如何在R数据框中使用不同的名称创建重复列？
在R数据框中创建重复列的最简单方法是用$符号设置新列，如果我们要使用其他名称，则可以简单地传递一个新名称。例如，如果我们有一个包含第x列的数据帧df，而我们希望有一个新的x1列，其值与x中的值相同，则可以将其设为df$x1<-df$x。
示例
> set.seed(254) > x<-LETTERS[1:20] > y<-rnorm(20,1,0.5) > z<-rpois(20,5) > a<-rexp(20,3.15) > b<-runif(20,1,10) > c<-rnorm(20,25,2) > df<-data.frame(x,y,z,a,b,c) > df
输出结果
x y z a b c 1 A 0.8709244 9 0.072625990 5.125432 26.84561 2 B 1.7993156 3 0.012325435 8.709408 29.25686 3 C 1.0673554 3 0.116407319 6.162522 24.45550 4 D 0.7591570 6 0.132844837 2.233053 22.78211 5 E 1.5101376 11 0.143086285 7.034326 23.05859 6 F 1.1484377 3 0.244212366 2.148795 26.76058 7 G 0.9359269 7 0.453025589 2.572604 25.09759 8 H 1.8053553 4 0.405635819 2.211568 27.35471 9 I 0.0227141 1 0.681061571 1.939878 23.64751 10 J 1.1996667 3 0.073740911 1.018387 24.03023 11 K 0.7770920 3 0.243659953 2.834134 25.22378 12 L 1.2767936 3 0.147269006 9.057046 25.19877 13 M 1.8200664 5 0.087731612 8.750051 27.73970 14 N 0.8545241 5 0.790998463 4.542890 25.35204 15 O 0.9362344 3 0.182957462 1.883847 23.53194 16 P 1.2897848 3 0.531395356 1.718161 24.98864 17 Q 0.6280537 2 0.001632791 6.674458 29.35283 18 R 1.6190747 9 0.327203858 4.176428 25.95383 19 S 1.1918612 2 0.171366109 4.499863 24.79101 20 T 1.4844707 3 0.077982281 6.824088 26.07107
在df中创建ID列，该列与x重复：
示例
> df$ID<-df$x > df
输出结果
x y z a b c ID 1 A 0.8709244 9 0.072625990 5.125432 26.84561 A 2 B 1.7993156 3 0.012325435 8.709408 29.25686 B 3 C 1.0673554 3 0.116407319 6.162522 24.45550 C 4 D 0.7591570 6 0.132844837 2.233053 22.78211 D 5 E 1.5101376 11 0.143086285 7.034326 23.05859 E 6 F 1.1484377 3 0.244212366 2.148795 26.76058 F 7 G 0.9359269 7 0.453025589 2.572604 25.09759 G 8 H 1.8053553 4 0.405635819 2.211568 27.35471 H 9 I 0.0227141 1 0.681061571 1.939878 23.64751 I 10 J 1.1996667 3 0.073740911 1.018387 24.03023 J 11 K 0.7770920 3 0.243659953 2.834134 25.22378 K 12 L 1.2767936 3 0.147269006 9.057046 25.19877 L 13 M 1.8200664 5 0.087731612 8.750051 27.73970 M 14 N 0.8545241 5 0.790998463 4.542890 25.35204 N 15 O 0.9362344 3 0.182957462 1.883847 23.53194 O 16 P 1.2897848 3 0.531395356 1.718161 24.98864 P 17 Q 0.6280537 2 0.001632791 6.674458 29.35283 Q 18 R 1.6190747 9 0.327203858 4.176428 25.95383 R 19 S 1.1918612 2 0.171366109 4.499863 24.79101 S 20 T 1.4844707 3 0.077982281 6.824088 26.07107 T
在df中创建“评级”列，该列与z相同：
示例
> df$Rating<-df$z > df
输出结果
x y z a b c ID Rating 1 A 0.8709244 9 0.072625990 5.125432 26.84561 A 9 2 B 1.7993156 3 0.012325435 8.709408 29.25686 B 3 3 C 1.0673554 3 0.116407319 6.162522 24.45550 C 3 4 D 0.7591570 6 0.132844837 2.233053 22.78211 D 6 5 E 1.5101376 11 0.143086285 7.034326 23.05859 E 11 6 F 1.1484377 3 0.244212366 2.148795 26.76058 F 3 7 G 0.9359269 7 0.453025589 2.572604 25.09759 G 7 8 H 1.8053553 4 0.405635819 2.211568 27.35471 H 4 9 I 0.0227141 1 0.681061571 1.939878 23.64751 I 1 10 J 1.1996667 3 0.073740911 1.018387 24.03023 J 3 11 K 0.7770920 3 0.243659953 2.834134 25.22378 K 3 12 L 1.2767936 3 0.147269006 9.057046 25.19877 L 3 13 M 1.8200664 5 0.087731612 8.750051 27.73970 M 5 14 N 0.8545241 5 0.790998463 4.542890 25.35204 N 5 15 O 0.9362344 3 0.182957462 1.883847 23.53194 O 3 16 P 1.2897848 3 0.531395356 1.718161 24.98864 P 3 17 Q 0.6280537 2 0.001632791 6.674458 29.35283 Q 2 18 R 1.6190747 9 0.327203858 4.176428 25.95383 R 9 19 S 1.1918612 2 0.171366109 4.499863 24.79101 S 2 20 T 1.4844707 3 0.077982281 6.824088 26.07107 T 3
在df中创建“权重”列，它是c的副本：
示例
> df$Weight<-df$c > df
输出结果
x y z a b c ID Rating Weight 1 A 0.8709244 9 0.072625990 5.125432 26.84561 A 9 26.84561 2 B 1.7993156 3 0.012325435 8.709408 29.25686 B 3 29.25686 3 C 1.0673554 3 0.116407319 6.162522 24.45550 C 3 24.45550 4 D 0.7591570 6 0.132844837 2.233053 22.78211 D 6 22.78211 5 E 1.5101376 11 0.143086285 7.034326 23.05859 E 11 23.05859 6 F 1.1484377 3 0.244212366 2.148795 26.76058 F 3 26.76058 7 G 0.9359269 7 0.453025589 2.572604 25.09759 G 7 25.09759 8 H 1.8053553 4 0.405635819 2.211568 27.35471 H 4 27.35471 9 I 0.0227141 1 0.681061571 1.939878 23.64751 I 1 23.64751 10 J 1.1996667 3 0.073740911 1.018387 24.03023 J 3 24.03023 11 K 0.7770920 3 0.243659953 2.834134 25.22378 K 3 25.22378 12 L 1.2767936 3 0.147269006 9.057046 25.19877 L 3 25.19877 13 M 1.8200664 5 0.087731612 8.750051 27.73970 M 5 27.73970 14 N 0.8545241 5 0.790998463 4.542890 25.35204 N 5 25.35204 15 O 0.9362344 3 0.182957462 1.883847 23.53194 O 3 23.53194 16 P 1.2897848 3 0.531395356 1.718161 24.98864 P 3 24.98864 17 Q 0.6280537 2 0.001632791 6.674458 29.35283 Q 2 29.35283 18 R 1.6190747 9 0.327203858 4.176428 25.95383 R 9 25.95383 19 S 1.1918612 2 0.171366109 4.499863 24.79101 S 2 24.79101 20 T 1.4844707 3 0.077982281 6.824088 26.07107 T 3 26.07107