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The JSM conference in Chicago, July 31 thru August 4, 2016, is one of the largest to be found on statistics, with many terrific talks for R users. We’ve listed some of the sessions that we’re particularly excited about below. These include talks from RStudio employees, like Hadley Wickham, Yihui Xie, Mine Cetinkaya-Rundel, Garrett Grolemund, and Joe Cheng, but also include a bunch of other talks about R that we think look interesting.

When you’re not in one of the sessions below, please visit us in the exhibition area, booth #126-128. We’ll have copies of all our cheat sheets and stickers, and it’s a great place to learn about the other stuff we’ve been working on lately:  from Sparklyr and R Markdown Notebooks to the latest in RStudio Server Pro, Shiny Server Pro, shinyapps.io, RStudio Connect (beta) and more!

Another great place to chat with people interested in R is the Statistical Computing and Graphics Mixer at 6pm on Monday in the Hilton Stevens Salon A4. It’s advertised as a business meeting in the program, but don’t let that put you off – it’s open to all.

SUNDAY

Session 21: Statistical Computing and Graphics Student Awards
Sunday, July 31, 2016 : 2:00 PM to 3:50 PM, CC-W175b

Session 47 Making the Most of R Tools
Hadley Wickham, RStudio (Discussant)
Sunday, July 31, 2016: 4:00 PM to 4:50 PM, CC-W183b

Thinking with Data Using R and RStudio: Powerful Idioms for Analysts
Nicholas Jon Horton, Amherst College; Randall Pruim, Calvin College ; Daniel Kaplan, Macalester College
Transform Your Workflow and Deliverables with Shiny and R Markdown
Garrett Grolemund, RStudio

Session 54 Recent Advances in Information Visualization
Yihui Xie, RStudio (organizer)
Sunday, July 31, 2016: 4:00 PM to 4:50 PM, CC-W183c

Session 85 Reproducibility Promotes Transparency, Efficiency, and Aesthetics
Richard Schwinn
Sunday, July 31, 2016 : 5:35 PM to 5:50 PM, CC-W176a

Session 88 Communicate Better with R, R Markdown, and Shiny
Garrett Grolemund, RStudio (Poster Session)
Sunday, July 31, 2016: 6:00 PM to 8:00 PM, CC-Hall F1 West

MONDAY

Session 106  Linked Brushing in R
Hadley Wickham, RStudio
Monday, August 1, 2016 : 8:35 AM to 8:55 AM, CC-W196b

Session 127 R Tools for Statistical Computing
Monday, August 1, 2016 : 8:30 AM to 10:20 AM, CC-W196c

8:35 AM The Biglasso Package: Extending Lasso Model Fitting to Big Data in R — Yaohui Zeng, University of Iowa ; Patrick Breheny, University of Iowa
8:50 AM Independent Sampling for a Spatial Model with Incomplete Data — Harsimran Somal, University of Iowa ; Mary Kathryn Cowles, University of Iowa
9:05 AM Introduction to the TextmineR Package for R — Thomas Jones, Impact Research
9:20 AM Vector-Generalized Time Series Models — Victor Miranda Soberanis, University of Auckland ; Thomas Yee, University of Auckland
9:35 AM New Computational Approaches to Large/Complex Mixed Effects Models — Norman Matloff, University of California at Davis
9:50 AM Broom: An R Package for Converting Statistical Modeling Objects Into Tidy Data Frames — David G. Robinson, Stack Overflow
10:05 AM Exact Parametric and Nonparametric Likelihood-Ratio Tests for Two-Sample Comparisons — Yang Zhao, SUNY Buffalo ; Albert Vexler, SUNY Buffalo ; Alan Hutson, SUNY Buffalo ; Xiwei Chen, SUNY Buffalo

Session 270 Automated Analytics and Data Dashboards for Evaluating the Impacts of Educational Technologies
Daniel Stanhope and Joyce Yu and Karly Rectanus
Monday, August 1, 2016 : 3:05 PM to 3:50 PM, CC-Hall F1 West

TUESDAY

Session 276 Statistical Tools for Clinical Neuroimaging
Ciprian Crainiceanu
Tuesday, August 2, 2016 : 7:00 AM to 8:15 AM, CC-W375a

Session 332 Doing More with Data in and Outside the Undergraduate Classroom
Mine Cetinkaya-Rundel, Duke University (organizer)
Tuesday, August 2, 2016 : 10:30 AM to 12:20 PM, CC-W184bc

Session 407 Interactive Visualizations and Web Applications for Analytics
Tuesday, August 2, 2016 : 2:00 PM to 3:50 PM, CC-W179a

2:05 PM Radiant: A Platform-Independent Browser-Based Interface for Business Analytics in R — Vincent Nijs, Rady School of Management
2:20 PM Rbokeh: An R Interface to the Bokeh Plotting Library — Ryan Hafen, Hafen Consulting
2:35 PM Composable Linked Interactive Visualizations in R with Htmlwidgets and Shiny — Joseph Cheng, RStudio
2:50 PM Papayar: A Better Interactive Neuroimage Plotter in R — John Muschelli, The Johns Hopkins University
3:05 PM Interactive and Dynamic Web-Based Graphics for Data Analysis — Carson Sievert, Iowa State University
3:20 PM HTML Widgets: Interactive Visualizations from R Made Easy! — Yihui Xie, RStudio ; Ramnath Vaidyanathan, Alteryx

WEDNESDAY

Session 475  Steps Toward Reproducible Research
Yihui Xie, RStudio  (Discussant)
Wednesday, August 3, 2016 : 8:30 AM to 10:20 AM, CC-W196c

8:35 AM Reproducibility for All and Our Love/Hate Relationship with Spreadsheets — Jennifer Bryan, University of British Columbia
8:55 AM Steps Toward Reproducible Research — Karl W. Broman, University of Wisconsin – Madison
9:15 AM Enough with Trickle-Down Reproducibility: Scientists, Open This Gate! Scientists, Tear Down This Wall! — Karthik Ram, University of California at Berkeley
9:35 AM Integrating Reproducibility into the Undergraduate Statistics Curriculum — Mine Cetinkaya-Rundel, Duke University

Session 581 Mining Text in R
David Marchette, Naval Surface Warfare Center
Wednesday, August 3, 2016 : 2:05 PM to 2:40 PM, CC-W180

THURSDAY

Session 696 Statistics for Social Good
Hadley Wickham, RStudio (Chair)
Thursday, August 4, 2016 : 10:30 AM to 12:20 PM, CC-W179a

Session 694 Web Application Teaching Tools for Statistics Using R and Shiny
Jimmy Doi and Gail Potter and Jimmy Wong and Irvin Alcaraz and Peter Chi
Thursday, August 4, 2016 : 11:05 AM to 11:20 AM, CC-W192a

Following our initial and very gratifying Shiny Developer Conference this past January, which sold out in a few days, RStudio is very excited to announce a new and bigger conference today!

rstudio::conf, the conference about all things R and RStudio, will take place January 13 and 14, 2017 in Orlando, Florida. The conference will feature talks and tutorials from popular RStudio data scientists and developers like Hadley Wickham, Yihui Xie, Joe Cheng, Winston Chang, Garrett Grolemund, and J.J. Allaire, along with lightning talks from RStudio partners and customers.

Preceding the conference, on January 11 and 12, RStudio will offer two days of optional training. Training attendees can choose from Hadley Wickham’s Master R training, a new Intermediate Shiny workshop from Shiny creator Joe Cheng or a new workshop from Garrett Grolemund that is based on his soon-to-be-published book with Hadley: Introduction to Data Science with R.

rstudio::conf is for R and RStudio users who want to learn how to write better shiny applications in a better way, explore all the new capabilities of the R Markdown authoring framework, apply R to big data and work effectively with Spark, understand the RStudio toolchain for data science with R, discover best practices and tips for coding with RStudio, and investigate enterprise scale development and deployment practices and tools, including the new RStudio Connect.

Not to be missed, RStudio has also reserved Universal Studio’s The Wizarding World of Harry Potter on Friday night, January 13, for the exclusive use of conference attendees!

Conference attendance is limited to 400. Training is limited to 70 students for each of the three 2-day workshops. All seats are are available on a first-come, first-serve basis.

Please go to http://www.rstudio.com/conference to purchase.

We hope to see you in Florida at rstudio::conf 2017!

For questions or issues registering, please email conf@rstudio.com. To ask about sponsorship opportunities contact anne@rstudio.com.

RStudio is pleased to notify account holders of recent updates to shinyapps.io.

Note: Action is required if your shiny application URL includes internal.shinyapps.io

What’s New?

We have updated the authentication and invitation system to improve the user experience, security, and extensibility for anyone with private applications. You may have already noticed some changes to the authentication flow for your applications if you are a Standard or Professional account holder.

As a part of these changes, we have eliminated the IFRAME and the associated RStudio branding, except for customers using custom domains where the IFRAME is still required.

For customers on free plans, we will replace the RStudio branding bar with a softer, less intrusive branding overlay.

Possible Action Required

If you have used the provided URL from shinyapps.io for your shiny applications like most accounts, no action is needed. Your applications will simply benefit from the improvements.

If your shiny application URL begins with internal.shinyapps.io you must change it.

To complete the update we will SHUTDOWN all internal.shinyapps.io URLs on March 2, 2016. If you have publicly linked your application to internal.shinyapps.io or you have embedded applications on your website by directly referring to the internal.shinyapps.io URL, you MUST change your links to the URL you see in the shinyapps.io dashboard for your application.

While relatively few accounts are impacted and no action is required for most shinyapps.io users, if you have questions please contact shinyapps-support@rstudio.com.

Thank you all for your help and thanks for using shinyapps.io!

The RStudio shinyapps.io Team

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.

It’s time to share “What’s New” in shinyapps.io!

  • Custom Domainshost your shiny applications on your own domain (Professional Plan only).  Learn more.
  • Bigger applications – include up to 1GB of data with your application bundles!
  • Bigger packages – until now shinyapps.io could only support installation of packages under 100MB; now it’s 1GB! (attention users of BioConductor packages especially)
  • Better locale detection – the newest shinyapps package now detects and maps your locale appropriately if it varies from the locale of shinyapps.io  (you will need to update  your shinyapps package)
  • Application deletion – you can now delete applications permanently. First archive your application, then delete it. Note: Be careful; all deletes are permanent.
  • Transfer / Rename accounts – select a different name for your account or transfer control to another shinyapps.io account holder.
  • “What’s New” is New your dashboard displays the latest enhancements to shinyapps.io under…you guessed it… “What’s New”!

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!

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!

 

ShinyApps.io dashboard

Some of the most innovative Shiny apps share data across user sessions. Some apps share the results of one session to use in future sessions, others track user characteristics over time and make them available as part of the app.

This level of sophistication creates tricky design choices when you host your app on a server. A nimble server will open new instances of your app to speed up performance, or relaunch your app on a bigger server when it becomes popular. How should you ensure that your app can find and use its data trail along the way?

Shiny Server developer Jeff Allen explains the best ways to share data between sessions in Share data across sessions with ShinyApps.io, a new article at the Shiny Dev Center.

R Markdown’s new interactive documents provide a quick, light-weight way to use Shiny. An interactive document embeds Shiny elements in an R Markdown report. The report becomes “live”, a choose your own adventure that readers can control and explore. Interactive documents are easy to create and easy to share.

Create an interactive document

To create an interactive document use RStudio to create a new R Markdown file, choose the Shiny document template, then click “Run Document” to show a preview:

storms.002

Embed R code chunks in your report where you like. Interactive documents use the same syntax as R Markdown and knitr. Set echo = FALSE. Your reader won’t see the code, just its results.

 

  storms2.001

Include Shiny widgets and outputs in your code chunks. R Markdown will insert the widgets directly into your final document. When a reader toggles a widget, the parts of the document that depend on it will update instantly.

 storms.003

That’s it! No extra files are needed.

Note that in order to use interactive documents you should be running the latest version of RStudio (v0.98.932 or higher). Alternatively if you are not using RStudio be sure to follow the directions here to install all of the required components.

Share your document

Interactive documents can be run locally on the desktop or be deployed Shiny Server v1.2 or ShinyApps just like any other Shiny application. See the RMarkdown v2 website for more details on deploying interactive documents.

Use pre-packaged tools

Interactive documents make it easy to insert powerful tools into a report. For example, you can insert a kmeans clustering tool into your document with one line of code, as below. kmeans_cluster is a widget built from a Shiny app and intended for use in interactive documents.

storms.004

You can build your own widgets with shinyApp, a new function that repackages Shiny apps as functions. shinyApp is easy to use. Its first argument takes the code that appears in an app’s ui.R file. The second argument takes the code that appears in the app’s server.R file. The source of kmeans_cluster reveals how simple this is.

Be a hero

Ready to be a hero? You can use the `shinyApp` function to make out of the box widgets that students, teachers, and data scientists will use everyday. Widgets can

  • fit models
  • compare distributions
  • visualize data
  • demonstrate teaching examples
  • act as quizzes or multiple choice questions
  • and more

These widgets are not made yet, they are low hanging fruit for any Shiny developer. If you know how to program with Shiny (or want to learn), and would like to make your mark on R, consider authoring a package that makes widgets available for interactive documents.

Get started!

To learn more about interactive documents visit http://rmarkdown.rstudio.com/authoring_shiny.html.

 

We’re excited to introduce to you our new website for Shiny: shiny.rstudio.com!

shiny-rstudio-com

We’ve included articles on many Shiny-related topics, dozens of example applications, and an all-new tutorial for getting started.

Whether you’re a beginner or expert at Shiny, we hope that having these resources available in one place will help you find the information you need.

We’d also like to announce Shiny 0.9, now available on CRAN. This release includes many bug fixes and new features, including:

New application layout options

Until now, the vast majority of Shiny apps have used a sidebar-style layout. Shiny 0.9 introduces new layout features to:

  1. Make it easy to create custom page layouts using the Bootstrap grid system. See our new application layout guide or a live example.
  2. Provide navigation bars and lists for separating your application into different pages. See navbarPage and navlistPanel, and this example.
  3. Enhance tabsetPanel to allow pill-style tabs, and to let tabs be placed above, below, or to either side of tab content.
  4. Create floating panels and place them relative to the sides of the page, optionally making them draggable. See absolutePanel or this example.
  5. Use Bootstrap themes to easily modify the fonts and colors of your application. Example

You can see many of these features in action together in our reimplementation of the Washington Post’s interactive article on Super Zips.

Selectize.js integration

The JavaScript library selectize.js provides a much more flexible interface compared to the basic select input. It allows you to type and search in the options, use placeholders, control the number of options/items to show/select, and so on.

selectize

We have integrated selectize.js in shiny 0.9, and selectInput now creates selectize inputs by default. (You can revert back to plain select inputs by passing selectize=FALSE to selectInput.) For more advanced uses, we have included a new selectizeInput function that lets you pass options to selectize.

Please check out this example to see a subset of features of the selectize input. There is also an example comparing the select and selectize input.

Showcase mode

Shiny apps can now (optionally) run in a “showcase” mode in which the app’s R code can be automatically displayed within the app. Most of the Shiny example apps in our new gallery use showcase mode.

Showcase example

As you interact with the application, reactive expressions and outputs in server.R will light up as they execute. This can be helpful in visualizing the reactivity in your app.

See this article to learn more.

As always, you can install the latest release of Shiny by running this command at the R console:

install.packages("shiny")

The complete list of bug fixes and features is available in the NEWS file.

We hope you’ll find these new features helpful in exploring and understanding your data!