This function sets a variable to NA based on one or several logical conditions. It would most naturally be used inside a dplyr-mutate call. By default, the conditions are combined with a logical OR, yet this can be changed to AND by setting operator = "&".
na_when(x, ..., operator = "|")The variable to transform.
One or more logical conditions, involving x or other variables.
Name of a logical operator to combine the conditions. Defaults to "|" (or),
"&" (and) is the other common choice, though "xor" would also work.
Note that the function is called na_when to prevent clashing with dplyr's na_if ...
even though the latter might be the more intuitive name.
library(dplyr)
ess_health %>%
mutate(eisced = na_when(eisced, cntry == "DE", agea < 21))
#> # A tibble: 7,226 × 23
#> cntry gndr agea eisced pweight pspwght health height weight icbrnct etfruit
#> <chr> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1 DE 1 52 NA 2.30 0.608 1 187 78 1 1
#> 2 DE 2 52 NA 2.30 0.463 2 168 110 1 4
#> 3 DE 1 62 NA 2.30 0.640 1 181 84 1 5
#> 4 DE 2 62 NA 2.30 1.14 3 155 63 1 5
#> 5 DE 2 20 NA 2.30 0.853 1 160 70 1 2
#> 6 DE 1 49 NA 2.30 0.364 2 177 89 1 3
#> 7 DE 1 63 NA 2.30 0.310 3 169 87 1 1
#> 8 DE 2 32 NA 2.30 1.35 3 163 62 1 3
#> 9 DE 2 66 NA 2.30 0.341 1 157 56 1 1
#> 10 DE 1 15 NA 2.30 1.74 3 172 72 1 4
#> # ℹ 7,216 more rows
#> # ℹ 12 more variables: eatveg <dbl>, dosprt <dbl>, cgtsmke <dbl>,
#> # alcfreq <dbl>, fltdpr <dbl>, flteeff <dbl>, slprl <dbl>, wrhpp <dbl>,
#> # fltlnl <dbl>, enjlf <dbl>, fltsd <dbl>, cldgng <dbl>
mtcars %>%
mutate(carb = na_when(carb, cyl > 6, mpg < 19, operator = "&"))
#> 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 NA
#> 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 NA
#> 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 NA
#> Merc 450SL 17.3 8 275.8 180 3.07 3.730 17.60 0 0 3 NA
#> Merc 450SLC 15.2 8 275.8 180 3.07 3.780 18.00 0 0 3 NA
#> Cadillac Fleetwood 10.4 8 472.0 205 2.93 5.250 17.98 0 0 3 NA
#> Lincoln Continental 10.4 8 460.0 215 3.00 5.424 17.82 0 0 3 NA
#> Chrysler Imperial 14.7 8 440.0 230 3.23 5.345 17.42 0 0 3 NA
#> 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 NA
#> AMC Javelin 15.2 8 304.0 150 3.15 3.435 17.30 0 0 3 NA
#> Camaro Z28 13.3 8 350.0 245 3.73 3.840 15.41 0 0 3 NA
#> 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 NA
#> 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 NA
#> Volvo 142E 21.4 4 121.0 109 4.11 2.780 18.60 1 1 4 2