really as fantastic as getting in a classroom in particular person, the prepared products and code are online.
The GitHub repository is at https://github.com/rstudio-conf-2020/time-collection-forecasting and his Forecasting Concepts and Apply textbook is no cost online at https://otexts.com/fpp3/.
Fashionable geospatial information analysis in R
“You will learn to read, manipulate, and visualize spatial information and you will be launched to features that will have you stating, ‘I did not know you could do that in R!’” touts this workshop’s overview. This is a further one I desire I could have attended.
This class showcased the sf, tmap, mapview, raster, and dplyr deals.
Most of the workshop info is not on GitHub right, but there is a essential repo at https://github.com/rstudio-conf-2020/geospatial with guidance on how to obtain the relaxation.
Workshop leader Zev Ross mentioned he posted each substantial-res slides for viewing and a PDF model for obtain.
Equipment discovering in R
There had been two workshops on machine discovering this 12 months: an introduction to the still-evolving tidymodels machine discovering bundle ecosystem and a a lot more highly developed session with Max Kuhn, creator of the perfectly-recognized caret bundle.
Introduction to machine discovering with the tidyverse
This workshop has its individual website exactly where you can obtain slides, workout routines, and solutions from Alison Hill’s periods: https://conf20-intro-ml.netlify.com/products/. There is also a GitHub repo.
Applied machine discovering in R
Max Kuhn’s session has a website at https://rstudio-conf-2020.github.io/used-ml/README.html. Towards the prime there are inbound links to see sections 1 through 6 independently. There is also a GitHub repo.
Deep discovering with Keras and TensorFlow in R
Test out the strong GitHub repo which features a quantity of R Markdown notebooks with code and explanations as perfectly as inbound links to slides and information. This was taught by Brad Boehmke, director of information science at 84.51°.
Text mining with tidy information concepts
Julia Silge, co-writer of Text Mining with R, led this workshop. Her slides are at http://bit.ly/silge-rstudioconf-1 (Working day 1) and bit.ly/silge-rstudioconf-2 (Working day 2). The GitHub repo at https://github.com/rstudio-conf-2020/text-mining includes slides and R Markdown files with code.
Huge information analysis in R
This workshop, taught by RStudio engineer James Blair, targeted on working with dplyr with information.desk, databases, and Spark for substantial-scale information. It also used the vroom, dtplyr, and DBI deals.
The GitHub repo at https://github.com/rstudio-conf-2020/significant-data includes an intro, slides, and workbook listing with R Markdown files. The workshop workout routines and code are also available as on online book at https://rstudio-conf-2020.github.io/significant-information/introduction-to-vroom.html.
Shiny from start off to complete
If you’ve wanted to learn the Shiny R interactive internet framework — or if you’ve worked with it but wanted to up your game — Macalester Higher education professor Danny Kaplan’s Shiny workshop GitHub repository features slides and task code. You can also clone the task with a no cost RStudio Cloud account at https://rstudio.cloud/task/865256.
In addition to the workshop GitHub repo, there is a js4shiny.com website that is absolutely truly worth a take a look at.
R Markdown and interactive dashboards
This two-working day workshop by Yihui Xie (creator of several R deals such as knitr and DT and the co-writer of Shiny, R Markdown, and leaflet) and RStudio instruction director Carl Howe was aimed at serving to attendees make highly effective interactive files and dashboards.
The aims, in accordance to the workshop description, integrated the next:
- The full abilities of R Markdown
- How to parameterize and publish studies from R Markdown
- How to make interactive dashboards working with htmlwidgets and Shiny
The workshop GitHub repo at https://github.com/rstudio-conf-2020/rmarkdown-dashboard includes a products listing with slides, workout routines, cheat sheets, and a lot more.
What they forgot to teach you about R
It seems like an introductory workshop, but this was actually “designed for seasoned R and RStudio consumers who want to (re)design their R life style,” in accordance to the session overview. “You’ll learn holistic workflows that tackle the most popular sources of friction in information analysis. We’ll function on task-oriented workflows, model management for information science (Git/GitHub), and how to approach for collaboration, interaction, and iteration (such as R Markdown).” Instructors Kara Woo, Jenny Bryan, and Jim Hester are all perfectly-recognized in the tidyverse world.
Come across the GitHub repository at https://github.com/rstudio-conf-2020/what-they-forgot and “the one genuine URL that inbound links to all the things!” at https://rstd.io/wtf-2020-rsc.
Creating tidy instruments
Taught by Charlotte Wickham and Hadley Wickham, this workshop was aimed at “those who have embraced the tidyverse and now want to extend it to satisfy their individual wants,” in accordance to the workshop overview. It discusses API design, practical programming instruments, the basics of object design in Amazon S3, and the tidy eval procedure for non-typical evaluation.
There is a GitHub repo with slides, R Markdown files, and a lot more.
A simple introduction to information visualization with ggplot2
This workshop included “basic concepts guiding productive information visualizations” as perfectly as discovering how to develop fantastic graphics with ggplot2. It was taught by Duke College professor Kieran Healy, writer of Facts Visualization: A Functional Introduction. The workshop repo is at https://github.com/rstudio-conf-2020/dataviz.
My organization’s to start with R bundle
If you’re fascinated in generating deals at your place of work for “easier information accessibility, shared functions for information transformation and analysis, and a popular search and feel for reporting,” you could want to look at out this workshop products by software engineer Prosperous Iannone and R developer and Ph.D. college student Malcolm Barrett.
You can find the GitHub repo at https://github.com/rstudio-conf-2020/my-org-to start with-pkg.
Workshops for R newbies
R for Excel Users was, not amazingly, a workshop aimed at electrical power Excel consumers who want to start off incorporating R into their workflow.
And Introduction to Facts Science in the Tidyverse, taught by Hadley Wickham and Amelia McNamara, was a “two-working day, hands-on workshop created for people who are brand new to R and RStudio.”