RStudio is RStupendous

September 3, 2012
By

(This article was first published on Datavore Consulting » R, and kindly contributed to R-bloggers)

I am a sucker for beautiful applications (like the ggplot2 web tool mentioned here). The latest R-related application to catch my eye is RStudio.

RStudio™ is a free and open source integrated development environment (IDE) for R. You can run it on your desktop (Windows, Mac, or Linux) or even over the web using RStudio Server.

For a glimpse of the beauty of RStudio, take 2 minutes to watch the screencast found on the RStudio home page. If you watch the screencast, you will also get an overview of the functionality of RStudio.

You may find RStudio described as a GUI for R (see here), but that refers to the GUI elements present in RStudio that facilitate code development. If you want to use R without writing code, you have a few options, such as Deducer and R Commander, but to exploit the full power of R you will eventually need to learn how to write code.

I hadn’t previously sought out a text editor (or IDE) for R because I was satisfied with the features of the built-in editor for R on Mac OS X (known as R.app; see here for a comparison of R.app and RStudio). As such, my enthusiasm for RStudio is not based on a comparison to popular alternatives such as Emacs Speaks Statistics (ESS) and Tinn-R. But the beauty, cross-platform compatibility, and generally favorable reviews of RStudio made it the top candidate to take for a test drive.

I will not duplicate the efforts of previous bloggers (see here and here) by providing an overview of RStudio’s best features, but I particularly love the integration with the wonderful R package knitr for dynamic report generation in LaTeX, HTML, Markdown, and more. I first started using LaTeX to typeset my dissertation, became smitten, and vowed to never use Word again (an overzealous oath). However, I only recently created my first dynamic report using knitr and LaTeX. I anticipate that my exploration of knitr, facilitated by RStudio, will spawn several future blog posts, partly because it allows me to continue to beat the drum for reproducible research.

Lastly, if you are using R on Windows through the built-in editor, then you are missing out on a number of wonderful features to improve your workflow and you should download RStudio, ESS, or Tinn-R immediately.

To leave a comment for the author, please follow the link and comment on his blog: Datavore Consulting » R.

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