At useR! 2014, one of the most anticipated presentations was Joe Cheng’s Shiny: R made interactive. It was but one of the of a fantastic series of talks by RStudio representatives; check out Winston Chang’s ggvis: Interactive graphics in R for another great talk. Shiny begins with your R code and ends with the customer’s view: an interactive, browser-accessible application. This enables you to place a great deal of power into your users’ hands to customize their view and provides a variety of new and innovative ways to interact with the data, such as by tuning parameters and focusing on sub-populations. Essentially, Shiny functions by allowing you to “wire up” up a reactive application, greatly speeding up the development of a data and analysis based web app.
Shiny comes out of the box with a number of standard industry UI widgets such as date inputs, file inputs, sliders, buttons - the standard widget toolbox. Shiny also leverages a simple panel-based layout manager which, in concert with the widgets, allows for a fluid development experience.
Video Highlights#
If you’re interested in bypassing Joe Cheng’s fantastic explanation and you want to cut right to his first demo, he presents a web application for k-means clustering on the iris data set:
Joe’s next demo involves a slick mapping component. Here you begin to see how Shiny apps have the potential to leverage intriguing data sources and provide first rate visualizations beginning only with ZIP codes and a limited amount of R code:
He then shows an amazing example of what an R developer with no previous web development experience can build using Shiny.
For his final demo, Joe embeds Shiny interactive documents using R markdown and combines them with Yihui Xie’s knitR. This is demoed in the video below with an application which parses the logs for RStudio’s CRAN mirror and visualizes package download trends.
Shiny is a fun and easy way to widen the audience interacting with your data analyses. It leverages fantastic modern programming paradigms to provide a system with sane defaults and powerful components to interface the web with R. Enjoy!