使用if条件更新列()中的错误

Question

我使用了下面的代码，但是它给了我错误

UPDATED_PENALTY['HISTORIC_PENALTY'] <- ave(UPDATED_PENALTY$PENALTY, UPDATED_PENALTY$OFFICIAL_NUMBER, FUN=cumsum)
UPDATED_PENALTY['cum_prodsum']<-NA
UPDATED_PENALTY %>%
  mutate(cum_prodsum = ifelse(UPDATED_PENALTY$INSPECTION_CLEARED==TRUE, UPDATED_PENALTY$HISTORIC_PENALTY*0.9, UPDATED_PENALTY$HISTORIC_PENALTY*0.9 + UPDATED_PENALTY$PENALTY))

错误

Error in `mutate()`:
! Problem while computing `cum_prodsum = ifelse(...)`.
x `cum_prodsum` must be size 12 or 1, not 32217.
i The error occurred in group 1: OFFICIAL_NUMBER = "XXXXX".
Run `rlang::last_error()` to see where the error occurred.

另外，我想先排除每个“官方编号”的“历史惩罚”，并复制它的值，其余全部应用上述内容。

Answer 1

我们可以这么做

library(dplyr)
UPDATE_PENALTY <- UPDATE_PENALTY %>%
        ungroup %>% 
        mutate(cum_prodsum = case_when(INSPECTION_COUNT == 1 
   ~ HISTORIC_PENALTY, 
    INSPECTION_CLEARED ~ HISTORIC_PENALTY*0.9, 
     TRUE  ~HISTORIC_PENALTY*0.9  + PENALTY))

-output

UPDATE_PENALTY
# A tibble: 46 × 7
   OFFICIAL_NUMBER NUM_DEF PENALTY INSPECTION_COUNT INSPECTION_CLEARED HISTORIC_PENALTY cum_prodsum
   <chr>             <dbl>   <dbl>            <int> <lgl>                         <dbl>       <dbl>
 1 170718               14      60                1 FALSE                            60        60  
 2 803729                0       0                1 TRUE                              0         0  
 3 803729               65     311                2 FALSE                           311       591. 
 4 170718                8      24                2 FALSE                            84        99.6
 5 170718                0       0                3 TRUE                             84        75.6
 6 170718               39     110                4 FALSE                           194       285. 
 7 170718                0       0                5 TRUE                            194       175. 
 8 170718                1       5                6 FALSE                           199       184. 
 9 170718                0       0                7 TRUE                            199       179. 
10 170718                0       0                8 TRUE                            199       179. 
# … with 36 more rows