添加作為其他列總和的列

輸入資料：

Director= c("Director A", "Director B", "Director C")
Salary = c(40000, 35000, 50000)
Listed boards = c(1, 0, 3)
Unlisted boards = c(4, 2, 6)
Other boards = c(2, 3, 3)
Number of qualifications = c(1, 2, 1)

df_directors = data.frame(Director, Salary, Listed boards, Unlisted boards, Other boards, Number of qualifications) 

現在我想創建一個額外的列來求和并替換關于板的三列。所以我的輸出資料應該是這樣的：

Director         Salary         Boards         Number of qualifications
Director A       40000          7              1
Director B       35000          5              2
Director C       50000          12             1

這段代碼不知何故不起作用。

df_directors <- df_directors %>%
  rowwise() %>%
  mutate(rBoards = sum(c_across(all_of(Listed Boards:Other Boards))))

uj5u.com熱心網友回復：

我們可以使用rowSumswith select：

library(dplyr)

df_directors %>% 
  transmute(Director, Salary, Boards = rowSums(select(., contains("boards"))),Number_of_qualifications)

第一個解決方案：

library(dplyr)

df_directors %>% 
  mutate(Boards = rowSums(select(., contains("boards")))) %>% 
  select(1,2,Boards,6)

    Director Salary Boards Number_of_qualifications
1 Director A  40000      7                        1
2 Director B  35000      5                        2
3 Director C  50000     12                        1

uj5u.com熱心網友回復：

我們可以rowSums使用base R

library(dplyr)
df_directors %>% 
  transmute(Director, Salary, 
   Boards = rowSums(across(ends_with('boards')), na.rm = TRUE),
        `Number of qualifications`)

-輸出

    Director Salary Boards Number of qualifications
1 Director A  40000      7                        1
2 Director B  35000      5                        2
3 Director C  50000     12                        1

在OP的代碼中，當列名中有空格時需要反引號

 df_directors %>%
  rowwise() %>%
  mutate(rBoards = sum(c_across(`Listed boards`:`Other boards`))) %>%
   ungroup

-輸出

# A tibble: 3 × 7
  Director   Salary `Listed boards` `Unlisted boards` `Other boards` `Number of qualifications` rBoards
  <chr>       <dbl>           <dbl>             <dbl>          <dbl>                      <dbl>   <dbl>
1 Director A  40000               1                 4              2                          1       7
2 Director B  35000               0                 2              3                          2       5
3 Director C  50000               3                 6              3                          1      12

資料

df_directors <- structure(list(Director = c("Director A", "Director B", "Director C"
), Salary = c(40000, 35000, 50000), `Listed boards` = c(1, 0, 
3), `Unlisted boards` = c(4, 2, 6), `Other boards` = c(2, 3, 
3), `Number of qualifications` = c(1, 2, 1)), 
class = "data.frame", row.names = c(NA, 
-3L))

uj5u.com熱心網友回復：

rowSums并grep用于識別。

cbind(df_directors[1:2], Boards=rowSums(df_directors[grep('boards$', names(df_directors))]), df_directors[ncol(df_directors)])
#     Director Salary Boards Number.of.qualifications
# 1 Director A  40000      7                        1
# 2 Director B  35000      5                        2
# 3 Director C  50000     12                        1

資料：

df_directors <- structure(list(Director = c("Director A", "Director B", "Director C"
), Salary = c(40000, 35000, 50000), Listed.boards = c(1, 0, 3
), Unlisted.boards = c(4, 2, 6), Other.boards = c(2, 3, 3), Number.of.qualifications = c(1, 
2, 1)), class = "data.frame", row.names = c(NA, -3L))

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