In the morning, you’ll learn an easy workflow for documenting, code, analysis, and results, with R. We’ll start by writing reports with markdown, an easy to learn markup language, and then go on to cover the three main paradigms of reporting: dynamic documents, convertible formats, and interactive reports. In the afternoon, you will learn how to use the Shiny R package to build and style interactive apps that you can publish over the web.
Should I take this course?
This class will be a good fit for you if you have some experience programming in R already. You should have written a number of functions, and be comfortable with R’s basic data structures (vectors, matrices, arrays, lists, and data frames). Above all, you should feel comfortable debugging R's error messages.
If in doubt, you can assess whether you are ready for this course by taking the Shiny prerequisites quiz. Pay particular attention to the first three questions that involve error messages. If you have trouble answering these questions, you will likely find this course frustrating and fast-paced.
What should I bring?
- A laptop.
- The latest version of R.
- A recent version of the RStudio IDE. (Even if you don’t use it, you’ll want to experience it for package development.)
We’ll let know know what packages you need to install a few days before the class. At the course, you’ll download an (electronic) copy of all slides, code, and data.
Who will I learn from?
The class is taught by Garrett Grolemund. Garrett is the Editor-in-Chief of shiny.rstudio.com, the development center for the Shiny R package, and is the author of Hands-On Programming with R as well as Data Science with R, a forthcoming book by O’Reilly Media. Garrett works as a Data Scientist and Chief Instructor for RStudio, Inc.
How is the course organised?
The course contains four modules that are organized around warm ups, instruction, and hands on coding exercises.
Reports - The day starts with some warmups to get your brain in R-mode, and to make sure your foundations are solid. Then you'll learn a new way to write R code, in an R Markdown file. These files are the lingua franca of reporting in R. You can run them as normal R code, compile them into reports that include the results of your code, and export them into a variety of formats, including pdfs, word documents, and slide shows. In this module, you will learn to
- Write in markdown
- Embed code chunks into R Markdown files
- Convert file types
Interactivity - After you get comfortable with R Markdown, you will learn how to make your files interactive, allowing your readers to explore your data and to test out your code. You'll learn how to
- Add interactive widgets to your reports
- Create tables and graphs to display
- Streamline how your report handles interactions
- Refactor your code into a standalone app
- Customize the layout of your app
- Polish the appearance of your app
Share - At the end of the day, you will learn how to deploy your finished products to the web, or to embed them inside of R. We'll cover three tools that can help you do this quickly and with no hassle:
Is Seattle too far?
We're holding the same workshop in six cities across the country this spring. Consider attending on one of the dates and places below.
- March 2 - Washington, DC
- March 4 - New York, NY
- March 6 - Boston, MA
- April 15 - Los Angeles, CA
- April 17 - San Francisco, CA
- April 20 - Seattle, WA
In certain cases, we may need to cancel this workshop due to circumstances beyond our control or otherwise. If this happens, RStudio will refund all registration fees for those who signed up. RStudio is not responsible for any related expenses incurred by registered attendees (including but not limited to travel and hotel expenses).
More than 2 weeks before course: full refund, less 10% adminstrative fee.
1-2 weeks before course: 50% refund.
Less than 1 week before course: no refund available
All public workshops hosted by RStudio come with a no-questions-asked money-back guarantee.
There are no student discounts for this workshop. Please contact Elizabeth Oberg with questions.
When & Where
RStudio™ offers open source and enterprise-ready professional software packages and products for R. The free RStudio integrated development environment (IDE), Shiny interactive application framework, and R Markdown reproducible reporting package, are just a few of the many popular tools we provide to make using R a better experience. Please contact us at http://www.rstudio.com to learn how RStudio Server Pro and Shiny Server Pro can give your organization the professional environment R developers need to deliver the interactive dashboards, applications and reporting experiences business users want.