Originally published at: http://www.sitepoint.com/introduction-r-rstudio/
With increased computing power comes increased access to large amounts of freely accessible data. People are tracking their lives with productivity, calorie, fitness and sleep trackers. Governments are publishing survey data left and right, and companies conduct audience testing that needs analyzing. There’s a lot of data out there even now, ready to be grabbed and looked at.
In this tutorial, we’ll look at the basics of the R programming language – a language built solely for statistical computing. I won’t bore you with Wikipedia definitions – instead, let’s dive right into it. In this introduction, we’ll cover the installation of the default IDE and language, and its data types.
R is both a programming language and a software environment, which means it’s fully self-contained. There are two steps to getting it installed:
- download and install the latest R: http://www.r-project.org/
- download and install RStudio, the R IDE: http://www.rstudio.com/
Both are free, both open source. R will be installed as the underlying engine that powers RStudio’s computations, while RStudio will provide sample data, command autocompletion, help files, and an effective interface for getting things done quickly. You could write R code in simple text files as in most other languages, but that’s really not recommended given how many commands there are and how complex things can quickly get.
After you’ve installed the tools, launch R Studio.
Let’s briefly explain the GUI. There are four main parts. I’ll explain the default order, though note that this can be changed in Settings/Preferences -> Pane Layout.