dplyr: Replace multiple values based on condition in a selection of columns

Question

I try to conditionally replace multiple values in a data frame.

In the following data set, I want to replace in columns 3:5 all values of 2 by "X" and all values of 3 by "Y", but only for measure == "led"

condition: measure == "led" replace: value "2" by "X" and value "3" by "Y" (in columns 3:5)

library(data.table)
dt <- data.table(measure = sample(c('cfl', 'led', 'linear', 'exit'), 20, replace=T),
                 site = sample(1:6, 20, replace=T),
                 space = sample(1:4, 20, replace=T),
                 qty = sample(1:6, 20, replace=T),
                 qty.exit = sample(1:6, 20, replace=T),
                 cf = sample(1:6, 20, replace=T))

Is there a simple dplyr solution for that? Many thanks!

Answer 1

A dplyr solution:

library(dplyr)
dt %>%
  mutate(across(3:5, ~ ifelse(measure == "led", stringr::str_replace_all(
    as.character(.),
    c("2" = "X", "3" = "Y")
  ), .)))

Result:

   measure site space qty qty.exit cf
 1:     led    4     1   4        6  3
 2:    exit    4     2   1        4  6
 3:     cfl    1     4   6        2  3
 4:  linear    3     4   1        3  5
 5:     cfl    5     1   6        1  6
 6:    exit    4     3   2        6  4
 7:    exit    5     1   4        2  5
 8:    exit    1     4   3        6  4
 9:  linear    3     1   5        4  1
10:     led    4     1   1        1  1
11:    exit    5     4   3        5  2
12:     cfl    4     2   4        5  5
13:     led    4     X   Y        Y  4
...

Answer 2

For the sake of completeness, here is a data.table solution using a look-up table and an update join .

As mentioned in danlooo's comment , all elements of a column must have the same type. So, it is necessary to coerce all numbers to type character before joining.

library(data.table)
# create look-up table
lut <- fread(
  "measure, old, new
  led,      2,   X
  led,      3,   Y",
  colClasses = c(old = "character")
)
# perform coersion and update join for each column
for(col in colnames(dt)[3:5]) {
  set(dt, , col, as.character(dt[[col]]))
  dt[lut, on = c("measure", paste0(col, "==old")), (col) := new][]
}
dt

 measure site space qty qty.exit cf 1: cfl 3 4 4 3 3 2: cfl 1 2 3 5 5 3: cfl 1 2 6 5 5 4: cfl 3 1 5 4 6 5: led 4 4 X 6 3 6: exit 5 1 6 5 6 7: led 5 4 X 4 4 8: led 5 XX 6 5 9: cfl 4 4 5 2 1 10: exit 2 2 1 2 4 11: linear 4 3 1 1 1 12: exit 3 4 4 2 1 13: linear 2 3 5 5 5 14: exit 1 1 2 6 6 15: cfl 2 1 1 5 3 16: cfl 6 2 5 4 1 17: led 3 X 4 1 2 18: exit 6 2 4 4 5 19: led 2 X 1 X 6 20: led 4 XYX 1

Data

library(data.table)
set.seed(42) # required for reproducible data
dt <- data.table(measure = sample(c('cfl', 'led', 'linear', 'exit'), 20, replace=T),
                 site = sample(1:6, 20, replace=T),
                 space = sample(1:4, 20, replace=T),
                 qty = sample(1:6, 20, replace=T),
                 qty.exit = sample(1:6, 20, replace=T),
                 cf = sample(1:6, 20, replace=T))