I have survey data that require several case specific recodes that I need to perform, but I want to avoid creating a new line of code for each and every recode (because there will be dozens). I am hoping there is a way I can recode the data using a crosswalk that only recodes the value for which is required based on the su_id and the Q# that needs the recode.
su_id <- 100001:100010
Q1 <- c(1, 2, 5, 6, 2, 3, 4, 2, 1, 6)
Q2 <- c(2, 4, 6, 4, 3, 6, 2, 1, 6, 5)
data <- data.frame(su_id, Q1, Q2)
su_id <- c( 100004, 100010, 100003, 100006, 100009)
var <- c("Q1", "Q1", "Q2", "Q2", "Q2")
newVal <- c(4, 4, 5, 5, 5)
cw <- data.frame(su_id, var, newVal)
#data:
su_id Q1 Q2
1 100001 1 2
2 100002 2 4
3 100003 5 6
4 100004 6 4
5 100005 2 3
6 100006 3 6
7 100007 4 2
8 100008 2 1
9 100009 1 6
10 100010 6 5
#Crosswalk:
su_id var newVal
1 100004 Q1 4
2 100010 Q1 4
3 100003 Q2 5
4 100006 Q2 5
5 100009 Q2 5
I started trying to iterate on something like this, but obviously this won't do the trick, but hopefully this gives an idea of what I am trying to accomplish. Can anyone advise on how/if this is possible?
su_idToChange <- cw$su_id
varToChange <- cw$var
newValToChange <- cw$newVal
for(i in su_idToChange) {
data_new <- data %>%
mutate(across(all_of(varToChange), case_when(su_id %in% su_idToChange
~ coalesce(deframe(cw[cw$var == "Q1" | cw$var == "Q2", ][-1])[.], .))))
}
Thank you!
If I understood your question right, you are trying to perform something like this:
my_change_fun <- function(data, cw) {
for (i in seq_len(nrow(cw))) {
data[data$su_id == cw[i, 1], cw[i, 2]] <- cw[i, 3]
}
data
}
my_change_fun(data, cw)
#> su_id Q1 Q2
#> 1 100001 1 2
#> 2 100002 2 4
#> 3 100003 5 5
#> 4 100004 4 4
#> 5 100005 2 3
#> 6 100006 3 5
#> 7 100007 4 2
#> 8 100008 2 1
#> 9 100009 1 5
#> 10 100010 4 5
Created on 2021-08-30 by the reprex package (v2.0.1)