mutate() adds new variables and preserves existing ones; transmute() adds new variables and drops existing ones. Both functions preserve the number of rows of the input. New variables overwrite existing variables of the same name. Variables can be removed by setting their value to NULL.

mutate(.data, ...)

# S3 method for data.frame
mutate(
  .data,
  ...,
  .keep = c("all", "used", "unused", "none"),
  .before = NULL,
  .after = NULL
)

transmute(.data, ...)

Arguments

.data

A data.frame.

...

Name-value pairs of expressions, each with length 1L. The name of each argument will be the name of a new column and the value will be its corresponding value. Use a NULL value in mutate to drop a variable. New variables overwrite existing variables of the same name.

.keep

This argument allows you to control which columns from .data are retained in the output:

  • "all", the default, retains all variables.

  • "used" keeps any variables used to make new variables; it's useful for checking your work as it displays inputs and outputs side-by-side.

  • "unused" keeps only existing variables not used to make new variables.

  • "none", only keeps grouping keys (like transmute()).

Grouping variables are always kept, unconditional to .keep.

.before, .after

<poor-select> Optionally, control where new columns should appear (the default is to add to the right hand side). See relocate() for more details.

Useful mutate functions

Examples

mutate(mtcars, mpg2 = mpg * 2)
#> mpg cyl disp hp drat wt qsec vs am gear carb mpg2 #> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 42.0 #> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 42.0 #> Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 45.6 #> Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 42.8 #> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 37.4 #> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 36.2 #> Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 28.6 #> Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 48.8 #> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 45.6 #> Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 38.4 #> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 35.6 #> Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 32.8 #> Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 34.6 #> Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 30.4 #> Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 20.8 #> Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 20.8 #> Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 29.4 #> Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 64.8 #> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 60.8 #> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 67.8 #> Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 43.0 #> Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 31.0 #> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 30.4 #> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 26.6 #> Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 38.4 #> Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 54.6 #> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 52.0 #> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 60.8 #> Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 31.6 #> Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 39.4 #> Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 30.0 #> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2 42.8
mtcars %>% mutate(mpg2 = mpg * 2)
#> mpg cyl disp hp drat wt qsec vs am gear carb mpg2 #> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 42.0 #> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 42.0 #> Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 45.6 #> Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 42.8 #> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 37.4 #> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 36.2 #> Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 28.6 #> Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 48.8 #> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 45.6 #> Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 38.4 #> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 35.6 #> Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 32.8 #> Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 34.6 #> Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 30.4 #> Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 20.8 #> Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 20.8 #> Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 29.4 #> Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 64.8 #> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 60.8 #> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 67.8 #> Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 43.0 #> Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 31.0 #> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 30.4 #> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 26.6 #> Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 38.4 #> Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 54.6 #> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 52.0 #> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 60.8 #> Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 31.6 #> Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 39.4 #> Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 30.0 #> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2 42.8
mtcars %>% mutate(mpg2 = mpg * 2, cyl2 = cyl * 2)
#> mpg cyl disp hp drat wt qsec vs am gear carb mpg2 #> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 42.0 #> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 42.0 #> Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 45.6 #> Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 42.8 #> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 37.4 #> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 36.2 #> Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 28.6 #> Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 48.8 #> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 45.6 #> Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 38.4 #> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 35.6 #> Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 32.8 #> Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 34.6 #> Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 30.4 #> Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 20.8 #> Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 20.8 #> Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 29.4 #> Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 64.8 #> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 60.8 #> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 67.8 #> Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 43.0 #> Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 31.0 #> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 30.4 #> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 26.6 #> Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 38.4 #> Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 54.6 #> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 52.0 #> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 60.8 #> Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 31.6 #> Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 39.4 #> Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 30.0 #> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2 42.8 #> cyl2 #> Mazda RX4 12 #> Mazda RX4 Wag 12 #> Datsun 710 8 #> Hornet 4 Drive 12 #> Hornet Sportabout 16 #> Valiant 12 #> Duster 360 16 #> Merc 240D 8 #> Merc 230 8 #> Merc 280 12 #> Merc 280C 12 #> Merc 450SE 16 #> Merc 450SL 16 #> Merc 450SLC 16 #> Cadillac Fleetwood 16 #> Lincoln Continental 16 #> Chrysler Imperial 16 #> Fiat 128 8 #> Honda Civic 8 #> Toyota Corolla 8 #> Toyota Corona 8 #> Dodge Challenger 16 #> AMC Javelin 16 #> Camaro Z28 16 #> Pontiac Firebird 16 #> Fiat X1-9 8 #> Porsche 914-2 8 #> Lotus Europa 8 #> Ford Pantera L 16 #> Ferrari Dino 12 #> Maserati Bora 16 #> Volvo 142E 8
# Newly created variables are available immediately mtcars %>% mutate(mpg2 = mpg * 2, mpg4 = mpg2 * 2)
#> mpg cyl disp hp drat wt qsec vs am gear carb mpg2 #> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 42.0 #> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 42.0 #> Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 45.6 #> Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 42.8 #> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 37.4 #> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 36.2 #> Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 28.6 #> Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 48.8 #> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 45.6 #> Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 38.4 #> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 35.6 #> Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 32.8 #> Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 34.6 #> Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 30.4 #> Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 20.8 #> Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 20.8 #> Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 29.4 #> Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 64.8 #> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 60.8 #> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 67.8 #> Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 43.0 #> Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 31.0 #> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 30.4 #> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 26.6 #> Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 38.4 #> Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 54.6 #> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 52.0 #> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 60.8 #> Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 31.6 #> Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 39.4 #> Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 30.0 #> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2 42.8 #> mpg4 #> Mazda RX4 84.0 #> Mazda RX4 Wag 84.0 #> Datsun 710 91.2 #> Hornet 4 Drive 85.6 #> Hornet Sportabout 74.8 #> Valiant 72.4 #> Duster 360 57.2 #> Merc 240D 97.6 #> Merc 230 91.2 #> Merc 280 76.8 #> Merc 280C 71.2 #> Merc 450SE 65.6 #> Merc 450SL 69.2 #> Merc 450SLC 60.8 #> Cadillac Fleetwood 41.6 #> Lincoln Continental 41.6 #> Chrysler Imperial 58.8 #> Fiat 128 129.6 #> Honda Civic 121.6 #> Toyota Corolla 135.6 #> Toyota Corona 86.0 #> Dodge Challenger 62.0 #> AMC Javelin 60.8 #> Camaro Z28 53.2 #> Pontiac Firebird 76.8 #> Fiat X1-9 109.2 #> Porsche 914-2 104.0 #> Lotus Europa 121.6 #> Ford Pantera L 63.2 #> Ferrari Dino 78.8 #> Maserati Bora 60.0 #> Volvo 142E 85.6
# You can also use mutate() to remove variables and modify existing variables mtcars %>% mutate( mpg = NULL, disp = disp * 0.0163871 # convert to litres )
#> cyl disp hp drat wt qsec vs am gear carb #> Mazda RX4 6 2.621936 110 3.90 2.620 16.46 0 1 4 4 #> Mazda RX4 Wag 6 2.621936 110 3.90 2.875 17.02 0 1 4 4 #> Datsun 710 4 1.769807 93 3.85 2.320 18.61 1 1 4 1 #> Hornet 4 Drive 6 4.227872 110 3.08 3.215 19.44 1 0 3 1 #> Hornet Sportabout 8 5.899356 175 3.15 3.440 17.02 0 0 3 2 #> Valiant 6 3.687098 105 2.76 3.460 20.22 1 0 3 1 #> Duster 360 8 5.899356 245 3.21 3.570 15.84 0 0 3 4 #> Merc 240D 4 2.403988 62 3.69 3.190 20.00 1 0 4 2 #> Merc 230 4 2.307304 95 3.92 3.150 22.90 1 0 4 2 #> Merc 280 6 2.746478 123 3.92 3.440 18.30 1 0 4 4 #> Merc 280C 6 2.746478 123 3.92 3.440 18.90 1 0 4 4 #> Merc 450SE 8 4.519562 180 3.07 4.070 17.40 0 0 3 3 #> Merc 450SL 8 4.519562 180 3.07 3.730 17.60 0 0 3 3 #> Merc 450SLC 8 4.519562 180 3.07 3.780 18.00 0 0 3 3 #> Cadillac Fleetwood 8 7.734711 205 2.93 5.250 17.98 0 0 3 4 #> Lincoln Continental 8 7.538066 215 3.00 5.424 17.82 0 0 3 4 #> Chrysler Imperial 8 7.210324 230 3.23 5.345 17.42 0 0 3 4 #> Fiat 128 4 1.289665 66 4.08 2.200 19.47 1 1 4 1 #> Honda Civic 4 1.240503 52 4.93 1.615 18.52 1 1 4 2 #> Toyota Corolla 4 1.165123 65 4.22 1.835 19.90 1 1 4 1 #> Toyota Corona 4 1.968091 97 3.70 2.465 20.01 1 0 3 1 #> Dodge Challenger 8 5.211098 150 2.76 3.520 16.87 0 0 3 2 #> AMC Javelin 8 4.981678 150 3.15 3.435 17.30 0 0 3 2 #> Camaro Z28 8 5.735485 245 3.73 3.840 15.41 0 0 3 4 #> Pontiac Firebird 8 6.554840 175 3.08 3.845 17.05 0 0 3 2 #> Fiat X1-9 4 1.294581 66 4.08 1.935 18.90 1 1 4 1 #> Porsche 914-2 4 1.971368 91 4.43 2.140 16.70 0 1 5 2 #> Lotus Europa 4 1.558413 113 3.77 1.513 16.90 1 1 5 2 #> Ford Pantera L 8 5.751872 264 4.22 3.170 14.50 0 1 5 4 #> Ferrari Dino 6 2.376130 175 3.62 2.770 15.50 0 1 5 6 #> Maserati Bora 8 4.932517 335 3.54 3.570 14.60 0 1 5 8 #> Volvo 142E 4 1.982839 109 4.11 2.780 18.60 1 1 4 2
# By default, new columns are placed on the far right. # You can override this with `.before` or `.after`. df <- data.frame(x = 1, y = 2) df %>% mutate(z = x + y)
#> x y z #> 1 1 2 3
df %>% mutate(z = x + y, .before = 1)
#> z x y #> 1 3 1 2
df %>% mutate(z = x + y, .after = x)
#> x z y #> 1 1 3 2
# By default, mutate() keeps all columns from the input data. # You can override with `.keep` df <- data.frame( x = 1, y = 2, a = "a", b = "b", stringsAsFactors = FALSE ) df %>% mutate(z = x + y, .keep = "all") # the default
#> x y a b z #> 1 1 2 a b 3
df %>% mutate(z = x + y, .keep = "used")
#> x y z #> 1 1 2 3
df %>% mutate(z = x + y, .keep = "unused")
#> a b z #> 1 a b 3
df %>% mutate(z = x + y, .keep = "none") # same as transmute()
#> z #> 1 3
# mutate() vs transmute -------------------------- # mutate() keeps all existing variables mtcars %>% mutate(displ_l = disp / 61.0237)
#> mpg cyl disp hp drat wt qsec vs am gear carb #> Mazda RX4 21.0 6 160.0 110 3.90 2.620 16.46 0 1 4 4 #> Mazda RX4 Wag 21.0 6 160.0 110 3.90 2.875 17.02 0 1 4 4 #> Datsun 710 22.8 4 108.0 93 3.85 2.320 18.61 1 1 4 1 #> Hornet 4 Drive 21.4 6 258.0 110 3.08 3.215 19.44 1 0 3 1 #> Hornet Sportabout 18.7 8 360.0 175 3.15 3.440 17.02 0 0 3 2 #> Valiant 18.1 6 225.0 105 2.76 3.460 20.22 1 0 3 1 #> Duster 360 14.3 8 360.0 245 3.21 3.570 15.84 0 0 3 4 #> Merc 240D 24.4 4 146.7 62 3.69 3.190 20.00 1 0 4 2 #> Merc 230 22.8 4 140.8 95 3.92 3.150 22.90 1 0 4 2 #> Merc 280 19.2 6 167.6 123 3.92 3.440 18.30 1 0 4 4 #> Merc 280C 17.8 6 167.6 123 3.92 3.440 18.90 1 0 4 4 #> Merc 450SE 16.4 8 275.8 180 3.07 4.070 17.40 0 0 3 3 #> Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 3 #> Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 3 #> Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 4 #> Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 4 #> Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 4 #> Fiat 128 32.4 4 78.7 66 4.08 2.200 19.47 1 1 4 1 #> Honda Civic 30.4 4 75.7 52 4.93 1.615 18.52 1 1 4 2 #> Toyota Corolla 33.9 4 71.1 65 4.22 1.835 19.90 1 1 4 1 #> Toyota Corona 21.5 4 120.1 97 3.70 2.465 20.01 1 0 3 1 #> Dodge Challenger 15.5 8 318.0 150 2.76 3.520 16.87 0 0 3 2 #> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 2 #> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 4 #> Pontiac Firebird 19.2 8 400.0 175 3.08 3.845 17.05 0 0 3 2 #> Fiat X1-9 27.3 4 79.0 66 4.08 1.935 18.90 1 1 4 1 #> Porsche 914-2 26.0 4 120.3 91 4.43 2.140 16.70 0 1 5 2 #> Lotus Europa 30.4 4 95.1 113 3.77 1.513 16.90 1 1 5 2 #> Ford Pantera L 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 4 #> Ferrari Dino 19.7 6 145.0 175 3.62 2.770 15.50 0 1 5 6 #> Maserati Bora 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8 #> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2 #> displ_l #> Mazda RX4 2.621932 #> Mazda RX4 Wag 2.621932 #> Datsun 710 1.769804 #> Hornet 4 Drive 4.227866 #> Hornet Sportabout 5.899347 #> Valiant 3.687092 #> Duster 360 5.899347 #> Merc 240D 2.403984 #> Merc 230 2.307300 #> Merc 280 2.746474 #> Merc 280C 2.746474 #> Merc 450SE 4.519556 #> Merc 450SL 4.519556 #> Merc 450SLC 4.519556 #> Cadillac Fleetwood 7.734700 #> Lincoln Continental 7.538055 #> Chrysler Imperial 7.210313 #> Fiat 128 1.289663 #> Honda Civic 1.240502 #> Toyota Corolla 1.165121 #> Toyota Corona 1.968088 #> Dodge Challenger 5.211090 #> AMC Javelin 4.981671 #> Camaro Z28 5.735477 #> Pontiac Firebird 6.554830 #> Fiat X1-9 1.294579 #> Porsche 914-2 1.971365 #> Lotus Europa 1.558411 #> Ford Pantera L 5.751864 #> Ferrari Dino 2.376126 #> Maserati Bora 4.932510 #> Volvo 142E 1.982836
# transmute keeps only the variables you create mtcars %>% transmute(displ_l = disp / 61.0237)
#> displ_l #> Mazda RX4 2.621932 #> Mazda RX4 Wag 2.621932 #> Datsun 710 1.769804 #> Hornet 4 Drive 4.227866 #> Hornet Sportabout 5.899347 #> Valiant 3.687092 #> Duster 360 5.899347 #> Merc 240D 2.403984 #> Merc 230 2.307300 #> Merc 280 2.746474 #> Merc 280C 2.746474 #> Merc 450SE 4.519556 #> Merc 450SL 4.519556 #> Merc 450SLC 4.519556 #> Cadillac Fleetwood 7.734700 #> Lincoln Continental 7.538055 #> Chrysler Imperial 7.210313 #> Fiat 128 1.289663 #> Honda Civic 1.240502 #> Toyota Corolla 1.165121 #> Toyota Corona 1.968088 #> Dodge Challenger 5.211090 #> AMC Javelin 4.981671 #> Camaro Z28 5.735477 #> Pontiac Firebird 6.554830 #> Fiat X1-9 1.294579 #> Porsche 914-2 1.971365 #> Lotus Europa 1.558411 #> Ford Pantera L 5.751864 #> Ferrari Dino 2.376126 #> Maserati Bora 4.932510 #> Volvo 142E 1.982836