我知道这是标记数据表，但另一种方法是使用dplyr::mutate()和dplyr::across()，其中.names参数和dplyr::case_when用于逻辑：

library(dplyr)

dt %>%
  mutate(across(q1:q3, ~case_when(.x %in% 1:2 ~ "Yes", 
                                  .x %in% 3 ~ "NO",
                                  .x %in% 4 ~ "IDK"),
                .names = "{.col}_cat"))

输出

ID   sex age q1 q2 q3 q1_cat q2_cat q3_cat
1:  1   Man  35  1  1  2    Yes    Yes    Yes
2:  2 Woman  50 NA  3  1   <NA>     NO    Yes
3:  3   Man  23 NA  2  4   <NA>    Yes    IDK
4:  4 Woman  78  1 NA  4    Yes   <NA>    IDK

library(data.table)
nm1 <- paste0("q", 1:3)
nm2 <- setNames(c("YES", "YES", "NO", "IDK"), 1:4)
 dt[, paste0(nm1, "_cat") := lapply(.SD, \(x) nm2[as.character(x)]), 
  .SDcols = nm1]

• 输出

> dt
   ID   sex age q1 q2 q3 q1_cat q2_cat q3_cat
1:  1   Man  35  1  1  2    YES    YES    YES
2:  2 Woman  50 NA  3  1   <NA>     NO    YES
3:  3   Man  23 NA  2  4   <NA>    YES    IDK
4:  4 Woman  78  1 NA  4    YES   <NA>    IDK

这是添加这些列的一种简单方法，但如果整个数据集有更多问题，则可能会变得笨拙。

library(data.table)
library(dplyr)
#> 
#> Attaching package: 'dplyr'
#> The following objects are masked from 'package:data.table':
#> 
#>     between, first, last
#> The following objects are masked from 'package:stats':
#> 
#>     filter, lag
#> The following objects are masked from 'package:base':
#> 
#>     intersect, setdiff, setequal, union

dt <- data.table(ID = c(1, 2, 3, 4),
                 sex = c("Man", "Woman", "Man", "Woman"),
                 age = c(35, 50, 23, 78),
                 q1= c(1, NA, NA, 1), 
                 q2= c(1, 3, 2, NA), 
                 q3= c(2, 1, 4, 4))

dt %>%
  mutate(q1_cat = 
           case_when(
             q1 == 1 ~ 'YES',
             q1 == 2 ~ 'YES',
             q1 == 3 ~ 'NO',
             q1 == 4 ~ 'IDK'
           ),
         q2_cat = 
           case_when(
             q2 == 1 ~ 'YES',
             q2 == 2 ~ 'YES',
             q2 == 3 ~ 'NO',
             q2 == 4 ~ 'IDK'
           ),
         q3_cat = 
           case_when(
             q3 == 1 ~ 'YES',
             q3 == 2 ~ 'YES',
             q3 == 3 ~ 'NO',
             q3 == 4 ~ 'IDK'
           )
  )
#>    ID   sex age q1 q2 q3 q1_cat q2_cat q3_cat
#> 1:  1   Man  35  1  1  2    YES    YES    YES
#> 2:  2 Woman  50 NA  3  1   <NA>     NO    YES
#> 3:  3   Man  23 NA  2  4   <NA>    YES    IDK
#> 4:  4 Woman  78  1 NA  4    YES   <NA>    IDK

创建于2023-03-27带有reprex v2.0.2
直接更改q1，q2，... qN的内容是否有用？