The R Language
Chapter 1 Introduction
Chapter Goals
What Is R?
Installing R
Choosing an IDE
Your First Program
How to Get Help in R
Installing Extra Related Software
Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Exercises
Chapter 2 A Scientific Calculator
Chapter Goals
Mathematical Operations and Vectors
Assigning Variables
Special Numbers
Logical Vectors
Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Exercises
Chapter 3 Inspecting Variables and Your Workspace
Chapter Goals
Classes
Different Types of Numbers
Other Common Classes
Checking and Changing Classes
Examining Variables
The Workspace
Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Exercises
Chapter 4 Vectors, Matrices, and Arrays
Chapter Goals
Vectors
Matrices and Arrays
Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Exercises
Chapter 5 Lists and Data Frames
Chapter Goals
Lists
NULL
Pairlists
Data Frames
Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Exercises
Chapter 6 Environments and Functions
Chapter Goals
Environments
Functions
Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Exercises
Chapter 7 Strings and Factors
Chapter Goals
Strings
Factors
Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Exercises
Chapter 8 Flow Control and Loops
Chapter Goals
Flow Control
Loops
Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Exercises
Chapter 9 Advanced Looping
Chapter Goals
Replication
Looping Over Lists
Looping Over Arrays
Multiple-Input Apply
Split-Apply-Combine
The plyr Package
Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Exercises
Chapter 10 Packages
Chapter Goals
Loading Packages
Installing Packages
Maintaining Packages
Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Exercises
Chapter 11 Dates and Times
Chapter Goals
Date and Time Classes
Conversion to and from Strings
Time Zones
Arithmetic with Dates and Times
Lubridate
Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Exercises
The Data Analysis Workflow
Chapter 12 Getting Data
Chapter Goals
Built-in Datasets
Reading Text Files
Reading Binary Files
Web Data
Accessing Databases
Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Exercises
Chapter 13 Cleaning and Transforming
Chapter Goals
Cleaning Strings
Manipulating Data Frames
Sorting
Functional Programming
Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Exercises
Chapter 14 Exploring and Visualizing
Chapter Goals
Summary Statistics
The Three Plotting Systems
Scatterplots
Line Plots
Histograms
Box Plots
Bar Charts
Other Plotting Packages and Systems
Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Exercises
Chapter 15 Distributions and Modeling
Chapter Goals
Random Numbers
Distributions
Formulae
A First Model: Linear Regressions
Other Model Types
Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Exercises
Chapter 16 Programming
Chapter Goals
Messages, Warnings, and Errors
Error Handling
Debugging
Testing
Magic
Object-Oriented Programming
Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Exercises
Chapter 17 Making Packages
Chapter Goals
Why Create Packages?
Prerequisites
The Package Directory Structure
Your First Package
Documenting Packages
Checking and Building Packages
Maintaining Packages
Summary
Test Your Knowledge: Quiz
Test Your Knowledge: Exercises
Appendixes
Appendix Properties of Variables
Appendix Other Things to Do in R
Appendix Answers to Quizzes
Appendix Solutions to Exercises
Appendix Bibliography

Learn how to perform data analysis with the R language and software environment, even if you have little or no programming experience. With the tutorials in this hands-on guide, you’ll learn how to use the essential R tools you need to know to analyze data, including data types and programming concepts.

The second half of Learning R shows you real data analysis in action by covering everything from importing data to publishing your results. Each chapter in the book includes a quiz on what you’ve learned, and concludes with exercises, most of which involve writing R code.
Write a simple R program, and discover what the language can do
Use data types such as vectors, arrays, lists, data frames, and strings
Execute code conditionally or repeatedly with branches and loops
Apply R add-on packages, and package your own work for others
Learn how to clean data you import from a variety of sources
Understand data through visualization and summary statistics
Use statistical models to pass quantitative judgments about data and make predictions
Learn what to do when things go wrong while writing data analysis code