this is a followup question from my previous post.
My dataframe arranges visit for a specific PK based on dates, with a columns for:

• visit number
• visit date
• exam done in that visit

I am trying to turn it back to a wide dataframe. in which, each row is a visit, and there is a column for each test type. for each visit, columns that

Netting this dataframe:

# A tibble: 14 × 9
# Groups:   PK, visit [7]
   PK        visit test         date       toddler module1   rbs   srs adi_score
   <chr>     <dbl> <chr>        <date>       <dbl>   <dbl> <dbl> <dbl>     <dbl>
 1 683865865     1 date_toddler 2020-12-08       7      NA    NA    NA        NA
 2 683865865     2 date_toddler 2021-11-10      10      NA    NA    NA        NA
 3 683865865     3 date_module1 2022-02-10      NA      10    NA    NA        NA
 4 683865865     4 date_module1 2022-08-24      NA      10    NA    NA        NA
 5 683865865     4 date_srs_pr  2022-08-24      NA      NA    NA    79        NA
 6 683865865     5 date_srs_pr  2023-01-12      NA      NA    NA    83        NA
 7 683865865     6 date_module1 2023-08-21      NA      10    NA    NA        NA
 8 683865865     6 date_srs_pr  2023-09-21      NA      NA    NA    90        NA
 9 683865865    NA date_adi     NA              NA      NA    NA    NA        NA
10 683865865    NA date_module2 NA              NA      NA    NA    NA        NA
11 683865865    NA date_module3 NA              NA      NA    NA    NA        NA
12 683865865    NA date_module4 NA              NA      NA    NA    NA        NA
13 683865865    NA date_rbsr    NA              NA      NA    NA    NA        NA
14 683865865    NA date_srs_sch NA              NA      NA    NA    NA        NA

example of wanted data:

         PK visit  toddler   module1   rbs   srs  adi_score
1 683865865     1        7        NA    NA    NA         NA
2 683865865     2       10        NA    NA    NA         NA  
3 683865865     3       NA        10    NA    NA         NA
4 683865865     4       NA        10    NA    79         NA
5 683865865     5       NA        NA    NA    83         NA
6 683865865     6       NA        10    NA    90         NA

I have tried melting into long, and then wide again, but because there are multiple ID’s each with a different amount of visits, im getting the values in LISTS and NULLS.