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Installing R and RStudio on your computer
To get into using R and RStudio, you're going to neeed to have a copy installed on your computer (duh!). Fortunately, getting set up is relatively quick and easy to do!
R is a statistical programming language, providing us the toolbox needed to do our data science. To access the tools contained within the R language, we need to go ahead and download a copy to our computers.
Installing R onto Windows 10 is pretty straightforward. The easiest way to go about it is through the Central R Archive Network (CRAN, for short). Just jump onto the CRAN downloads page, click download R for windows, then click install R for the first time, and then download the latest version of R.
Once the download is complete, you will have a file called R-version_number-win.exe. Run this .exe file and step thought he installation wizard - the defaults are generally fien so just click through until the process is complete. Congrats! You now have an R installation ready to go on your computer.
Installing R onto macOS is very similiar to installing on Windows. The easiest way to go about it is through the Central R Archive Network (CRAN, for short), jump onto the CRAN downloads page, click download R for (Mac) OS X, then download the latest version under latest relases to start your download.
Run that downloaded R-version_number.pkg package, and feel free to leave the defaults, just like in windows and BAM! A shiny new R installation ready for you to play with.
If R is our toolbox for data science, then RStudio is the workshop in which we can do our data wrangling work. Just like a workshop, RStudio provides us a contained place to build new projects, keep our tools and data organised and up to date, and save us the hassle of the cat walking though the paint tray and traipsing it all through the house...
Those aren't my paint pawprints...
Anyway, let's go ahead and install RStudio!
Note: you need to already have a copy of R on your computer for all this RStudio-ing to work.
Like installing R, installing RStudio is pretty straightforward. We're going to go to the RStudio downloads page, choose the RStudio Desktop version, and download the latest version for Windows - it should be at the top of the all installers list. Once downloaded, go ahead and run the RStudio-version_number.exe file, again choosing the default options.
Much like the windows installation, we're going to head over to the RStudio downloads page, choose the RStudio Desktop version, and download the latest version for macOS, second form the top of the all installers list. Once downloaded, go ahead and run the RStudio-version_number.dmg file, choosing the default options. Simples.
One last option if you're struggling to setup R and RStudio on your computer is to run a cloud instance of RStudio. This allows you to access RStudio through a web browser and run your code on a distant supercomputer over in RStudio headquarters. Pretty cool, right!
The Melbourne Research Cloud provides Infrastructure-as-a-Service cloud computing to the University of Melbourne researchers, providing access to a robust set of on-demand virtualized computing resources (such as servers and storage). The service makes it easy for researchers to quickly access scalable computational power as their research grows, without the overhead of spending precious time and money setting up their own compute environment.
Now that we've got our R toolbox and RStudio workshop, it's time to go ahead and add some tools, known in R lingo as packages. These packages provide extra functionality above and beyond what you can do using just R. Today we're going to install the tidyverse package, a set of tools for wrangling and analysing tidy data (more on that later).
To install this package, go ahead and open RStudio and paste the following into the interactive console (the panel on the left of RStudio),
and hit enter on your keyboard to execute this code.
You now have everything you need to get started with your RStudio journey!