如何找到R向量中不同值的数量？
当我们在R向量中重复元素并且向量大小很大时，我们可能想知道该向量中的不同值。这将帮助我们了解向量中的唯一值，以便我们可以创建适当的图表并使用该向量执行适当的分析。这可以通过使用具有唯一性的长度函数来完成。
例子
> x1<-sample(1:5,50,replace=TRUE) > x1
输出结果
[1] 2 5 5 3 2 4 3 3 1 4 5 4 5 3 3 1 1 2 5 1 3 2 4 1 3 1 5 4 2 5 5 3 2 4 1 1 1 3 [39] 3 5 2 5 4 2 2 2 4 1 1 1
> length(unique(x1))
输出结果
[1] 5
示例
> x2<-rpois(100,5) > x2
输出结果
[1] 2 2 9 5 4 3 2 6 5 11 5 2 3 5 0 5 3 9 6 3 5 6 5 9 6 [26] 4 2 3 7 4 5 6 6 3 7 9 5 5 3 0 8 3 1 9 4 3 4 5 4 5 [51] 7 2 5 6 6 6 5 10 4 7 6 5 8 5 1 6 6 3 6 5 4 6 7 6 4 [76] 3 4 8 7 6 9 11 5 1 4 4 2 2 4 4 3 6 4 9 6 4 3 2 12 4
> length(unique(x2))
输出结果
[1] 13
示例
> x3<-rpois(100,2) > length(unique(x3)) [1] 6 > x3
输出结果
[1] 3 4 2 3 1 1 2 0 1 2 3 4 1 3 0 2 1 2 4 1 1 2 3 2 3 2 2 2 1 0 1 1 3 3 1 2 2 [38] 2 1 2 0 4 0 2 3 2 2 2 3 1 5 2 4 4 3 2 2 0 2 2 4 3 3 2 0 3 2 2 0 1 2 3 0 2 [75] 4 3 1 3 1 2 2 0 3 2 3 0 3 1 1 3 0 0 1 2 2 1 1 1 2 3
> length(unique(x3))
输出结果
[1] 6
示例
> x4<-rnorm(50,mean=2,sd=10) > x4
输出结果
[1] -9.6766233 1.9169099 3.2885540 0.5412437 0.3608904 19.6355200 [7] 9.6258651 13.1143108 -7.2320695 3.6434184 13.5482519 1.4347858 [13] -19.2936065 5.4484576 -17.0495545 -6.1117015 15.2400432 8.1563685 [19] 12.9166896 5.0660486 0.8984124 -7.2431277 17.9291375 2.4501060 [25] -5.1512840 10.6522310 12.7444096 20.9565477 -4.0299730 -1.9086782 [31] -2.1622203 -1.7565742 -1.6663095 -0.9567745 16.4182041 -4.9753829 [37] -1.8816751 8.5253645 13.2477245 -5.7211080 -3.0808622 7.2362059 [43] 12.1775423 -0.5116459 -12.2999345 19.0912103 16.3506957 -5.1037115 [49] 1.3493243 -15.5946874
> length(unique(x4))
输出结果
[1] 50
示例
> x5<-runif(50,2,5) > x5
输出结果
[1] 4.146702 3.055000 4.839670 4.229320 2.152358 4.941094 2.653467 2.108588 [9] 2.782112 4.161247 2.743683 2.704747 2.063036 2.793862 4.075405 2.104008 [17] 2.188358 3.193118 3.470085 3.893146 4.170213 2.230297 3.264338 4.921180 [25] 4.441417 2.671303 3.469227 2.034021 2.775807 3.363796 4.222930 4.971980 [33] 2.996615 4.834374 4.885560 4.697832 3.478148 4.354806 4.409357 4.033303 [41] 3.743833 2.992004 2.003944 2.197406 2.257856 2.039329 3.007237 2.357793 [49] 3.780786 2.111938
> length(unique(x5))
输出结果
[1] 50
示例
> x6<-rpois(100,10) > x6
输出结果
[1] 2 12 7 25 12 5 6 13 15 4 11 10 10 7 12 9 8 14 9 9 12 12 7 10 13 [26] 9 8 6 7 17 17 9 16 12 6 7 8 10 9 7 11 7 11 15 4 13 15 5 13 8 [51] 8 12 13 12 8 11 9 15 7 13 7 10 9 8 14 10 14 6 10 6 6 8 15 7 9 [76] 10 12 11 11 10 14 9 7 12 10 14 7 6 9 9 11 11 10 12 12 12 13 14 9 8
> length(unique(x6))
输出结果
[1] 16
示例
> x7<-rep(LETTERS[1:10],5) > x7
输出结果
[1] "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "A" "B" "C" "D" "E" "F" "G" "H" "I" [20] "J" "A" "B" "C" "D" "E" "F" "G" "H" "I" "J" "A" "B" "C" "D" "E" "F" "G" "H" [39] "I" "J" "A" "B" "C" "D" "E" "F" "G" "H" "I" "J"
> length(unique(x7))
输出结果
[1] 10
示例
> x8<-sample(LETTERS[1:26],50,replace=TRUE) > x8
输出结果
[1] "U" "P" "G" "Y" "J" "S" "Z" "C" "Y" "M" "P" "S" "N" "S" "J" "B" "P" "K" "S" [20] "X" "C" "G" "V" "W" "X" "L" "H" "W" "M" "T" "U" "R" "J" "B" "I" "S" "L" "J" [39] "X" "L" "Y" "W" "F" "H" "W" "M" "K" "M" "B" "H"
> length(unique(x8))
输出结果
[1] 21
示例
> x9<-sample(letters[1:26],50,replace=TRUE) > x9
输出结果
[1] "l" "s" "v" "w" "t" "c" "d" "u" "u" "l" "x" "m" "g" "v" "x" "z" "v" "w" "c" [20] "e" "t" "t" "v" "o" "w" "f" "j" "m" "y" "w" "l" "q" "r" "t" "g" "n" "j" "p" [39] "a" "x" "i" "c" "k" "h" "z" "d" "q" "e" "w" "j"
> length(unique(x9))
输出结果
[1] 25
示例
> x10<-rbinom(50,10,0.5) > x10
输出结果
[1] 2 4 4 7 6 5 5 4 1 8 6 4 6 7 5 6 4 6 8 5 5 6 5 2 3 3 3 5 3 5 4 5 7 5 8 5 7 6 [39] 7 4 5 2 3 5 4 6 1 7 4 5
> length(unique(x10))
输出结果
[1] 8