Can We Install R For Free In Mac

  1. Can We Install R For Free In Mac Operating System
  2. Can We Install R For Free In Macbook
  3. Can We Install R For Free In Mac Operating System
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Mixed emotions

Wow! Has it been a year? Another major update from The RFoundation (the recent 4.0.0release in April). I’m always happy to see thecontinuing progress and the combination of new features and bug fixes, but Ialso dread the upgrade because it means I have to address the issue of what todo about the burgeoning number of packages (libraries) I have installed. I wrotea fairly comprehensive post about it last year. I just took the plunge this yearand almost everything seems to still work. Vindication!

The details are here in the old postbut since this is timely I republish the basics.

I’m aware that there are full-fledged packagemanagers likepackrat and checkpoint and even a package designed to manage the upgrade foryou on windows, but I’m a Mac user and wanted to do things my own way and Idon’t need that level of sophistication.

So I set out to do the following:

  1. Capture a list of everything I had installed under R 3.6.x and, veryimportantly, as much as I could about where I got the package e.g. CRAN or GitHub or ???
  2. Keep a copy for my own edification and potential future use.
  3. Do a clean R 4.0.0 install and not copy any library directories manually orcreate symlinks or any other thing at the OS level.
  4. Take a look at the list I produced in #1 above but mainly to just downloadand install the exact same packages if I can find them.
  5. Make the process mainly scripted and automatic and available again forthe future – it worked this year let’s hope it works again next.

Before you upgrade!

Let’s load tidyverse to have access to all it’s various functions andfeatures and then build a dataframe called allmypackages with the basicinformation about the packages I currently have installed in R 3.6.3.

Note – I’m writing this after already upgrading so there will be a few inconsistencies in the output

  • This could just as easily be a tibble but I chose as.data.frame
  • I am deliberately removing base packages from the dataframe by filter
  • I am eliminating columns I really don’t care about with select

A function to do the hard work

As I mentioned above the stack overflow post was a good start but I wanted moreinformation from the function. Rather than TRUE/FALSE to is it github I wouldlike as much information as possible about where I got the package. Thepackage~source function will be applied to the Package column for each rowof our dataframe. For exampleas.character(packageDescription('ggplot2')$Repository) will get back “CRAN”,and as.character(packageDescription('CHAID')$Repository) will yield “R-Forge”.For GitHub packages the result is character(0) which has a length of zero.So we’ll test with an if else clause. If we get an answer like “CRAN” we’lljust return it. If not, we’ll see if there is a GitHub repo listed withas.character(packageDescription(pkg)$GithubRepo) as well as a GitHub usernameas.character(packageDescription(pkg)$GithubUsername). If they exist we’llconcatenate and return. If not we’ll return “Other”. Besides being gooddefensive programming this may catch the package you have built for yourself asis the case for me.

What’s in your libraries?

Now that we have the package_source function we can add a column to our dataframe and do a little looking.

And just to be on the safe side we’ll also write a copy out as a csv file so wehave it around in case we ever need to refer back.

Can We Install R For Free In Mac Operating System

Go ahead and install R 4.0.0

At this point we have what we need, so go ahead and download and install R4.0.0. At the end of the installation process you’ll have a pristine copy with anew (mostly empty) library directory (on my system it’s/Library/Frameworks/R.framework/Versions/4.0/). When next you restart R and RStudio you’ll see a clean new version. Let’s make use of our data frame toautomate most of the process of getting nice clean copies of the libraries wewant.

We’ll start by getting the entire tidyverse since we need several parts andbecause installing it will trigger the installation of quite a few dependenciesand bootstrap our work.

Now we have R 4.0.0 and some additional packages. Let’s see what we can do.First let’s create two dataframes, one with our old list and one with what wehave right now. Then we can use anti_join to make a dataframe that lists thedifferences thediff. We can use filter and pull to generate a vector ofjust the the packages that are on CRAN we want to install.

Just do it!

Now that you have a nice automated list of everything that is a CRAN package youcan give it a final look and see if there is anything else you’d like to filterout. Once you are sure the list is right one final pipe will set the process inmotion.

Depending on the speed of your network connection and the number of packages youhave that will run for a few minutes.

That takes care of our CRAN packages. What about GitHub? Here’s another chanceto review what you have and whether you still want need these packages. You canautomate the process and once again feed the right vector todevtools::install_github().

Same with the one package I get from R-Forge…

At the end of this process you should have a nice clean R install that has allthe packages you choose to maintain as well as a detailed listing of what thoseare.

Done

Hope you enjoyed the post. Comments always welcomed. Especially please letme know if you actually use the tools and find them useful.

Chuck

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This directory contains binaries for a base distribution and packages to run on macOS. Releases for old Mac OS X systems (through Mac OS X 10.5) and PowerPC Macs can be found in the old directory.

Note: Although we take precautions when assembling binaries, please use the normal precautions with downloaded executables.

Visual studio 2015 community edition free download offline installer. 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 4.1.0 'Camp Pontanezen' released on 2021/05/19

Please check the SHA1 checksum of the downloaded image to ensure that it has not been tampered with or corrupted during the mirroring process. For example type
openssl sha1 R-4.1.0.pkg
in the Terminal application to print the SHA1 checksum for the R-4.1.0.pkg image. On Mac OS X 10.7 and later you can also validate the signature using
pkgutil --check-signature R-4.1.0.pkg

Latest release:

R-4.1.0.pkg (notarized and signed)
SHA1-hash: df4d6fc17bbf6b7a27d4e015c0084d4bb6f7b428
(ca. 87MB)
R 4.1.0 binary for macOS 10.13 (High Sierra) and higher, Intel 64-bit build, signed and notarized package.
Contains R 4.1.0 framework, R.app GUI 1.76 in 64-bit for Intel Macs, Tcl/Tk 8.6.6 X11 libraries and Texinfo 6.7. 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.

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.

This release supports Intel Macs, but it is also known to work using Rosetta2 on M1-based Macs. For native Apple silicon arm64 binary see below.

Important: this release uses Xcode 12.4 and GNU Fortran 8.2. If you wish to compile R packages from sources, you may need to download GNU Fortran 8.2 - see the tools directory.

R-4.1.0-arm64.pkg (notarized and signed)
SHA1-hash: 7354c1b249cab9bafea6ae67c73563303a05fa17
(ca. 88MB)
R 4.1.0 binary for macOS 11 (Big Sur) and higher, Apple silicon arm64 build, signed and notarized package.
Contains R 4.1.0 framework, R.app GUI 1.76 for Apple silicon Macs (M1 and higher), Tcl/Tk 8.6.11 X11 libraries and Texinfo 6.7.
Important: this version does NOT work on older Intel-based Macs.

Note: the use of X11 (including tcltk) requires XQuartz. Always re-install XQuartz when upgrading your macOS to a new major version.

This release uses Xcode 12.4 and experimental GNU Fortran 11 arm64 fork. If you wish to compile R packages from sources, you may need to download GNU Fortran for arm64 from https://mac.R-project.org/libs-arm64. Any external libraries and tools are expected to live in /opt/R/arm64 to not conflict with Intel-based software and this build will not use /usr/local to avoid such conflicts.

NEWS (for Mac GUI)News features and changes in the R.app Mac GUI
Mac-GUI-1.76.tar.gz
SHA1-hash: 304980f3dab7a111534daead997b8df594c60131
Sources for the R.app GUI 1.76 for Mac OS X. This file is only needed if you want to join the development of the GUI (see also Mac-GUI repository), 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-3.6.3.nn.pkg (signed)
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.
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!
The new R.app Cocoa GUI has been written by Simon Urbanek and Stefano Iacus with contributions from many developers and translators world-wide, see 'About R' in the GUI.

Subdirectories:

toolsAdditional 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).
baseBinaries of R builds for macOS 10.13 or higher (High Sierra), Intel build
contribBinaries of package builds for macOS 10.13 or higher (High Sierra), Intel build
big-sur-arm64Binaries for macOS 11 or higher (Big Sur) for arm64-based Macs (aka Apple silicon such as the M1 chip)
el-capitanBinaries of package builds for OS X 10.11 or higher (El Capitan build)
mavericksBinaries of package builds for Mac OS X 10.9 or higher (Mavericks build)
oldPreviously 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.

For

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!

Package maintainers should visit CRAN check summary page to see whether their package is compatible with the current build of R for macOS.

Can We Install R For Free In Macbook

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.

Can We Install R For Free In Mac Operating System

Last modified: 2021/05/20, by Simon Urbanek