R语言技术手册(第二版,影印版)
Joseph Adler
出版时间:2013年06月
页数:724
“虽然R语言是免费和强大的,但是它很难入门。《R语言技术手册》是你学习R语言的重要帮手,同时也是每位数据科学家的优秀参考手册。”
——DJ Patil
Greylock风投公司的入驻数据科学家
“R语言正快速成为统计学中的通用语言,而《R语言技术手册》是初学者的最佳起点。从数据可视化到时间序列分析,这本书涵盖了从事强大数据科学工作所需的各个方面。”
——Anthony Goldbloom
Kaggle公司的创办者和执行总裁

如果你选择R语言用于统计计算和数据可视化,那么本书将可以为你提供开源R语言及其软件环境的快速实用指南。你将学习如何编写R函数和使用R包来帮助你准备、可视化和分析数据。本书作者Joseph Adler讲解了来自医药、商业和体育方面大量实例的处理过程。
本次第二版更新基于R语言2.14和2.15版本,包括了这样一些新的扩展章节:R性能、ggplot2数据可视化包和基于Hadoop的并行R计算。
  1. Chapter 1: Getting and Installing R
  2. R Versions
  3. Getting and Installing Interactive R Binaries
  4. Chapter 2: The R User Interface
  5. The R Graphical User Interface
  6. The R Console
  7. Batch Mode
  8. Using R Inside Microsoft Excel
  9. RStudio
  10. Other Ways to Run R
  11. Chapter 3: A Short R Tutorial
  12. Basic Operations in R
  13. Functions
  14. Variables
  15. Introduction to Data Structures
  16. Objects and Classes
  17. Models and Formulas
  18. Charts and Graphics
  19. Getting Help
  20. Chapter 4: R Packages
  21. An Overview of Packages
  22. Listing Packages in Local Libraries
  23. Loading Packages
  24. Exploring Package Repositories
  25. Installing Packages From Other Repositories
  26. Custom Packages
  27. The R Language
  28. Chapter 5: An Overview of the R Language
  29. Expressions
  30. Objects
  31. Symbols
  32. Functions
  33. Objects Are Copied in Assignment Statements
  34. Everything in R Is an Object
  35. Special Values
  36. Coercion
  37. The R Interpreter
  38. Seeing How R Works
  39. Chapter 6: R Syntax
  40. Constants
  41. Operators
  42. Expressions
  43. Control Structures
  44. Accessing Data Structures
  45. R Code Style Standards
  46. Chapter 7: R Objects
  47. Primitive Object Types
  48. Vectors
  49. Lists
  50. Other Objects
  51. Attributes
  52. Chapter 8: Symbols and Environments
  53. Symbols
  54. Working with Environments
  55. The Global Environment
  56. Environments and Functions
  57. Exceptions
  58. Chapter 9: Functions
  59. The Function Keyword
  60. Arguments
  61. Return Values
  62. Functions as Arguments
  63. Argument Order and Named Arguments
  64. Side Effects
  65. Chapter 10: Object-Oriented Programming
  66. Overview of Object-Oriented Programming in R
  67. Object-Oriented Programming in R: S4 Classes
  68. Old-School OOP in R: S3
  69. Working with Data
  70. Chapter 11: Saving, Loading, and Editing Data
  71. Entering Data Within R
  72. Saving and Loading R Objects
  73. Importing Data from External Files
  74. Exporting Data
  75. Importing Data From Databases
  76. Getting Data from Hadoop
  77. Chapter 12: Preparing Data
  78. Combining Data Sets
  79. Transformations
  80. Binning Data
  81. Subsets
  82. Summarizing Functions
  83. Data Cleaning
  84. Finding and Removing Duplicates
  85. Sorting
  86. Data Visualization
  87. Chapter 13: Graphics
  88. An Overview of R Graphics
  89. Graphics Devices
  90. Customizing Charts
  91. Chapter 14: Lattice Graphics
  92. History
  93. An Overview of the Lattice Package
  94. High-Level Lattice Plotting Functions
  95. Customizing Lattice Graphics
  96. Low-Level Functions
  97. Chapter 15: ggplot2
  98. A Short Introduction
  99. The Grammar of Graphics
  100. A More Complex Example: Medicare Data
  101. Quick Plot
  102. Creating Graphics with ggplot2
  103. Learning More
  104. Statistics with R
  105. Chapter 16: Analyzing Data
  106. Summary Statistics
  107. Correlation and Covariance
  108. Principal Components Analysis
  109. Factor Analysis
  110. Bootstrap Resampling
  111. Chapter 17: Probability Distributions
  112. Normal Distribution
  113. Common Distribution-Type Arguments
  114. Distribution Function Families
  115. Chapter 18: Statistical Tests
  116. Continuous Data
  117. Discrete Data
  118. Chapter 19: Power Tests
  119. Experimental Design Example
  120. t-Test Design
  121. Proportion Test Design
  122. ANOVA Test Design
  123. Chapter 20: Regression Models
  124. Example: A Simple Linear Model
  125. Details About the lm Function
  126. Subset Selection and Shrinkage Methods
  127. Nonlinear Models
  128. Survival Models
  129. Smoothing
  130. Machine Learning Algorithms for Regression
  131. Chapter 21: Classification Models
  132. Linear Classification Models
  133. Machine Learning Algorithms for Classification
  134. Chapter 22: Machine Learning
  135. Market Basket Analysis
  136. Clustering
  137. Chapter 23: Time Series Analysis
  138. Autocorrelation Functions
  139. Time Series Models
  140. Additional Topics
  141. Chapter 24: Optimizing R Programs
  142. Measuring R Program Performance
  143. Optimizing Your R Code
  144. Other Ways to Speed Up R
  145. Chapter 25: Bioconductor
  146. An Example
  147. Key Bioconductor Packages
  148. Data Structures
  149. Where to Go Next
  150. Chapter 26: R and Hadoop
  151. R and Hadoop
  152. Other Packages for Parallel Computation with R
  153. Where to Learn More
  154. Appendix R Reference
  155. base
  156. boot
  157. class
  158. cluster
  159. codetools
  160. foreign
  161. grDevices
  162. graphics
  163. grid
  164. KernSmooth
  165. lattice
  166. MASS
  167. methods
  168. mgcv
  169. nlme
  170. nnet
  171. rpart
  172. spatial
  173. splines
  174. stats
  175. stats4
  176. survival
  177. tcltk
  178. tools
  179. utils
  180. Bibliography
书名:R语言技术手册(第二版,影印版)
作者:Joseph Adler
国内出版社:东南大学出版社
出版时间:2013年06月
页数:724
书号:978-7-5641-4203-2
原版书书名:R in a Nutshell, 2nd Edition
原版书出版商:O'Reilly Media
Joseph Adler
 
约瑟夫·阿德勒(Joseph Adler)拥有多年数据挖掘和数据分析经验,曾就职于DoubleClick、美国运通和VeriSign公司。约瑟夫毕业于麻省理工学院,期间取得了计算机科学和电子工程的学士及硕士学位。他拥有多项计算机安全和密码学领域的专利,并且是《棒球技巧》(Baseball Hacks)的作者。目前,他在LinkedIn公司任高级数据科学家。
 
 
he animal on the cover of R in a Nutshell is a harpy eagle (Harpia harpyja). Black feathers line the top half of the bird, while white feathers mostly make up the balance, although the underside of its wings may be striped black and white. Unlike other species of birds, male and female harpy eagles appear virtually identical.

These eagles—the most powerful, carnivorous raptors in the Americas—typically inhabit tropical rain forests. They prey upon animals that live in trees: sloths, monkeys, opossums, and even other birds, such as macaws. The eagle is named after the harpies of ancient Greek mythology, female wind spirits who were said to be human from the chest to their ankles and eagle from the neck up. Mythological harpies tormented people as they carried them to the underworld with their clawed feet; perhaps similarly, harpy eagles’ talons violently pierce and subdue their prey before the eagles carry them back to their nests. Harpy eagles also inspire modern-day life: the eagle is the national bird of Panama and is pictured on the country’s coat of arms. The bird also inspired the design of Fawkes the Phoenix in the Harry Potter film series. The cover image is from Cassell’s Natural History.