匹配和重新排序 R 中多列中的行（tidyverse）

Question

I have a dataset like this (in the actual dataset, I have more columns like subj01):

# A tibble: 10 x 4
    item subj01 subj02 subj03
   <int>  <dbl>  <dbl>  <dbl>
 1     1      1      1      1
 2     2      2      2      6
 3     3      5      5      9
 4     4      9      6     NA
 5     5     10      8     NA
 6     6     NA      9     NA
 7     7     NA     10     NA
 8     8     NA     NA     NA
 9     9     NA     NA     NA
10    10     NA     NA     NA

I created the dataset using the code below.

data = tibble(item = 1:10, subj01 = c(1,2,5,9,10,NA,NA,NA,NA,NA), subj02 = c(1,2,5,6,8,9,10,NA,NA,NA), subj03 = c(1,6,9,NA,NA,NA,NA,NA,NA,NA))

I would like to reorder all the columns beginning with "subj" so that the position of the values match that in the item column.

That is, for this example dataset, I would like to end up with this:

# A tibble: 10 x 4
    item subj01 subj02 subj03
   <int>  <dbl>  <dbl>  <dbl>
 1     1      1      1      1
 2     2      2      2     NA
 3     3     NA     NA     NA
 4     4     NA     NA     NA
 5     5      5      5     NA
 6     6     NA      6      6
 7     7     NA     NA     NA
 8     8     NA      8     NA
 9     9      9      9      9
10    10     10     10     NA

I've figured that I can match and re-order one column by running this:

data$subj01[match(data$item,data$subj01)]
 [1]  1  2 NA NA  5 NA NA NA  9 10

But I am struggling to apply this across multiple columns (ideally I'd like to embed the command in a dplyr pipe).

I tried the command below, but this gave me an error "Error in mutate(x. = x.[match(item, x.)]): object 'x.' not found".

data = data %>% across(mutate(x.=x.[match(item,x.)]))

I'd appreciate any suggestions. Thank you.

Answer 1

library(tidyverse)
data %>%
  pivot_longer(-item) %>%
  filter(!is.na(value)) %>%
  mutate(item = value) %>%
  complete(item = 1:10, name) %>%
  pivot_wider(names_from = name, values_from = value)

# A tibble: 10 × 4
    item subj01 subj02 subj03
   <dbl>  <dbl>  <dbl>  <dbl>
 1     1      1      1      1
 2     2      2      2     NA
 3     3     NA     NA     NA
 4     4     NA     NA     NA
 5     5      5      5     NA
 6     6     NA      6      6
 7     7     NA     NA     NA
 8     8     NA      8     NA
 9     9      9      9      9
10    10     10     10     NA