如何在R向量中找到NA的位置？
当我们在R向量中有NA值/缺失值时，我们想要替换那些NA值，为此我们可能需要这些值的位置。这些位置在我们想要手动替换缺失值的情况下尤其有用。替换可以通过在is.na中使用which函数来完成。
示例1
x1<−sample(c(NA,0,1),100,replace=TRUE) x1输出结果
[1] NA NA 1 0 1 0 1 0 0 1 NA 1 NA NA 0 NA 1 0 NA 1 1 1 0 NA 0 [26] 1 NA NA NA 0 1 NA 1 0 1 NA 0 0 1 0 1 NA 1 0 1 0 0 NA 1 1 [51] 0 0 NA 0 0 1 1 NA 1 1 1 0 0 1 1 1 0 0 0 0 NA 1 NA NA NA [76] NA 1 0 NA NA 1 1 NA 0 NA 1 1 0 0 NA 1 NA 0 NA NA 0 1 NA 0 NA
示例
which(is.na(x1))输出结果
[1] 1 2 11 13 14 16 19 24 27 28 29 32 36 42 48 53 58 71 73 [20] 74 75 76 79 80 83 85 90 92 94 95 98 100
例2
x2<−sample(c(NA,0:9),150,replace=TRUE) x2输出结果
[1] 6 4 4 1 NA 5 1 NA 9 7 5 5 7 5 2 1 2 4 3 9 5 NA 0 1 9 [26] 1 6 7 1 8 8 1 4 7 1 3 2 6 4 9 NA 4 3 8 7 1 0 6 7 8 [51] 6 4 6 6 6 8 3 6 3 9 4 4 NA 9 0 6 8 7 1 0 9 0 3 3 8 [76] 5 1 3 NA 4 5 6 7 9 NA 0 6 3 9 9 5 NA 1 7 3 4 5 NA 2 8 [101] 4 9 5 2 NA 6 9 0 4 5 3 6 5 0 3 8 8 4 5 9 5 1 4 4 2 [126] 2 5 6 2 8 9 2 NA 1 2 1 9 1 7 4 0 8 8 0 8 1 7 3 6 9
示例
which(is.na(x2))输出结果
[1] 5 8 22 41 63 79 85 92 98 105 133
例3
x3<−sample(c(NA,10,99),150,replace=TRUE) x3输出结果
[1] 99 99 10 10 NA 99 10 99 NA NA 99 NA NA 99 NA 99 99 10 10 99 NA 10 NA 99 10 [26] NA NA NA NA NA 10 10 99 10 10 10 99 99 10 10 99 99 NA 10 NA NA 10 10 99 99 [51] 99 NA 99 99 99 99 NA 99 NA NA NA 99 NA 99 99 99 99 99 10 10 99 10 NA NA 10 [76] 10 99 10 99 NA NA 10 99 10 99 NA 10 99 NA 99 10 99 99 NA NA 10 10 99 NA 10 [101] 99 NA NA 99 NA 10 99 99 10 NA 99 10 NA NA 10 NA 10 NA 10 99 NA 99 NA NA 10 [126] 10 NA 10 NA 99 NA 99 NA NA 10 10 10 99 NA 99 10 10 NA NA 10 99 NA 10 10 99
示例
which(is.na(x3))输出结果
which(is.na(x3))
例4
x4<−sample(c(NA,rnorm(5)),80,replace=TRUE) x4输出结果
[1] NA 0.4902959 NA -0.1427441 -0.0157058 0.3530351 [7] NA NA −0.0157058 −0.1427441 −0.0157058 NA [13] −0.1427441 −0.1427441 −0.0157058 0.4902959 0.3530351 NA [19] 0.4902959 0.3530351 0.3530351 0.4902959 NA 0.2005032 [25] NA −0.0157058 0.3530351 0.2005032 −0.1427441 −0.1427441 [31] 0.2005032 −0.0157058 0.4902959 0.2005032 −0.0157058 −0.1427441 [37] 0.4902959 NA NA 0.4902959 −0.0157058 −0.1427441 [43] 0.3530351 −0.1427441 −0.1427441 NA 0.4902959 NA [49] 0.3530351 0.3530351 0.4902959 0.2005032 0.3530351 −0.0157058 [55] 0.2005032 NA 0.4902959 −0.0157058 0.3530351 0.3530351 [61] 0.2005032 0.3530351 0.4902959 0.4902959 −0.0157058 0.4902959 [67] −0.0157058 0.4902959 −0.1427441 −0.1427441 −0.1427441 −0.1427441 [73] 0.4902959 0.4902959 0.2005032 0.3530351 0.4902959 −0.1427441 [79] 0.4902959 0.4902959
示例
which(is.na(x4))输出结果
[1] 1 3 7 8 12 18 23 25 38 39 46 48 56
例5
x5<−sample(c(NA,rnorm(5,25,3.1)),80,replace=TRUE) x5输出结果
[1] NA 20.85061 23.28236 27.07661 23.92421 26.08445 26.08445 27.07661 [9] NA 26.08445 26.08445 26.08445 23.92421 23.28236 27.07661 27.07661 [17] NA NA 26.08445 23.28236 26.08445 23.28236 27.07661 23.92421 [25] NA NA 20.85061 NA 26.08445 23.28236 NA NA [33] 23.92421 27.07661 23.28236 23.28236 20.85061 23.28236 23.92421 27.07661 [41] 20.85061 27.07661 23.28236 23.92421 NA NA 23.28236 23.28236 [49] 23.92421 26.08445 NA NA NA 23.92421 20.85061 27.07661 [57] 23.28236 23.28236 20.85061 23.28236 27.07661 NA 20.85061 27.07661 [65] 20.85061 NA 20.85061 23.28236 20.85061 23.92421 27.07661 26.08445 [73] 27.07661 23.92421 27.07661 20.85061 26.08445 26.08445 23.28236 20.85061
示例
which(is.na(x5))
例6
x6<−sample(c(NA,rpois(10,5)),150,replace=TRUE) x6输出结果
[1] 6 5 4 6 NA 4 3 4 NA 6 6 3 3 5 9 3 6 3 3 4 4 6 6 4 6 [26] 5 6 6 6 5 4 9 6 4 4 3 6 3 9 3 6 4 9 6 4 6 4 NA 6 6 [51] 6 6 3 6 6 3 4 NA 6 4 4 4 6 6 4 6 6 4 6 5 6 6 4 6 3 [76] 5 4 NA 6 3 6 5 NA 5 4 5 4 9 6 5 NA 4 6 NA 5 NA 3 6 NA 3 [101] 3 6 6 NA 6 6 4 4 4 3 9 NA 9 3 4 4 5 NA 6 6 3 4 6 NA 6 [126] 3 4 6 3 3 6 3 4 5 4 4 6 4 3 3 4 5 5 4 3 4 5 6 9 3
示例
which(is.na(x6))输出结果
[1] 5 9 48 58 78 83 91 94 96 99 104 112 118 124
例7
x7<−sample(c(NA,rexp(10,2.01)),80,replace=TRUE) x7输出结果
[1] 0.07553376 0.42805544 0.07934303 2.82645498 0.07553376 0.07934303 [7] NA NA 0.42805544 0.39840736 0.07553376 0.13041258 [13] 0.42805544 0.13041258 0.68973943 0.13041258 0.89757427 NA [19] 0.07934303 0.68973943 0.89757427 0.13041258 0.07934303 0.06858492 [25] 0.13041258 0.89757427 0.13041258 0.68973943 0.39840736 2.82645498 [31] 0.13041258 0.06858492 0.72781631 0.89757427 0.13041258 0.39840736 [37] 0.42805544 0.42805544 0.07553376 0.72781631 0.13041258 0.39840736 [43] 0.68973943 0.72781631 0.07553376 0.13041258 0.42805544 0.13041258 [49] 2.82645498 0.72781631 0.42805544 0.13041258 0.06858492 0.39840736 [55] 0.39840736 0.07934303 0.06858492 2.82645498 NA 0.07934303 [61] NA NA 0.07934303 0.42805544 0.72781631 NA [67] 0.39840736 0.06858492 0.89757427 0.42805544 0.72781631 0.68973943 [73] 0.07553376 0.06858492 0.13041258 0.42805544 0.13041258 2.82645498 [79] 0.13041258 0.07934303
示例
which(is.na(x7))输出结果
[1] 7 8 18 59 61 62 66
例8
x8<−sample(c(NA,rnorm(10,1,0.25)),80,replace=TRUE) x8输出结果
[1] 0.9030808 0.8823065 0.6860899 0.5996056 0.7197702 0.6860899 0.6860899 [8] 0.6860899 0.9454482 0.5708919 0.5708919 0.8432231 0.6860899 0.9030808 [15] 0.9030808 0.9030808 0.4306264 0.8823065 0.5996056 0.7197702 0.9454482 [22] 0.6860899 0.8432231 0.4306264 0.9810333 0.7197702 0.5708919 NA [29] 0.9810333 0.9454482 0.7197702 0.9454482 0.9454482 0.7197702 0.4306264 [36] 0.8823065 0.6860899 0.7197702 0.9454482 0.6860899 0.5708919 0.9454482 [43] 0.6860899 0.9030808 NA 0.9030808 0.4306264 0.8432231 0.6860899 [50] NA 0.9030808 NA 0.9810333 0.9454482 0.7197702 0.8432231 [57] NA 0.5708919 NA 0.8823065 0.4306264 0.9810333 0.8432231 [64] 0.8823065 0.5996056 0.8432231 0.5996056 0.8823065 0.7197702 0.5996056 [71] 0.5996056 0.9454482 0.4306264 0.4306264 0.4306264 NA 0.9810333 [78] 0.8823065 0.9454482 0.9454482
示例
which(is.na(x8))输出结果
[1] 28 45 50 52 57 59 76