Error when using case_when with mutate and functions: getting closest number to zero with NA

I am trying to flag the closest number of days from an accident to when someone got insurance. 0 represents the same day, a negative number represents insurance prior to accident and a positive number represents insurance post accident.

Data

df <- data.frame(id=1:4, accident1=c(-1,3,4, NA), accident2=c(100, -2, NA, NA), accident3=c(-3,1,2, NA))
    
> df
  id accident1 accident2 accident3
1  1        -1       100        -3
2  2         3        -2         1
3  3         4        NA         2
4  4        NA        NA        NA

Code:

library(DescTools)
library(dplyr)

df %>%
  rowwise() %>%
  mutate(magic=
           case_when(
             accident1 <0 |accident2<0 |accident3<0 ~ as.numeric(pmax(accident1, accident2, accident3, na.rm=T)),
             accident1 >0 |accident2>0 | accident3>0 ~ as.numeric(pmin(accident1, accident2, accident3, na.rm=T)),
             accident1 > 0 & accident2 > 0 & accident3>0 ~ as.numeric(pmin(accident1, accident2, accident3, na.rm=T)),
             accident1 < 0 & accident2 < 0 & accident3 < 0 ~ as.numeric(pmax(accident1, accident2, accident3, na.rm=T)),
             TRUE ~ NA_real_)) %>%
         rowwise() %>% 
  # not working
  mutate(magic= case_when(
             (accident1 >0 |accident2<0 |accident3<0) & (accident1 >0 |accident2>0 | accident3>0) ~ 
               Closest(as.numeric(unlist(c(accident1, accident2, accident3))), 0, na.rm=T), TRUE~magic))

Result without last row in data (all NAs):

# A tibble: 3 × 5
# Rowwise: 
     id accident1 accident2 accident3 magic
  <int>     <dbl>     <dbl>     <dbl> <dbl>
1     1        -1       100        -3    -1
2     2         3        -2         1     1
3     3         4        NA         2     2

However, when I try this with NA in last row:

Error: Problem with `mutate()` column `magic`.
ℹ `magic = case_when(...)`.
ℹ `magic` must be size 1, not 0.
ℹ Did you mean: `magic = list(case_when(...))` ?
ℹ The error occurred in row 4.
Run `rlang::last_error()` to see where the error occurred.
In addition: Warning message:
Problem with `mutate()` column `magic`.
ℹ `magic = case_when(...)`.
ℹ no non-missing arguments to min; returning Inf
ℹ The warning occurred in row 4.

Any advice on how to get the code to work on row 4 with NAs?

>Solution :

The main reason is the last element which returns numeric(0) because all the elements are NA and we used na.rm = TRUE for Closest. We can prevent that by indexing to return first element and this changes to NA

library(dplyr)
df %>% 
  mutate(magic=
           case_when(
             accident1 <0 |accident2<0 |accident3<0 ~ as.numeric(pmax(accident1, accident2, accident3, na.rm=T)),
             accident1 >0 |accident2>0 | accident3>0 ~ as.numeric(pmin(accident1, accident2, accident3, na.rm=T)),
             accident1 > 0 & accident2 > 0 & accident3>0 ~ as.numeric(pmin(accident1, accident2, accident3, na.rm=T)),
             accident1 < 0 & accident2 < 0 & accident3 < 0 ~ as.numeric(pmax(accident1, accident2, accident3, na.rm=T)),
             TRUE ~ NA_real_)) %>%
         rowwise() %>%  
  mutate(magic= case_when(
             (accident1 >0 |accident2<0 |accident3<0) & (accident1 >0 |accident2>0 | accident3>0) ~ 
               Closest(as.numeric(unlist(c(accident1, accident2, accident3))), 0, na.rm=TRUE)[1], TRUE~magic))

-output

# A tibble: 4 × 5
# Rowwise: 
     id accident1 accident2 accident3 magic
  <int>     <dbl>     <dbl>     <dbl> <dbl>
1     1        -1       100        -3    -1
2     2         3        -2         1     1
3     3         4        NA         2     2
4     4        NA        NA        NA    NA

It is more easier to understand if we do this only on Closest

> apply(df[-1], 1, function(x) Closest(x, 0, na.rm = TRUE))
[[1]]
accident1 
       -1 

[[2]]
accident3 
        1 

[[3]]
accident3 
        2 

[[4]]
named numeric(0)  ####

The solution does index, so that numeric(0) becomes NA

numeric(0)[1]
[1] NA

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