create many columns and set value based on previous columns by lapply-CodePudding

I have a table with description of symptoms like below:

DT <- data.table(no = c(1, 2, 3),
symptom = c("headache and numbness", "tachycardia, sometimes headahce", "breath difficulty with limb numbness"))

the keywords I'm focusing on look like this

key.word <- list(
  head = c("head", "headache"),
  chest = c("breath", "tachycardia", "palpitaion")

I want to add two columns that describe whether the keyword is mentioned in the variable symptom, the desirable result looks like this

    result <- data.table(no = c(1, 2, 3),
                 symptom = c("headache and numbness", "tachycardia, sometimes headahce", "breath difficulty with limb numbness"),
                 head = c(T, T, F),
                 chest = c(F, T, T))

I can do this job by

DT[symptom %like% paste0(head, collapse = "|"), head := T]
DT[symptom %like% paste0(chest, collapse = "|"), chest := T]

But I'm wondering if there is a way to do this with lapply and datatable? (which seemed to be more elegant). Thanks in advance!

CodePudding user response：

Here is a data.table option

DT[ , lapply(
    key.word, function(x) any(sapply(x, function(w) grepl(w, symptom)))), 
    by = list(no, symptom)]
#   no                              symptom  head chest
#1:  1                headache and numbness  TRUE FALSE
#2:  2      tachycardia, sometimes headahce  TRUE  TRUE
#3:  3 breath difficulty with limb numbness FALSE  TRUE

The internal sapply loop is necessary as pattern in grepl is not vectorised.

CodePudding user response：

Not sure if you are looking only for DT or lapply option, but using dplyr and stringr:

DT %>% mutate(head = str_detect(symptom, str_c(key.word[[1]], collapse = '|')),
               chest =str_detect(symptom, str_c(key.word[[2]], collapse = '|')))
   no                              symptom  head chest
1:  1                headache and numbness  TRUE FALSE
2:  2      tachycardia, sometimes headahce  TRUE  TRUE
3:  3 breath difficulty with limb numbness FALSE  TRUE