Running R scripts from the command line can be a powerful way to: Automate your R scripts Integrate R into production Call R through other tools or systems There are basically two Linux command...

Design a computing infrastructure and choose packages that can set you and your learners on the happy path.

Safely Deploy R to Production

Does your R package work best with some configuration? You probably want it to be easily found by your package. Does your R package download huge datasets that don’t change much on the provider side? Maybe you want to save the corresponding data somewhere persistent so that things will go faster during the next R session. In this blog post we shall explain how an R package developer can go about using and setting persistent configuration and data on the user’s machine.

Learn R, R tutorials, R resources, blog posts and the latest updates about the statistical programming R language.

We deliver software development and ML solutions for Fortune 500 companies. We are an RStudio Full Service Certified Partner and global leaders in R Shiny.

Technical details and select highlights of my project to bring RStudio addins to VSCode.

Data table backend for dplyr. Contribute to tidyverse/dtplyr development by creating an account on GitHub.

:calendar: R htmlwidget for tui-calendar. Contribute to dreamRs/tuicalendr development by creating an account on GitHub.

all-contributions as an R package. Contribute to ropenscilabs/allcontributors development by creating an account on GitHub.

No interruptions. That was our team’s goal for RStudio Package Manager 1.1.0 - we set out to make R package installation fast enough that it wouldn’t interrupt your work. More and more data scientists use Linux environments, whether to access extra horsepower during development or to run production code in containers. Unfortunately, the rise in Linux environments has seen a corresponding increase in package installation pain. For Windows and Mac OS, CRAN provides pre-compiled binary packages that install almost instantly, but the same binaries are not available on Linux.

Shiny Server Pro allows you to scale Shiny applications to support multiple simultaneous users. The scaling is accomplished by setting 3 arguments in the configuration file (/etc/shiny-server/shiny...

Spelling Dictionaries Overview RStudio uses the Hunspell engine for spell-checking on Linux and Windows. Hunspell is also used by a wide-variety of other products including Chrome, Firefox, and L...

Starting from RStudio 1.2.937, the following file sources support custom commands while sourcing them: R, D3 and SQL file sources. This is accomplished by specifing a !source or !preview comment he...

This article has been updated to reflect the RStudio terminal feature as of version 1.3.1056-1. General Usage Introduction Getting Started Multiple Terminals Terminal Names Execute in Terminal B...

The following steps represent a minimal workflow for using Python with RStudio Connect via the reticulate package, whether you are using the RStudio IDE on your local machine or RStudio Server Pro....

Switching Themes Modern Theme Sky Theme Dark Theme Classic Theme Custom Editor Themes Themes API Switching Themes RStudio provides support for three global themes that customize RStudio's user int...

Overview 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 th...