Shiny Server 1.5.7.907 and Shiny Server Pro 1.5.7.954 are now available. Highlights for this release are a major-version Node upgrade, support for HTTP gzip/deflate compression and (optionally) secure cookies, and numerous bug fixes. We’ve also dropped support for some Linux distro versions that have reached their end of life. Shiny Server 1.5.7.907 Upgrade to Node v8.10.0. Dropped support for Ubuntu 12.04 and SLES 11. Support gzip/deflate compression for HTTP responses. Read more →

Join RStudio Chief Data Scientist Hadley Wickham for his popular Building tidy tools workshop in San Francisco! If you’d missed the sold out course at rstudio::conf 2018 now is your chance. Register here: https://www.rstudio.com/workshops/extending-the-tidyverse/ You should take this class if you have some experience programming in R and you want to learn how to tackle larger scale problems. You’ll get the most if you’re already familiar with the basics of functions (i. Read more →

It has been more than two years since we announced the initial version of the DT package. Today we want to highlight a few significant changes and new features in the recent releases v0.3 and v0.4. The full changes can be found in the release notes. Editable tables Now you can make a table editable through the new argument datatable(..., editable = TRUE). Then you will be able to edit a cell by double-clicking on it. Read more →

We are pleased to announce the reticulate package, a comprehensive set of tools for interoperability between Python and R. The package includes facilities for: Calling Python from R in a variety of ways including R Markdown, sourcing Python scripts, importing Python modules, and using Python interactively within an R session. Translation between R and Python objects (for example, between R and Pandas data frames, or between R matrices and NumPy arrays). Read more →

In an effort to streamline product development, maintenance, and support to ensure the best experience for our users, we have created a strategy for operating system and browser deprecation. This will allow us to focus our work on modern platforms, and to encourage best practices in R development. This policy applies to all of our products and packages, and has been posted to the website here. This strategy is included in our Support Agreement, the full text of which can be found here. Read more →

RStudio Connect v1.5.14 is now available! This release includes support for secure environment variables, customizing email subject lines, and beta support for serving TensorFlow models. This release introduces beta support for SuSE and will be the last version of RStudio Connect to support Ubuntu 12.04 and Internet Explorer 10. Contact sales@rstudio.com for more information on supported platforms. Secure Environment Variables Environment variables for executable content can be configured in the RStudio Connect Dashboard. Read more →

We are excited to announce the first formal summer internship program at RStudio. The goal of our internship program is to enable RStudio employees to collaborate with current students (broadly construed: if you think of yourself as a student you quality) to create impactful and useful applications that will help both RStudio users and the broader R community, and help ensure that the community of R developers is representative of the community of R users. Read more →

Over the past year we’ve been hard at work on creating R interfaces to TensorFlow, an open-source machine learning framework from Google. We are excited about TensorFlow for many reasons, not the least of which is its state-of-the-art infrastructure for deep learning applications. In the 2 years since it was initially open-sourced by Google, TensorFlow has rapidly become the framework of choice for both machine learning practitioners and researchers. On Saturday, we formally announced our work on TensorFlow during J. Read more →

We are excited to share that sparklyr 0.7 is now available on CRAN! Sparklyr provides an R interface to Apache Spark. It supports dplyr syntax for working with Spark DataFrames and exposes the full range of machine learning algorithms available in Spark. You can also learn more about Apache Spark and sparklyr in spark.rstudio.com and our new webinar series on Apache Spark. Features in this release: Adds support for ML Pipelines which provide a uniform set of high-level APIs to help create, tune, and deploy machine learning pipelines at scale. Read more →

We’re pleased to announce RStudio Connect 1.5.12. This release includes support for viewing historical content, per-application timeout settings, and important improvements and bug fixes. Historical Content RStudio Connect now retains and displays historical content. By selecting the content’s history, viewers can easily navigate, compare, and email prior versions of content. Historical content is especially valuable for scheduled reports. Previously published documents, plots, and custom versions of parameterized reports are also saved. Read more →