The R Project for Statistical Computing 4.0.3

All Checks are Passing

2 Passing Test

Validation Testing Passed

Verification Testing Passed


To install The R Project for Statistical Computing, run the following command from the command line or from PowerShell:


To upgrade The R Project for Statistical Computing, run the following command from the command line or from PowerShell:


To uninstall The R Project for Statistical Computing, run the following command from the command line or from PowerShell:


NOTE: This applies to both open source and commercial editions of Chocolatey.

1. Ensure you are set for organizational deployment

Please see the organizational deployment guide

  • Open Source or Commercial:
    • Proxy Repository - Create a proxy nuget repository on Nexus, Artifactory Pro, or a proxy Chocolatey repository on ProGet. Point your upstream to Packages cache on first access automatically. Make sure your choco clients are using your proxy repository as a source and NOT the default community repository. See source command for more information.
    • You can also just download the package and push it to a repository Download

3. Enter your internal repository url

(this should look similar to

4. Choose your deployment method:

choco upgrade r -y --source="'STEP 3 URL'" [other options]

See options you can pass to upgrade.

See best practices for scripting.

Add this to a PowerShell script or use a Batch script with tools and in places where you are calling directly to Chocolatey. If you are integrating, keep in mind enhanced exit codes.

If you do use a PowerShell script, use the following to ensure bad exit codes are shown as failures:

choco upgrade r -y --source="'STEP 3 URL'"

Write-Verbose "Exit code was $exitCode"
$validExitCodes = @(0, 1605, 1614, 1641, 3010)
if ($validExitCodes -contains $exitCode) {
  Exit 0

Exit $exitCode

- name: Ensure r installed
    name: r
    state: present
    version: 4.0.3
    source: STEP 3 URL

See docs at

Coming early 2020! Central Managment Reporting available now! More information...

chocolatey_package 'r' do
  action    :install
  version  '4.0.3'
  source   'STEP 3 URL'

See docs at

    Name: r,
    Version: 4.0.3,
    Source: STEP 3 URL

Requires Otter Chocolatey Extension. See docs at

cChocoPackageInstaller r
   Name     = 'r'
   Ensure   = 'Present'
   Version  = '4.0.3'
   Source   = 'STEP 3 URL'

Requires cChoco DSC Resource. See docs at

package { 'r':
  provider => 'chocolatey',
  ensure   => '4.0.3',
  source   => 'STEP 3 URL',

Requires Puppet Chocolatey Provider module. See docs at

salt '*' chocolatey.install r version="4.0.3" source="STEP 3 URL"

See docs at

5. If applicable - Chocolatey configuration/installation

See infrastructure management matrix for Chocolatey configuration elements and examples.

This package was approved as a trusted package on 11 Oct 2020.


Introduction to R

R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are some important differences, but much code written for S runs unaltered under R.

R provides a wide variety of statistical (linear and nonlinear modelling, classical statistical tests, time-series analysis, classification, clustering, …) and graphical techniques, and is highly extensible. The S language is often the vehicle of choice for research in statistical methodology, and R provides an Open Source route to participation in that activity.

One of R’s strengths is the ease with which well-designed publication-quality plots can be produced, including mathematical symbols and formulae where needed. Great care has been taken over the defaults for the minor design choices in graphics, but the user retains full control.

R is available as Free Software under the terms of the Free Software Foundation’s GNU General Public License in source code form. It compiles and runs on a wide variety of UNIX platforms and similar systems (including FreeBSD and Linux), Windows and MacOS.

The R environment

R is an integrated suite of software facilities for data manipulation, calculation and graphical display. It includes

  • an effective data handling and storage facility,
  • a suite of operators for calculations on arrays, in particular matrices,
  • a large, coherent, integrated collection of intermediate tools for data analysis,
  • graphical facilities for data analysis and display either on-screen or on hardcopy, and
  • a well-developed, simple and effective programming language which includes conditionals, loops, user-defined recursive functions and input and output facilities.
  • The term “environment” is intended to characterize it as a fully planned and coherent system, rather than an incremental accretion of very specific and inflexible tools, as is frequently the case with other data analysis software.

R, like S, is designed around a true computer language, and it allows users to add additional functionality by defining new functions. Much of the system is itself written in the R dialect of S, which makes it easy for users to follow the algorithmic choices made. For computationally-intensive tasks, C, C++ and Fortran code can be linked and called at run time. Advanced users can write C code to manipulate R objects directly.

Many users think of R as a statistics system. We prefer to think of it of an environment within which statistical techniques are implemented.
R can be extended (easily) via packages. There are about eight packages supplied with the R distribution and many more are available through the CRAN family of Internet sites covering a very wide range of modern statistics.

R has its own LaTeX-like documentation format, which is used to supply comprehensive documentation, both on-line in a number of formats and in hardcopy.

Package Parameters

  • /UseInf: - Change the inno setup configuration file to use/save when installing

choco install r --params "'/UseInf:C:\r.inf'"

Log in or click on link to see number of positives.

In cases where actual malware is found, the packages are subject to removal. Software sometimes has false positives. Moderators do not necessarily validate the safety of the underlying software, only that a package retrieves software from the official distribution point and/or validate embedded software against official distribution point (where distribution rights allow redistribution).

Chocolatey Pro provides runtime protection from possible malware.

Version Downloads Last Updated Status
The R Project for Statistical Computing 4.0.2 2484 Monday, June 22, 2020 Approved
The R Project for Statistical Computing 4.0.1 554 Saturday, June 6, 2020 Approved
The R Project for Statistical Computing 4.0.0 1480 Friday, April 24, 2020 Approved
The R Project for Statistical Computing 3.6.3 2283 Saturday, February 29, 2020 Approved
The R Project for Statistical Computing 3.6.2 2952 Thursday, December 12, 2019 Approved
The R Project for Statistical Computing 3.6.1 2593 Saturday, July 6, 2019 Approved
The R Project for Statistical Computing 3.6.0 1327 Friday, April 26, 2019 Approved
The R Project for Statistical Computing 3.5.3 473 Monday, March 11, 2019 Approved
The R Project for Statistical Computing 3.5.2 1407 Thursday, December 20, 2018 Approved
Discussion for the The R Project for Statistical Computing Package

Ground Rules:

  • This discussion is only about The R Project for Statistical Computing and the The R Project for Statistical Computing package. If you have feedback for Chocolatey, please contact the Google Group.
  • This discussion will carry over multiple versions. If you have a comment about a particular version, please note that in your comments.
  • The maintainers of this Chocolatey Package will be notified about new comments that are posted to this Disqus thread, however, it is NOT a guarantee that you will get a response. If you do not hear back from the maintainers after posting a message below, please follow up by using the link on the left side of this page or follow this link to contact maintainers. If you still hear nothing back, please follow the package triage process.
  • Tell us what you love about the package or The R Project for Statistical Computing, or tell us what needs improvement.
  • Share your experiences with the package, or extra configuration or gotchas that you've found.
  • If you use a url, the comment will be flagged for moderation until you've been whitelisted. Disqus moderated comments are approved on a weekly schedule if not sooner. It could take between 1-5 days for your comment to show up.
comments powered by Disqus