YakData SmartDesktop with RStudio Desktop Server is the best way to download & install RStudio Desktop for use on Mac or Windows computers in 2022. It includes R 4.1.2 from the Rocker project, the RStudio IDE as a web app, hundreds of top data science packages included and it is all managed easily with Docker Desktop. This is the smart way to develop R programs, Shiny web apps & RMarkdown docs on your desktop in 2022.
+ Save hours of time to get up and running with a complete desktop IDE for R.
+ Includes over 200 of the most commonly used R packages pre-installed. Preloaded with the tidyverse, verse and geospatial-related tools from the R rocker-org project. Includes tex & publishing-related packages from verse.
+ Designed to install packages from RStudio Package Manager on a fixed date. Easily change this in Rprofile.site. Rapid installation of most packages as this image is based on Ubuntu.
+ Easy access to all the RStudio configuration and startup values.
+ The end of complex uninstall/upgrade paths for R and RStudio on your laptop/desktop system.
+ Easily recreate an identical environment on another system.
+ Run multiple versions of R side-by-side with multiple SmartDesktop project directories.
+ Define various environments for a particular R version with multiple docker-compose files.
+ Control resources used by your R sessions with docker-compose. No more system lock because an R session unexpectedly stole all your desktop resources.
+ Pause and restart a long-running R session with Docker Desktop!
Install and setup
Head over to https://github.com/Stephen-McDaniel/SmartDesktop-RStudio#-install-and-setup to get up and running with YakData SmartDesktop for RStudio.
If you benefit from this project, please click the button on this GitHub repository and let your colleagues know about it.
+ RStudio Open Source Server IDE is a free, open-source IDE for R, Shiny apps and RMarkdown content.
+ The RStudio Open Source Server IDE is backed by years of development, feedback and releases.
+ Make it easy to create a reproducible, self-contained R development environment on any system.
RStudio IDE repository: https://github.com/rstudio/rstudio
RStudio Package Manager: https://packagemanager.rstudio.com/client/#/
Docker Desktop: https://docs.docker.com/desktop/
Alternatives include self-install of the R, the RStudio IDE, tidyverse, verse and more directly on your OS.
RStudio is the leading development environment for R programming, R Shiny apps and RMaarkdown documents. Features include:
+ Highly customizable with powerful tools for R including a console, source editor, plot viewer, workspace management, integrated help, command history and more.
+ Execute code incrementally by line, by selected text or as a complete program.
+ Syntax highlighting editor with drop-down code completion.
+ Smooth integration of R Shiny app development including a local Shiny server and the ability to debug your app in a local browser.
+ RStudio Desktop in this project runs as a desktop server, ensuring reproducibility and portability.
Once you work with Docker Desktop, you will wonder why you wasted all those hours struggling with R installation directly on your computer!
+ Containerize and share any application locally and on your favorite cloud platform, in multiple languages and frameworks.
+ It is easy to install, setup and use a complete Docker development environment.
+ If you use a Windows computer, gain the ability to toggle between Linux and Windows Server environments ON YOUR LOCAL COMPUTER!
+ Volume mounting for code and data, including file change notifications and easy access to running containers on the localhost network.
The tidyverse includes many leading R packages for data science, forecasting, analytics and data management. The developers state, “The tidyverse is an opinionated collection of R packages designed for data science. All packages share an underlying design philosophy, grammar, and data structures.”
A subset of the included packages: ggplot2, dplyr, tidyr, readr, purrr, tibble, stringr, forcats and many other packages with more specialized usage. They are not loaded automatically with library(tidyverse), so you’ll need to load each one with its own call to library().