R is a free software environment for statistical computing and graphics. It runs a wide variety of UNIX platforms, Windows and MacOS. It is similar to the S language and was developed a Bell Laboratories (formerly AT&T, now Lucent Technologies). John Chambers and colleagues developed R as a different way to put in place S language.
Why learn R?
If you’re in business, R is a must since it has the best qualities for it. It has a business capability, it is rather easy to learn, free, and is growing very fast. Also, you don’t have to be a rocket scientist to learn this data science, you don’t even have to be a computer scientist because that is not what it is meant for. R is designed so that everyone can have access to data science while still being high-performance.
Or just for fun, if you enjoy programming and are looking to learn a new language R is an easy and fun one.
So, interested now? Here come the books you can use
The Art of R Programming
- Norman Matloff brings a book that goes really easy on you. “The Art of R Programming” is a very simple approach to a very thorough introduction of the R language. The great thing about it is that it is designed assuming you don’t know anything about programming or data science. It’ll leave everything super clear and it is written in a very digestible way.
This book will teach you about functional and object-oriented programming. You’ll learn how to run mathematical simulations, rearrange complex data into much simpler ways, and make these data arrangements useful.
The first few chapters cover the language’s basic data. It introduces various flow control structures. What follows math and simulations in R, giving some good examples of what the language is useful for. After this, the author covers input/output, dealing with strings and R’s graphing capabilities. In the last few chapters, Matloff covers debugging, performance tradeoffs, interfacing R with other programming languages (using functions written in C/C++ from R, as well as using R in Python) and various approaches to parallelizing R.
This book is great because it tackles important issues you’ll face when using R, and shows you how to tackle them easily.
Learning R: A Step-By-Step Function Guide to Data Analysis
What this book will do is introduce concepts from the beginner’s point of view. The great thing about it is that it doesn’t just throw you 500 pages of theory, it will provide you with exercises and tutorials for you to get your code writing on point.
In the first part, you’ll learn the basics. How to set it up, pick an IDE (Integrated Development Environment), and how to write your first program. You’ll also find things about looping constructs, environment, and packages. Later in the book, you’ll read about data analysis in action. Chapters covering topics that range from importing data to publishing results. You’ll learn about modeling, visualizing, and transforming this data.
The thing about R is that you need two skills, programming and data analysis, this book can help you get both.
R in Action
The book begins by introducing the R language, then it goes into databases and datasets. You’ll be getting a crash course on statistics and methods to deal with messy and incomplete data that would otherwise (using traditional methods) be difficult to analyze. All this accompanied by a variety of exercises that help better land the concepts.
This is one of the longest books in the market of R language books, and even though it is pretty clear, the language is still technical and heavy. Some chapters need you to re-read them. Anyway, being so thick and so complete, this is definitely one of the best books on the market.
You’ll not only learn the basics but truly be turned from a novice programmer to a semi-experienced one.
R for everyone
- “R for everyone” by Jared Lander is oriented towards those who want the statistics. How to use R for advanced analytics and graphics for everyday users. The thing is R is kind of hard to learn if you know nothing about statistics. This book tries to teach you that, but, honestly, it won’t be really useful if you don’t have some statistics knowledge.
First, the book gives you an introduction to the R language. What it is, how to set it up, what’s RStudio, R packages, what do I use them for, etc. And that’s where the book taking you by the hand ends.
When you start entering the chapters that cover probability, models using ggplot2, multivariate time series data, hierarchical clustering, etc… It gets a little more complicated.
Anyway, as long as you know a little about statistics and take it slow, this book will have you building powerful statistical models that answer even the most challenging questions.
R for dummies
This book is especially great for those who have no programming experience whatsoever. It’ll start at the very beginning and use tons of practical examples, step-by-step exercises, and sample code. It will guide you through lists, data frames, and other R data structures, while learning to interact with other programs, such as Microsoft Excel.
The only issue with this book is that it really skims the details, and it stays on the very basics of the language. It might be a good place to start but if you want to do more complicated things with R, you’ll need to pick up one of the other, more complex books.