The original deadline for the Table Contest was scheduled for October 31. Given requests and very interesting data becoming available next week, we're extended the deadline by two weeks to November 14. Read more →

When our customers ask us why RStudio's products support Python as well, we have a simple answer: It's because our data shows that our customers use R and Python for different tasks Read more →

This post is part of a series on new features in RStudio 1.4, currently available as a preview release. RStudio v1.4 introduces the capability to configure your workbench with multiple source columns. Multiple source columns give you the ability to view your source editors side-by-side and quickly reference code and data without switching tabs. Configuring a Side-by-Side View Your default RStudio view will not change after installing RStudio v1.4. Follow the instructions below to configure your new layout: Read more →

Back in July we made the difficult decision to cancel rstudio:conf(2021) for the health and safety of our attendees and the broader community. Today, we are thrilled to announce that rstudio::global(2021), our first ever virtual event focused on all things R and RStudio, now has a date locked in: January 21, 2021! Our goal is to make rstudio::global(2021) our most inclusive and global event, making the most of the freedom from geographical and economic constraints that comes with an online event. Read more →

This post is part of a series on new features in RStudio 1.4, currently available as a preview release. What’s a Command Palette? Just as a paint palette gives the artist instant access to all their colors, a command palette is a software affordance that gives instant, searchable access to all of a program’s commands. RStudio 1.4 introduces this very popular tool to our workbench. Command palettes have become a fixture of modern IDEs, and with good reason. Read more →

Photo by Kelly Sikkema on Unsplash Surviving the Data Deluge Many of the strategies at my old investment shop were thematically oriented. Among them was the notion of the “data deluge.” We sought to invest in companies that were positioned to help other companies manage the exponentially growing torrent of data arriving daily and turn that data into actionable business intelligence. Ironically, we ourselves struggled to effectively use our own data. Read more →

Andy Nicholls and Michael Rimler from healthcare firm GlaxoSmithKline plc (GSK) answer questions posed during their recent webinar, Using R to Drive Agility in Clinical Reporting. Read more →

Last week, we introduced RStudio’s new visual markdown editor. Today, we’re excited to introduce some of the expanded support for Python in the next release of RStudio. Python Support The RStudio 1.4 release introduces a number of features that will further improve the Python editing experience in RStudio: The default Python interpreter to be used by RStudio / reticulate can now be customized in the Global Options pane, Read more →

Today we’re excited to announce availability of our first Preview Release for RStudio 1.4, a major new release which includes the following new features: A visual markdown editor that provides improved productivity for composing longer-form articles and analyses with R Markdown. New Python capabilities, including display of Python objects in the Environment pane, viewing of Python data frames, and tools for configuring Python versions and conda/virtual environments. The ability to add source columns to the IDE workspace for side-by-side text editing. Read more →

As of this writing, two deep learning frameworks are widely used in the Python community: TensorFlow and PyTorch. TensorFlow, together with its high-level API Keras, has been usable from R since 2017, via the tensorflow and keras packages. Today, we are thrilled to announce that now, you can use Torch natively from R! This post addresses three questions: What is deep learning, and why might I care? What’s the difference between torch and tensorflow? Read more →