Recode a variable using a pair of vectors matched by row (i.e. a dictionary of the sort commonly made using a spreadsheet). This allows you to translate a variable from one coding scheme to another using arbitrary conditional matching in situations where it would be overly tedious to use recode, if_else, or case_when to recode a variable because there are many conditional replacements to be specified.
translate(y, old, new)A vector that you wish to translate/recode.
A vector containing values of the old coding scheme with corresponding values/rows in "new". Should be the same length as the "new" vector.
A vector containing values of the new coding scheme with corresponding values/rows in "old". Should be the same length as the "old" vector.
An updated version of the input vector that has been translated from the old coding scheme to the new one.
data(mtcars)
old_values <- c(1:10)
new_values <- c("one", "two", "three", "four", "five",
"six", "seven", "eight", "nine", "ten")
#use it on its own
translate(y = mtcars$cyl, old = old_values, new = new_values)
#> [1] "six" "six" "four" "six" "eight" "six" "eight" "four" "four"
#> [10] "six" "six" "eight" "eight" "eight" "eight" "eight" "eight" "four"
#> [19] "four" "four" "four" "eight" "eight" "eight" "eight" "four" "four"
#> [28] "four" "eight" "six" "eight" "four"
#or within a dplyr::mutate call
dplyr::mutate(mtcars,
translated_cyl = translate(cyl,
old = old_values,
new = new_values))
#> 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
#> translated_cyl
#> Mazda RX4 six
#> Mazda RX4 Wag six
#> Datsun 710 four
#> Hornet 4 Drive six
#> Hornet Sportabout eight
#> Valiant six
#> Duster 360 eight
#> Merc 240D four
#> Merc 230 four
#> Merc 280 six
#> Merc 280C six
#> Merc 450SE eight
#> Merc 450SL eight
#> Merc 450SLC eight
#> Cadillac Fleetwood eight
#> Lincoln Continental eight
#> Chrysler Imperial eight
#> Fiat 128 four
#> Honda Civic four
#> Toyota Corolla four
#> Toyota Corona four
#> Dodge Challenger eight
#> AMC Javelin eight
#> Camaro Z28 eight
#> Pontiac Firebird eight
#> Fiat X1-9 four
#> Porsche 914-2 four
#> Lotus Europa four
#> Ford Pantera L eight
#> Ferrari Dino six
#> Maserati Bora eight
#> Volvo 142E four