With dplyr you can do something like this:
library(tidyverse)
#> Warning: package 'tibble' was built under R version 3.5.2
index_1 <- sample(mtcars$gear, 5)
index_2 <- sample(mtcars$hp, 5)
index_3 <- sample(mtcars$disp, 5)
index <- c(index_1, index_2, index_3)
mtcars %>%
mutate_all(~ifelse(.x %in% index, 48, .x))
#> mpg cyl disp hp drat wt qsec vs am gear carb
#> 1 21.0 6 160.0 110 3.90 2.620 16.46 0 1 48 48
#> 2 21.0 6 160.0 110 3.90 2.875 17.02 0 1 48 48
#> 3 22.8 48 108.0 93 3.85 2.320 18.61 1 1 48 1
#> 4 21.4 6 258.0 110 3.08 3.215 19.44 1 0 48 1
#> 5 18.7 8 360.0 175 3.15 3.440 17.02 0 0 48 2
#> 6 18.1 6 225.0 48 2.76 3.460 20.22 1 0 48 1
#> 7 14.3 8 360.0 245 3.21 3.570 15.84 0 0 48 48
#> 8 24.4 48 146.7 62 3.69 3.190 20.00 1 0 48 2
#> 9 22.8 48 140.8 95 3.92 3.150 22.90 1 0 48 2
#> 10 19.2 6 167.6 48 3.92 3.440 18.30 1 0 48 48
#> 11 17.8 6 167.6 48 3.92 3.440 18.90 1 0 48 48
#> 12 16.4 8 48.0 48 3.07 4.070 17.40 0 0 48 48
#> 13 17.3 8 48.0 48 3.07 3.730 17.60 0 0 48 48
#> 14 15.2 8 48.0 48 3.07 3.780 18.00 0 0 48 48
#> 15 10.4 8 472.0 205 2.93 5.250 17.98 0 0 48 48
#> 16 10.4 8 460.0 215 48.00 5.424 17.82 0 0 48 48
#> 17 14.7 8 440.0 230 3.23 5.345 17.42 0 0 48 48
#> 18 32.4 48 78.7 66 4.08 2.200 19.47 1 1 48 1
#> 19 30.4 48 75.7 52 4.93 1.615 18.52 1 1 48 2
#> 20 33.9 48 71.1 48 4.22 1.835 19.90 1 1 48 1
#> 21 21.5 48 120.1 97 3.70 2.465 20.01 1 0 48 1
#> 22 15.5 8 48.0 150 2.76 3.520 16.87 0 0 48 2
#> 23 15.2 8 304.0 150 3.15 3.435 17.30 0 0 48 2
#> 24 13.3 8 48.0 245 3.73 3.840 15.41 0 0 48 48
#> 25 19.2 8 48.0 175 3.08 3.845 17.05 0 0 48 2
#> 26 27.3 48 79.0 66 4.08 1.935 18.90 1 1 48 1
#> 27 26.0 48 120.3 91 4.43 2.140 16.70 0 1 5 2
#> 28 30.4 48 95.1 48 3.77 1.513 16.90 1 1 5 2
#> 29 15.8 8 351.0 264 4.22 3.170 14.50 0 1 5 48
#> 30 19.7 6 48.0 175 3.62 2.770 15.50 0 1 5 6
#> 31 15.0 8 301.0 335 3.54 3.570 14.60 0 1 5 8
#> 32 21.4 48 121.0 109 4.11 2.780 18.60 1 1 48 2
Created on 2019-02-25 by the reprex package (v0.2.1)
thank you very much, Rui! I didn’t think it would be this complicated, I wouldn’t have come to that result! Super thanks, worked perfectly on the original data!
– r_rabbit