Fans pick 67 books like The R Book

By Michael J. Crawley,

Here are 67 books that The R Book fans have personally recommended if you like The R Book. Shepherd is a community of 12,000+ authors and super readers sharing their favorite books with the world.

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Book cover of R for Data Science: Import, Tidy, Transform, Visualize, and Model Data

Tilman M. Davies Author Of The Book of R: A First Course in Programming and Statistics

From my list on intro to programming and data science with R.

Why am I passionate about this?

I’m an applied statistician and academic researcher/lecturer at New Zealand’s oldest university – the University of Otago. R facilitates everything I do – research, academic publication, and teaching. It’s the latter part of my job that motivated my own book on R. From first-year statistics students who have never seen R to my own Ph.D. students using R to implement novel and highly complex statistical methods and models, my experience is that all ultimately love the ease with which the R language permits exploration, visualisation, analysis, and inference of one’s data. The ever-growing need in today’s society for skilled statisticians and data scientists means there's never been a better time to learn this essential language.

Tilman's book list on intro to programming and data science with R

Tilman M. Davies Why did Tilman love this book?

For those intending to use R with an eye on the popular 'Tidyverse' suite of packages – which facilitate the handling, manipulation, and visualisation of data setsit's hard to go past this book. From the founding contributors of the RStudio/Tidyverse worlds, this is a great way to learn about this dialect of R against the overarching backdrop of statistical data analysis and data science.

By Hadley Wickham, Garrett Grolemund,

Why should I read it?

1 author picked R for Data Science as one of their favorite books, and they share why you should read it.

What is this book about?

Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along…


Book cover of R in Action: Data Analysis and Graphics with R

Tilman M. Davies Author Of The Book of R: A First Course in Programming and Statistics

From my list on intro to programming and data science with R.

Why am I passionate about this?

I’m an applied statistician and academic researcher/lecturer at New Zealand’s oldest university – the University of Otago. R facilitates everything I do – research, academic publication, and teaching. It’s the latter part of my job that motivated my own book on R. From first-year statistics students who have never seen R to my own Ph.D. students using R to implement novel and highly complex statistical methods and models, my experience is that all ultimately love the ease with which the R language permits exploration, visualisation, analysis, and inference of one’s data. The ever-growing need in today’s society for skilled statisticians and data scientists means there's never been a better time to learn this essential language.

Tilman's book list on intro to programming and data science with R

Tilman M. Davies Why did Tilman love this book?

This provides a superb balance between technical aspects of R coding and the statistical methods that motivate its use. It's rare to find a book on topics like this that are written with Kabacoff's easygoing yet precise style, which makes it ideal for beginners. From my own experience, it is obvious the author has spent many years teaching this type of content, knowing where things deserve extra explanation up front and where other more technical details can be relegated to more advanced texts.

By Robert I. Kabacoff,

Why should I read it?

1 author picked R in Action as one of their favorite books, and they share why you should read it.

What is this book about?

DESCRIPTION

R is a powerful language for statistical computing and graphics that can handle virtually any data-crunching task. It runs on all important platforms and provides thousands of useful specialized modules and utilities. This makes R a great way to get meaningful information from mountains of raw data.



R in Action, Second Edition is language tutorial focused on practical problems. Written by a research methodologist, it takes a direct and modular approach to quickly give readers the information they need to produce useful results. Focusing on realistic data analyses and a comprehensive integration of graphics, it follows the steps that…


Book cover of R For Dummies

Tilman M. Davies Author Of The Book of R: A First Course in Programming and Statistics

From my list on intro to programming and data science with R.

Why am I passionate about this?

I’m an applied statistician and academic researcher/lecturer at New Zealand’s oldest university – the University of Otago. R facilitates everything I do – research, academic publication, and teaching. It’s the latter part of my job that motivated my own book on R. From first-year statistics students who have never seen R to my own Ph.D. students using R to implement novel and highly complex statistical methods and models, my experience is that all ultimately love the ease with which the R language permits exploration, visualisation, analysis, and inference of one’s data. The ever-growing need in today’s society for skilled statisticians and data scientists means there's never been a better time to learn this essential language.

Tilman's book list on intro to programming and data science with R

Tilman M. Davies Why did Tilman love this book?

A gentle yet detailed book for beginner programmers. A great book for those who know they'll be getting up to some programming in R but who are very new to programming in general. The book's chapters are filled with content on the syntax, usage, and 'best practice' guidelines. The examples guide the reader in a step-by-step fashion to maximise understanding. An especially unique chapter providing examples on things you can do in R that you might've otherwise done in Excel is one of its stand-out features.

By Andrie De Vries, Joris Meys,

Why should I read it?

1 author picked R For Dummies as one of their favorite books, and they share why you should read it.

What is this book about?

Mastering R has never been easier Picking up R can be tough, even for seasoned statisticians and data analysts. R For Dummies, 2nd Edition provides a quick and painless way to master all the R you'll ever need. Requiring no prior programming experience and packed with tons of practical examples, step-by-step exercises, and sample code, this friendly and accessible guide shows you how to know your way around lists, data frames, and other R data structures, while learning to interact with other programs, such as Microsoft Excel. You'll learn how to reshape and manipulate data, merge data sets, split and…


Book cover of A First Course in Statistical Programming with R

Tilman M. Davies Author Of The Book of R: A First Course in Programming and Statistics

From my list on intro to programming and data science with R.

Why am I passionate about this?

I’m an applied statistician and academic researcher/lecturer at New Zealand’s oldest university – the University of Otago. R facilitates everything I do – research, academic publication, and teaching. It’s the latter part of my job that motivated my own book on R. From first-year statistics students who have never seen R to my own Ph.D. students using R to implement novel and highly complex statistical methods and models, my experience is that all ultimately love the ease with which the R language permits exploration, visualisation, analysis, and inference of one’s data. The ever-growing need in today’s society for skilled statisticians and data scientists means there's never been a better time to learn this essential language.

Tilman's book list on intro to programming and data science with R

Tilman M. Davies Why did Tilman love this book?

From well-known authorities in the R-sphere (including a former R Core Team member), this is a long-standing text whose first edition was one of the early books intended to teach R to beginners. It provides concise instructions and examples on how R is used as a programming language before focusing on 'number-crunching' statistical methods that are typically seen as computationally intensive. One of the notable features of this book is the statistical methods at hand are not just illustrated using 'black-box' code--the reader is provided with the necessary mathematical detail to understand what's going on behind the scenes for those that are so inclined.

By W. John Braun, Duncan J. Murdoch,

Why should I read it?

1 author picked A First Course in Statistical Programming with R as one of their favorite books, and they share why you should read it.

What is this book about?

This third edition of Braun and Murdoch's bestselling textbook now includes discussion of the use and design principles of the tidyverse packages in R, including expanded coverage of ggplot2, and R Markdown. The expanded simulation chapter introduces the Box-Muller and Metropolis-Hastings algorithms. New examples and exercises have been added throughout. This is the only introduction you'll need to start programming in R, the computing standard for analyzing data. This book comes with real R code that teaches the standards of the language. Unlike other introductory books on the R system, this book emphasizes portable programming skills that apply to most…


Book cover of Computer Age Statistical Inference, Algorithms, Evidence, and Data Science

Ron S. Kenett Author Of The Real Work of Data Science: Turning Data into Information, Better Decisions, and Stronger Organizations

From my list on how numbers turn into information.

Why am I passionate about this?

I was trained as a mathematician but have always been motivated by problem-solving challenges. Statistics and analytics combine mathematical models with statistical thinking. My career has always focused on this combination and, as a statistician, you can apply it in a wide range of domains. The advent of big data and machine learning algorithms has opened up new opportunities for applied statisticians. This perspective complements computer science views on how to address data science. The Real Work of Data Science, covers 18 areas (18 chapters) that need to be pushed forward in order to turning data into information, better decisions, and stronger organizations

Ron's book list on how numbers turn into information

Ron S. Kenett Why did Ron love this book?

The text covers classic statistical inference, early computer-age methods, and twenty-century topics. This puts a unique perspective on current analytic technologies labeled machine learning, artificial intelligence, and statical learning. The examples used provide a powerful description of the methods covered and the compare and contrast sections highlight the evolution of analytics. This book by Efron and Hastie is a natural follow-up source for readers interested in more details.

By Bradley Efron, Trevor Hastie,

Why should I read it?

2 authors picked Computer Age Statistical Inference, Algorithms, Evidence, and Data Science as one of their favorite books, and they share why you should read it.

What is this book about?

The twenty-first century has seen a breathtaking expansion of statistical methodology, both in scope and influence. 'Data science' and 'machine learning' have become familiar terms in the news, as statistical methods are brought to bear upon the enormous data sets of modern science and commerce. How did we get here? And where are we going? How does it all fit together? Now in paperback and fortified with exercises, this book delivers a concentrated course in modern statistical thinking. Beginning with classical inferential theories - Bayesian, frequentist, Fisherian - individual chapters take up a series of influential topics: survival analysis, logistic…


Book cover of All-in On AI: How Smart Companies Win Big with Artificial Intelligence

Roger W. Hoerl Author Of Statistical Thinking: Improving Business Performance

From my list on AI and data science that are actually readable.

Why am I passionate about this?

As a professional statistician, I am naturally interested in AI and data science. However, in our current information age, everyone, in all segments of society, needs to understand the basics of AI and data science. These basics include such things as what these disciplines are, what they can contribute to society, and perhaps most importantly, what can go wrong. However, I have found that much of the literature on these topics is highly technical and beyond the reach of most readers. These books are specifically selected because they are readable by virtually everyone, and yet convey the key concepts needed to be data-literate in the 21st century. Enjoy!

Roger's book list on AI and data science that are actually readable

Roger W. Hoerl Why did Roger love this book?

Books on AI often go to extremes, either promoting it as the solution to all the world’s problems, or depicting it as an evil that will destroy humanity.

This book is much more practical, and based on experience using AI in actual business applications. It is the result of considerable research, involving investigation of applications not only in silicon-valley, but from various business sectors, such as Airbus, Ping, Progressive Insurance, and Capital One Bank.

Don’t let the title fool you; this book is not simply a promotion of AI, but addresses the practical issues that have to be considered if success is to be achieved. For example, they argue that “the most important aspect in AI success is not machinery, but human leadership, behavior, and change.”

By Thomas H. Davenport, Nitin Mittal,

Why should I read it?

2 authors picked All-in On AI as one of their favorite books, and they share why you should read it.

What is this book about?

A Wall Street Journal bestseller

A Publisher's Weekly bestseller

A fascinating look at the trailblazing companies using artificial intelligence to create new competitive advantage, from the author of the business classic, Competing on Analytics, and the head of Deloitte's US AI practice.

Though most organizations are placing modest bets on artificial intelligence, there is a world-class group of companies that are going all-in on the technology and radically transforming their products, processes, strategies, customer relationships, and cultures.

Though these organizations represent less than 1 percent of large companies, they are all high performers in their industries. They have better business…


Book cover of Nicely Said: Writing for the Web with Style and Purpose

Rachel McConnell Author Of Why You Need a Content Team and How to Build One

From my list on copywriters looking to move into UX content design.

Why am I passionate about this?

I moved into content design from a career in brand and marketing, at a time when the discipline was emerging and not many people really knew what it was. Much of my time since has been spent educating people and organisations and sharing knowledge to help them make better content decisions. Throughout this time, I’ve learnt most of what I know through the experience of working with the design teams, but so many books have also helped me along the way and made my work so much better. I love content design – having the power to improve people's experiences with brands through words is so rewarding, and these books will inspire others to do the same.

Rachel's book list on copywriters looking to move into UX content design

Rachel McConnell Why did Rachel love this book?

I’m picking this book because it’s actually useful for anyone in content, whether you’re a marketing strategist, UX writer, or content designer. It’s easy to read, and a lovely overview of creating more effective content – with guidance on how to adapt tone for different scenarios, and a brilliant exercise for proposition development. It was one of the first books I read about web content, and still one of the books I refer back to again and again.

By Nicole Fenton, Kate Kiefer-Lee,

Why should I read it?

1 author picked Nicely Said as one of their favorite books, and they share why you should read it.

What is this book about?

Whether you're new to web writing, or you're a professional writer looking to deepen your skills, this book is for you. You'll learn how to write web copy that addresses your readers' needs and supports your business goals.

Learn from real-world examples and interviews with people who put these ideas into action every day: Kristina Halvorson of Brain Traffic, Tiffani Jones Brown of Pinterest, Randy J. Hunt of Etsy, Gabrielle Blair of Design Mom, Mandy Brown of Editorially, Sarah Richards of GOV.UK, and more.
Topics include:

* Write marketing copy, interface flows, blog posts, legal policies, and emails
* Develop…


Book cover of Processing: A Programming Handbook for Visual Designers and Artists

Scott Murray Author Of Unstuck: Javascript

From my list on learning how to code interactive graphics.

Why am I passionate about this?

I’ve been making web pages since the World Wide Web began in the mid-1990s. Back then, the web was visually quite sparse. It wasn’t until the late 2000s that new browser capabilities let the web get visually interesting and an exciting place for interactive graphics. Graphics are great: they can be informational (like charts and maps) or purely aesthetic. My personal journey of learning to code interactive graphics has been so rewarding that I’ve shared the love with others through teaching creative coding workshops and undergraduate courses. If you’re new to coding or computer graphics, I hope you’ll give one of these books a try!

Scott's book list on learning how to code interactive graphics

Scott Murray Why did Scott love this book?

This book changed my life. Known simply as “the blue book” in creative coding circles, I discovered this in a bookstore in Cambridge, Mass., just blocks from where Casey and Ben had created Processing at MIT (and then wrote this book). It opened me up to Processing—their programming language for artists and designers—but also to code as a creative medium. Until then, I saw code as a dry, tedious way to fight with computers. Now I know that code can be just as expressive, engaging, and emotional as prose and poetry.

While the syntax in this book is for Processing (which you can download and run on your computer for free), the concepts are equally applicable to p5.js (which runs in a web browser, also for free).

By Casey Reas, Ben Fry,

Why should I read it?

1 author picked Processing as one of their favorite books, and they share why you should read it.

What is this book about?

The new edition of an introduction to computer programming within the context of the visual arts, using the open-source programming language Processing; thoroughly updated throughout.

The visual arts are rapidly changing as media moves into the web, mobile devices, and architecture. When designers and artists learn the basics of writing software, they develop a new form of literacy that enables them to create new media for the present, and to imagine future media that are beyond the capacities of current software tools. This book introduces this new literacy by teaching computer programming within the context of the visual arts. It…


Book cover of The Closed World: Computers and the Politics of Discourse in Cold War America

Philip Mirowski Author Of The Knowledge We Have Lost in Information: The History of Information in Modern Economics

From my list on the politics of science.

Why am I passionate about this?

I am an economist who came to realize that the marketplace of ideas was a political doctrine, and not an empirical description of how we came to know what we think we know. Science has never functioned in the same manner across centuries; it was only during my lifetime that it became recast as a subset of market reality. I have spent a fair amount of effort exploring how economics sought to attain the status of a science; but now the tables have turned. It is now scientists who are trained to become first and foremost market actors, finally elevating the political dominance of the economists.

Philip's book list on the politics of science

Philip Mirowski Why did Philip love this book?

Edwards revealed how the very architecture of early computers owed a debt to the political structures of the Cold War. The innovation of a command/control/information infrastructure set the template for military regimentation, and subsequently for the surveillance society we currently inhabit. The story of how cybernetics—a field that never quite made the grade as pure science—nevertheless conquered the culture, is fascinating.

By Paul Edwards,

Why should I read it?

1 author picked The Closed World as one of their favorite books, and they share why you should read it.

What is this book about?

The Closed World offers a radically new alternative to the canonical histories of computers and cognitive science. Arguing that we can make sense of computers as tools only when we simultaneously grasp their roles as metaphors and political icons, Paul Edwards shows how Cold War social and cultural contexts shaped emerging computer technology―and were transformed, in turn, by information machines.

The Closed World explores three apparently disparate histories―the history of American global power, the history of computing machines, and the history of subjectivity in science and culture―through the lens of the American political imagination. In the process, it reveals intimate…


Book cover of Design Drawing

Alan Hughes Author Of Interior Design Drawing

From my list on exploring interior design and our understanding.

Why am I passionate about this?

As a child my heroes were designers and I thought designers could design across many disciplines, this was what I understood and aspired to. I'm fortunate to have been a designer, illustrator, and design teacher for many years. Passionate about the process I firmly believe if you can design in one area you can design in another. Understanding your material's potential is the key. As a tutor and author my job is to unwrap a student’s talent, support and encourage that unique view through skills building and advice to help them. I believe good design can solve many of the world’s problems and passing on that message is valuable.

Alan's book list on exploring interior design and our understanding

Alan Hughes Why did Alan love this book?

Ching has a great gift for illustrating with his visuals, and his amazing handwritten text, all manner of information about drawing and designing space. This is a comprehensive and instructional book introducing design drawing from basic principles to the communication of designed space as a structural diagram or atmospheric perspective. A wonderful exploration of sketching and drawing methods to illustrate theory, atmosphere, and the communication of three-dimensional space.  For me, it transcended the textbook approach and provided a clear exploration of the communication of design method and its potential outcomes.

By Francis D. K. Ching, Steven P. Juroszek,

Why should I read it?

1 author picked Design Drawing as one of their favorite books, and they share why you should read it.

What is this book about?

THE CLASSIC GUIDE TO DRAWING FOR DESIGNERS, REVISED AND UPDATED TO INCLUDE CURRENT DIGITAL-DRAWING TECHNIQUES

Hand drawing is an integral part of the design process and central to the architecture profession. An architect's precise interpretation and freedom of expression are captured through hand drawing, and it is perhaps the most fundamental skill that the designer must develop in order to communicate thoughts and ideas effectively. In his distinctive style, world-renowned author Francis D. K. Ching presents Design Drawing, Third Edition, the classic guide to hand drawing that clearly demonstrates how to use drawing as a practical tool for formulating and…


Book cover of R for Data Science: Import, Tidy, Transform, Visualize, and Model Data
Book cover of R in Action: Data Analysis and Graphics with R
Book cover of R For Dummies

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5 book lists we think you will like!

Interested in data processing, probability, and data science?

Data Processing 27 books
Probability 21 books
Data Science 24 books