你可以通过提供.names
参数来实现这一点:
描述如何命名输出列的粘合规范.这可以使用{.col}
代表选定的列名,{.fn}
代表正在应用的函数的名称.
如果没有.names
,则该函数将应用于在位的列.对于.names
,正在使用其规范创建新的列.
我将以mtcars
为例:
vars_to_mc <- c("mpg", "cyl", "disp")
mtcars |>
mutate(
across(
all_of(vars_to_mc),
\(x) x - mean(x, na.rm = TRUE),
.names = "{.col}_mc"
)
)
dplyr::mutate_at()
现在已经过时了.从字符向量中 Select 变量的当前方法是dplyr::all_of()
.
输出:
mpg cyl disp hp drat wt qsec vs am gear carb mpg_mc cyl_mc disp_mc
Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 0.909375 -0.1875 -70.721875
Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 0.909375 -0.1875 -70.721875
Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 2.709375 -2.1875 -122.721875
Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 1.309375 -0.1875 27.278125
Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 -1.390625 1.8125 129.278125
Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 -1.990625 -0.1875 -5.721875
Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 -5.790625 1.8125 129.278125
Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 4.309375 -2.1875 -84.021875
Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 2.709375 -2.1875 -89.921875
Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 -0.890625 -0.1875 -63.121875
Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 -2.290625 -0.1875 -63.121875
Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 -3.690625 1.8125 45.078125
Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 -2.790625 1.8125 45.078125
Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 -4.890625 1.8125 45.078125
Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 -9.690625 1.8125 241.278125
Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 -9.690625 1.8125 229.278125
Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 -5.390625 1.8125 209.278125
Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 12.309375 -2.1875 -152.021875
Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 10.309375 -2.1875 -155.021875
Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 13.809375 -2.1875 -159.621875
Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 1.409375 -2.1875 -110.621875
Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 -4.590625 1.8125 87.278125
AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 -4.890625 1.8125 73.278125
Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 -6.790625 1.8125 119.278125
Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 -0.890625 1.8125 169.278125
Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 7.209375 -2.1875 -151.721875
Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 5.909375 -2.1875 -110.421875
Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 10.309375 -2.1875 -135.621875
Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 -4.290625 1.8125 120.278125
Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 -0.390625 -0.1875 -85.721875
Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 -5.090625 1.8125 70.278125
Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2 1.309375 -2.1875 -109.721875