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Update Nov 2 2015: Wow, that was fast. Registration is full. If you add yourself to the waitlist, we’ll contact you first if/when we do this conference again.
In the three years since we launched Shiny, our focus has been on helping people get started with Shiny. But there’s a huge difference between using Shiny and using it well, and we want to start getting serious about helping people use Shiny most effectively. It’s the difference between having apps that merely work, and apps that are performant, robust, and maintainable.
That’s why RStudio is thrilled to announce the first ever Shiny Developer Conference, to be held at Stanford University on January 30-31, 2016, three months from today. We’ll skip past the basics, and dig into principles and practices that will simultaneously simplify and improve the robustness of your code. We’ll introduce you to some brand new tools we’ve created to help you build ever larger and more complex apps. And we’ll show you what to do if things go wrong.
Check out the agenda to see the complete lineup of speakers and talks.
We’re capping the conference at just 90 people, so if you’d like to level up your Shiny skills, register now at http://shiny2016.eventbrite.com.
Hope to see you there!
Note that this conference is intended for R users who are already comfortable writing Shiny apps. We won’t cover the basics of Shiny app creation at all. If you’re looking to get started with Shiny, please see our tutorial.
RStudio will again teach the new essentials for doing (big) data science in R at this year’s Strata NYC conference, September 29 2015 (http://strataconf.com/big-data-conference-ny-2015/public/schedule/detail/44154). You will learn from Garrett Grolemund, Yihui Xie, and Nathan Stephens who are all working on fascinating new ways to keep the R ecosystem apace of the challenges facing those who work with data.
- R Quickstart: Wrangle, transform, and visualize data
Instructor: Garrett Grolemund (90 minutes)
- Work with Big Data in R
Instructor: Nathan Stephens (90 minutes)
- Reproducible Reports with Big Data
Instructor: Yihui Xie (90 minutes)
- Interactive Shiny Applications built on Big Data
Instructor: Garrett Grolemund (90 minutes)
If you plan to stay for the full Strata Conference+Hadoop World be sure to look us up at booth 633 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! (http://strataconf.com/big-data-conference-ny-2015)
Five months ago we launched shinyapps.io. Since then, more than 25,000 accounts have been created and countless Shiny applications have been deployed. It’s incredibly exciting to see!
It’s also given us lots of data and feedback on how we can make shinyapps.io better. Today, we’re happy to tell you about some changes to our subscription Plans that we hope will make shinyapps.io an even better experience for Shiny developers and their application users.
New Starter Plan – More active hours and apps, less money
For many people the price difference between the Free and the Basic plan was too much. We heard you. Effective today there is a new Starter Plan for only $9 per month or $100 per year. The Starter Plan has the same features as the Free plan but allows 100 active hours per month and up to 25 applications. It’s perfect for the active Shiny developer on a budget!
More Active Hours for Basic, Standard, and Professional Plans
Once you’re up and running with Shiny we want to make sure even the most prolific developers and popular applications have the active hours they need. Today we’re doubling the number of active hours per month for the Basic (now 500), Standard (now 2,000), and Professional (now 10,000) plans. In practice, very few accounts exceeded the old limits for these plans but now you can be sure your needs are covered.
New Performance Boost features for the Basic Plan
In addition to supporting multiple R worker processes per application, which keeps your application responsive as more people use it, we’ve added more memory (up to 8GB) on Basic plans and above. While the data shows that most applications work fine without these enhancements, if you expect many users at the same time or your application is memory or CPU intensive, the Basic Plan has the performance boost you need. The Basic plan also allows unlimited applications and 500 active hours per month.
Traditionally, the mechanisms for obtaining R and related software have used standard HTTP connections. This isn’t ideal though, as without a secure (HTTPS) connection there is less assurance that you are downloading code from a legitimate source rather than from another server posing as one.
Recently there have been a number of changes that make it easier to use HTTPS for installing R, RStudio, and packages from CRAN:
- Downloads of R from the main CRAN website now use HTTPS;
Downloads of RStudio from our website now use HTTPS; and
It is now possible to install packages from CRAN over HTTPS.
There are a number of ways to ensure that installation of packages from CRAN are performed using HTTPS. The most recent version of R (v3.2.2) makes this the default behavior. The most recent version of RStudio (v0.99.473) also attempts to configure secure downloads from CRAN by default (even for older versions of R). Finally, any version of R or RStudio can use secure HTTPS downloads by making some configuration changes as described in the Secure Package Downloads for R article in our Knowledge Base.
Configuring Secure Connections to CRAN
While the simplest way to ensure secure connections to CRAN is to run the updated versions mentioned above, it’s important to note that it is not necessary to upgrade R or RStudio to achieve this end. Rather, two configuration changes can be made:
- The R
download.file.methodoption needs to specify a method that is capable of HTTPS; and
- The CRAN mirror you are using must be capable of HTTPS connections (not all of them are).
The specifics of the required changes for various products, platforms, and versions of R are described in-depth in the Secure Package Downloads for R article in our Knowledge Base.
Recommendations for RStudio Users
We’ve made several changes to RStudio IDE to ensure that HTTPS connections are used throughout the product:
- The default
download.file.methodoption is set to an HTTPS compatible method (with a warning displayed if a secure method can’t be set);
- The configured CRAN mirror is tested for HTTPS compatibility and a warning is displayed if the mirror doesn’t support HTTPS;
- HTTPS is used for user selection of a non-default CRAN mirror;
- HTTPS is used for in-product documentation links;
- HTTPS is used when checking for updated versions of RStudio (applies to desktop version only); and
- HTTPS is used when downloading Rtools (applies to desktop version only).
If you are running RStudio on the desktop we strongly recommend that you update to the latest version (v0.99.473).
Recommendations for Server Administrators
If you are running RStudio Server it’s possible to make the most important security enhancements by changing your configuration rather than updating to a new version. The Secure Package Downloads for R article in our Knowledge Base provides documentation on how do this.
In this case in-product documentation links and user selection of a non-default CRAN mirror will continue to use HTTP rather than HTTPS however these are less pressing concerns than CRAN package installation. If you’d like these functions to also be performed over HTTPS then you should upgrade your server to the latest version of RStudio.
If you are running Shiny Server we recommend that you modify your configuration to support HTTPS package downloads as described in the Secure Package Downloads for R article.
The Joint Statistics Meetings starting August 8 is the biggest meetup for statisticians in the world. Navigating the sheer quantity of interesting talks is challenging – there can be up to 50 sessions going on at a time!
To prepare for Seattle, we asked RStudio’s Chief Data Scientist Hadley Wickham for his top session picks. Here are 9 talks, admittedly biased towards R, graphics, and education, that really interested him and might interest you, too.
Check out these talks
Undergraduate Curriculum: The Pathway to Sustainable Growth in Our Discipline
Sunday, 1400-1550, CC-607
Statistics with Computing in the Evolving Undergraduate Curriculum
In these back to back sessions, learn how statisticians are rising to the challenge of teaching computing and big(ger) data.
Recent Advances in Interactive Graphics for Data Analysis
This is an exciting session discussing innovations in interactive visualisation, and it’s telling that all of them connect with R. Hadley will be speaking about ggvis in this session.
Preparing Students to Work in Industry
Monday, 1400-1550, CC-4C4
If you’re a student about to graduate, we bet there will be some interesting discussion for you here.
Stat computing and graphics mixer
Monday, 1800-2000, S-Ravenna
This is advertised as a business meeting, but don’t be confused. It’s the premier social event for anyone interested in computing or visualisation!
Statistical Computing and Graphics Student Paper Competition
Tuesday, 0830-1020, CC-308
Hear this year’s winners of the student paper award talk about visualising phylogenetic data, multiple change point detection, capture-recapture data and teaching intro stat with R. All four talks come with accompanying R packages!
The Statistics Identity Crisis: Are We Really Data Scientists?
Tuesday, 0830-1020, CC-609
This session, organised by Jeffrey Leek, features an all-star cast of Alyssa Frazee, Chris Volinsky, Lance Waller, and Jenny Bryan.
Doing Good with Data Viz
Wednesday, 0830-1020, CC-2B
Hear Jake Porway, Patrick Ball, and Dino Citraro talk about using data to do good. Of all the sessions, you shouldn’t miss, this is the one you really shouldn’t miss. (But unfortunately it conflicts with another great session – you have difficult choices ahead.)
Statistics at Scale: Applications from Tech Companies
Wednesday, 0830-1020, CC-204
Hilary Parker has organised a fantastic session where you’ll learn how companies like Etsy, Microsoft, and Facebook do statistics at scale. Get there early because this session is going to be PACKED!
There are hundreds of sessions at the JSM, so no doubt we’ve missed other great ones. If you think we’ve missed a “don’t miss” session, please add it to the comments so others can find it.
Visit RStudio at booth #435
In between session times you’ll find the RStudio team hanging out at booth #435 in the expo center (at the far back on the right). Please stop by and say hi! We’ll have stickers to show your R pride and printed copies of many of our cheatsheets.
See you in Seattle!
To paraphrase Yogi Berra, “Predicting is hard, especially about the future”. In 1993, when Ross Ihaka and Robert Gentleman first started working on R, who would have predicted that it would be used by millions in a world that increasingly rewards data literacy? It’s impossible to know where R will go in the next 20 years, but at RStudio we’re working hard to make sure the future is bright.
Today, we’re excited to announce our participation in the R Consortium, a new 501(c)6 nonprofit organization. The R Consortium is a collaboration between the R Foundation, RStudio, Microsoft, TIBCO, Google, Oracle, HP and others. It’s chartered to fund and inspire ideas that will enable R to become an even better platform for science, research, and industry. The R Consortium complements the R Foundation by providing a convenient funding vehicle for the many commercial beneficiaries of R to give back to the community, and will provide the resources to embark on ambitious new projects to make R even better.
We believe the R Consortium is critically important to the future of R and despite our small size, we chose to join it at the highest contributor level (alongside Microsoft). Open source is a key component of our mission and giving back to the community is extremely important to us.
The community of R users and developers have a big stake in the language and its long-term success. We all want free and open source R to continue thriving and growing for the next 20 years and beyond. The fact that so many of the technology industry’s largest companies are willing to stand behind R as part of the consortium is remarkable and we think bodes incredibly well for the future of R.
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