**PRAISE FOR** *THE ART OF R PROGRAMMING*

A deep guide to becoming a competent R programmer for statistical software and data analysis. Covers R's core data structures, programming constructs, object-oriented features, graphics, debugging, performance, and interfacing with other languages for production-quality work.

This page is free — overview and chapter list only.
The complete book body is sold separately.

Full book: $2.99 USDC via x402 ·
Per chapter: $0.25 USDC

Buy / open complete book (HTML)
· Complete book Markdown (.md)

Agents: start with free /library/discovery.json, sample free teaser chapters,
then pay for individual chapters or the complete book URL above.
Append .md to any content URL for Markdown with YAML front matter.

Chapters

  1. A Tour Of Statistical Software Design (Free teaser)
  2. Why Use R For Your Statistical Work ($0.25)
  3. Whom Is This Book For ($0.25)
  4. 11 How To Run R ($0.25)
  5. 12 A First R Session ($0.25)
  6. 13 Introduction To Functions ($0.25)
  7. 14 Preview Of Some Important R Data Structures ($0.25)
  8. 15 Extended Example Regression Analysis Of Exam Grades ($0.25)
  9. 16 Startup And Shutdown ($0.25)
  10. 17 Getting Help ($0.25)
  11. 21 Scalars Vectors Arrays And Matrices ($0.25)
  12. 22 Declarations ($0.25)
  13. 24 Common Vector Operations ($0.25)
  14. 25 Using All And Any ($0.25)
  15. 26 Vectorized Operations ($0.25)
  16. 27 Na And Null Values ($0.25)
  17. 28 Filtering ($0.25)
  18. 29 A Vectorized If Then Else The Ifelse Function ($0.25)
  19. 210 Testing Vector Equality ($0.25)
  20. 31 Creating Matrices ($0.25)
  21. 32 General Matrix Operations ($0.25)
  22. 33 Applying Functions To Matrix Rows And Columns ($0.25)
  23. 34 Adding And Deleting Matrix Rows And Columns ($0.25)
  24. 36 Avoiding Unintended Dimension Reduction ($0.25)
  25. 38 Higher Dimensional Arrays ($0.25)
  26. 42 General List Operations ($0.25)
  27. 43 Accessing List Components And Values ($0.25)
  28. 44 Applying Functions To Lists ($0.25)
  29. 45 Recursive Lists ($0.25)
  30. 51 Creating Data Frames ($0.25)
  31. 52 Other Matrix Like Operations ($0.25)
  32. 53 Merging Data Frames ($0.25)
  33. 54 Applying Functions To Data Frames ($0.25)
  34. 62 Common Functions Used With Factors ($0.25)
  35. 63 Working With Tables ($0.25)
  36. 64 Other Factor And Table Related Functions ($0.25)
  37. 71 Control Statements ($0.25)
  38. 72 Arithmetic And Boolean Operators And Values ($0.25)
  39. 74 Return Values ($0.25)
  40. 75 Functions Are Objects ($0.25)
  41. 76 Environment And Scope Issues ($0.25)
  42. 77 No Pointers In R ($0.25)
  43. 78 Writing Upstairs ($0.25)
  44. 791 A Quicksort Implementation ($0.25)
  45. 792 Extended Example A Binary Search Tree ($0.25)
  46. 7102 Extended Example A Self Bookkeeping Vector Class ($0.25)
  47. 7112 The Edit Function ($0.25)
  48. 811 Extended Example Calculating A Probability ($0.25)
  49. 813 Minima And Maxima ($0.25)
  50. 814 Calculus ($0.25)
  51. 841 Extended Example Vector Cross Product ($0.25)
  52. Extended Example Finding Stationary Distributions Of Markov ($0.25)
  53. 861 Built In Random Variate Generators ($0.25)
  54. 863 Extended Example A Combinatorial Simulation ($0.25)
  55. 912 Example Oop In The Lm Linear Model Function ($0.25)
  56. 913 Finding The Implementations Of Generic Methods ($0.25)
  57. 914 Writing S3 Classes ($0.25)
  58. 916 Extended Example A Class For Storing Upper Triangular Ma ($0.25)
  59. 113 Use Of String Utilities In The Edtdbg Debugging Tool ($0.25)
  60. 121 Creating Graphs ($0.25)
  61. 122 Customizing Graphs ($0.25)
  62. 123 Saving Graphs To Files ($0.25)
  63. 124 Creating Three Dimensional Plots ($0.25)
  64. 131 Fundamental Principles Of Debugging ($0.25)
  65. 133 Using R Debugging Facilities ($0.25)
  66. 134 Moving Up In The World More Convenient Debugging Tools ($0.25)
  67. 137 Running Gdb On R Itself ($0.25)
  68. 142 The Dreaded For Loop ($0.25)
  69. 143 Functional Programming And Memory Issues ($0.25)
  70. 144 Using Rprof To Find Slow Spots In Your Code ($0.25)
  71. 146 Oh No The Data Doesnt Fit Into Memory ($0.25)
  72. 151 Writing Cc Functions To Be Called From R ($0.25)
  73. 152 Using R From Python ($0.25)
  74. 162 Introducing The Snow Package ($0.25)
  75. 163 Resorting To C ($0.25)
  76. 164 General Performance Considerations ($0.25)
  77. 165 Debugging Parallel R Code ($0.25)
  78. A3 Installing From Source ($0.25)
  79. B3 Downloading A Package From The Web ($0.25)
  80. B4 Listing The Functions In A Package ($0.25)