Register your product to gain access to bonus material or receive a coupon.
R in 24 Hours, Sams Teach Yourself
- By Andy Nicholls, Richard Pugh, Aimee Gott
- Published Dec 22, 2015 by Sams. Part of the Sams Teach Yourself series.
Book
- Sorry, this book is no longer in print.
eBook (Watermarked)
- Your Price: $25.59
- List Price: $31.99
- Includes EPUB and PDF
- About eBook Formats
This eBook includes the following formats, accessible from your Account page after purchase:
EPUB
The open industry format known for its reflowable content and usability on supported mobile devices.
PDF
The popular standard, used most often with the free Adobe® Reader® software.
This eBook requires no passwords or activation to read. We customize your eBook by discreetly watermarking it with your name, making it uniquely yours.
About
Features
- Reflects the authors' 10+ years of applied R consulting throughout industry and academia
- Builds skills one step at a time, in 24 one-hour lessons that take reader from the absolute basics to advanced techniques
- Covers importing, manipulating, summarizing, modeling, and plotting data; formalizing analytical code; and building R packages using the latest best practices
- Shows how to use today's most popular and up-to-date analysis packages for R
- Teaches through practical instructions, realistic examples, hands-on workshops, Q-and-As, quizzes, exercises, tips, and more
Description
- Copyright 2016
- Dimensions: 7" x 9-1/8"
- Pages: 624
- Edition: 1st
- Book
- ISBN-10: 0-672-33848-3
- ISBN-13: 978-0-672-33848-9
In just 24 lessons of one hour or less, Sams Teach Yourself R in 24 Hours helps you learn all the R skills you need to solve a wide spectrum of real-world data analysis problems. You’ll master the entire data analysis workflow, learning to build code that’s efficient, reproducible, and suitable for sharing with others.
This book’s straightforward, step-by-step approach teaches you how to import, manipulate, summarize, model, and plot data with R; formalize your analytical code; and build powerful R packages using current best practices.
Practical, hands-on examples show you how to apply what you learn.
Quizzes and exercises help you test your knowledge and stretch your skills.
Learn How To
- Install, configure, and explore the R environment, including RStudio
- Use basic R syntax, objects, and packages
- Create and manage data structures, including vectors, matrices, and arrays
- Understand lists and data frames
- Work with dates, times, and factors
- Use common R functions, and learn to write your own
- Import and export data and connect to databases and spreadsheets
- Use the popular tidyr, dplyr and data.table packages
- Write more efficient R code with profiling, vectorization, and initialization
- Plot data and extend your graphical capabilities with ggplot2 and Lattice graphics
- Develop common types of models
- Construct high-quality packages, both simple and complex
- Write R classes: S3, S4, and Reference Classes
- Use R to generate dynamic reports
- Build web applications with Shiny
Register your book at informit.com/register for convenient access to updates and corrections as they become available.
This book’s source code can be found at http://www.mango-solutions.com/wp/teach-yourself-r-in-24-hours-book/.
Extras
Companion Site
You can find all of the code in this book in an R package called Mango training available from CRAN.
. Sample Content
Online Sample Chapter
Multi-Mode Data Structures in R
Sample Pages
Download the sample pages (includes Chapter 4 and Index)
Table of Contents
Preface xii
HOUR 1: The R Community 1
A Concise History of R 1
The R Community 3
R Development 7
Summary 8
Q&A 8
Workshop 9
Activities 9
HOUR 2: The R Environment 11
Integrated Development Environments 11
R Syntax 14
R Objects 16
Using R Packages 23
Internal Help 28
Summary 29
Q&A 30
Workshop 30
Activities 32
HOUR 3: Single-Mode Data Structures 33
The R Data Types 33
Vectors, Matrices, and Arrays 34
Vectors 35
Matrices 49
Arrays 58
Relationship Between Single-Mode Data Objects 60
Summary 62
Q&A 62
Workshop 63
Activities 64
HOUR 4: Multi-Mode Data Structures 67
Multi-Mode Structures 67
Lists 68
Data Frames 86
Exploring Your Data 93
Summary 98
Q&A 98
Workshop 100
Activities 101
HOUR 5: Dates, Times, and Factors 103
Working with Dates and Times 103
The lubridate Package 107
Working with Categorical Data 108
Summary 112
Q&A 112
Workshop 113
Activities 114
HOUR 6: Common R Utility Functions 115
Using R Functions 115
Functions for Numeric Data 117
Logical Data 121
Missing Data 122
Character Data 123
Summary 125
Q&A 126
Workshop 126
Activities 127
HOUR 7: Writing Functions: Part I 129
The Motivation for Functions 129
Creating a Simple Function 130
The If/Else Structure 136
Summary 146
Q&A 147
Workshop 148
Activities 149
HOUR 8: Writing Functions: Part II 151
Errors and Warnings 151
Checking Inputs 155
The Ellipsis 157
Checking Multivalue Inputs 162
Using Input Definition 164
Summary 168
Q&A 168
Workshop 170
Activities 171
HOUR 9: Loops and Summaries 173
Repetitive Tasks 173
The “apply” Family of Functions 181
The apply Function 183
The lapply Function 195
The sapply Function 204
The tapply Function 208
Summary &