When was the last time you update your R and RStudio?
I installed RStudio and R a year ago, and never update it since then. Today I just noticed I cannot install new R packages because of my old R version. So I explore some ways to update R and would like to share with someone who is also looking to update R on RStudio.
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The problem
RStudio and R cannot update on their own because some packages may not work after switching to the new version (You can still downgrade R version in RStudio if something went wrong though). After you install the new version, the previously installed packages will not go to next version. So it is required extra procedures to move the packages.
Here are 3 ways you can update R version in RStudio. Note that we need to move the install R packages, which I will show how at the end.
3 Solutions to update R on RStudioSolution 1) Manually install (Recommended if you don't care about the old packages)
The first method is to download a new version of R from R website > CRAN. Then restart your RStudio. The new R version will be loaded automatically.
The new R version appear right after I install R and restart RStudio
Update 29/05/2019: For Mac users, solution 3 is too painful and not working well for me. This method is fast and working well. I would recommend to save your time from headache and use this method. Take note of your previous packages so you can install them again as needed.
Solution 2) Windows only – use installr
installr is the R package which helps install and update software.
The R code you will need for updating R is: (credit goes to Cara Wogsland for the code)
install.packages('installr')
library(installr)
updateR()
You can find the tutorial on how to use installr to update RStudio on R-Statistics website.
Solution 3) Mac only – use updateR
Similar to installr, updateR is the package to help updating R on Mac OS.
The R code you will need is these 5 lines: (credit goes to jroberayalas for the code)
install.packages('devtools') #assuming it is not already installed
library(devtools)
install_github('andreacirilloac/updateR')
library(updateR)
updateR(admin_password = 'Admin user password')
You can find in-depth tutorial on how to use updateR package on this blog.
How to move the previously installed R packages
This is the instructions for Mac OS user (who used solution 1 or 3 above). For Windows user, installr package will do this for you Age of mythology mac torrent.
(credit goes to RyanStochastic and micstr):
1. Move all folders from your old R version to new R version.
/Library/Frameworks/R.framework/Versions/x.xx/Resources/library
Replace x.xx with the old and new R version at a time.
Note that you have to move only the packages that are not currently in the destination folder (because those are the base packages, and you don’t want to ruin them). But if you already did replaced everything, the next step will solve this for you. Mp3 songs download for mac.
If you cannot find the proper path, you can run this command to check: installed.packages()
2. Update the moved packages
Run the following command in R. Type ‘y’ for every question that popped up.
update.packages(checkBuilt=TRUE)
3. Type the following command in R to check if everything went well
packageStatus()
That’s it! Hope you guys success in updating R. If not, please check in the reference link below.
References: https://stackoverflow.com/questions/13656699/update-r-using-rstudio
Download R-studio For MacThis is the new home for experimental binaries and documentation related to R for macOS. To learn more about the R software or download released versions, please visit www.r-project.org.
All software on this page is strictly experimental and subject to acceptance of the supplied R license agreement and the disclaimer at the end of the page.
Important note about R 4.0.0
Starting with R 4.0.0 alpha we are building R using standard Apple tools (Xcode 11.4) and GNU Fortran 8.2 from fxcoudert and the target is macOS 10.13 (High Sierra). All dependent static libraries are available in the libs-4 directory. Please make sure you remove any modifications to build flags from your home since no custom compilers are used anymore. For more information about alternative OpenMP options (as in older version) see the openmp page of this site. IndexWindows For Mac Free DownloadNightly builds for macOSR framework
The installer image (*.pkg) is packaged exactly the same way as the CRAN release of R (including the GUI) and it will update your R version (unless you use pkgutil - see instructions during installation and/or the 'Multiple versions'section of the R Installation and Administration manual). Junos vpn client for mac download.
Alternatively, you can use the tar-ball (*.tar.gz) in the table above. The tar-ball must be unpacked in the root directory using:
$ tar fvxz R*.tar.gz -C /
Download parallel space for mac. NOTE: The tar-ball does not contain the GUI (see below for a separate download).
NOTE: The installer includes Tcl/Tk package which will install in /usr/local. It is optional (only needed for the tcltk R package) and can be unchecked at installation time.
If you see any issues with the builds, please contact Simon Urbanek (the macOS maintainer of R) or report on the R-SIG-Mac mailing list.
Mac OS X GUI
To install, open the image and drag the R icon to your Applications folder. Alternatively the GUI can be run directly off that image without copying if you just want to test it. Build configurations with '64' suffix are 64-bit builds, all others are 32-bit (except for Debug). If you want to use both, rename one of them or place them in different directories.
ToolsIn order to compile R and R packages you will need Xcode Developer Tools and a Fortran compiler. For details and download, please read the Tools page. The R 4.0.0 and higer binaries are built using Xcode 11.4.Experimental binary packagesThis site no longer hosts experimental packages. It is now the master repository for released R package binaries. If you have issues with other mirrors, try using https://mac.r-project.org/ as your mirror as it is updated first.Legacy RThe current build supports only macOS X 10.13 (High Sierra) or higher. Older versions of macOS are not supported in binary form, but R can be compiled from sources for such legacy OS versions. Last released version for Mac OS X 10.4 (Tiger) was R 2.10.1Download Mac Os Free, last release for Mac OS X 10.5 (Leopard) was R 2.15.3, last release for Mac OS X 10.11 (El Capitan) was R 3.6.3.R On MacOther binariesThe following binaries are not maintained or supported by R-core and are provided without any guarantee and for convenience only (Mac OS X 10.4.4 or higher required). They match the binaries used on the CRAN binary build machine and thus are recommended for use with CRAN R package binaries.
More external libraries for R 4.0.0 and higher can be found in the /libs-4/ directory. For older versions see the /libs/ directory.
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