Learning R programming by reading books: A book list #rstats

November 26, 2016
By

(This article was first published on Blog of Statistical Estimation, and kindly contributed to R-bloggers)

R is an open-source software package and rapidly increases its popularity in both industry and academics. Google trend is probably the best tool to show you how popular R is since it allows us to rank the search interest among five major statistical software packages. You can clearly observe that R has been the top search interest since 2011 and continues to maintain its top place.

Despite R’s popularity, it is still very daunting to learn R as R has no click-and-point feature like SPSS and learning R usually takes lots of time. No worries! As self-R learner like us, we constantly receive the requests about how to learn R. Besides hiring someone to teach you or paying tuition fees for online courses, our suggestion is that you can also pick up some books that fit your current R programming level. Therefore, in this post, we would like to share some good books that teach you how to learn programming in R based on three levels: elementary, intermediate, and advanced levels. Each level focuses on one task so you will know whether these books fit your needs. While the following books do not necessarily focus on the task we define, you should focus the task when you reading these books so you are not lost in contexts.

Elementary level: Books introducing R

If you are not a statistics student or graduate, you probably learn statistics from using software like Excel, SPSS, STATA, SAS, Matlab…etc. A great start is to learn R with something that you are familiar with. The following books will help convert your knowledge to learning R.

R books for other statistical software users
Book Cover Extracted summary
Book Title: R Through Excel:
A Spreadsheet Interface for Statistics, Data Analysis, and Graphics

Author: Heiberger, Richard M., Neuwirth, Erich
This book builds on RExcel, a free add-in for Excel that can
be downloaded from the R distribution network. RExcel seamlessly
integrates the entire set of R’s statistical and graphical methods
into Excel
Book Title: R for SAS and SPSS Users
Author: Muenchen, Robert A
This book introduces R using SAS and SPSS terms with which you are
already familiar. It demonstrates which of the add-on packages are
most like SAS and SPSS and compares them to R’s built-in functions.
Book Title: R for Stata Users
Author: Muenchen, Robert A., Hilbe, Joseph M.
This book introduces R using Stata terminology with which you are
already familiar. It steps through more than 30 programs written
in both languages, comparing and contrasting the two packages’
different approaches.
Book Title: R and MATLAB
Author: David E. Hiebeler
This book is designed for users who already know R or MATLAB and
now need to learn the other platform. The book makes the transition
from one platform to the other as quick and painless as possible.
Book Title: Python for R Users
Author: Ajay Ohri
This book is the first of its kind to provide a reference that enables
students and practitioners to easily learn to code in Python if they are
familiar with R and vice versa, even if they are beginners in the second
language. It also provides a detailed introduction and overview of each
language to the reader who might be unfamiliar with the other.

Another way to leverage your knowledge is by using your field knowledge like finance, economics, education…et al. You can find those books in my another post here.

Intermediate level: Books instructing you how to write functions

Books instructing you how to write functions
Book Cover Extracted summary
Book Title: Hands-On Programming with R:
Write Your Own Functions and Simulations

Author: Garrett Grolemund
This book teach you to learn how to load data, assemble
and disassemble data objects, navigate R’s environment
system, write your own functions, and use all of R’s
programming tools.
Book Title: Art of R Programming
Author: Norman Matloff
This book takes you on a guided tour of software
development with R, from basic types and data structures to
advanced topics. No statistical knowledge is required,
and your programming skills can range from hobbyist to pro.
Book Title: Software for Data Analysis
Programming with R

Author: Chambers, John
This book guides the reader through programming with R,
beginning with simple interactive use and progressing by
gradual stages, starting with simple functions.
Book Title: Introduction to Scientific Programming and
Simulation Using R

Author: Owen Jones et al.
This book introduces scientific programming and stochastic
modelling in a clear, practical, and thorough way. Readers
learn programming by experimenting with the provided R code
and data.

Advanced level: Books teaching you how to write packages

Making packages is a great way to share your code and most importantly you will learn how to document your code. The following books do not only teach you how to write a package but also instruct you how to test the code and equip you with great programmer tools and knowledge.

Books teaching you how to write packages
Book Cover Extracted summary
Book Title: R packages
Author: Hadley Wickham
This book shows you how to bundle reusable R functions, sample
data, and documentation together by applying author Hadley
Wickham’s package development philosophy.
Book Title: Extending R
Author: John M. Chambers
This book covers key concepts and techniques in R to support
analysis and research projects. It presents the core ideas of R,
provides programming guidance for projects of all scales, and
introduces new, valuable techniques that extend R.
Book Title: Advanced R
Author: Hadley Wickham
This book presents useful tools and techniques for attacking many
types of R programming problems, helping you avoid mistakes and
dead ends. With more than ten years of experience programming in R,
the author illustrates the elegance, beauty, and flexibility in R.

Notice that the information above is directly collected from the publisher website and we just summarize it for you. Further details about these books can be assessed by clicking the book title links to the book publisher. Happy learning R and hope you enjoy the book list above!

To leave a comment for the author, please follow the link and comment on their blog: Blog of Statistical Estimation.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)