背景

我有一个简单的辅助函数，该函数适用left_join于传递给其他表的任何数量的表，gather并返回一个对象。

例

# Settings ----------------------------------------------------------------

library("tidyverse")
set.seed(123)

# Data --------------------------------------------------------------------

sample_one <-
    tibble(
        column_a = c(1, 2),
        column_b = runif(n = 2),
        column_other = runif(n = 2)
    )
sample_two <-
    tibble(
        column_a = c(1, 2),
        column_b = runif(n = 2),
        column_other = runif(n = 2)
    )
sample_three <-
    tibble(
        column_a = c(1, 2),
        column_b = runif(n = 2),
        column_other = runif(n = 2)
    )

# Function ----------------------------------------------------------------

left_join_on_column_a <- function(keep_var, ...) {
    keep_var <- enquo(keep_var)
    dots <- list(...)
    clean_dfs <- map(dots, select, !!keep_var, "column_a")
    reduce(.x = clean_dfs,
           .f = left_join,
           "column_a") %>%
        gather(key = "model_type", !!keep_var, -column_a)
}

# Test --------------------------------------------------------------------

left_join_on_column_a(keep_var = column_b, sample_one, sample_two, sample_three)

问题

我希望能够以编程方式修改以下suffix参数left_join：

后缀如果x和y中存在非联接重复变量，则将这些后缀添加到输出中以消除歧义。应该是长度为2的字符向量。

当前结果

# A tibble: 6 x 3
  column_a model_type column_b
     <dbl> <chr>         <dbl>
1        1 column_b.x   0.288 
2        2 column_b.x   0.788 
3        1 column_b.y   0.940 
4        2 column_b.y   0.0456
5        1 column_b     0.551 
6        2 column_b     0.457 

所需结果

# A tibble: 6 x 3
  column_a model_type      column_b
     <dbl> <chr>            <dbl>
1        1 sample_one       0.288 
2        2 sample_one       0.788 
3        1 sample_two       0.940 
4        2 sample_two       0.0456
5        1 sample_three     0.551 
6        2 sample_three     0.457 

该model_type列反映通过传递的对象的名称...。

尝试次数

我试图捕获传入的对象的名称，...但它不是命名对象，因此没有任何意义：

left_join_on_column_a <- function(keep_var, ...) {
    keep_var <- enquo(keep_var)
    dots <- list(...)
    table_names <- names(dots)
    clean_dfs <- map(dots, select, !!keep_var, "column_a")
    reduce(.x = clean_dfs,
           .f = left_join,
           "column_a", 
           table_names) %>%
        gather(key = "model_type", !!keep_var, -column_a)
}