Computerworld’s Beginners Guide to R

June 17, 2013
By

(This article was first published on Revolutions, and kindly contributed to R-bloggers)

Sharon Machlis is not only the online managing editor at Computerworld, she's also a budding data scientist who recently started learning the R language. To the benefit of all other new R users, she's shared her learnings in an excellent 6-part beginners guide to R, published by Computerworld. It's jam-packed with useful information for anyone getting started with R, interspersed with handy links to source materials if you want to go in-depth. She explains the goals of the guide as follows: 

Our aim here isn't R mastery, but giving you a path to start using R for basic data work: Extracting key statistics out of a data set, exploring a data set with basic graphics and reshaping data to make it easier to analyze.

Each of the six parts is concentrated on a theme, and provides pages of useful content. Here's a quick rundown:

Part 1: Introduction. This section provides an overview of why you should care about R (and in particular, the importance of reproducible research). You'll learn how to download R and the R commands you'll use in your first R session.

Part 2: Getting your data into R. You'll start by playing with R's buit-in data sets and quickly progress to importing data from text files. Also provided are pointers on reading data from other formats, including from databases using SQL queries, and from Google Spreadsheets. You'll also learn how to use public data sources like Quantmod, Quandl and DataMarket.

Part 3: Easy ways to do basic data analysis. This section covers looking at data, calculating summary statistics, subsetting data, and creating tables.

Part 4: Painless data visualization. This section covers basic R graphics (scatterplots, bar graphs and histograms), and also covers the more advanced (and better looking) graphics created by the ggplot2 package. There's also some useful guidance on choosing colors for color-coded charts and how to export graphics to a file. (However, I'll chime in and say don't use JPG for statistical graphics — it's almost always a bad choice.)

Part 5: Syntax quirks you'll want to know: An important topic most tutorials ignore, this section explains some of the R mysteries that may be stumbling blocks, especially for programmers familiar with other languages. There are also many useful tidbits on R data types, loops and even how to use SQL with R objects.

Part 6: Useful resources. This is a very comprehensive list of other resources to learn more about R. Included here are recommended R books (including R for Dummies, co-authored by Revolution Analytics' Andrie de Vries), online references, videos, online tutorials, communities, and blogs. There's also a pointer to software to enhance R, including RStudio and Revolution R Enterprise

If you're just getting started with R, this is a great resource to accelerate your learning. And even if you've already spent some time with R, the abundant links (and especially Part 6) are a great launching point for a deeper dive into specialized topics. It's well worth checking out: get started with Part 1 at the link below.

Computerworld: Beginner's guide to R: Introduction

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