Using both Python and R combines the speed of Python for big data analytics with R’s statistical libraries to support your analysis needs. Conda is the solution to manage both environments.

As a package manager, conda provides many advantages. It is a cross-platform tool working on Windows, OS X, and Linux. It works for all kinds of packages, not just Python packages. And it has full support for virtual environments.

We are bringing conda’s power to the R ecosystem by building conda packages for R and the R packages on CRAN. The support is still preliminary, but we plan to have full support for the full ecosystem in the coming months. Anaconda Server users will also reap the benefits of these improvements to R support with conda.

For those who are interested in trying the preliminary support, the R packages are all on my Anaconda.org channel, and the recipes for the packages are all in the conda-recipes GitHub repo. conda create -c r -n r r will download R from our official R channel on Anaconda.org.

If you are interested in building your own conda packages for R, take a look at the documentation for conda build, the example recipes. An upcoming version of conda build will include a command conda skeleton cran which will allow building recipes for packages on CRAN automatically. You can share these packages with others using Anaconda.org.


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Let us know your thoughts and feedback on Twitter, #Rconda, or in the comments below.


About the Author

Aaron has a M.S. in mathematics from New Mexico State University and a B.S. in mathematics from New Mexico Tech. He is passionate about software, Python, mathematics, and the intersection of the three. Aaron is the lead developer of SymP …

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