如果我们要按顺序将一个向量的名称与另一个具有相同值的向量中的字符串向量值进行匹配，则可以使用pmatch函数。pmatch函数表示模式匹配，因此它匹配所有对应的值并返回这些值的索引。查看以下示例以了解其工作原理。
x1<-c("A","B","C")
x1输出结果
[1] "A" "B" "C"
y1=structure(c(1,2,3),.Names=c("C","A","B"))
y1输出结果
C A B 1 2 3
pmatch(x1,names(y1))
输出结果
[1] 2 3 1
x2<-sample(c("A","B","C"),80,replace=TRUE)
x2输出结果
[1] "C" "B" "B" "B" "C" "C" "B" "A" "A" "A" "A" "A" "A" "A" "A" "B" "C" "A" "B" [20] "A" "A" "C" "C" "C" "B" "B" "C" "B" "B" "A" "A" "B" "C" "C" "B" "C" "B" "A" [39] "C" "C" "C" "A" "A" "A" "B" "C" "C" "C" "B" "C" "B" "A" "A" "B" "C" "A" "C" [58] "A" "A" "A" "B" "C" "B" "B" "A" "B" "C" "B" "A" "A" "A" "B" "C" "A" "C" "A" [77] "C" "A" "B" "A"
y2<-sample(setNames(c(1,2,3),c("B","C","A")),80,replace=TRUE)
y2输出结果
C B A A B B B B A B A A B A A A A C C C B B C C C B B B C A B A C B B B C C C C 2 1 3 3 1 1 1 1 3 1 3 3 1 3 3 3 3 2 2 2 1 1 2 2 2 1 1 1 2 3 1 3 2 1 1 1 2 2 2 2 B C A B B B B B C C C B B A C C A A A A B B C B A A A A B C C A A B B C B A C C 1 2 3 1 1 1 1 1 2 2 2 1 1 3 2 2 3 3 3 3 1 1 2 1 3 3 3 3 1 2 2 3 3 1 1 2 1 3 2 2
pmatch(x2,names(y2))
输出结果
[1] 1 2 5 6 18 19 7 3 4 9 11 12 14 15 16 8 20 17 10 30 32 23 24 25 13 [26] 21 29 22 26 43 54 27 33 37 28 38 31 57 39 40 42 58 59 60 34 49 50 51 35 55 [51] 36 65 66 41 56 67 63 68 72 73 44 70 45 46 78 47 71 48 NA NA NA 52 76 NA 79 [76] NA 80 NA 53 NA
x3<-sample(c("India","China","Bangladesh","Russia"),80,replace=TRUE)
x3输出结果
[1] "China" "India" "Bangladesh" "Bangladesh" "Bangladesh" [6] "India" "China" "India" "Russia" "Bangladesh" [11] "Bangladesh" "China" "Bangladesh" "China" "Bangladesh" [16] "Russia" "Russia" "India" "India" "China" [21] "China" "Bangladesh" "Bangladesh" "Russia" "Russia" [26] "Bangladesh" "Russia" "Bangladesh" "China" "India" [31] "India" "Russia" "India" "Russia" "India" [36] "Bangladesh" "Russia" "Russia" "China" "India" [41] "Russia" "Bangladesh" "Bangladesh" "India" "Bangladesh" [46] "India" "India" "India" "India" "Russia" [51] "Bangladesh" "India" "India" "Russia" "Bangladesh" [56] "India" "India" "India" "China" "Bangladesh" [61] "India" "Russia" "China" "Russia" "India" [66] "India" "Russia" "India" "China" "Russia" [71] "China" "Russia" "Bangladesh" "Bangladesh" "China" [76] "Russia" "India" "Russia" "China" "India"
y3<-
sample(setNames(c(25,24,32,27),c("Russia","China","India","Bangladesh")),80,replace= TRUE)
y3输出结果
Bangladesh India Russia China Bangladesh India China 27 32 25 24 27 32 24 India Bangladesh China China India Russia Russia 32 27 24 24 32 25 25 China China Bangladesh Russia Russia China China 24 24 27 25 25 24 24 Russia Russia Russia India Russia China China 25 25 25 32 25 24 24 Russia Bangladesh Bangladesh Bangladesh Russia India China 25 27 27 27 25 32 24 Bangladesh Russia India Russia India Russia India 27 25 32 25 32 25 32 Russia Russia Bangladesh India China China China 25 25 27 32 24 24 24 India India Russia Russia Bangladesh China Bangladesh 32 32 25 25 27 24 27 China India Bangladesh Bangladesh China India Russia 24 32 27 27 24 32 25 China Bangladesh India Bangladesh India Russia China 24 27 32 27 32 25 24 Russia Bangladesh Russia Russia Russia Russia Russia 25 27 25 25 25 25 25 China Bangladesh India 24 27 32
pmatch(x3,names(y3))
输出结果
[1] 4 2 1 5 9 6 7 8 3 17 30 10 31 11 32 13 14 12 25 15 16 36 45 18 19 [26] 54 22 56 20 34 38 23 40 24 42 59 26 29 21 46 33 60 65 50 67 51 58 62 66 37 [51] 72 68 80 39 79 NA NA NA 27 NA NA 41 28 43 NA NA 44 NA 35 52 47 53 NA NA 48 [76] 63 NA 69 49 NA
x4<-sample(c("80 degree","90 degree","100 degree"),80,replace=TRUE)
x4输出结果
[1] "80 degree" "100 degree" "90 degree" "80 degree" "80 degree" [6] "80 degree" "100 degree" "100 degree" "80 degree" "90 degree" [11] "80 degree" "90 degree" "80 degree" "80 degree" "80 degree" [16] "100 degree" "100 degree" "80 degree" "90 degree" "100 degree" [21] "90 degree" "90 degree" "80 degree" "90 degree" "80 degree" [26] "80 degree" "90 degree" "80 degree" "90 degree" "100 degree" [31] "80 degree" "90 degree" "90 degree" "100 degree" "100 degree" [36] "90 degree" "100 degree" "90 degree" "90 degree" "100 degree" [41] "90 degree" "100 degree" "80 degree" "80 degree" "90 degree" [46] "100 degree" "100 degree" "100 degree" "90 degree" "100 degree" [51] "80 degree" "100 degree" "80 degree" "80 degree" "90 degree" [56] "100 degree" "80 degree" "80 degree" "100 degree" "80 degree" [61] "80 degree" "80 degree" "80 degree" "80 degree" "100 degree" [66] "100 degree" "100 degree" "80 degree" "90 degree" "80 degree" [71] "80 degree" "90 degree" "80 degree" "80 degree" "80 degree" [76] "90 degree" "100 degree" "80 degree" "80 degree" "80 degree"
<y4<-sample(setNames(c(90,100,80),c("90 degree","100 degree","80
degree")),80,replace=TRUE)
y4输出结果
90 degree 100 degree 80 degree 100 degree 90 degree 90 degree 90 degree 90 100 80 100 90 90 90 100 degree 80 degree 80 degree 90 degree 90 degree 90 degree 100 degree 100 80 80 90 90 90 100 80 degree 80 degree 80 degree 100 degree 100 degree 100 degree 100 degree 80 80 80 100 100 100 100 100 degree 100 degree 100 degree 80 degree 80 degree 100 degree 100 degree 100 100 100 80 80 100 100 80 degree 80 degree 100 degree 100 degree 90 degree 90 degree 100 degree 80 80 100 100 90 90 100 80 degree 90 degree 100 degree 80 degree 100 degree 80 degree 100 degree 80 90 100 80 100 80 100 90 degree 90 degree 90 degree 100 degree 90 degree 100 degree 80 degree 90 90 90 100 90 100 80 80 degree 90 degree 90 degree 90 degree 100 degree 80 degree 80 degree 80 90 90 90 100 80 80 90 degree 100 degree 100 degree 90 degree 80 degree 100 degree 80 degree 90 100 100 90 80 100 80 80 degree 90 degree 100 degree 100 degree 100 degree 100 degree 100 degree 80 90 100 100 100 100 100 80 degree 100 degree 80 degree 80 degree 100 degree 100 degree 80 degree 80 100 80 80 100 100 80 90 degree 90 degree 100 degree 90 90 100
pmatch(x4,names(y4))
输出结果
[1] 3 2 1 9 10 15 4 8 16 5 17 6 25 26 29 14 18 30 7 19 11 12 36 13 39 [26] 41 33 49 34 20 50 37 43 21 22 44 23 45 47 24 51 27 55 56 52 28 31 32 53 35 [51] 61 38 63 64 57 40 71 73 42 74 77 NA NA NA 46 48 54 NA 60 NA NA 65 NA NA NA [76] 78 58 NA NA NA