Referencing a function argument as a column name in pivot_longer

November 1, 2023

I’m trying to write a function that uses pivot_longer, and would like to use my function object as the object of the names_to argument in pivot_longer.

record <- c(1, 2, 3, 4, 5, 6, 7, 8, 9, 10)
x214532 <- c("shirts, shoes",
"shoes, purses, hats",
"shirts, shoes, hats, heavy machinery",
"sponges, shoes",
"hats, heavy machinery",
"",
"heavy machinery, purses, shirts",
"heavy machinery, shoes, sponges",
"sponges",
"shoes")
screening_data_responses_char <- data.frame(record, x214532)

   record                              x214532
1       1                        shirts, shoes
2       2                  shoes, purses, hats
3       3 shirts, shoes, hats, heavy machinery
4       4                       sponges, shoes
5       5                hats, heavy machinery
6       6                                     
7       7      heavy machinery, purses, shirts
8       8      heavy machinery, shoes, sponges
9       9                              sponges
10     10                                shoes

Ultimately I’m trying to un-concatenate column x214532 and create a long dataset that separates the data into the items listed in the columns and then creates a long dataset, like this:

   record         x214532
1       1          shirts
2       1           shoes
3       2           shoes
4       2          purses
5       2            hats
6       3          shirts
7       3           shoes
8       3            hats
9       3 heavy machinery
10      4         sponges
11      4           shoes
12      5            hats
13      5 heavy machinery
14      6                
15      7 heavy machinery
16      7          purses
17      7          shirts
18      8 heavy machinery
19      8           shoes
20      8         sponges
21      9         sponges
22     10           shoes

I’d like the column containing the data to still be called x214532, but I’m having trouble passing it through names_to of pivot_longer. Here’s what I’ve got:

remove_col_prefix <- function(x) {
  pattern <- "^[^_]+_"
  stringr::str_remove(x, pattern)
}

deconcatenate <- function(questionID) {
  screening_data_responses_questionID <- cSplit_e(data=screening_data_responses_char,split.col=questionID,sep=",",type="character")
  screening_data_responses_questionID <- screening_data_responses_questionID %>% 
    select(-questionID) %>% 
    pivot_longer(cols=c(starts_with(questionID)), 
                 names_to="questionID", 
                 values_to="questionID_resp") %>% 
    drop_na(questionID_resp) %>% 
    select(-questionID_resp) %>% 
    mutate(questionID=remove_col_prefix(questionID)) %>%
    select(c(deid_pat_id, questionID))
  
  screening_data_responses_char <- screening_data_responses_char %>% 
    select(-questionID)
  
  screening_data_responses_char <-merge(screening_data_responses_char,screening_data_responses_questionID,by="deid_pat_id",all=TRUE)
  }


screening_data_responses_char <- deconcatenate(questionID="x214532")

Things I’ve tried:

-{{}} and !! operators (Using function arguments as column names)

-enquo

-this cement function: (https://adv-r.hadley.nz/quasiquotation.html)

-deparse(subsitute(x))

Things I’ve gotten:

-The column disappears entirely from the output

-The column is called questionID instead of x214532

-The column is called questionID and all of the text turns into x214532

I’m sure there are a few things that I’m doing wrong, or possibly something that I’ve gotten right in pivot_longer but need to also change further down the syntax, but I can’t quite figure it out. Any assistance would be appreciated!

>Solution :

A much easier approach may be to use tidyr::separate_longer_delim() instead of pivot_longer() and a complicated pipe:

tidyr::separate_longer_delim(data = screening_data_responses_char, 
                             cols = x214532, 
                             delim = ",")

Output:

   record          x214532
1       1           shirts
2       1            shoes
3       2            shoes
4       2           purses
5       2             hats
6       3           shirts
7       3            shoes
8       3             hats
9       3  heavy machinery
10      4          sponges
11      4            shoes
12      5             hats
13      5  heavy machinery
14      6                 
15      7  heavy machinery
16      7           purses
17      7           shirts
18      8  heavy machinery
19      8            shoes
20      8          sponges
21      9          sponges
22     10            shoes