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We’re pleased to announce that the final version of RStudio v0.99 is available for download now. Highlights of the release include:
- A new data viewer with support for large datasets, filtering, searching, and sorting.
- Complete overhaul of R code completion with many new features and capabilities.
- The source editor now provides code diagnostics (errors, warnings, etc.) as you work.
- User customizable code snippets for automating common editing tasks.
- Tools for Rcpp: completion, diagnostics, code navigation, find usages, and automatic indentation.
- Many additional source editor improvements including multiple cursors, tab re-ordering, and several new themes.
- An enhanced Vim mode with visual block selection, macros, marks, and subset of : commands.
There are also lots of smaller improvements and bug fixes across the product. Check out the v0.99 release notes for details on all of the changes.
We’ve completely overhauled the data viewer with many new capabilities including live update, sorting and filtering, full text searching, and no row limit on viewed datasets.
See the data viewer documentation for more details.
Previously RStudio only completed variables that already existed in the global environment. Now completion is done based on source code analysis so is provided even for objects that haven’t been fully evaluated:
Completions are also provided for a wide variety of specialized contexts including dimension names in [ and [[:
We’ve added a new inline code diagnostics feature that highlights various issues in your R code as you edit.
For example, here we’re getting a diagnostic that notes that there is an extra parentheses:
Here the diagnostic indicates that we’ve forgotten a comma within a shiny UI definition:
Code snippets are text macros that are used for quickly inserting common snippets of code. For example, the
fun snippet inserts an R function definition:
If you select the snippet from the completion list it will be inserted along with several text placeholders which you can fill in by typing and then pressing Tab to advance to the next placeholder:
Other useful snippets include:
sourcefor the library, require, and source functions
matfor defining data frames and matrices
eifor conditional expressions
sapply, etc. for the apply family of functions
sgfor defining S4 classes/methods.
See the code snippets documentation for additional details.
Try it Out
RStudio is excited to announce the general availability (GA) of shinyapps.io.
Shinyapps.io is an easy to use, secure, and scalable hosted service already being used by thousands of professionals and students to deploy Shiny applications on the web. Effective today, shinyapps.io has completed beta testing and is generally available as a commercial service for anyone.
As regular readers of our blog know, Shiny is a popular free and open source R package from RStudio that simplifies the creation of interactive web applications, dashboards, and reports. Until today, Shiny Server and Shiny Server Pro were the most popular ways to share shiny apps. Now, there is a commercially supported alternative for individuals and groups who don’t have the time or resources to install and manage their own servers.
We want to thank the nearly 8,000 people who created at least one shiny app and deployed it on shinyapps.io during its extensive alpha and beta testing phases! The service was improved for everyone because of your willingness to give us feedback and bear with us as we continuously added to its capabilities.
For R users developing shiny applications that haven’t yet created a shinyapps.io account, we hope you’ll give it a try soon! We did our best to keep the pricing simple and predictable with Free, Basic, Standard, and Professional plans. Each paid plan has features and functionality that we think will appeal to different users and can be purchased with a credit card by month or year. You can learn more about shinyapps.io pricing plans and product features on our website.
We hope to see your shiny app on shinyapps.io soon!
Sometimes the universe surprises us. In this case, it was in a good way and we genuinely appreciated it.
Earlier this week we learned that the Infoworld Testing Center staff selected RStudio as one of 32 recipients of the 2015 Technology of the Year Award.
We thought it was cool because it was completely unsolicited, we’re in very good company (some of our favorite technologies like Docker, Github, node.js…even my Dell XPS 15 Touch!…were also award winners) and the description of our products was surprisingly elegant – simple and accurate.
We know Infoworld wouldn’t have known about us if our customers hadn’t brought us to their attention.
Great news for Shiny and R Markdown enthusiasts!
An Interactive Reporting Workshop with Shiny and R Markdown is coming to a city near you. Act fast as only 20 seats are available for each workshop.
You can find out more / register by clicking on the link for your city!
|East Coast||West Coast|
|March 2 – Washington, DC||April 15 – Los Angeles, CA|
|March 4 – New York, NY||April 17 – San Francisco, CA|
|March 6 – Boston, MA||April 20 – Seattle, WA|
You’ll want to take this workshop if…
You have some experience working with 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).
You will learn from…
The workshop is taught by Garrett Grolemund. Garrett is the Editor-in-Chief of shiny.rstudio.com, the development center for the Shiny R package. He is also 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. GitHub
Shiny version 0.11 is available now! Notable changes include:
- Shiny has migrated from Bootstrap 2 to Bootstrap 3 for its web front end. More on this below.
- The old jsliders have been replaced with ion.rangeSlider. These sliders look better, are easier for users to interact with, and support updating more fields from the server side.
- There is a new
passwordInput()which can be used to create password fields.
eventReactive()functions greatly streamline the use of
actionButtonand other inputs that act more like events than reactive inputs.
For a full set of changes, see the NEWS file. To install, run:
We’ve also posted an article with notes on upgrading to 0.11.
Bootstrap 3 migration
In all versions of Shiny prior to 0.11, Shiny has used the Bootstrap 2 framework for its web front-end. Shiny generates HTML that is structured to work with Bootstrap, and this makes it easy to create pages with sidebars, tabs, dropdown menus, mobile device support, and so on.
The Bootstrap development team stopped development on the Bootstrap 2 series after version 2.3.2, which was released over a year ago, and has since focused their efforts on Bootstrap 3. The new version of Bootstrap builds on many of the same underlying ideas, but it also has many small changes – for example, many of the CSS class names have changed.
In Shiny 0.11, we’ve moved to Bootstrap 3. For most Shiny users, the transition will be seamless; the only differences you’ll see are slight changes to fonts and spacing.
If, however, you customized any of your code to use features specific to Bootstrap 2, then you may need to update your code to work with Bootstrap 3 (see the Bootstrap migration guide for details). If you don’t want to update your code right away, you can use the shinybootstrap2 package for backward compatibility with Bootstrap 2 – using it requires adding just two lines of code. If you do use shinybootstrap2, we suggest using it just as an interim solution until you update your code for Bootstrap 3, because Shiny development going forward will use Bootstrap 3.
Why is Shiny moving to Bootstrap 3? One reason is support: as mentioned earlier, Bootstrap 2 is no longer developed and is no longer supported. Another reason is that there is dynamic community of actively-developed Bootstrap 3 themes. (Themes for Bootstrap 2 also exist, but there is less development activity.) Using these themes will allow you to customize the appearance of a Shiny app so that it doesn’t just look like… a Shiny app.
We’ve also created a package that make it easy to use Bootstrap themes: shinythemes. Here’s an example using the included Flatly theme:
See the shinythemes site for more screenshots and instructions on how to use it.
The shinydashboard package still under development, but feel free to try it out and give us feedback.
As R users know, we’re continuously improving the RStudio IDE. This includes RStudio Server Pro, where organizations who want to deploy the IDE at scale will find a growing set of features recently enhanced for them.
If you’re not already familiar with RStudio Server Pro here’s an updated summary page and a comparison to RStudio Server worth checking out. Or you can skip all of that and download a free 45 day evaluation right now!
WHAT’S NEW IN RSTUDIO SERVER PRO (v0.98.1091)
Naturally, the latest RStudio Server Pro has all of the new features found in the open source server version of the RStudio IDE. They include improvements to R Markdown document and Shiny app creation, making R package development easier, better debugging and source editing, and support for Internet Explorer 10 and 11 and RHEL 7.
Recently, we added even more powerful features exclusively for RStudio Server Pro:
- Load balancing based on factors you control. Load balancing ensures R users are automatically assigned to the best available server in a cluster.
- Flexible resource allocation by user or group. Now you can allocate cores, set scheduler priority, control the version(s) of R and enforce memory and CPU limits.
- New security enhancements. Leverage PAM to issue Kerberos tickets, move Google Accounts support to OAuth 2.0, and allow administrators to disable access to various features.
For a full list of what’s changed in more depth, make sure to read the RStudio Server Pro admin guide.
THE RSTUDIO SERVER PRO BASICS
In addition to the newest features above there are many more that make RStudio Server Pro an upgrade to the open source IDE. Here’s a quick list:
- An administrative dashboard that provides insight into active sessions, server health, and monitoring of system-wide and per-user performance and resources
- Authentication using system accounts, ActiveDirectory, LDAP, or Google Accounts
- Full support for the Pluggable Authentication Module (PAM)
- HTTP enhancements add support for SSL and keep-alive for improved performance
- Ability to restrict access to the server by IP
- Customizable server health checks
- Suspend, terminate, or assume control of user sessions for assistance and troubleshooting
That’s a lot to discover! Please download the newest version of RStudio Server Pro and as always let us know how it’s working and what else you’d like to see.
RStudio is happy to announce the availability of the shinyapps.io beta.
Shinyapps.io is an easy to use, secure, and scalable hosted service already being used by thousands of professionals and students to deploy Shiny applications on the web. Today we are releasing a significant upgrade as we transition from alpha to beta, the final step before general availability (GA) later this quarter.
New Feature Highlights in shinyapps.io beta
- Secure and manage authorized users with support for new authentication systems, including Google, GitHub, or a shinyapps.io account.
- Tune application performance by controlling the resources available. Run multiple R processes per application instance and add application instances.
- Track performance metrics and simplify application management in a new shinyapps.io dashboard. See an application’s active connections, CPU, memory, and network usage. Review application logs, start, stop, restart, rebuild and archive applications all from one convenient place.
During the beta period, these and all other features in shinyapps.io are available at no charge. At the end of the beta, users may subscribe to a plan of their choice or transition their applications to the free plan.
If you do not already have an account, we encourage anyone developing Shiny applications to consider shinyapps.io beta and appreciate any and all feedback on our features or proposed packaging and pricing.
Happy New Year!
An htmlwidget works just like an R plot except it produces an interactive web visualization. A line or two of R code is all it takes to produce a D3 graphic or Leaflet map. Widgets can be used at the R console as well as embedded in R Markdown reports and Shiny web applications. Here’s an example of using leaflet directly from the R console:
When printed at the console the leaflet widget displays in the RStudio Viewer pane. All of the tools typically available for plots are also available for widgets, including history, zooming, and export to file/clipboard (note that when not running within RStudio widgets will display in an external web browser).
Here’s the same widget in an R Markdown report. Widgets automatically print as HTML within R Markdown documents and even respect the default knitr figure width and height.
Widgets also provide Shiny output bindings so can be easily used within web applications. Here’s the same widget in a Shiny application:
The htmlwidgets framework is a collaboration between Ramnath Vaidyanathan (rCharts), Kenton Russell (Timely Portfolio), and RStudio. We’ve all spent countless hours creating bindings between R and the web and were motivated to create a framework that made this as easy as possible for all R developers.
Here are a few widget libraries that have been built so far:
- leaflet, a library for creating dynamic maps that support panning and zooming, with various annotations like markers, polygons, and popups.
- dygraphs, which provides rich facilities for charting time-series data and includes support for many interactive features including series/point highlighting, zooming, and panning.
- networkD3, a library for creating D3 network graphs including force directed networks, Sankey diagrams, and Reingold-Tilford tree networks.
- DataTables, which displays R matrices or data frames as interactive HTML tables that support filtering, pagination, and sorting.
- rthreejs, which features 3D scatterplots and globes based on WebGL.
All of these libraries combine visualization with direct interactivity, enabling users to explore data dynamically. For example, time-series visualizations created with dygraphs allow dynamic panning and zooming:
To learn more about the framework and see a showcase of the available widgets in action check out the htmlwidgets web site. To learn more about building your own widgets, install the htmlwidgets package from CRAN and check out the developer documentation.
RStudio has teamed up with O’Reilly media to create a new way to learn R!
The Introduction to Data Science with R video course is a comprehensive introduction to the R language. It’s ideal for non-programmers with no data science experience or for data scientists switching to R from Excel, SAS or other software.
Join RStudio Master Instructor Garrett Grolemund as he covers the three skill sets of data science: computer programming (with R), manipulating data sets (including loading, cleaning, and visualizing data), and modeling data with statistical methods. You’ll learn R’s syntax and grammar as well as how to load, save, and transform data, generate beautiful graphs, and fit statistical models to the data.
All of the techniques introduced in this video are motivated by real problems that involve real datasets. You’ll get plenty of hands-on experience with R (and not just hear about it!), and lots of help if you get stuck.
You’ll also learn how to use the ggplot2, reshape2, and dplyr packages.
The course contains over eight hours of instruction. You can access the first hour free from O’Reilly’s website. The course covers the same content as our two day Introduction to Data Science with R workshop, right down to the same exercises. But unlike our workshops, the videos are self-paced, which can help you learn R in a more relaxed way.
To learn more, visit Introduction to Data Science with R.
Are you headed to Strata? It’s just around the corner!
We particularly hope to see you at R Day on October 15, where we will cover a raft of current topics that analysts and R users need to pay attention to. The R Day tutorials come from Hadley Wickham, Winston Chang, Garrett Grolemund, J.J. Allaire, and Yihui Xie who are all working on fascinating new ways to keep the R ecosystem apace of the challenges facing those who work with data.
If you plan to stay for the full Strata Conference+Hadoop World be sure to look us up in the Innovator Pavilion booth P14 during the Expo Hall hours. We’ll have the latest books from RStudio authors and “shiny” t-shirts to win. Share with us what you’re doing with RStudio and get your product and company questions answered by RStudio employees.
See you in New York City!