r语言 - 如何使用字符向量的元素作为使用非标准求值 := 运算符的函数的符号参数

Question

我正在尝试编写一个接受变量名称的字符向量作为符号参数的函数。

以下是从questionr包中的"生育率"数据集中提取的一些数据。重要的是它包含一些标记数据的列。

library(tidyverse)
library(labelled)
df <- structure(list(id_woman = structure(c(391, 1643, 85, 881, 1981, 
1072, 1978, 1607, 738), label = "Woman Id", 
format.spss = "F8.0"), 
weight = structure(c(1.80315, 1.80315, 1.80315, 1.80315, 
1.80315, 0.997934, 0.997934, 0.997934, 0.192455), 
label = "Sample weight", format.spss = "F8.2"), 
residency = structure(c(2, 2, 2, 2, 2, 2, 2, 2, 2), 
label = "Urban / rural residency", 
labels = c(urban = 1, rural = 2), 
class = "haven_labelled"), 
region = structure(c(4, 4, 4, 4, 4, 3, 3, 3, 3), label = "Region", 
labels = c(North = 1, East = 2, South = 3, West = 4),
class = "haven_labelled")), 
row.names = c(NA, -9L), class = c("tbl_df", "tbl", "data.frame"))

此函数仅采用变量名称并将其从标记数据转换为因子。

my.func <- function(var){
df %>%
mutate({{var}} := to_factor({{var}}))
}

这两条线都有效。

my.func(residency)
my.func("residency")

他们返回以下内容：

id_woman weight residency    region
<dbl>  <dbl> <fct>     <dbl+lbl>
1      391  1.80  rural     4 [West] 
2     1643  1.80  rural     4 [West] 
3       85  1.80  rural     4 [West] 
4      881  1.80  rural     4 [West] 
5     1981  1.80  rural     4 [West] 
6     1072  0.998 rural     3 [South]
7     1978  0.998 rural     3 [South]
8     1607  0.998 rural     3 [South]
9      738  0.192 rural     3 [South]

如果我尝试提供变量名称作为向量的一部分，麻烦就来了，如下所示：

var.names <- c("residency", "region")
my.func(var.names[1])
Error: The LHS of `:=` must be a string or a symbol
Call `rlang::last_error()` to see a backtrace 

我试过这个，但也失败了。

my.func(rlang::sym(var.names[1]))
Error: The LHS of `:=` must be a string or a symbol
Call `rlang::last_error()` to see a backtrace 

Answer 1

在这种情况下，我们必须评估 (!!(

my.func(!!var.names[1])
# A tibble: 9 x 4
#  id_woman weight residency    region
#     <dbl>  <dbl> <fct>     <dbl+lbl>
#1      391  1.80  residency 4 [West] 
#2     1643  1.80  residency 4 [West] 
#3       85  1.80  residency 4 [West] 
#4      881  1.80  residency 4 [West] 
#5     1981  1.80  residency 4 [West] 
#6     1072  0.998 residency 3 [South]
#7     1978  0.998 residency 3 [South]
#8     1607  0.998 residency 3 [South]
#9      738  0.192 residency 3 [South]