Getting a subset of a data structure

Problem

You want to do get a subset of the elements of a vector, matrix, or data frame.

Solution

To get a subset based on some conditional criterion, the subset() function or indexing using square brackets can be used. In the examples here, both ways are shown.

  1. # A sample vector
  2. v <- c(1,4,4,3,2,2,3)
  4. subset(v, v<3)
  5. #> [1] 1 2 2
  6. v[v<3]
  7. #> [1] 1 2 2
  10. # Another vector
  11. t <- c("small", "small", "large", "medium")
  13. # Remove "small" entries
  14. subset(t, t!="small")
  15. #> [1] "large"  "medium"
  16. t[t!="small"]
  17. #> [1] "large"  "medium"

One important difference between the two methods is that you can assign values to elements with square bracket indexing, but you cannot with subset().

  1. v[v<3] <- 9
  3. subset(v, v<3) <- 9
  4. #> Error in subset(v, v < 3) <- 9: could not find function "subset<-"

With data frames:

  1. # A sample data frame
  2. data <- read.table(header=T, text='
  3.  subject sex size
  4.        1   M    7
  5.        2   F    6
  6.        3   F    9
  7.        4   M   11
  8.  ')
  11. subset(data, subject < 3)
  12. #>   subject sex size
  13. #> 1       1   M    7
  14. #> 2       2   F    6
  15. data[data$subject < 3, ]
  16. #>   subject sex size
  17. #> 1       1   M    7
  18. #> 2       2   F    6
  21. # Subset of particular rows and columns
  22. subset(data, subject < 3, select = -subject)
  23. #>   sex size
  24. #> 1   M    7
  25. #> 2   F    6
  26. subset(data, subject < 3, select = c(sex,size))
  27. #>   sex size
  28. #> 1   M    7
  29. #> 2   F    6
  30. subset(data, subject < 3, select = sex:size)
  31. #>   sex size
  32. #> 1   M    7
  33. #> 2   F    6
  34. data[data$subject < 3, c("sex","size")]
  35. #>   sex size
  36. #> 1   M    7
  37. #> 2   F    6
  40. # Logical AND of two conditions
  41. subset(data, subject < 3  &  sex=="M")
  42. #>   subject sex size
  43. #> 1       1   M    7
  44. data[data$subject < 3  &  data$sex=="M", ]
  45. #>   subject sex size
  46. #> 1       1   M    7
  49. # Logical OR of two conditions
  50. subset(data, subject < 3  |  sex=="M")
  51. #>   subject sex size
  52. #> 1       1   M    7
  53. #> 2       2   F    6
  54. #> 4       4   M   11
  55. data[data$subject < 3  |  data$sex=="M", ]
  56. #>   subject sex size
  57. #> 1       1   M    7
  58. #> 2       2   F    6
  59. #> 4       4   M   11
  62. # Condition based on transformed data
  63. subset(data, log2(size) > 3 )
  64. #>   subject sex size
  65. #> 3       3   F    9
  66. #> 4       4   M   11
  67. data[log2(data$size) > 3, ]
  68. #>   subject sex size
  69. #> 3       3   F    9
  70. #> 4       4   M   11
  73. # Subset if elements are in another vector
  74. subset(data, subject %in% c(1,3))
  75. #>   subject sex size
  76. #> 1       1   M    7
  77. #> 3       3   F    9
  78. data[data$subject %in% c(1,3), ]
  79. #>   subject sex size
  80. #> 1       1   M    7
  81. #> 3       3   F    9

Notes

Also see ../Indexing into a data structure.