We are excited to announce the general availability of RStudio Server Pro 1.2, and to introduce RStudio Server Pro Standard and RStudio Server Pro Enterprise. RStudio customers have made it clear to us that the future of data analysis is moving to a more elastic and flexible computational model. RStudio Server Pro now allows you to execute R processes remotely, and introduces new packaging and pricing to reflect this new trend. Read more →

RStudio is excited to announce RStudio Team, a new software bundle that makes it easier and more economical to adopt our commercially licensed and supported professional offerings. RStudio Team includes RStudio Server Pro, RStudio Connect, and RStudio Package Manager. With RStudio Team, your data science team will be properly equipped to analyze data at scale using R and Python; manage R packages; and create and share plots, Shiny apps, R Markdown documents, REST APIs (with plumber), and even Jupyter Notebooks, with your entire organization. Read more →

We're excited to announce the official release of RStudio 1.2! What’s new in RStudio 1.2? Over a year in the making, this new release of RStudio includes dozens of new productivity enhancements and capabilities. You’ll now find RStudio a more comfortable workbench for working in SQL, Stan, Python, and D3. Testing your R code is easier, too, with integrations for shinytest and testthat. Create, and test, and publish APIs in R with Plumber. Read more →

We’re excited to announce the release of Shiny v1.3.2. This release has two main features: a new reactivity debugging tool we call reactlog, and much faster serving of static file assets. Introducing reactlog: Visually debug your reactivity issues Debugging faulty reactive logic can be challenging, as we’ve written and talked about in the past. In particular, some of the most difficult Shiny app bugs to track down are when reactive expressions and observers re-execute either too often (i. Read more →

Installing R packages on Linux systems has always been a risky affair. In RStudio Package Manager 1.0.8, we’re giving administrators and R users the information they need to make installing packages easier. We’ve also made it easier to use Package Manager offline and improved search performance. New to RStudio Package Manager? Download the 45-day evaluation today to see how RStudio Package Manager can help you, your team, and your entire organization access and organize R packages. Read more →

Back in January we announced the first Shiny contest. The time has come to share the results with you! First and foremost, we were overwhelmed (in the best way possible!) by the 136 submissions! Reviewing all these submissions was incredibly inspiring and humbling. We really appreciate the time and effort each contestsant put into building these apps, as well as submitting them as a fully reproducible artifacts via RStudio Cloud. Read more →

We received almost 400 applications for our 2019 internship program from students with very diverse backgrounds. After interviewing several dozen people and making some very difficult decisions, we are pleased to announce that these twelve interns have accepted positions with us for this summer: Therese Anders: Calibrated Peer Review. Prototype tools to conduct experiments to see whether calibrated peer review is a useful and feasible feedback strategy in introductory data science classes and industry workshops. Read more →

RStudio Connect 1.7.2 is ready to download, and this release contains some long-awaited functionality that we are excited to share. Several authentication and user-management tooling improvements have been added, including the ability to change authentication providers on an existing server, new group support options, and the official introduction of SAML as a supported authentication provider (currently a beta feature*). But that’s not all… keep reading to learn about great additions to the RStudio Connect UI, updates to Python support, and a brand new Admin dashboard view for tracking scheduled content. Read more →

With much excitement built over the past three years, we are thrilled to share that sparklyr 1.0 is now available on CRAN! The sparklyr package provides an R interface to Apache Spark. It supports dplyr, MLlib, streaming, extensions and many other features; however, this particular release enables the following new features: Arrow enables faster and larger data transfers between Spark and R. XGBoost enables training gradient boosting models over distributed datasets. Read more →

When you run an R script in RStudio today, the R console waits for it to complete, and you can’t do much with RStudio until the script is finished running. When your R scripts take a long time to run, it can be difficult to get much done in RStudio while they do, unless you’re willing to juggle multiple instances of RStudio. In RStudio 1.2, we’re introducing two new features to keep you productive while your code’s working: local jobs and remote jobs. Read more →