Book description
R is the world's most popular language for developing statistical software: Archaeologists use it to track the spread of ancient civilizations, drug companies use it to discover which medications are safe and effective, and actuaries use it to assess financial risks and keep economies running smoothly.
The Art of R Programming takes you on a guided tour of software development with R, from basic types and data structures to advanced topics like closures, recursion, and anonymous functions. No statistical knowledge is required, and your programming skills can range from hobbyist to pro.
Along the way, you'll learn about functional and object-oriented programming, running mathematical simulations, and rearranging complex data into simpler, more useful formats. You'll also learn to:
•Create artful graphs to visualize complex data sets and functions
•Write more efficient code using parallel R and vectorization
•Interface R with C/C++ and Python for increased speed or functionality
•Find new R packages for text analysis, image manipulation, and more
•Squash annoying bugs with advanced debugging techniques
Whether you're designing aircraft, forecasting the weather, or you just need to tame your data, The Art of R Programming is your guide to harnessing the power of statistical computing.
Publisher resources
Table of contents
- Cover Page
- Title Page
- Copyright Page
- BRIEF CONTENTS
- CONTENTS IN DETAIL
- Acknowledgments
- Introduction
- 1. Getting Started
- 2. Vectors
- 3. Matrices and Arrays
- 4. Lists
- 5. Data Frames
- 6. Factors and Tables
-
7. R Programming Structures
- Control Statements
- Arithmetic and Boolean Operators and Values
- Default Values for Arguments
- Return Values
- Functions Are Objects
- Environment and Scope Issues
- No Pointers in R
- Writing Upstairs
- Recursion
- Replacement Functions
- Tools for Composing Function Code
- Writing Your Own Binary Operations
- Anonymous Functions
- 8. Doing Math and Simulations in R
- 9. Object-Oriented Programming
- 10. Input/Output
- 11. String Manipulation
-
12. Graphics
-
Creating Graphs
- The Workhorse of R Base Graphics: The plot() Function
- Adding Lines: The abline() Function
- Starting a New Graph While Keeping the Old Ones
- Extended Example: Two Density Estimates on the Same Graph
- Extended Example: More on the Polynomial Regression Example
- Adding Points: The points() Function
- Adding a Legend: The legend() Function
- Adding Text: The text() Function
- Pinpointing Locations: The locator() Function
- Restoring a Plot
- Customizing Graphs
- Saving Graphs to Files
- Creating Three-Dimensional Plots
-
Creating Graphs
-
13. Debugging
- Fundamental Principles of Debugging
- Why Use a Debugging Tool?
- Using R Debugging Facilities
- Moving Up in the World: More Convenient Debugging Tools
- Ensuring Consistency in Debugging Simulation Code
- Syntax and Runtime Errors
- Running GDB on R Itself
- 14. Performance Enhancement: Speed and Memory
- 15. Interfacing R to Other Languages
- 16. Parallel R
- A. Installing R
- B. Installing and Using Packages
- Index
- Colophon
- About the Author
Product information
- Title: The Art of R Programming
- Author(s):
- Release date: October 2011
- Publisher(s): No Starch Press
- ISBN: 9781593273842
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