R and Python are currently the top programming languages preferred for accomplishing data science and so they have a fair share of advantages and disadvantages over one another.
Python is preferred for Machine Learning owing to its production-ready built and the ease of integrating data analysis with web apps. Whereas R is preferred by data miners and statisticians for developing statistical computing software by virtue of its inherent statistical nature.
R is a complete platform for statistical programming and not only a programming language. So in this article, we are going to focus on the best R books that will help you realize your dream of working in the lucrative field of data science or make you better at it if you’re already living the dream.
Best R Books
Before we begin, take note that this is the list of 10 best R books in a general way i.e. we aren’t comparing these books among themselves. The book detailed at number 1 need not be better than the book mentioned on number 2 and others. Also all of them are worthy – in our opinion – to be on the list.
1. R in Action
Latest Edition – Second
Formats Available – Paperback
Publisher – Dreamtech Press
Reading Level – Beginner/Intermediate
Ratings:
- Amazon – 4.5/5(141 ratings)
- Goodreads – 4.2/5 (233 votes)
Since that aside from maintaining the popular Quick-R website, Dr. Robert L. Kabacoff has penned several great books on R, including R in Action. Also The book detailing R, now in its second edition, presents readers with detailed real-world examples belonging to business, science, and technology.
In addition to detailing real data science scenarios and practical R-based solutions, the R in Action book offers a crash course in statistics. This primarily involves detailing powerful methods for making sense out of incomplete, unclear, vast amounts of data.
R in Action also details out the graphical capabilities of R for exploring, managing, and solving data visualization challenges. The latest edition of the R in Action book adds more chapters that detail data mining, dynamic report writing, and forecasting.
Topics covered:
- Basics of ggplot2.
- Data mining.
- Data visualization.
- EDA (Exploratory Data Analysis).
- Graphics in R.
- Machine learning models.
2. R for Data Science
Latest Edition – First
Formats Available – Kindle and Paperback
Publisher – O’Reilly
Reading Level – Beginner
Ratings:
- Amazon – 4.7 (666 ratings)
- Goodreads – 4.6 (640 votes)
Hadley Wickham is a reputed writer when it comes to writing about the inner (and outer) workings of the R programming language, and also data science. The R for Data Science is a complete package for readers interested in dissecting and digesting both data science and R served from a single plate.
The R for Data Science book begins with developing a holistic understanding of data science, the implementation of the discipline, and the science behind it as well. Sooner from the early chapters, the book picks up the pace on leveraging the R platform for accomplishing various data science tasks and operations.
The (credited) main author of the book – Garrett Grolemund – is a Master Instructor at RStudio – takes on the mantle to explain the practical, real-world implementation of the synergy among R and data science in a way that is both captivating and motivating to do and know more.
Topics covered:
- Data wrangling.
- Data visualization.
- Exploratory data analysis.
- Fundamentals of R.
- Fundamentals of data science.
- Implementation of R and data science.
3. The Art of R Programming – A Tour of Statistical Software Design
Latest Edition – First
Formats Available – Kindle and Paperback
Publisher – No Starch Press
Reading Level – Beginner
Ratings:
- Amazon – 4.4/5 (200 ratings)
- Goodreads – 4.1/5 (533 votes)
Another book that secures its place among the best R books is The Art of R Programming by Norman Matloff. The author of the book is the creator of several popular software packages as well as serves as a Professor of Computer Science at the University of California. So, learning from him, is obviously, great.
The Art of R Programming doesn’t require any statistical knowledge and will work for you even if you’re having a low-level/beginner-level competency in programming. Hence, it is a perfect fit for beginners. The R Programming book offers a thorough understanding of software development using R.
Also other than R and software development, The Art of R Programming also covers object-oriented and functional programming paradigms, complex data rearrangement, and running mathematical simulations.
Topics covered:
- Complex functions.
- Data visualization.
- Fundamentals of R.
- Statistical programming.
- Statistical software development.
4. Hands-On Programming with R: Write Your Own Functions and Simulations
Latest Edition – First
Formats Available – Kindle and Paperback
Publisher – Shroff/O’Reilly
Reading Level – Intermediate
Ratings:
- Amazon – 4.4/5 (131 ratings)
- Goodreads – 4.4/5 (129 votes)
The Hands-On Programming with R book details assembling and disassembling data objects, loading data, navigating the R environment, using the tools available for R, and developing user-defined functions. The book does so using an easy-to-comprehend language.
To make learning fun, The Hands-On Programming with R book features 3 casino-games-inspired practical data analysis projects. Each includes comprehensive examples that involve using a range of R programming skills, such as data visualization and modeling.
Hands-On Programming with R is written by Garrett Grolemund, the RStudio Master Instructor who is also the co-author of another superb book based on the R platform, R for Data Science. Aside from focusing on R, the instructor uses the book to educate readers about data science and the art of programming.
Topics covered:
- Basics of R.
- Data modeling.
- Data visualization.
- Fundamentals of data science.
- Complementary R tools and software.
5. R Graphics Cookbook: Practical Recipes for Visualizing Data
Latest Edition – Second
Formats Available – Kindle and Paperback
Publisher – Shroff/O’Reilly
Reading Level – Advanced
Ratings:
- Amazon – 4.6/5 (33 ratings)
- Goodreads – 4.2/5 (261 votes)
For readers seeking a book that vividly explains R but stays focused on its graphical capabilities, an excellent read is the R Graphics Cookbook. It features 150+ illustrations, called recipes, for generating high-quality graphics quickly using the R platform.
Each recipe takes on a specific problem with a detailed solution. The why and how of the so-called recipe is also explained in detail so as to develop a robust understanding of the related concepts among the readers. Most examples leverage the extensively popular ggplot2 package.
The R Graphics Cookbook is written by Winston Chang, a software engineer at RStudio. Interestingly, the R Graphics Cookbook is an updated version of the author’s past project, the Cookbook for R. It was a website detailing programs for efficiently handling the usual tasks in R.
Topics covered:
- Data visualization.
- Graphics in R.
- Solutions to common/redundant tasks.
- The visual design of graphics.
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