我有一个非常宽的数据帧（远大于此处为reprex提供的数据）。
使用下面提供的数据（分配给my_wide_data），我想利用dplyr::coalesce以及来自dplyr的精选助手（例如dplyr::starts_with）。
# dput output assigned to my_wide_data
structure(list(myvar1 = c(10L, 3L, 11L, 2L, 4L, 5L, 2L, 6L, 1L,
4L, 12L, 9L, 12L, 2L, 3L, 1L, 2L, 8L, 1L, 2L, 3L, 3L, 8L, 11L,
10L, 6L, 3L, 10L, 5L, 2L, 8L, 3L, 1L, 6L, 2L, 1L, 8L, 4L, 10L,
3L, 1L, 4L, 2L, 12L, 3L, 2L, 5L, 1L, 3L, 5L, 3L, 2L, 12L, 3L,
6L, 11L, 12L, 2L, 6L, 10L, 3L, 10L, 3L, 2L, 2L, 2L, 2L, 3L, 6L,
3L, 6L, 10L, 1L, 3L, 3L, 6L, 2L, 3L, 3L, 3L, 2L, 3L, 2L, 10L,
3L, 3L, 4L, 1L, 3L, 2L, 3L, 9L, 1L, 1L, NA, 5L, 1L, 8L, 3L, 10L,
3L, 3L, 4L, 7L, 10L, 2L, 2L, 11L, 6L, 11L, 6L, 4L, 4L, 12L, 6L,
6L, 1L, 2L, 11L, 2L, 2L, 11L, 3L, 2L, 3L, 2L, 2L, 3L, 3L, 9L,
2L, 1L, 1L, 4L, 2L, 8L, 2L, 10L, 6L, 3L, 1L, 6L, 2L, 10L, 3L,
5L, 6L, 3L, 4L, 10L, 9L, 3L, 4L, 3L, 2L, 3L, 9L, 3L, 3L, 1L,
10L, 4L, 4L, 6L, 2L, 7L, 3L, 2L, 3L, 1L, 3L, 3L, 3L, 7L, 2L,
2L, 6L, 2L, 4L, 3L, 3L, 4L, 2L, 4L, 2L, 5L, 5L, 3L, 6L, 5L, 4L,
5L, 4L, 4L, 10L, 1L, 9L, 4L, 4L, 4L, 4L, 8L, 6L, 5L), myvar2 = c(24L,
24L, 27L, 8L, 9L, 15L, 1L, 27L, 3L, 23L, 28L, 10L, 24L, 5L, 14L,
17L, 16L, 28L, 29L, 16L, 3L, 13L, 7L, 13L, 18L, 25L, 10L, 10L,
15L, 27L, 21L, 17L, 25L, 25L, 15L, 25L, 21L, 13L, 9L, 28L, 1L,
13L, 19L, 21L, 23L, 15L, NA, 29L, 12L, 25L, 1L, 5L, 12L, 7L,
15L, 25L, 4L, 8L, 30L, 25L, 8L, NA, 6L, 16L, 14L, 7L, 20L, 26L,
19L, 10L, 1L, 15L, 30L, 7L, 16L, 23L, 24L, 21L, 8L, 1L, 1L, 10L,
26L, 28L, 5L, 7L, 21L, 10L, 13L, 26L, 14L, 5L, 22L, 18L, NA,
NA, 9L, 20L, 17L, 23L, 3L, 13L, 7L, 5L, 6L, 9L, 8L, 15L, 9L,
10L, 15L, 13L, NA, 30L, 22L, 14L, 9L, 16L, 6L, 13L, 19L, 15L,
1L, 7L, 19L, 25L, 10L, NA, 8L, 25L, 5L, 2L, 16L, 8L, 19L, 18L,
27L, 2L, NA, 16L, 29L, 4L, 7L, 27L, 24L, 5L, 6L, 17L, 16L, 13L,
11L, NA, 12L, 9L, 8L, 1L, NA, 5L, 12L, 3L, 3L, 10L, 16L, 16L,
5L, 24L, 10L, 17L, 23L, 19L, 12L, 12L, 18L, 6L, 1L, 3L, 15L,
26L, 28L, 28L, 27L, 3L, 18L, 22L, 13L, 11L, 30L, 24L, 1L, 25L,
21L, 7L, 14L, 16L, 9L, 3L, 28L, 11L, 17L, 11L, 25L, 23L, 7L,
21L), myvar3 = c(78L, 79L, 78L, 78L, 79L, 78L, 79L, 77L, 79L,
79L, 76L, 78L, 78L, 79L, 79L, 79L, 79L, 78L, 79L, 79L, 79L, 79L,
78L, 78L, 78L, 79L, 79L, 78L, 78L, 79L, 78L, 79L, 79L, 78L, 79L,
79L, 78L, 78L, 78L, 79L, 79L, 79L, 79L, 78L, 79L, 79L, 73L, 79L,
79L, 79L, 79L, 79L, 72L, 79L, 78L, 78L, 78L, 79L, 78L, 78L, 79L,
78L, 79L, 79L, 79L, 79L, 79L, 78L, 78L, 79L, 78L, 78L, 79L, 79L,
79L, 76L, 79L, 78L, 79L, 79L, 79L, 79L, 79L, 75L, 79L, 79L, 79L,
79L, 79L, 79L, 79L, 78L, 79L, 79L, 77L, 78L, 79L, 78L, 79L, 78L,
79L, 79L, 79L, 78L, 78L, 79L, 79L, 78L, 78L, 78L, 78L, 79L, 79L,
78L, 78L, 76L, 79L, 76L, 77L, 79L, 79L, 78L, 79L, 79L, 79L, 79L,
79L, 79L, 79L, 78L, 78L, 79L, 78L, 79L, 79L, 78L, 79L, 78L, 79L,
79L, 79L, 79L, 79L, 78L, 79L, 79L, 77L, 79L, 79L, 78L, 78L, 79L,
78L, 79L, 79L, 79L, 78L, 79L, 79L, 79L, 78L, 79L, 79L, 78L, 79L,
78L, 79L, 79L, 78L, 79L, 79L, 79L, 79L, 79L, 79L, 79L, 78L, 79L,
78L, 79L, 79L, 79L, 79L, 79L, 78L, 79L, 79L, 79L, 79L, 79L, 79L,
79L, 78L, 79L, 78L, 79L, 78L, 79L, 79L, 79L, 79L, 76L, 78L, 79L
)), class = "data.frame", row.names = c(NA, -204L)) -> my_wide_data
换句话说，而不是
my_wide_data %>%
mutate(coalesce_var <- coalesce(myvar1, myvar2, myvar3))
我希望能够做类似
的事情my_wide_data %>%
mutate(coalesce_var <- coalesce(starts_with("my")))
问题：是否有可能在dplyr或tidyverse中的其他地方完成此类内容？
答案 0 :(得分：4)
以下工作利用coalesce(...)可以接受列表
vecs <- list(
c(1, 2, NA, NA, 5),
c(NA, NA, 3, 4, 5)
)
coalesce(!!! vecs)
您可以使用select中的辅助函数并将生成的所选数据框转换为列表
my_wide_data %>%
mutate(coalesce_var = coalesce(!!! select(., starts_with("my"))))
# myvar1 myvar2 myvar3 coalesce_var
# 1 10 24 78 10
# 2 3 24 79 3
# 3 11 27 78 11
# 4 2 8 78 2
# 5 4 9 79 4
# etc
编辑这是另一种结构 - 我更喜欢
library(rlang)
library(tidyselect)
my_wide_data %>%
mutate(coalesce_var = coalesce(!!! syms(vars_select(names(.), starts_with("my")))))