我有一个数据框，例如mtcars：
> glimpse(mtcars)
Observations: 32
Variables: 11
$ mpg <dbl> 21.0, 21.0, 22.8, 21.4, 18.7, 18.1, 14.3, 24.4, 22.8, 19.2, 17.8, 16.4, 17.3, 15.2, 10.4, 10.4, 14.7, 32.4, 30.4, 33.9, 21.5, 15.5, 15.2, 13.3, 19.2, …
$ cyl <dbl> 6, 6, 4, 6, 8, 6, 8, 4, 4, 6, 6, 8, 8, 8, 8, 8, 8, 4, 4, 4, 4, 8, 8, 8, 8, 4, 4, 4, 8, 6, 8, 4
$ disp <dbl> 160.0, 160.0, 108.0, 258.0, 360.0, 225.0, 360.0, 146.7, 140.8, 167.6, 167.6, 275.8, 275.8, 275.8, 472.0, 460.0, 440.0, 78.7, 75.7, 71.1, 120.1, 318.0,…
$ hp <dbl> 110, 110, 93, 110, 175, 105, 245, 62, 95, 123, 123, 180, 180, 180, 205, 215, 230, 66, 52, 65, 97, 150, 150, 245, 175, 66, 91, 113, 264, 175, 335, 109
$ drat <dbl> 3.90, 3.90, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3.92, 3.92, 3.07, 3.07, 3.07, 2.93, 3.00, 3.23, 4.08, 4.93, 4.22, 3.70, 2.76, 3.15, 3.73, 3.08, …
$ wt <dbl> 2.620, 2.875, 2.320, 3.215, 3.440, 3.460, 3.570, 3.190, 3.150, 3.440, 3.440, 4.070, 3.730, 3.780, 5.250, 5.424, 5.345, 2.200, 1.615, 1.835, 2.465, 3.5…
$ qsec <dbl> 16.46, 17.02, 18.61, 19.44, 17.02, 20.22, 15.84, 20.00, 22.90, 18.30, 18.90, 17.40, 17.60, 18.00, 17.98, 17.82, 17.42, 19.47, 18.52, 19.90, 20.01, 16.…
$ vs <dbl> 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1
$ am <dbl> 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1
$ gear <dbl> 4, 4, 4, 3, 3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 3, 3, 3, 3, 4, 5, 5, 5, 5, 5, 4
$ carb <dbl> 4, 4, 1, 1, 2, 1, 4, 2, 2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2, 1, 1, 2, 2, 4, 2, 1, 2, 2, 4, 6, 8, 2
假设我想对功能进行重新排序，以使hp是出现在数据框中而不是mpg的第一列。
我知道我可以像这样使用dplyr：
> glimpse(mtcars %>% select_at(vars(hp, mpg:disp, drat:carb)))
Observations: 32
Variables: 11
$ hp <dbl> 110, 110, 93, 110, 175, 105, 245, 62, 95, 123, 123, 180, 180, 180, 205, 215, 230, 66, 52, 65, 97, 150, 150, 245, 175, 66, 91, 113, 264, 175, 335, 109
$ mpg <dbl> 21.0, 21.0, 22.8, 21.4, 18.7, 18.1, 14.3, 24.4, 22.8, 19.2, 17.8, 16.4, 17.3, 15.2, 10.4, 10.4, 14.7, 32.4, 30.4, 33.9, 21.5, 15.5, 15.2, 13.3, 19.2, …
$ cyl <dbl> 6, 6, 4, 6, 8, 6, 8, 4, 4, 6, 6, 8, 8, 8, 8, 8, 8, 4, 4, 4, 4, 8, 8, 8, 8, 4, 4, 4, 8, 6, 8, 4
$ disp <dbl> 160.0, 160.0, 108.0, 258.0, 360.0, 225.0, 360.0, 146.7, 140.8, 167.6, 167.6, 275.8, 275.8, 275.8, 472.0, 460.0, 440.0, 78.7, 75.7, 71.1, 120.1, 318.0,…
$ drat <dbl> 3.90, 3.90, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3.92, 3.92, 3.07, 3.07, 3.07, 2.93, 3.00, 3.23, 4.08, 4.93, 4.22, 3.70, 2.76, 3.15, 3.73, 3.08, …
$ wt <dbl> 2.620, 2.875, 2.320, 3.215, 3.440, 3.460, 3.570, 3.190, 3.150, 3.440, 3.440, 4.070, 3.730, 3.780, 5.250, 5.424, 5.345, 2.200, 1.615, 1.835, 2.465, 3.5…
$ qsec <dbl> 16.46, 17.02, 18.61, 19.44, 17.02, 20.22, 15.84, 20.00, 22.90, 18.30, 18.90, 17.40, 17.60, 18.00, 17.98, 17.82, 17.42, 19.47, 18.52, 19.90, 20.01, 16.…
$ vs <dbl> 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1
$ am <dbl> 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1
$ gear <dbl> 4, 4, 4, 3, 3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 3, 3, 3, 3, 4, 5, 5, 5, 5, 5, 4
$ carb <dbl> 4, 4, 1, 1, 2, 1, 4, 2, 2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2, 1, 1, 2, 2, 4, 2, 1, 2, 2, 4, 6, 8, 2
是否有更短，更优雅的方法？
（特别欢迎使用tidyverse或base r解决方案）
答案 0 :(得分：2)
library(tidyverse)
mtcars %>%
select(hp, everything())
#> hp mpg cyl disp drat wt qsec vs am gear carb
#> Mazda RX4 110 21.0 6 160.0 3.90 2.620 16.46 0 1 4 4
#> Mazda RX4 Wag 110 21.0 6 160.0 3.90 2.875 17.02 0 1 4 4
#> Datsun 710 93 22.8 4 108.0 3.85 2.320 18.61 1 1 4 1
#> Hornet 4 Drive 110 21.4 6 258.0 3.08 3.215 19.44 1 0 3 1
#> Hornet Sportabout 175 18.7 8 360.0 3.15 3.440 17.02 0 0 3 2
#> Valiant 105 18.1 6 225.0 2.76 3.460 20.22 1 0 3 1
#> Duster 360 245 14.3 8 360.0 3.21 3.570 15.84 0 0 3 4
#> Merc 240D 62 24.4 4 146.7 3.69 3.190 20.00 1 0 4 2
#> Merc 230 95 22.8 4 140.8 3.92 3.150 22.90 1 0 4 2
#> Merc 280 123 19.2 6 167.6 3.92 3.440 18.30 1 0 4 4
#> Merc 280C 123 17.8 6 167.6 3.92 3.440 18.90 1 0 4 4
#> Merc 450SE 180 16.4 8 275.8 3.07 4.070 17.40 0 0 3 3
#> Merc 450SL 180 17.3 8 275.8 3.07 3.730 17.60 0 0 3 3
#> Merc 450SLC 180 15.2 8 275.8 3.07 3.780 18.00 0 0 3 3
#> Cadillac Fleetwood 205 10.4 8 472.0 2.93 5.250 17.98 0 0 3 4
#> Lincoln Continental 215 10.4 8 460.0 3.00 5.424 17.82 0 0 3 4
#> Chrysler Imperial 230 14.7 8 440.0 3.23 5.345 17.42 0 0 3 4
#> Fiat 128 66 32.4 4 78.7 4.08 2.200 19.47 1 1 4 1
#> Honda Civic 52 30.4 4 75.7 4.93 1.615 18.52 1 1 4 2
#> Toyota Corolla 65 33.9 4 71.1 4.22 1.835 19.90 1 1 4 1
#> Toyota Corona 97 21.5 4 120.1 3.70 2.465 20.01 1 0 3 1
#> Dodge Challenger 150 15.5 8 318.0 2.76 3.520 16.87 0 0 3 2
#> AMC Javelin 150 15.2 8 304.0 3.15 3.435 17.30 0 0 3 2
#> Camaro Z28 245 13.3 8 350.0 3.73 3.840 15.41 0 0 3 4
#> Pontiac Firebird 175 19.2 8 400.0 3.08 3.845 17.05 0 0 3 2
#> Fiat X1-9 66 27.3 4 79.0 4.08 1.935 18.90 1 1 4 1
#> Porsche 914-2 91 26.0 4 120.3 4.43 2.140 16.70 0 1 5 2
#> Lotus Europa 113 30.4 4 95.1 3.77 1.513 16.90 1 1 5 2
#> Ford Pantera L 264 15.8 8 351.0 4.22 3.170 14.50 0 1 5 4
#> Ferrari Dino 175 19.7 6 145.0 3.62 2.770 15.50 0 1 5 6
#> Maserati Bora 335 15.0 8 301.0 3.54 3.570 14.60 0 1 5 8
#> Volvo 142E 109 21.4 4 121.0 4.11 2.780 18.60 1 1 4 2
由reprex package（v0.2.1）于2019-03-08创建
答案 1 :(得分：0)
dplyr导入tidyselect辅助函数everything，顾名思义，它将选择所有内容。可以将其与其他列选择结合使用，因此在这种情况下，选择hp，然后选择所有内容-由于列只能出现一次，因此具有hp的含义，然后所有内容< em> else 。
library(dplyr)
mtcars %>%
select(hp, everything()) %>%
head()
#> hp mpg cyl disp drat wt qsec vs am gear carb
#> Mazda RX4 110 21.0 6 160 3.90 2.620 16.46 0 1 4 4
#> Mazda RX4 Wag 110 21.0 6 160 3.90 2.875 17.02 0 1 4 4
#> Datsun 710 93 22.8 4 108 3.85 2.320 18.61 1 1 4 1
#> Hornet 4 Drive 110 21.4 6 258 3.08 3.215 19.44 1 0 3 1
#> Hornet Sportabout 175 18.7 8 360 3.15 3.440 17.02 0 0 3 2
#> Valiant 105 18.1 6 225 2.76 3.460 20.22 1 0 3 1
几种基本的R方式可能涉及根据位置cbind列。在这种情况下，hp是第4列，因此我将mtcars的第4列与所有{em>但 mtcars的第4列绑定在一起（输出与上方）：
cbind(mtcars[4], mtcars[-4])
或者基于名称，在这里我首先为等于"hp"，然后不等于"hp"的列名称子集：
cbind(mtcars[names(mtcars) == "hp"], mtcars[names(mtcars) != "hp"])
我敢肯定，还有其他基本的R方法-肯定可以用subset来完成。