r - 使用 dplyr::mutate() 修改任意列属性

Question

我想修改 dplyr::mutate() 中的列属性。以下是一些示例数据:

library(dplyr, warn.conflicts = FALSE)

v1 <- tibble(
  id = 1:5,
  visit = 1,
  x = 1:5,
  y = c(0, 0, 0, 1, 1)
)

我想得到的最终结果与我从中得到的结果相同:

attr(v1$id, "source") <- "Collected at v1"
attr(v1$visit, "source") <- "Collected at v1"
attr(v1$x, "source") <- "Collected at v1"
attr(v1$y, "source") <- "Collected at v1"

我知道我可以只使用 for 循环。

for (col in names(v1)) {
  attr(v1[[col]], "source") <- "Collected at v1"
}

但是，我有理由想在 dplyr 中执行此操作。我正在努力做到这一点。

v1 %>% 
  mutate(
    across(
      .cols = everything(),
      .fns  = ~ function_to_update_attributes("source", "Collected at v1")
    )
  )

现在，我什至不能让它对单个变量起作用。这是我得到的最接近的结果。

v1 %>% 
  mutate(
    id = `<-`(attr(.[["id"]], "source"), "Collected at v1")
  )

哪个返回

# A tibble: 5 × 4
  id              visit     x     y
  <chr>           <dbl> <int> <dbl>
1 Collected at v1     1     1     0
2 Collected at v1     1     2     0
3 Collected at v1     1     3     0
4 Collected at v1     1     4     1
5 Collected at v1     1     5     1

😞 欢迎并赞赏任何建设性反馈!

这也发布在 RStudio 社区上:https://community.rstudio.com/t/modify-arbitrary-column-attributes-using-dplyr-mutate/144502

Answer 1

我们可以使用 dplyr 直接在向量上应用属性

library(dplyr)
v1 <- v1 %>%
    mutate(across(everything(), 
     ~ {attr(.x, "source") <- "Collected at v1"
    .x} ))

-输出

> str(v1)
tibble [5 × 4] (S3: tbl_df/tbl/data.frame)
 $ id   : int [1:5] 1 2 3 4 5
  ..- attr(*, "source")= chr "Collected at v1"
 $ visit: num [1:5] 1 1 1 1 1
  ..- attr(*, "source")= chr "Collected at v1"
 $ x    : int [1:5] 1 2 3 4 5
  ..- attr(*, "source")= chr "Collected at v1"
 $ y    : num [1:5] 0 0 0 1 1
  ..- attr(*, "source")= chr "Collected at v1"

或者如果我们想使用访问列名使用cur_column()并分配 <<-

v1 %>%
  mutate(across(everything(), 
  ~ {attr(v1[[cur_column()]], "source") <<- "Collected at v1"
   .x})) 

-输出

> str(v1)
tibble [5 × 4] (S3: tbl_df/tbl/data.frame)
 $ id   : int [1:5] 1 2 3 4 5
  ..- attr(*, "source")= chr "Collected at v1"
 $ visit: num [1:5] 1 1 1 1 1
  ..- attr(*, "source")= chr "Collected at v1"
 $ x    : int [1:5] 1 2 3 4 5
  ..- attr(*, "source")= chr "Collected at v1"
 $ y    : num [1:5] 0 0 0 1 1
  ..- attr(*, "source")= chr "Collected at v1"

---

或者如果我们想复制相同的行为，即使用原始数据对象名称及其列名称，如 for循环，使用 reduce

library(purrr)
v1 <- reduce(names(v1), ~ {
         attr(.x[[.y]], "source") <- "Collected at v1"
             .x}, .init = v1)

-输出

> str(v1)
tibble [5 × 4] (S3: tbl_df/tbl/data.frame)
 $ id   : int [1:5] 1 2 3 4 5
  ..- attr(*, "source")= chr "Collected at v1"
 $ visit: num [1:5] 1 1 1 1 1
  ..- attr(*, "source")= chr "Collected at v1"
 $ x    : int [1:5] 1 2 3 4 5
  ..- attr(*, "source")= chr "Collected at v1"
 $ y    : num [1:5] 0 0 0 1 1
  ..- attr(*, "source")= chr "Collected at v1"