如何根据元素的手动位置对R中的向量排序？
要基于元素的手动位置对向量进行排序，我们可以将阶跃函数与因子函数一起使用。因子函数将通过将级别定义为矢量元素来帮助我们按所需顺序排列矢量元素，而order函数将对它们进行排序。查看以下示例以了解其工作原理。
例1
> x1<-sample(0:4,200,replace=T) > x1输出结果
[1] 0 1 0 0 1 2 1 2 3 1 2 2 2 4 3 1 4 1 0 1 1 3 3 0 0 4 4 2 4 2 4 2 0 4 0 1 1 [38] 4 2 0 1 0 3 0 4 3 2 0 0 3 2 0 1 0 0 0 4 2 2 4 2 0 4 3 3 1 3 1 2 3 0 2 2 0 [75] 1 1 4 4 4 0 4 0 3 4 0 3 1 4 2 2 3 0 2 4 3 1 2 1 1 3 1 3 4 4 3 1 1 4 4 1 0 [112] 2 2 4 0 0 2 2 1 2 4 4 0 4 1 2 0 3 0 0 4 1 2 4 0 1 1 0 4 1 3 2 0 4 4 2 4 1 [149] 3 4 4 3 2 1 2 2 0 3 4 1 0 1 4 4 0 4 0 2 3 4 1 4 3 2 1 2 4 0 1 3 0 4 2 4 4 [186] 4 3 2 3 4 1 1 0 0 4 0 4 4 0 2
示例
> x1[order(factor(x1,levels=c(3,1,0,4,2)))]输出结果
[1] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 1 1 1 1 1 1 1 1 1 [38] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 [75] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [112] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 [149] 4 4 4 4 4 4 4 4 4 4 4 4 4 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 [186] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2
例2
> x2<-sample(1:4,300,replace=T) > x2输出结果
[1] 1 2 3 4 4 3 2 1 4 3 4 1 1 2 3 1 1 3 3 4 2 3 3 2 2 4 1 3 2 2 3 1 4 4 3 2 1 [38] 3 2 4 3 1 2 4 4 3 4 1 1 1 4 2 4 3 1 4 4 3 1 3 3 3 4 4 1 3 4 4 1 3 3 3 1 1 [75] 1 2 3 1 4 1 2 4 1 1 4 1 1 4 1 1 1 4 2 1 2 1 3 4 4 1 3 3 4 4 4 3 1 4 1 1 3 [112] 4 3 2 2 3 2 3 4 4 2 3 4 3 2 2 2 1 2 1 3 1 1 1 3 4 1 2 3 1 2 4 1 2 1 2 2 1 [149] 4 1 1 1 1 2 2 3 3 1 1 2 3 4 2 2 2 1 1 3 1 1 3 3 2 1 2 4 2 1 1 3 1 3 1 3 3 [186] 3 3 1 4 2 3 3 4 4 3 4 3 1 4 3 2 4 4 2 3 1 3 3 2 3 4 4 1 4 4 3 4 1 3 1 4 2 [223] 2 2 4 1 4 1 4 2 4 2 4 2 4 4 1 1 2 1 1 4 4 4 1 4 3 2 1 1 4 3 4 3 2 3 2 4 3 [260] 3 4 4 3 2 2 1 3 3 4 1 2 3 2 3 4 2 1 2 1 3 1 2 3 2 1 4 3 3 1 2 4 2 2 3 2 3 [297] 4 3 4 1
示例
> x2[order(factor(x2,levels=c(3,2,1,4)))]输出结果
[1] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 [38] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 [75] 3 3 3 3 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 [112] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 1 1 1 1 1 1 [149] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [186] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [223] 1 1 1 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 [260] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 [297] 4 4 4 4
范例3
> x3<-sample(0:2,300,replace=T) > x3输出结果
[1] 1 0 1 1 1 1 1 2 2 1 2 1 2 1 0 1 1 0 0 0 0 2 0 1 1 1 2 0 0 0 0 2 1 0 0 2 1 [38] 0 0 1 1 2 1 0 0 0 0 1 2 2 2 1 2 2 2 0 2 2 0 0 1 0 2 0 0 2 1 2 2 0 2 0 1 0 [75] 0 0 0 1 1 1 2 2 2 1 0 1 0 1 0 0 0 0 1 2 1 2 0 2 2 2 2 0 1 0 1 0 2 2 1 2 0 [112] 0 2 1 1 2 0 2 0 0 2 0 0 1 2 1 1 0 0 1 0 2 0 0 1 1 1 0 1 1 2 2 2 1 2 0 2 0 [149] 0 0 1 1 1 0 0 1 1 1 2 2 1 2 1 2 0 0 0 0 1 2 1 0 1 1 2 1 1 1 2 1 2 1 2 0 2 [186] 1 0 2 0 2 2 1 1 1 2 1 0 1 1 1 1 1 1 1 1 1 2 2 0 2 1 2 1 2 1 2 2 2 0 0 0 2 [223] 1 1 0 1 0 0 0 0 1 1 0 1 2 1 2 1 2 0 2 1 2 1 1 1 2 2 2 1 1 1 1 2 2 0 0 2 2 [260] 2 1 1 0 2 2 2 0 1 2 0 1 1 1 1 0 0 0 2 2 0 0 1 1 1 2 1 2 1 1 0 1 1 1 2 2 1 [297] 1 0 1 0
示例
> x3[order(factor(x3,levels=c(2,0,1)))]输出结果
[1] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 [38] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 [75] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [112] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 [149] 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 [186] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [223] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [260] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [297] 1 1 1 1
例子4
> x4<-sample(1:10,300,replace=T) > x4输出结果
[1] 7 6 4 4 5 4 4 5 8 7 10 4 6 8 10 7 6 4 9 5 3 6 2 1 3 [26] 7 10 5 4 4 8 9 8 4 2 6 6 6 4 4 1 6 1 9 9 10 10 7 3 9 [51] 1 4 10 5 1 9 6 2 8 1 10 6 8 10 4 9 5 9 4 5 7 1 8 5 7 [76] 5 6 6 10 8 6 8 7 9 10 6 7 2 9 4 5 7 5 7 4 5 1 9 4 6 [101] 9 1 3 3 9 5 1 8 1 3 10 4 3 6 10 3 1 3 10 5 6 5 8 3 9 [126] 8 5 10 7 3 6 6 1 5 10 1 6 3 4 10 6 9 1 10 1 1 1 1 4 3 [151] 2 6 1 6 2 5 5 7 8 10 5 5 1 9 10 10 3 6 10 5 3 4 2 10 9 [176] 2 7 4 3 3 9 3 5 1 3 8 1 5 7 8 9 8 3 5 2 1 7 6 2 9 [201] 9 5 6 7 10 7 3 6 5 2 5 8 1 3 9 1 5 10 7 3 9 3 3 7 3 [226] 2 7 3 8 1 6 2 8 3 3 9 8 10 3 10 10 8 8 2 6 9 7 3 6 6 [251] 10 9 4 2 9 8 10 7 10 2 1 8 10 10 7 2 10 8 2 5 10 4 10 8 9 [276] 1 9 4 10 4 1 2 7 1 9 2 5 3 5 3 6 9 9 6 8 7 10 5 6 9
示例
> x4[order(factor(x4,levels=c(2,4,6,8,10,1,3,5,7,9)))]输出结果
[1] 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 2 4 4 4 4 4 [26] 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 4 6 6 6 6 [51] 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 6 [76] 6 6 6 6 6 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 8 [101] 8 8 8 8 8 8 8 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 [126] 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 10 1 1 1 1 1 1 [151] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 [176] 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 3 [201] 3 3 3 3 3 3 3 3 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 [226] 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 5 7 7 7 7 7 7 7 7 7 [251] 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 7 9 9 9 9 9 9 9 9 [276] 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9 9
范例5
> x5<-sample(21:25,200,replace=T) > x5输出结果
[1] 25 22 25 24 24 25 24 24 22 22 25 25 24 21 21 24 24 24 25 22 24 22 25 22 24 [26] 21 24 24 21 21 25 22 23 21 21 22 23 22 22 25 23 25 22 21 22 25 24 25 21 24 [51] 23 21 22 22 24 24 24 24 25 24 23 21 25 24 22 23 23 24 25 21 23 23 21 25 22 [76] 23 21 25 23 21 23 21 25 24 22 24 22 22 21 21 21 24 22 25 23 22 23 24 24 22 [101] 23 21 24 25 24 22 25 25 22 22 22 25 25 22 24 25 22 22 24 23 23 21 22 25 25 [126] 21 24 23 25 25 23 22 21 21 22 24 24 24 25 24 24 22 23 22 21 23 21 24 25 23 [151] 25 22 21 25 25 23 23 23 24 21 24 22 21 22 24 25 22 24 23 22 25 24 23 23 24 [176] 25 24 25 23 23 21 22 22 24 21 22 24 21 22 22 24 24 25 24 21 22 25 23 23 22
示例
> x5[order(factor(x5,levels=c(25,24,21,22,23)))]输出结果
[1] 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 [26] 25 25 25 25 25 25 25 25 25 25 25 25 25 25 25 24 24 24 24 24 24 24 24 24 24 [51] 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 24 [76] 24 24 24 24 24 24 24 24 24 24 24 24 24 24 21 21 21 21 21 21 21 21 21 21 21 [101] 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 21 22 22 22 [126] 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 [151] 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 22 23 23 23 23 23 23 23 [176] 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23 23