Presented By O'Reilly and Cloudera
Make Data Work
5–7 May, 2015 • London, UK

Reproducible research with R and Shiny

Garrett Grolemund (RStudio), Colin Gillespie (Jumping Rivers | Newcastle University)
13:30–17:00 Tuesday, 5/05/2015
Data Science
Location: St. James / Regents
Average rating: ***..
(3.75, 4 ratings)

Prerequisite Knowledge

Students should have a basic familiarity with R, I'll teach the rest. If you know how to create an object, write a function, and use the $ you will be good to go.

Materials or downloads needed in advance

Please take a moment **before** you arrive at the workshop to install the most up-to-date versions of the software that we will use on your laptop:
  1. R
    Please ensure that you have R version 3.2.0 installed on your laptop. You can download R for free at:
  2. RStudio
    Please download and install the RStudio Desktop IDE version 0.98.1103 or higher, which can be downloaded for free at:
  3. shiny, rmarkdown, and packrat R packages
    Please install the most up to date versions of the shiny, rmarkdown, and packrat packages. To do this, connect to the internet, open RStudio and run install.packages(c("shiny", "rmarkdown", "packrat"))
  4. The reportsWS R package
    Please install the reportsWS package, which contains many of the exercises that we will work on. The package is hosted on github, not CRAn. You can download it by opening RStudio, connecting to the internet, and running the following two commands in order:
    • install.packages("devtools")
    • devtools::install_github("rstudio/reportsWS")

If you are a Windows user, please disregard any warnings that appear about RTools.


Learn how to combine the best ideas of reproducible research into a simple, easy to use workflow with R. Do you know that R can do more than analyze your data? R provides an easy way to report your results and make your research reproducible. This tutorial will teach you how to use R’s reporting power with three R packages:

The Packrat package automatically captures the dependencies of your code when you run it, making sure that you can exactly reproduce results in the future. With Packrat, you can always rerun your script in its original computing environment, even if the packages used by your script have been replaced or updated.

The R Markdown package builds dynamic documents, presentations, and reports straight from your code. It combines the core syntax of markdown (an easy-to-write plain text format) with embedded R code chunks that are run so their output can be included in the final document. R Markdown documents are fully reproducible (they can be automatically regenerated whenever underlying R code or data changes) and completely dynamic (you can export an R Markdown document as an html, pdf, or MS Word file, or a slide show).

The Shiny package creates an interactive dashboard for your analyses. With Shiny, you can let readers use your reports to explore, customize, and stress test your results. Readers can modify parameters, update data sets, and make other changes that will immediately propagate through the models, tables, and plots of your report.

Together these packages create a reporting pipeline that makes it easy to reproduce your research and communicate your results in an engaging way. We will examine this pipeline and practice using it with a series of exercises and instructor-led examples.

Photo of Garrett Grolemund

Garrett Grolemund


Garrett is the editor-in-chief of, 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.

Photo of Colin Gillespie

Colin Gillespie

Jumping Rivers | Newcastle University

Colin Gillespie is a statistician and an associate professor at Newcastle University, UK, where he works on computational statistics, big data problems, and scalable Bayesian inference. He has taught courses on R for over ten years, attracting participants from around the world.

Comments on this page are now closed.


Picture of Garrett Grolemund
Garrett Grolemund
1/05/2015 20:56 BST

I look forward to seeing everyone at the workshop.

I’ve had trouble updating the pre-requisites section on the website, so please take amoment and follow these steps to set up your laptop:

Please bring a laptop that has the latest versions of R and RStudio, as well as the latest versions of the reportsWS, rmarkdown, packrat, and shiny R packages.

You can download R from, RStudio from, and you can install the R packages by opening RStudio and running: install.packages(c(“rmarkdown”, “packrat”, “shiny”, “devtools”)). And then running: devtools::install_github(“rstudio/reportsWS”). If you are a Windows user, please disregard any warnings that appear about RTools.

See you soon.

Picture of Garrett Grolemund
Garrett Grolemund
13/04/2015 14:04 BST

Chris, Yes. Please bring a laptop with R, RStudio and each of the packages above installed (rmarkdown, packrat, shiny). This will be a hands on Worskshop!

Chris Webster
7/04/2015 13:38 BST

Question on R tutorial: Do participants in this tutorial need to bring a laptop?