Guide to a high-performance, powerful R installation

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R is an amazing language with 25 years of development behind it, but you can make the most from R with additional components. An IDE makes developing in R more convenient; packages extend R's capabilities; and multi-threaded libraries make computations faster. 

Since these additional components aren't included on the official R website, getting the ideal R environment set up can be a bit tricky. Fortunately, there's a handy R installation guide by Mauricio Vargas that explains how to get everything you need set up on Windows, Mac and Ubuntu Linux. On each platform, the guide describes how to install:

  • The R language engine
  • The RStudio IDE.
  • The tidyverse suite of packages
  • Multi-threaded math libraries (BLAS). On Windows, Mauricio recommends Microsoft R Open (“what made my R and Windows experience amazing”). For Mac and Unix he suggests installing OpenBLAS, but I'll add that Microsoft R Open provides BLAS acceleration on those platforms as well. It's easy to configure RStudio to use Microsoft R Open, too.

Find all the details in the installation guide, linked below.

DataCamp Community: How to install R on Windows, Mac OS X and Ubuntu

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