Advanced R helps you understand how R works at a fundamental level.
It is designed for R programmers who want to deepen their
understanding of the language, and programmers experienced in other
languages who want to understand what makes R different and
special. This book will teach you the foundations of R; three
fundamental programming paradigms (functional, object-oriented, and
metaprogramming); and powerful techniques for debugging and
optimising your code. By reading this book, you will learn: The
difference between an object and its name, and why the distinction
is important The important vector data structures, how they fit
together, and how you can pull them apart using subsetting The fine
details of functions and environments The condition system, which
powers messages, warnings, and errors The powerful functional
programming paradigm, which can replace many for loops The three
most important OO systems: S3, S4, and R6 The tidy eval toolkit for
metaprogramming, which allows you to manipulate code and control
evaluation Effective debugging techniques that you can deploy,
regardless of how your code is run How to find and remove
performance bottlenecks The second edition is a comprehensive
update: New foundational chapters: "Names and values," "Control
flow," and "Conditions" comprehensive coverage of object oriented
programming with chapters on S3, S4, R6, and how to choose between
them Much deeper coverage of metaprogramming, including the new
tidy evaluation framework use of new package like rlang
(http://rlang.r-lib.org), which provides a clean interface to
low-level operations, and purr (http://purrr.tidyverse.org/) for
functional programming Use of color in code chunks and figures
Hadley Wickham is Chief Scientist at RStudio, an Adjunct Professor
at Stanford University and the University of Auckland, and a member
of the R Foundation. He is the lead developer of the tidyverse, a
collection of R packages, including ggplot2 and dplyr, designed to
support data science. He is also the author of R for Data Science
(with Garrett Grolemund), R Packages, and ggplot2: Elegant Graphics
for Data Analysis.
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