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BOOKDOWN


WRITE HTML, PDF, EPUB, AND KINDLE BOOKS WITH R MARKDOWN

The bookdown package is an open-source R package that facilitates writing books
and long-form articles/reports with R Markdown. Features include:

 * Generate printer-ready books and ebooks from R Markdown documents.
 * A markup language easier to learn than LaTeX, and to write elements such as
   section headers, lists, quotes, figures, tables, and citations.
 * Multiple choices of output formats: PDF, LaTeX, HTML, EPUB, and Word.
 * Possibility of including dynamic graphics and interactive applications (HTML
   widgets and Shiny apps).
 * Support a wide range of languages: R, C/C++, Python, Fortran, Julia, Shell
   scripts, and SQL, etc.
 * LaTeX equations, theorems, and proofs work for all output formats.
 * Can be published to GitHub, bookdown.org, and any web servers.
 * Integrated with the RStudio IDE.
 * One-click publishing to https://bookdown.org.

Below is a list of featured books. For a full list, please see the archive page.
For the full documentation of the bookdown package, please see the free online
book bookdown: Authoring Books and Technical Documents with R Markdown.


R GRAPHICS COOKBOOK, 2ND EDITION


BY WINSTON CHANG

2023-04-25

This cookbook contains more than 150 recipes to help scientists, engineers,
programmers, and data analysts generate high-quality graphs quickly—without
having to comb through all the details of R’s graphing systems. Each recipe
tackles a specific problem with a solution you can apply to your own project and
includes a discussion of how and why the recipe works. […] Welcome to the R
Graphics Cookbook, a practical guide that provides more than 150 recipes to help
you generate high-quality graphs quickly, without having to comb through all the
details of R’s graphing systems. Each recipe … Read more →

1


STATISTICAL INFERENCE VIA DATA SCIENCE


BY CHESTER ISMAY AND ALBERT Y. KIM

2023-04-20

An open-source and fully-reproducible electronic textbook for teaching
statistical inference using tidyverse data science tools. […] This is the
website for Statistical Inference via Data Science: A ModernDive into R and the
Tidyverse! Visit the GitHub repository for this site and find the book on
Amazon. You can also purchase it at CRC Press. This work by Chester Ismay and
Albert Y. Kim is licensed under a Creative Commons
Attribution-NonCommercial-ShareAlike 4.0 International … Read more →

2


GEOCOMPUTATION WITH R


BY ROBIN LOVELACE, JAKUB NOWOSAD, JANNES MUENCHOW

2023-04-18

Welcome | Geocomputation with R is for people who want to analyze, visualize and
model geographic data with open source software. It is based on R, a statistical
programming language that has powerful data processing, visualization, and
geospatial capabilities. The book equips you with the knowledge and skills to
tackle a wide range of issues manifested in geographic data, including those
with scientific, societal, and environmental implications. This book will
interest people from many backgrounds, especially Geographic Information Systems
(GIS) users interested in applying their domain-specific knowledge in a powerful
open source language for data science, and R users interested in extending their
skills to handle spatial data. Read more →

3


BOOKDOWN: AUTHORING BOOKS AND TECHNICAL DOCUMENTS WITH R MARKDOWN


BY YIHUI XIE

2023-04-17

A guide to authoring books with R Markdown, including how to generate figures
and tables, and insert cross-references, citations, HTML widgets, and Shiny apps
in R Markdown. The book can be exported to HTML, PDF, and e-books (e.g. EPUB).
The book style is customizable. You can easily write and preview the book in
RStudio IDE or other editors, and host the book wherever you want
(e.g. bookdown.org). Read more →

4


R MARKDOWN: THE DEFINITIVE GUIDE


BY YIHUI XIE, J. J. ALLAIRE, GARRETT GROLEMUND

2023-04-06

The first official book authored by the core R Markdown developers that provides
a comprehensive and accurate reference to the R Markdown ecosystem. With R
Markdown, you can easily create reproducible data analysis reports,
presentations, dashboards, interactive applications, books, dissertations,
websites, and journal articles, while enjoying the simplicity of Markdown and
the great power of R and other languages. Read more →

5


BLOGDOWN: CREATING WEBSITES WITH R MARKDOWN


BY YIHUI XIE, AMBER THOMAS, ALISON PRESMANES HILL

2023-03-17

A guide to creating websites with R Markdown and the R package blogdown. […] A
note from the authors: Some of the information and instructions in this book are
now out of date because of changes to Hugo and the blogdown package. If you have
suggestions for improving this book, please file an issue in our GitHub
repository. Thanks for your patience while we work to update the book, and
please stay tuned for the revised version! In the meantime, you can find an
introduction to the changes and new features in the v1.0 release blog post and
this “Up & running with blogdown in 2021” blog post. … Read more →

6


R MARKDOWN COOKBOOK


BY YIHUI XIE, CHRISTOPHE DERVIEUX, EMILY RIEDERER

2022-11-07

This book showcases short, practical examples of lesser-known tips and tricks to
helps users get the most out of these tools. After reading this book, you will
understand how R Markdown documents are transformed from plain text and how you
may customize nearly every step of this processing. For example, you will learn
how to dynamically create content from R code, reference code in other documents
or chunks, control the formatting with customer templates, fine-tune how your
code is processed, and incorporate multiple languages into your analysis. Read
more →

7


TEXT MINING WITH R


BY JULIA SILGE AND DAVID ROBINSON

2022-11-02

A guide to text analysis within the tidy data framework, using the tidytext
package and other tidy tools […] This is the website for Text Mining with R!
Visit the GitHub repository for this site, find the book at O’Reilly, or buy it
on Amazon. This work by Julia Silge and David Robinson is licensed under a
Creative Commons Attribution-NonCommercial-ShareAlike 3.0 United States License.
… Read more →

8


R PROGRAMMING FOR DATA SCIENCE


BY ROGER D. PENG

2022-05-31

The R programming language has become the de facto programming language for data
science. Its flexibility, power, sophistication, and expressiveness have made it
an invaluable tool for data scientists around the world. This book is about the
fundamentals of R programming. You will get started with the basics of the
language, learn how to manipulate datasets, how to write functions, and how to
debug and optimize code. With the fundamentals provided in this book, you will
have a solid foundation on which to build your data science toolbox. Read more →

9


EFFICIENT R PROGRAMMING


BY COLIN GILLESPIE, ROBIN LOVELACE

2021-03-18

Efficient R Programming is about increasing the amount of work you can do with R
in a given amount of time. It’s about both computational and programmer
efficiency. […] This is the online version of the O’Reilly book: Efficient R
programming. Pull requests and general comments are welcome. Get a hard copy
from: Amazon (UK), Amazon (USA), O’Reilly Colin Gillespie is Senior Lecturer
(Associate Professor) at Newcastle University, UK. He is an Executive Editor of
the R Journal, with research interests including high performance statistical
computing and Bayesian statistics. Colin founded the … Read more →

10


BEYOND MULTIPLE LINEAR REGRESSION


BY PAUL ROBACK AND JULIE LEGLER

2021-01-26

An applied textbook on generalized linear models and multilevel models for
advanced undergraduates, featuring many real, unique data sets. It is intended
to be accessible to undergraduate students who have successfully completed a
regression course. Even though there is no mathematical prerequisite, we still
introduce fairly sophisticated topics such as likelihood theory, zero-inflated
Poisson, and parametric bootstrapping in an intuitive and applied manner. We
believe strongly in case studies featuring real data and real research
questions; thus, most of the data in the textbook arises from collaborative
research conducted by the authors and their students, or from student projects.
Our goal is that, after working through this material, students will develop an
expanded toolkit and a greater appreciation for the wider world of data and
statistical modeling. Read more →

11


ADVANCED R


BY HADLEY WICKHAM

2023-04-27*

This is the website for 2nd edition of “Advanced R”, a book in Chapman & Hall’s
R Series. The book is designed primarily for R users who want to improve their
programming skills and understanding of the language. It should also be useful
for programmers coming to R from other languages, as help you to understand why
R works the way it does. If you’re looking for the 1st edition, you can find it
at http://adv-r.had.co.nz/. This work, as a whole, is licensed under a Creative
Commons Attribution-NonCommercial-ShareAlike 4.0 International License. The code
contained in this book is simultaneously … Read more →

12


DATA SCIENCE AT THE COMMAND LINE, 2E


BY JEROEN JANSSENS

2023-04-27*

This thoroughly revised guide demonstrates how the flexibility of the command
line can help you become a more efficient and productive data scientist. You’ll
learn how to combine small yet powerful command-line tools to quickly obtain,
scrub, explore, and model your data. To get you started, author Jeroen Janssens
provides a Docker image packed with over 100 Unix power tools—useful whether you
work with Windows, macOS, or Linux. Read more →

13


DATA SCIENCE LIVE BOOK


BY PABLO CASAS

2023-04-27*

An intuitive and practical approach to data analysis, data preparation and
machine learning, suitable for all ages! […] This book is now available at
Amazon. Check it out! 📗 🚀. Link to the black & white version, also available
on full-color. It can be shipped to over 100 countries. 🌎 The book will
facilitate the understanding of common issues when data analysis and machine
learning are done. Building a predictive model is as difficult as one line of R
code: That’s it. But, data has its dirtiness in practice. We need to sculp it,
just like an artist does, to expose its information in order … Read more →

14


DATA VISUALIZATION


BY KIERAN HEALY

2023-04-27*

A practical introduction. […] Published by Princeton University Press.
Incomplete draft. This version: 2018-04-25. You should look at your data. Graphs
and charts let you explore and learn about the structure of the information you
collect. Good data visualizations also make it easier to communicate your ideas
and findings to other people. Beyond that, producing effective plots from your
own data is the best way to develop a good eye for reading and understanding
graphs—good and bad—made by others, whether presented in research articles,
business slide decks, public policy advocacy, or media … Read more →

15


ENGINEERING PRODUCTION-GRADE SHINY APPS


BY COLIN FAY, SÉBASTIEN ROCHETTE, VINCENT GUYADER, CERVAN GIRARD

2023-04-27*

A book about engineering shiny application that will later be sent to
production. This book cover project management, structuring your project,
building a solid testing suite, and optimizing your codebase. We describe in
this book a specific workflow: design, prototype, build, strengthen and deploy.
[…] Welcome to “Engineering Production-Grade Shiny Apps” by Colin Fay, Sébastien
Rochette, Vincent Guyader and Cervan Girard. This book is available in print,
published in the R Series by Chapman and Hall/CRC. You can grab a copy on
routledge.com. The online version of this book is free to read … Read more →

16


FORECASTING: PRINCIPLES AND PRACTICE (2ND ED)


BY OTEXTS.COM

2023-04-27*

This is the second edition of Forecasting: Principles & Practice, which uses the
forecast package in R. The third edition, which uses the fable package, is also
available. Welcome to our online textbook on forecasting. This textbook is
intended to provide a comprehensive introduction to forecasting methods and to
present enough information about each method for readers to be able to use them
sensibly. We don’t attempt to give a thorough discussion of the theoretical
details behind each method, although the references at the end of each chapter
will fill in many of those details. The book is … Read more →

17


FUNDAMENTALS OF DATA VISUALIZATION


BY CLAUS O. WILKE

2023-04-27*

A guide to making visualizations that accurately reflect the data, tell a story,
and look professional. […] This is the website for the book “Fundamentals of
Data Visualization,” published by O’Reilly Media, Inc. The website contains the
complete author manuscript before final copy-editing and other quality control.
If you would like to order an official hardcopy or ebook, you can do so at
various resellers, including Amazon, Barnes and Noble, Google Play, or Powells.
The book is meant as a guide to making visualizations that accurately reflect
the data, tell a story, and look professional. … Read more →

18


HANDS-ON PROGRAMMING WITH R


BY GARRETT GROLEMUND

2023-04-27*

This book will teach you how to program in R, with hands-on examples. I wrote it
for non-programmers to provide a friendly introduction to the R language. You’ll
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. Throughout the book, you’ll use your newfound skills to solve practical
data science problems. Read more →

19


INTRODUCTION TO DATA SCIENCE


BY RAFAEL A. IRIZARRY

2023-04-27*

This book introduces concepts and skills that can help you tackle real-world
data analysis challenges. It covers concepts from probability, statistical
inference, linear regression and machine learning and helps you develop skills
such as R programming, data wrangling with dplyr, data visualization with
ggplot2, file organization with UNIX/Linux shell, version control with GitHub,
and reproducible document preparation with R markdown. Read more →

20


R FOR DATA SCIENCE


BY HADLEY WICKHAM AND GARRETT GROLEMUND

2023-04-27*

This book will teach you how to do data science with R: You’ll learn how to get
your data into R, get it into the most useful structure, transform it, visualise
it and model it. In this book, you will find a practicum of skills for data
science. Just as a chemist learns how to clean test tubes and stock a lab,
you’ll learn how to clean data and draw plots—and many other things besides.
These are the skills that allow data science to happen, and here you will find
the best practices for doing each of these things with R. You’ll learn how to
use the grammar of graphics, literate programming, and reproducible research to
save time. You’ll also learn how to manage cognitive resources to facilitate
discoveries when wrangling, visualising, and exploring data. Read more →

21


R PACKAGES (2E)


BY HADLEY WICKHAM AND JENNIFER BRYAN

2023-04-27*

Learn how to create a package, the fundamental unit of shareable, reusable, and
reproducible R code. Hadley Wickham and Jennifer Bryan Welcome to R packages by
Hadley Wickham and Jennifer Bryan. Packages are the fundamental units of
reproducible R code. They include reusable R functions, the documentation that
describes how to use them, and sample data. In this book you’ll learn how to
turn your code into packages that others can easily download and use. Writing a
package can seem overwhelming at first. So start with the basics and improve it
over time. It doesn’t matter if your first version … Read more →

22
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