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Learn how to use R to turn data into insight, knowledge, and
understanding. Ideal for current and aspiring data scientists, this
book introduces you to doing data science with R and RStudio, as
well as the tidyverse-a collection of R packages designed to work
together to make data science fast, fluent, and fun. Even if you
have no programming experience, this updated edition will have you
doing data science quickly. You'll learn how to import, transform,
and visualize your data and communicate the results. And you'll get
a complete, big-picture understanding of the data science cycle and
the basic tools you need to manage the details. Each section in
this edition includes exercises to help you practice what you've
learned along the way. Updated for the latest tidyverse best
practices, new chapters dive deeper into visualization and data
wrangling, show you how to get data from spreadsheets, databases,
and websites, and help you make the most of new programming tools.
You'll learn how to: Visualize-create plots for data exploration
and communication of results Transform-discover types of variables
and the tools you can use to work with them Import-get data into R
and in a form convenient for analysis Program-learn R tools for
solving data problems with greater clarity and ease
Communicate-integrate prose, code, and results with Quarto
Turn your R code into packages that others can easily download and
use. This practical book shows you how to bundle reusable R
functions, sample data, and documentation together by applying the
package development philosophy used in the package known as the
tidyverse (and beyond). In the process, you'll work with devtools,
usethis, roxygen2, and testthat, a set of R packages that automate
common development tasks. Ideal for developers and data scientists,
this book gets you creating packages ASAP, then shows you how to
get progressively better over time. You'll learn to focus on what
you want your package to do, rather than thinking about package
structure. Learn the key components of an R package, including
code, documentation, and tests. Get tips on good style, such as
organizing functions into files. Streamline your development
process with usethis, devtools, and RStudio. Create high quality
packages by combining unit tests and continuous integration on
GitHub. Maximize your chances of a positive CRAN submission. Turn
your existing documentation into a beautiful and user friendly
website with pkgdown.
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.
*When R creates copies, and how it affects memory usage and code
performance *Everything you could ever want to know about functions
*The differences between calling and exiting handlers *How to
employ functional programming to solve modular tasks *The
motivation, mechanics, usage, and limitations of R's highly
pragmatic S3 OO system *The R6 OO system, which is more like OO
programming in other languages *The rules that R uses to parse and
evaluate expressions *How to use metaprogramming to generate HTML
or LaTeX with elegant R code *How to identify and resolve
performance bottlenecks
*When R creates copies, and how it affects memory usage and code
performance *Everything you could ever want to know about functions
*The differences between calling and exiting handlers *How to
employ functional programming to solve modular tasks *The
motivation, mechanics, usage, and limitations of R's highly
pragmatic S3 OO system *The R6 OO system, which is more like OO
programming in other languages *The rules that R uses to parse and
evaluate expressions *How to use metaprogramming to generate HTML
or LaTeX with elegant R code *How to identify and resolve
performance bottlenecks
Master the Shiny web framework-and take your R skills to a whole
new level. By letting you move beyond static reports, Shiny helps
you create fully interactive web apps for data analyses. Users will
be able to jump between datasets, explore different subsets or
facets of the data, run models with parameter values of their
choosing, customize visualizations, and much more. Hadley Wickham
from RStudio shows data scientists, data analysts, statisticians,
and scientific researchers with no knowledge of HTML, CSS, or
JavaScript how to create rich web apps from R. This in-depth guide
provides a learning path that you can follow with confidence, as
you go from a Shiny beginner to an expert developer who can write
large, complex apps that are maintainable and performant. Get
started: Discover how the major pieces of a Shiny app fit together
Put Shiny in action: Explore Shiny functionality with a focus on
code samples, example apps, and useful techniques Master
reactivity: Go deep into the theory and practice of reactive
programming and examine reactive graph components Apply best
practices: Examine useful techniques for making your Shiny apps
work well in production
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.
This new edition to the classic book by ggplot2 creator Hadley
Wickham highlights compatibility with knitr and RStudio. ggplot2 is
a data visualization package for R that helps users create data
graphics, including those that are multi-layered, with ease. With
ggplot2, it's easy to: produce handsome, publication-quality plots
with automatic legends created from the plot specification
superimpose multiple layers (points, lines, maps, tiles, box plots)
from different data sources with automatically adjusted common
scales add customizable smoothers that use powerful modeling
capabilities of R, such as loess, linear models, generalized
additive models, and robust regression save any ggplot2 plot (or
part thereof) for later modification or reuse create custom themes
that capture in-house or journal style requirements and that can
easily be applied to multiple plots approach a graph from a visual
perspective, thinking about how each component of the data is
represented on the final plot This book will be useful to everyone
who has struggled with displaying data in an informative and
attractive way. Some basic knowledge of R is necessary (e.g.,
importing data into R). ggplot2 is a mini-language specifically
tailored for producing graphics, and you'll learn everything you
need in the book. After reading this book you'll be able to produce
graphics customized precisely for your problems, and you'll find it
easy to get graphics out of your head and on to the screen or page.
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