Background
I have a simple helper function that applies left_join to any number of passed tables in other to gather them and return one object.
Example
# 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)
Problem
I would like to be able to programmatically modify the suffix argument of left_join:
suffix If there are non-joined duplicate variables in x and y, these suffixes will be added to the output to disambiguate them. Should be a character vector of length 2.
Current results
# 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
Desired results
# 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
The model_type column reflects name of the object passed via ....
Attempts
I was trying to capture names of the objects passed within ... but it's not a named object so it doesn't make sense:
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)
}