Learning R - A Step-by-Step Function Guide to Data Analysis

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

List of contents

Preface;
About This Book;
What Is in This Book;
Which Chapters Should I Read?;
Conventions Used in This Book;
Goals, Summaries, Quizzes, and Exercises;
Using Code Examples;
Safari® Books Online;
How to Contact Us;
Acknowledgments;
The R Language;
Chapter 1: Introduction;
1.1 Chapter Goals;
1.2 What Is R?;
1.3 Installing R;
1.4 Choosing an IDE;
1.5 Your First Program;
1.6 How to Get Help in R;
1.7 Installing Extra Related Software;
1.8 Summary;
1.9 Test Your Knowledge: Quiz;
1.10 Test Your Knowledge: Exercises;
Chapter 2: A Scientific Calculator;
2.1 Chapter Goals;
2.2 Mathematical Operations and Vectors;
2.3 Assigning Variables;
2.4 Special Numbers;
2.5 Logical Vectors;
2.6 Summary;
2.7 Test Your Knowledge: Quiz;
2.8 Test Your Knowledge: Exercises;
Chapter 3: Inspecting Variables and Your Workspace;
3.1 Chapter Goals;
3.2 Classes;
3.3 Different Types of Numbers;
3.4 Other Common Classes;
3.5 Checking and Changing Classes;
3.6 Examining Variables;
3.7 The Workspace;
3.8 Summary;
3.9 Test Your Knowledge: Quiz;
3.10 Test Your Knowledge: Exercises;
Chapter 4: Vectors, Matrices, and Arrays;
4.1 Chapter Goals;
4.2 Vectors;
4.3 Matrices and Arrays;
4.4 Summary;
4.5 Test Your Knowledge: Quiz;
4.6 Test Your Knowledge: Exercises;
Chapter 5: Lists and Data Frames;
5.1 Chapter Goals;
5.2 Lists;
5.3 NULL;
5.4 Pairlists;
5.5 Data Frames;
5.6 Summary;
5.7 Test Your Knowledge: Quiz;
5.8 Test Your Knowledge: Exercises;
Chapter 6: Environments and Functions;
6.1 Chapter Goals;
6.2 Environments;
6.3 Functions;
6.4 Summary;
6.5 Test Your Knowledge: Quiz;
6.6 Test Your Knowledge: Exercises;
Chapter 7: Strings and Factors;
7.1 Chapter Goals;
7.2 Strings;
7.3 Factors;
7.4 Summary;
7.5 Test Your Knowledge: Quiz;
7.6 Test Your Knowledge: Exercises;
Chapter 8: Flow Control and Loops;
8.1 Chapter Goals;
8.2 Flow Control;
8.3 Loops;
8.4 Summary;
8.5 Test Your Knowledge: Quiz;
8.6 Test Your Knowledge: Exercises;
Chapter 9: Advanced Looping;
9.1 Chapter Goals;
9.2 Replication;
9.3 Looping Over Lists;
9.4 Looping Over Arrays;
9.5 Multiple-Input Apply;
9.6 Split-Apply-Combine;
9.7 The plyr Package;
9.8 Summary;
9.9 Test Your Knowledge: Quiz;
9.10 Test Your Knowledge: Exercises;
Chapter 10: Packages;
10.1 Chapter Goals;
10.2 Loading Packages;
10.3 Installing Packages;
10.4 Maintaining Packages;
10.5 Summary;
10.6 Test Your Knowledge: Quiz;
10.7 Test Your Knowledge: Exercises;
Chapter 11: Dates and Times;
11.1 Chapter Goals;
11.2 Date and Time Classes;
11.3 Conversion to and from Strings;
11.4 Time Zones;
11.5 Arithmetic with Dates and Times;
11.6 Lubridate;
11.7 Summary;
11.8 Test Your Knowledge: Quiz;
11.9 Test Your Knowledge: Exercises;
The Data Analysis Workflow;
Chapter 12: Getting Data;
12.1 Chapter Goals;
12.2 Built-in Datasets;
12.3 Reading Text Files;
12.4 Reading Binary Files;
12.5 Web Data;
12.6 Accessing Databases;
12.7 Summary;
12.8 Test Your Knowledge: Quiz;
12.9 Test Your Knowledge: Exercises;
Chapter 13: Cleaning and Transforming;
13.1 Chapter Goals;
13.2 Cleaning Strings;
13.3 Manipulating Data Frames;
13.4 Sorting;
13.5 Functional Programming;
13.6 Summary;
13.7 Test Your Knowledge: Quiz;
13.8 Test Your Knowledge: Exercises;
Chapter 14: Exploring and Visualizing;
14.1 Chapter Goals;
14.2 Summary Statistics;
14.3 The Three Plotting Systems;
14.4 Scatterplots;
14.5 Line Plots;
14.6 Histograms;
14.7 Box Plots;
14.8 Bar Charts;
14.9 Other Plotting Packages and Systems;
14.10 Summary;
14.11 Test Your Knowledge: Quiz;
14.12 Test Your Knowledge: Exercises;
Chapter 15: Distributions and Modeling;
15.1 Chapter Goals;
15.2 Random Numbers;
15.3 Distributions;
15.4 Formulae;
15.5 A First Model: Linear Regressions;
15.6 Other Model Types;
15.7 Summary;
15.8 Test Your Knowledge: Quiz;
15.9 Test Your Knowledge: Exercises;
Chapter 16: Programming;
16.1 Chapter Goals;
16.2 Messages, Warnings, and Errors;
16.3 Error Handling;
16.4 Debugging;
16.5 Testing;
16.6 Magic;
16.7 Object-Oriented Programming;
16.8 Summary;
16.9 Test Your Knowledge: Quiz;
16.10 Test Your Knowledge: Exercises;
Chapter 17: Making Packages;
17.1 Chapter Goals;
17.2 Why Create Packages?;
17.3 Prerequisites;
17.4 The Package Directory Structure;
17.5 Your First Package;
17.6 Documenting Packages;
17.7 Checking and Building Packages;
17.8 Maintaining Packages;
17.9 Summary;
17.10 Test Your Knowledge: Quiz;
17.11 Test Your Knowledge: Exercises;
Appendixes;
Properties of Variables;
Other Things to Do in R;
Answers to Quizzes;
Solutions to Exercises;
Bibliography;
Index;
Colophon;

About the author

Richie is a data scientist with a background in chemical health and safety, and has worked extensively on tools to give non-technical users access to statistical models. He is the author of the R packages "assertive" for checking the state of your variables and "sig" to make sure your functions have a sensible API. He runs The Damned Liars statistics consultancy.

Summary

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.

Product details

• Authors: Richard Cotton, Cotton Richard
• Publisher: O'Reilly Media
• Languages: English
• Product format: Paperback / Softback
• Released: 01.09.2013
• EAN: 9781449357108
• ISBN: 978-1-4493-5710-8
• No. of pages: 400
• Dimensions: 182 mm x 233 mm x 21 mm
• Weight: 650 g
• Illustrations: w. figs.
• Subjects: Natural sciences, medicine, IT, technology > IT, data processing > Programming languages; Datenanalyse, allgemein, Datenerfassung und -analyse, Mathematische und statistische Software