Using R with conda — Anaconda Enterprise 4.4 documentation

Anaconda Enterprise: Documentation

# Using R with conda

For Linux, macOS and Windows

If you have conda installed, you can easily install the R programming language and over 80 of the most used R packages for data science with one command. Conda helps you keep your packages and dependencies up to date. You can also easily create and share your own custom R packages.

R-Essentials works very much like Anaconda:

- Installs all of the most popular packages with all of their dependencies with one command: `conda install -c r r-essentials`
- Update all of the packages and their dependencies with one command: `conda update -c r r-essentials`
- Update a single package in R-Essentials (if a new version of the package is available in the R channel) with the command `conda update r-XXXX`

## How to install “R Essentials”

1. Download and install Anaconda
2. Install the R Essentials package into the current environment: `conda install -c r r-essentials`

## Create and share your own custom R bundle

Building and sharing your own custom R bundles with others is like building and sharing conda packages.

For example, create a simple custom R bundle meta-package named “Custom-R-Bundle” containing several popular programs and their dependencies with the command:

    conda metapackage custom-r-bundle 0.1.0 --dependencies r-irkernel jupyter r-ggplot2 r-dplyr --summary "My custom R bundle"

Now you can easily share your new meta-package with friends and colleagues by uploading it to your channel on Anaconda Cloud:

    conda install anaconda-client
    anaconda login
    anaconda upload path/to/custom-r-bundle-0.1.0-0.tar.bz2

Your friends and colleagues now have access to your Custom-R-Bundle from any computer with the command:

    conda install -c <your anaconda.org username> custom-r-bundle

For more information, see Christine Doig’s blog post Jupyter and conda for R language.

Next, let’s look at Using Microsoft R Open.