新人求助，把数据框的每行按照某列拆分不同的行，只能用循环吗？

1、data.table包的tstrsplit函数是个好东西，按;分割时，长度不够的会用NA填充；
2、用melt()来个宽转长，对应baseR的reshape()

library("data.table")
x<-data.frame(year=c(2019,2019,2019,2020,2020),
              c1=c('a;b','c;d;e','f;g','h;i;j;k','l;m'))
setDT(x)
x[,tstrsplit(c1,";")]
#>    V1 V2   V3   V4
#> 1:  a  b <NA> <NA>
#> 2:  c  d    e <NA>
#> 3:  f  g <NA> <NA>
#> 4:  h  i    j    k
#> 5:  l  m <NA> <NA>

y<-x[,tstrsplit(c1,";")][,year:=x$year]
melt(y,id.vars="year",na.rm=TRUE)[order(year,value),.(c1=value,year)]
#>     c1 year
#>  1:  a 2019
#>  2:  b 2019
#>  3:  c 2019
#>  4:  d 2019
#>  5:  e 2019
#>  6:  f 2019
#>  7:  g 2019
#>  8:  h 2020
#>  9:  i 2020
#> 10:  j 2020
#> 11:  k 2020
#> 12:  l 2020
#> 13:  m 2020

^{Created on 2022-05-02 by the reprex package (v2.0.1)}

tctcab 不光学会了 separate_row() 函数，还学到了 reprex 包的用法

chuxinyuan 操作前新增一列行号就可以逆回去

library(tidyverse)

df=data.table::fread(
  "
year      c1
2019     a;b
2019   c;d;e
2019     f;g
2020 h;i;j;k
2020     l;m
"
)

df2 <- tidyr::separate_rows(df %>% rownames_to_column(),c1)
df2
#> # A tibble: 13 x 3
#>    rowname  year c1   
#>    <chr>   <int> <chr>
#>  1 1        2019 a    
#>  2 1        2019 b    
#>  3 2        2019 c    
#>  4 2        2019 d    
#>  5 2        2019 e    
#>  6 3        2019 f    
#>  7 3        2019 g    
#>  8 4        2020 h    
#>  9 4        2020 i    
#> 10 4        2020 j    
#> 11 4        2020 k    
#> 12 5        2020 l    
#> 13 5        2020 m

df2 %>% 
  dplyr::group_by(year, rowname) %>% 
  dplyr::summarise(c1 = str_flatten(c1, collapse = ";"))
#> `summarise()` has grouped output by 'year'. You can override using the
#> `.groups` argument.
#> # A tibble: 5 x 3
#> # Groups:   year [2]
#>    year rowname c1     
#>   <int> <chr>   <chr>  
#> 1  2019 1       a;b    
#> 2  2019 2       c;d;e  
#> 3  2019 3       f;g    
#> 4  2020 4       h;i;j;k
#> 5  2020 5       l;m