如何在R中连接以连字符分隔的字符串向量？
字符串向量的串联将在向量中创建值的组合，因此，我们可以将它们用于向量之间的交互。在R中，我们可以使用expand.grid和apply来创建这种类型的组合，如以下示例所示。
例子1
x1<-c("India","Russia","China")
y1<-c("UK","USA","Canada")
apply(expand.grid(x1,y1),1,paste,collapse="-")输出结果
[1] "India-UK" "Russia-UK" "China-UK" "India-USA" [5] "Russia-USA" "China-USA" "India-Canada" "Russia-Canada" [9] "China-Canada"
例子2
x2<-c("Hot","Cold")
y2<-c("Summer","Winter","Spring")
apply(expand.grid(x2,y2),1,paste,collapse="-")输出结果
[1] "Hot-Summer" "Cold-Summer" "Hot-Winter" "Cold-Winter" "Hot-Spring" [6] "Cold-Spring"
例子3
x3<-c("G1","G2","G3","G4","G5")
y3<-c("S1","S2","S3","S4")
z3<-c("P1","P2","P3","P4","P5")
apply(expand.grid(x3,y3,z3),1,paste,collapse="-")输出结果
[1] "G1-S1-P1" "G2-S1-P1" "G3-S1-P1" "G4-S1-P1" "G5-S1-P1" "G1-S2-P1" [7] "G2-S2-P1" "G3-S2-P1" "G4-S2-P1" "G5-S2-P1" "G1-S3-P1" "G2-S3-P1" [13] "G3-S3-P1" "G4-S3-P1" "G5-S3-P1" "G1-S4-P1" "G2-S4-P1" "G3-S4-P1" [19] "G4-S4-P1" "G5-S4-P1" "G1-S1-P2" "G2-S1-P2" "G3-S1-P2" "G4-S1-P2" [25] "G5-S1-P2" "G1-S2-P2" "G2-S2-P2" "G3-S2-P2" "G4-S2-P2" "G5-S2-P2" [31] "G1-S3-P2" "G2-S3-P2" "G3-S3-P2" "G4-S3-P2" "G5-S3-P2" "G1-S4-P2" [37] "G2-S4-P2" "G3-S4-P2" "G4-S4-P2" "G5-S4-P2" "G1-S1-P3" "G2-S1-P3" [43] "G3-S1-P3" "G4-S1-P3" "G5-S1-P3" "G1-S2-P3" "G2-S2-P3" "G3-S2-P3" [49] "G4-S2-P3" "G5-S2-P3" "G1-S3-P3" "G2-S3-P3" "G3-S3-P3" "G4-S3-P3" [55] "G5-S3-P3" "G1-S4-P3" "G2-S4-P3" "G3-S4-P3" "G4-S4-P3" "G5-S4-P3" [61] "G1-S1-P4" "G2-S1-P4" "G3-S1-P4" "G4-S1-P4" "G5-S1-P4" "G1-S2-P4" [67] "G2-S2-P4" "G3-S2-P4" "G4-S2-P4" "G5-S2-P4" "G1-S3-P4" "G2-S3-P4" [73] "G3-S3-P4" "G4-S3-P4" "G5-S3-P4" "G1-S4-P4" "G2-S4-P4" "G3-S4-P4" [79] "G4-S4-P4" "G5-S4-P4" "G1-S1-P5" "G2-S1-P5" "G3-S1-P5" "G4-S1-P5" [85] "G5-S1-P5" "G1-S2-P5" "G2-S2-P5" "G3-S2-P5" "G4-S2-P5" "G5-S2-P5" [91] "G1-S3-P5" "G2-S3-P5" "G3-S3-P5" "G4-S3-P5" "G5-S3-P5" "G1-S4-P5" [97] "G2-S4-P5" "G3-S4-P5" "G4-S4-P5" "G5-S4-P5"
例子4
x4<-c("Male","Female")
y4<-c("Tall","Short")
z4<-c("1000 to 2000","2001 to 5000","5001 to 10000",">10000")
a4<-c("Y1","Y2","Y3","Y4","Y5","Y6")
apply(expand.grid(x4,y4,z4,a4),1,paste,collapse="-")输出结果
[1] "Male-Tall-1000 to 2000-Y1" "Female-Tall-1000 to 2000-Y1" [3] "Male-Short-1000 to 2000-Y1" "Female-Short-1000 to 2000-Y1" [5] "Male-Tall-2001 to 5000-Y1" "Female-Tall-2001 to 5000-Y1" [7] "Male-Short-2001 to 5000-Y1" "Female-Short-2001 to 5000-Y1" [9] "Male-Tall-5001 to 10000-Y1" "Female-Tall-5001 to 10000-Y1" [11] "Male-Short-5001 to 10000-Y1" "Female-Short-5001 to 10000-Y1" [13] "Male-Tall->10000-Y1" "Female-Tall->10000-Y1" [15] "Male-Short->10000-Y1" "Female-Short->10000-Y1" [17] "Male-Tall-1000 to 2000-Y2" "Female-Tall-1000 to 2000-Y2" [19] "Male-Short-1000 to 2000-Y2" "Female-Short-1000 to 2000-Y2" [21] "Male-Tall-2001 to 5000-Y2" "Female-Tall-2001 to 5000-Y2" [23] "Male-Short-2001 to 5000-Y2" "Female-Short-2001 to 5000-Y2" [25] "Male-Tall-5001 to 10000-Y2" "Female-Tall-5001 to 10000-Y2" [27] "Male-Short-5001 to 10000-Y2" "Female-Short-5001 to 10000-Y2" [29] "Male-Tall->10000-Y2" "Female-Tall->10000-Y2" [31] "Male-Short->10000-Y2" "Female-Short->10000-Y2" [33] "Male-Tall-1000 to 2000-Y3" "Female-Tall-1000 to 2000-Y3" [35] "Male-Short-1000 to 2000-Y3" "Female-Short-1000 to 2000-Y3" [37] "Male-Tall-2001 to 5000-Y3" "Female-Tall-2001 to 5000-Y3" [39] "Male-Short-2001 to 5000-Y3" "Female-Short-2001 to 5000-Y3" [41] "Male-Tall-5001 to 10000-Y3" "Female-Tall-5001 to 10000-Y3" [43] "Male-Short-5001 to 10000-Y3" "Female-Short-5001 to 10000-Y3" [45] "Male-Tall->10000-Y3" "Female-Tall->10000-Y3" [47] "Male-Short->10000-Y3" "Female-Short->10000-Y3" [49] "Male-Tall-1000 to 2000-Y4" "Female-Tall-1000 to 2000-Y4" [51] "Male-Short-1000 to 2000-Y4" "Female-Short-1000 to 2000-Y4" [53] "Male-Tall-2001 to 5000-Y4" "Female-Tall-2001 to 5000-Y4" [55] "Male-Short-2001 to 5000-Y4" "Female-Short-2001 to 5000-Y4" [57] "Male-Tall-5001 to 10000-Y4" "Female-Tall-5001 to 10000-Y4" [59] "Male-Short-5001 to 10000-Y4" "Female-Short-5001 to 10000-Y4" [61] "Male-Tall->10000-Y4" "Female-Tall->10000-Y4" [63] "Male-Short->10000-Y4" "Female-Short->10000-Y4" [65] "Male-Tall-1000 to 2000-Y5" "Female-Tall-1000 to 2000-Y5" [67] "Male-Short-1000 to 2000-Y5" "Female-Short-1000 to 2000-Y5" [69] "Male-Tall-2001 to 5000-Y5" "Female-Tall-2001 to 5000-Y5" [71] "Male-Short-2001 to 5000-Y5" "Female-Short-2001 to 5000-Y5" [73] "Male-Tall-5001 to 10000-Y5" "Female-Tall-5001 to 10000-Y5" [75] "Male-Short-5001 to 10000-Y5" "Female-Short-5001 to 10000-Y5" [77] "Male-Tall->10000-Y5" "Female-Tall->10000-Y5" [79] "Male-Short->10000-Y5" "Female-Short->10000-Y5" [81] "Male-Tall-1000 to 2000-Y6" "Female-Tall-1000 to 2000-Y6" [83] "Male-Short-1000 to 2000-Y6" "Female-Short-1000 to 2000-Y6" [85] "Male-Tall-2001 to 5000-Y6" "Female-Tall-2001 to 5000-Y6" [87] "Male-Short-2001 to 5000-Y6" "Female-Short-2001 to 5000-Y6" [89] "Male-Tall-5001 to 10000-Y6" "Female-Tall-5001 to 10000-Y6" [91] "Male-Short-5001 to 10000-Y6" "Female-Short-5001 to 10000-Y6" [93] "Male-Tall->10000-Y6" "Female-Tall->10000-Y6" [95] "Male-Short->10000-Y6" "Female-Short->10000-Y6"