r语言 - 是否有一种方法运行dplyr函数在一组预定义的变量?

Question

df <- mtcars
prop <- df %>%
group_by(cyl, .drop = FALSE) %>%
filter(rowMeans(is.na(across(c(disp,  drat, wt)))) <= 0.5) %>%
summarise(N = n(), across(c(disp, drat, wt, qsec, vs), ~mean(. == 1, na.rm=TRUE))) %>%
select(disp,  drat, wt, qsec, vs)

是否有一种方法可以在外部向量上运行filter(),summarise()和select()，如:

select1 <- df %>% select(disp,  drat, wt)
select2 <- df %>% select(disp,  drat, wt, qsec, vs)

而不是每次都定义各自的变量来减少对错误的敏感性?

例如，summarise(N = n(), across(all_of(select2)), ~mean(. == 1, na.rm=TRUE)) %>%给了我一个错误。

谢谢!

Answer 1

使用!!from{rlang}

library(rlang)
library(dplyr)
df <- mtcars
select1 <- df %>% select(disp, drat, wt) %>% names()
select2 <- df %>% select(disp, drat, wt, qsec, vs) %>% names()
df %>%
group_by(cyl, .drop = FALSE) %>%
filter(rowMeans(is.na(across(!!select1))) <= 0.5) %>%
summarise(N = n(), across(!!select2, ~ mean(. == 1, na.rm = TRUE))) %>%
select(!!select2)
#> # A tibble: 3 × 5
#>    disp  drat    wt  qsec    vs
#>   <dbl> <dbl> <dbl> <dbl> <dbl>
#> 1     0     0     0     0 0.909
#> 2     0     0     0     0 0.571
#> 3     0     0     0     0 0

^{由reprex包(v2.0.1)在2022-07-12创建}