Jan 13, 2020 Access the interface for the R programming language to create programs for multiple platforms. Select a template for development or build a new project from scratch. Perform coding operations and check the integrity of the input data. Overview the structure to finalize a project. RStudio 1.2.5033 for Mac is free to download from our application. Download the R-3.2.3.pkg, which is the latest version as of this blog post. The package will download and double click to install. The installation is straight forward, select ‘Continue’ and follow the prompts. The R backend is now installed and we can move to installing RStudio. Step 2 – Installing R Studio.
This directory contains binaries for a base distribution and packages to run on Mac OS X (release 10.6 and above). Mac OS 8.6 to 9.2 (and Mac OS X 10.1) are no longer supported but you can find the last supported release of R for these systems (which is R 1.7.1) here. Releases for old Mac OS X systems (through Mac OS X 10.5) and PowerPC Macs can be found in the old directory.
Note: CRAN does not have Mac OS X systems and cannot check these binaries for viruses.Although we take precautions when assembling binaries, please use the normal precautions with downloaded executables.
Package binaries for R versions older than 3.2.0 are only available from the CRAN archive so users of such versions should adjust the CRAN mirror setting (https://cran-archive.r-project.org) accordingly.
R 3.6.3 'Holding the Windsock' released on 2020/02/29
Important: since R 3.4.0 release we are now providing binaries for OS X 10.11 (El Capitan) and higher using non-Apple toolkit to provide support for OpenMP and C++17 standard features. To compile packages you may have to download tools from the tools directory and read the corresponding note below.
Please check the MD5 checksum of the downloaded image to ensure that it has not been tampered with or corrupted during the mirroring process. For example type
md5 R-3.6.3.pkg
in the Terminal application to print the MD5 checksum for the R-3.6.3.pkg image. On Mac OS X 10.7 and later you can also validate the signature using
pkgutil --check-signature R-3.6.3.pkg
md5 R-3.6.3.pkg
in the Terminal application to print the MD5 checksum for the R-3.6.3.pkg image. On Mac OS X 10.7 and later you can also validate the signature using
pkgutil --check-signature R-3.6.3.pkg
Latest release:
R-3.6.3.pkg (notarized, for Catalina) SHA1-hash: 2677aaf9da03e101f9e651c80dbec25461479f56 (ca. 77MB) R-3.6.3.nn.pkg (regular) SHA1-hash: c462c9b1f9b45d778f05b8d9aa25a9123b3557c4 (ca. 77MB) | R 3.6.3 binary for OS X 10.11 (El Capitan) and higher, signed package. Contains R 3.6.3 framework, R.app GUI 1.70 in 64-bit for Intel Macs, Tcl/Tk 8.6.6 X11 libraries and Texinfo 5.2. The latter two components are optional and can be ommitted when choosing 'custom install', they are only needed if you want to use the tcltk R package or build package documentation from sources. macOS Catalina users must use notarized version which enforces hardened run-time. All others can use regular version which uses the same runtime as previous R releases. R 3.6.2 was the last version that can be run on Catalina with regular runtime. Note: the use of X11 (including tcltk) requires XQuartz to be installed since it is no longer part of OS X. Always re-install XQuartz when upgrading your macOS to a new major version. Important: this release uses Clang 7.0.0 and GNU Fortran 6.1, neither of which is supplied by Apple. If you wish to compile R packages from sources, you will need to download and install those tools - see the tools directory. |
NEWS (for Mac GUI) | News features and changes in the R.app Mac GUI |
Mac-GUI-1.70.tar.gz MD5-hash: b1ef5f285524640680a22965bb8800f8 | Sources for the R.app GUI 1.70 for Mac OS X. This file is only needed if you want to join the development of the GUI, it is not intended for regular users. Read the INSTALL file for further instructions. |
Note: Previous R versions for El Capitan can be found in the el-capitan/base directory.Binaries for legacy OS X systems: | |
R-3.3.3.pkg MD5-hash: 893ba010f303e666e19f86e4800f1fbf SHA1-hash: 5ae71b000b15805f95f38c08c45972d51ce3d027 (ca. 71MB) | R 3.3.3 binary for Mac OS X 10.9 (Mavericks) and higher, signed package. Contains R 3.3.3 framework, R.app GUI 1.69 in 64-bit for Intel Macs, Tcl/Tk 8.6.0 X11 libraries and Texinfo 5.2. The latter two components are optional and can be ommitted when choosing 'custom install', it is only needed if you want to use the tcltk R package or build package documentation from sources. Note: the use of X11 (including tcltk) requires XQuartz to be installed since it is no longer part of OS X. Always re-install XQuartz when upgrading your OS X to a new major version. |
R-3.2.1-snowleopard.pkg MD5-hash: 58fe9d01314d9cb75ff80ccfb914fd65 SHA1-hash: be6e91db12bac22a324f0cb51c7efa9063ece0d0 (ca. 68MB) | R 3.2.1 legacy binary for Mac OS X 10.6 (Snow Leopard) - 10.8 (Mountain Lion), signed package. Contains R 3.2.1 framework, R.app GUI 1.66 in 64-bit for Intel Macs. This package contains the R framework, 64-bit GUI (R.app), Tcl/Tk 8.6.0 X11 libraries and Texinfop 5.2. GNU Fortran is NOT included (needed if you want to compile packages from sources that contain FORTRAN code) please see the tools directory. NOTE: the binary support for OS X before Mavericks is being phased out, we do not expect further releases! |
Subdirectories:
tools | Additional tools necessary for building R for Mac OS X: Universal GNU Fortran compiler for Mac OS X (see R for Mac tools page for details). |
el-capitan | Binaries of package builds for OS X 10.11 or higher (El Capitan build) |
mavericks | Binaries of package builds for Mac OS X 10.9 or higher (Mavericks build) |
old | Previously released R versions for Mac OS X |
You may also want to read the R FAQ and R for Mac OS X FAQ. For discussion of Mac-related topics and reporting Mac-specific bugs, please use the R-SIG-Mac mailing list.
Information, tools and most recent daily builds of the R GUI, R-patched and R-devel can be found at http://mac.R-project.org/. Please visit that page especially during beta stages to help us test the Mac OS X binaries before final release!
Download R
Package maintainers should visit CRAN check summary page to see whether their package is compatible with the current build of R for Mac OS X.
Binary libraries for dependencies not present here are available from http://mac.R-project.org/libs and corresponding sources at http://mac.R-project.org/src.
Last modified: 2020/03/11, by Simon Urbanek
I have fallen in love with the R language and tool set over the last few weeks. I find that getting outside my comfort zone and learning new tools can always spur creativity and the open source community has a great many tools just waiting to be discovered. The fact that there is a free option for RStudio provides a powerful analysis tool to organizations without taking a large hit to the budget.
R is a statistical computing and graphics language and is available as free software under the GNU general public license. RStudio is a free and open source integrated development environment that puts a user interface over the R command line back end. The combination of the two provides a powerful data analysis toolset.
The tools are more command line and have a programming style rather than a point and click tool such as Microsoft’s Excel. This tool would appeal to the power user analyst or a user with more of a programming background.
R has a Very Active Community
The trouble with adding open source software to your workflow is making sure that the tool is active and being updated on a regular basis. The main criteria I look for is based on how large and active the community around the tool is.
- Do people have a passion for the software?
- Is there an active community?
- When was the last update?
- How often has the software been updated?
R has a large active community and provides functions and extensions to the tool set through external libraries which can be imported as you need and discover them.
Installing R & RStudio on a Mac
The installation on a Mac is simple and straight forward. There are 2 installations that are required, the R language and the RStudio front end. You can install a desktop or server version, however I find for personal use the desktop install and user experience easier to manage.
Step 1 – Installing R
RStudio requires R version 2.11.1 or higher which can be downloaded here; http://cran.rstudio.com/ . There will be 3 versions listed, select the “Download the R for (Mac) OS X” version by first selecting the option below.
This will take you to the binaries page. Download the R-3.2.3.pkg, which is the latest version as of this blog post.
The package will download and double click to install. The installation is straight forward, select ‘Continue’ and follow the prompts.
The R backend is now installed and we can move to installing RStudio.
Step 2 – Installing R Studio
The RStudio desktop version can be found here, https://www.rstudio.com/products/rstudio/#Desktop . There is an open source version and a purchased version that includes various options and support.
The icon above takes you to the various desktop versions, select the Mac OS X version.
Once Downloaded, double click on the RStudio package.
Drag the RStudio icon to the Application Folder
On my machine, I have an older version, you can select ‘Replace’ to only keep the new version.
In Launch Pad, Type in R in finder, you will see both R and RStudio. Select RStudio and the following message is displayed, Select Open to run RStudio
Step3 – Try it out
RStudio is now displayed. You get the option to see a demo which will allow us to see if all is working correctly.
Type the following 2 lines of code in the console and press enter;
Type the following 2 lines of code in the console and press enter;
X = rnorm(200)
Plot(x)
RStudio is now installed and ready for your analysis.
Resources available
There are many resources and tutorials that can be used to learn more about using the R language, I have listed a few below.
R Project for Statistical Computing, https://www.r-project.org
RStudio, https://www.rstudio.com/resources/training/online-learning/#R
I hope you find these useful.
Steve