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Download and Install R on Mac: A Simple Tutorial

How to Download and Install R for Mac OS X

R is a free and open-source software environment for statistical computing and graphics. It is widely used by data analysts, researchers, and programmers for data manipulation, visualization, and machine learning. R has a rich set of features and packages that make it a powerful tool for data science.

If you are a Mac user, you might be wondering how to download and install R on your computer. In this article, we will show you how to do that in a few simple steps. We will also show you how to verify the installation, run R, install additional packages, and update R when needed.

download r mac

How to Download R for Mac OS X

To download R for Mac OS X, you need to go to the , which is the official repository of R packages and binaries. CRAN stands for Comprehensive R Archive Network, and it hosts thousands of packages and extensions that enhance R's functionality.

On the CRAN website, click on the "Download R for (Mac) OS X" link. This will take you to a page where you can choose a mirror site that is closest to your location. A mirror site is a server that hosts a copy of the CRAN files, so choosing a nearby one will speed up your download.

On the mirror site page, click on the link for the latest R version for Mac OS X. As of June 2023, the latest version is R-4.3.0.pkg. Save this file to your computer and then double-click on it to run it. This will launch the installer program that will guide you through the installation process.

The installer will ask you to agree to the license terms, choose an installation location, select components to install, and create shortcuts. You can accept the default options or customize them according to your preferences. The installation should take a few minutes, depending on your system configuration.

How to download R for Mac OS X

Download R for macOS from CRAN

R for Mac installation guide

R for Mac tutorial and examples

R for Mac troubleshooting and FAQs

Download R for Mac with Homebrew

Download R for Mac with Anaconda

Download RStudio for Mac

Download R packages for Mac

Download Rtools for Mac

Download R Commander for Mac

Download R Shiny for Mac

Download R Markdown for Mac

Download R ggplot2 for Mac

Download R dplyr for Mac

Download R tidyr for Mac

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Download R magrittr for Mac

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Download R jsonlite for Mac

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Download R readr for Mac

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Download R haven for Mac

Download R foreign for Mac

Download R knitr for Mac

Download R bookdown for Mac

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Download R flexdashboard for Mac

Download R shinydashboard for Mac

Download R DT for Mac

Download R kableExtra for Mac

Download R testthat for Mac

Download R roxygen2 for Mac

Download R devtools for Mac

How to Verify the Installation and Run R

To verify that R has been installed correctly on your Mac, you can open the Terminal application and type R. This will start an interactive session of R in your terminal window. You should see something like this:

R version 4.3.0 (2023-04-21) -- "Already Tomorrow" Platform: x86_64-apple-darwin17.0 (64-bit) ... Type 'demo()' for some demos, 'help()' for on-line help, or 'help.start()' for an HTML browser interface to help. Type 'q()' to quit R. >

This shows you the version of R that you have installed, as well as some information about your platform and some tips on how to use R. You can type commands at the > prompt and press Enter to execute them. For example, you can type 2 + 2 and press Enter to see the result:

> 2 + 2 [1] 4

To exit R, type q()y to save it, n to discard it, or c to cancel the exit. If you save it, R will create a file called .RData in your current working directory, which you can load in your next session by typing load(".RData").

How to Install Additional Packages and Update R

One of the great advantages of R is that it has a large and active community of developers and users who create and share packages that extend R's functionality. A package is a collection of functions, data, and documentation that can be installed and loaded in R. There are thousands of packages available on CRAN and other sources, covering various topics and domains.

To install a package from CRAN, you can use the install.packages() function in R. For example, to install the package, which is a popular package for creating beautiful and complex graphics, you can type:

> install.packages("ggplot2")

This will download and install the package and its dependencies from CRAN. You can also specify a vector of package names to install multiple packages at once. For example, to install the package, which is a collection of packages for data manipulation and analysis, you can type:

> install.packages("tidyverse")

To load a package that you have installed, you can use the library() function in R. For example, to load the ggplot2 package, you can type:

> library(ggplot2)

This will make the functions and data from the package available in your session. You can also use the :: operator to access a specific function from a package without loading it. For example, to use the qplot() function from ggplot2, you can type:

> ggplot2::qplot(x = mpg, y = wt, data = mtcars)

This will create a scatter plot of miles per gallon versus weight for the mtcars dataset.

To update the packages that you have installed, you can use the update.packages() function in R. This will check if there are newer versions of your packages on CRAN and install them if there are. You can also specify a vector of package names to update only certain packages.

To update R itself, you can use the package, which is a package that allows you to update R from within R. To use this package, you need to install it first by typing:

> install.packages("installr")

Then, you can load it and run the updateR() function:

> library(installr) > updateR()

This will check if there is a newer version of R available and guide you through the update process.


In this article, we have shown you how to download and install R for Mac OS X, how to verify the installation and run R, how to install additional packages and update R. We hope that this article has helped you get started with using R on your Mac computer.

If you want to learn more about R and how to use it for data analysis and visualization, here are some resources that we recommend:

  • : A book by Hadley Wickham and Garrett Grolemund that teaches you how to use R for data import, wrangling, exploration, analysis, modeling, and communication.

  • : An integrated development environment (IDE) for R that provides a user-friendly interface and many tools for coding, debugging, testing, and deploying R projects.

  • : A website that aggregates blog posts from various R bloggers who share their insights, tips, tricks, and tutorials on using R.

  • : A website where you can ask and answer questions about R and get help from other R users and experts.

We hope you enjoyed this article and learned something new. If you have any feedback or questions, please feel free to leave a comment below. We would love to hear from you and help you with your R journey.


What is the difference between R and RStudio?

R is the software environment that runs the R code and provides the basic functionality for data analysis and visualization. RStudio is an IDE that provides a user-friendly interface and additional tools for working with R projects. You need to install R first before you can use RStudio.

How do I uninstall R from my Mac?

To uninstall R from your Mac, you need to delete the following files and folders:

  • The R application bundle from your Applications folder

  • The .RData file from your home directory (if you have one)

  • The .Rhistory file from your working directory (if you have one)

  • The .Renviron file from your home directory (if you have one)

  • The .Rprofile file from your home directory or working directory (if you have one)

  • The .Rapp.history file from your home directory (if you have one)

  • The .Rproj.user folder from your working directory (if you have one)

  • The .Rproj file from your working directory (if you have one)

  • The .R folder from your home directory (if you have one)

  • The .Rlibrary folder from your home directory (if you have one)

How do I change the working directory in R?</


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