Introduction to R and RStudio

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.

Graphs and Analytics

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.

Installing

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:

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.

RStudio IDE

IDE Areas

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.

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This is very intriguing. When I was studying at Cornell I used to get a taste of the programming language R, which is used for statistics in a transportation engineering course. It was very good read, thanks.

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Thanks! More R stuff coming soon!

Thank you for sharing us your ideas on R and Rstudio. Looks great!

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Thanks so much for this article and looking forward to future posts. Would really love seeing how to use functions effectively and using custom functions based on existing functions and libraries.

Love to see how to use R with JavaScript in the web would be great too.

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