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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.
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. https://supernalzing606.weebly.com/blog/authorware-7-free-download-full. https://pvuamn.weebly.com/dmg-2-35.html. 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 RStudio
Solution 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) Onlod dr. cleaner for mac.
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
![R software for mac R software for mac](/uploads/1/3/4/3/134360012/134905748.png)
library(devtools)
install_github('andreacirilloac/updateR')
library(updateR)
Cloudconvert dmg to zip. 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
(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.
If you cannot find the proper path, you can run this command to check: installed.packages()
2. Update the moved packages
Android kitkat 4.4 2 free download for pc. 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
version
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
R For Mac Os X
Download RStudio Latest Version for Windows, Mac & Ubuntu – RStudio is a programming language and software system designed specifically to do all things related to statistical computing. This programming language was first developed in 1993 by two statistical experts, Ross Ihaka and Robert Gentleman at Auckland University, New Zealand. Until now, the R programming language continued to grow rapidly along with the increasing popularity of the term “Big Data” and the increasing need for companies to be data scientists to process and analyze data in the company as a basis for policy making and automating business processes to be data-driven. Programming languages like Python and R have become the main choice for researchers and practitioners in the field of data science to process and analyze data both for research and business purposes. Therefore, for a beginner in the field of data science, R is a highly recommended programming language to master.
Why Can RStudio Become So Popular?
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Based on the publication released by IEEE Spectrum ranks languages in 2017, R belongs to the 10 most popular programming languages. R is in the 6th position above the Javascript and PHP programming languages which are in the 7th and 8th positions respectively. While the first rank is held by the Python programming language, which is also in great demand by data scientists. One of the reasons why R can fit into the most popular programming languages is that more and more people are using R in academic research papers. So, R proved very popular to be used by researchers in the field of statistics and data science. In addition, R is also developed open source so that it can be used legally without the need to pay for any license, aka free! Equally important is that R already has a large user community, so that any problems that we will encounter during the learning process can almost certainly be available on the StackOverflow website.
Installing RStudio
After getting to know the R programming language a little, the next step is to install this environment systems as IDEs to make it easier for us when coding later. Following are the steps for installing R:
First, you need to download RStudio first. Then, click the link Download R 3 for Windows (Assuming you use Windows OS), make sure the download process is complete 100%. Install the file downloaded in step 2 on PC or Laptop according to the OS version it has (64 bit or 32 bit). If the installation process has finished correctly, the R icon will appear on the desktop. Next, we need to install this app as an IDE. The app is specifically designed to make it easier for us to process coding and project management later. Therefore, we strongly recommend installing this application before starting to study the use of R itself. Some features of the app include code completion, syntax highlighting, smart indentation, etc. After you click the R icon, then the display will be directed to the Installers for Supported Platforms page section. Select the default option for each installation stage. If the installation process has finished correctly, the RStudio icon will appear on the desktop or toolbar.
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