Recode multiple missing values

Question

set.seed(1)
data=data.frame("a"=sample(-5:5, 20, r=T),
"b"=sample(-5:5, 20, r=T),
"c"=sample(-5:5, 20, r=T))

What is most effective way to set values : -5, -3, 4 to 'NA' across 'a' and 'b' and 'c' with using actual column names?

Answer 1

One option in base R (without any packages) is to replicate the values, do a comparison and assign to NA

data[data == c(-5, -3, 4)[col(data)]] <- NA

---

If we need only selected columns

nm1 <- c('a', 'c')
data[nm1][data[nm1]== c(-5, 4)[col(data[nm1])]] <- NA

If we are replacing multiple values for each column, then use lapply

data[nm1] <- lapply(data[nm1], function(x) replace(x, x %in% c(-5, -3, 4), NA))

---

In tidyverse , we can use case_when

library(dplyr)
data %>% 
    mutate_at(vars(nm1),  ~ case_when(!. %in% c(-5, -3, 4) ~ .))

For multiple values

data %>% 
   mutate_at(vars(nm1),  ~ case_when(. %in% 4 ~ 99L, !. %in% c(-5, -3) ~ .))
#    a  b  c
#1   3  3  3
#2  -2  3  2
#3   1 -1  3
#4  NA -1  1
#5  -4 -4  2
#6   1  4  0
#7   5  3 99
#8  -4 -5  1
#9   5 -2 NA
#10 NA -3 99
#11 NA  0  0
#12 -1  4  2
#13 -1  4 -4
#14 99  0 -4
#15  0 -2  0
#16 99 -2  0
#17  1  4 NA
#18  3  3 NA
#19 -1  1 NA
#20 -1  0  2

---

With data.table , we can use fcase

library(data.table)
setDT(data)[, (nm1) := lapply(.SD, function(x) fcase(x %in% 4 ~ 99L, !x %in% c(-5, -3) ~ x)), .SDcols = nm1]

Answer 2

Using dplyr , you can try:

data %>%
 mutate_at(vars(a, b, c), ~ replace(., . %in% c(-5, -3, 4), NA))

    a  b  c
1  NA  5 NA
2  -1 NA  2
3   1  2  3
4  NA -4  1
5  NA NA  0
6  NA -1  3
7   5 NA NA
8   2 -1  0
9   1 NA  3
10 NA -2  2

Answer 3

A data.table version:

library(data.table)

setDT(data)[, lapply(.SD, function(x) replace(x, x %in% c(-5, -3, 4), NA)), .SDcols = c('a', 'b', 'c')]

Output:

     a  b  c
 1:  3  3  3
 2: -2  3  2
 3:  1 -1  3
 4: NA -1  1
 5: -4 -4  2
 6:  1 NA  0
 7:  5  3 NA
 8: -4 NA  1
 9:  5 -2 NA
10: NA NA NA
11: NA  0  0
12: -1 NA  2
13: -1 NA -4
14: NA  0 -4
15:  0 -2  0
16: NA -2  0
17:  1 NA NA
18:  3  3 NA
19: -1  1 NA
20: -1  0  2