R 我如何折叠行以将NAs分组填充，使每列的行数不均匀？

我正在尝试格式化这些数据，以便将其输入到formattable表中

样本数据：

test <- tibble(group = c("A", "B", "B", "B", "C", "D"), 
           name = c("Steve", "Mike", "Paul", "Jaimie", "John", "Marco"),
           year = c(1988, 2001, 2001, 2002, 1997, 2000))

其中：

# A tibble: 6 x 3
  group name    year
  <chr> <chr>  <dbl>
1 A     Steve   1988
2 B     Mike    2001
3 B     Paul    2001
4 B     Jaimie  2002
5 C     John    1997
6 D     Marco   2000

# A tibble: 6 x 7
  group grouped_id `1988` `1997` `2000` `2001` `2002`
  <chr>      <int> <chr>  <chr>  <chr>  <chr>  <chr> 
1 A              1 Steve  NA     NA     NA     NA    
2 B              2 NA     NA     NA     Mike   NA    
3 B              3 NA     NA     NA     Paul   NA    
4 B              4 NA     NA     NA     NA     Jaimie
5 C              5 NA     John   NA     NA     NA    
6 D              6 NA     NA     Marco  NA     NA    

我试了又试

---

谢谢你的帮助

我们可以通过

行数

library(dplyr)
library(tidyr)
test %>%
   group_by(year) %>% 
   mutate(rn = row_number()) %>%
   ungroup %>%
   spread(year, name) %>%
   select(-rn)
# A tibble: 5 x 6
#  group `1988` `1997` `2000` `2001` `2002`
#  <chr> <chr>  <chr>  <chr>  <chr>  <chr> 
#1 A     Steve  <NA>   <NA>   <NA>   <NA>  
#2 B     <NA>   <NA>   <NA>   Mike   Jaimie
#3 B     <NA>   <NA>   <NA>   Paul   <NA>  
#4 C     <NA>   John   <NA>   <NA>   <NA>  
#5 D     <NA>   <NA>   Marco  <NA>   <NA>  

# A tibble: 6 x 7
  group grouped_id `1988` `1997` `2000` `2001` `2002`
  <chr>      <int> <chr>  <chr>  <chr>  <chr>  <chr> 
1 A              1 Steve  NA     NA     NA     NA    
2 B              2 NA     NA     NA     Mike   Jaimie    
3 B              3 NA     NA     NA     Paul   NA    
4 C              5 NA     John   NA     NA     NA    
5 D              6 NA     NA     Marco  NA     NA    

library(dplyr)
library(tidyr)
test %>%
   group_by(year) %>% 
   mutate(rn = row_number()) %>%
   ungroup %>%
   spread(year, name) %>%
   select(-rn)
# A tibble: 5 x 6
#  group `1988` `1997` `2000` `2001` `2002`
#  <chr> <chr>  <chr>  <chr>  <chr>  <chr> 
#1 A     Steve  <NA>   <NA>   <NA>   <NA>  
#2 B     <NA>   <NA>   <NA>   Mike   Jaimie
#3 B     <NA>   <NA>   <NA>   Paul   <NA>  
#4 C     <NA>   John   <NA>   <NA>   <NA>  
#5 D     <NA>   <NA>   Marco  <NA>   <NA>  

test %>%
       group_by(year) %>% 
       mutate(rn = row_number()) %>%
       ungroup %>%
       pivot_wider(names_from = year, values_from = name) %>%
       select(-rn)