How to perform a dplyr join with an environment variable

Question

I am relying on https://dplyr.tidyverse.org/articles/programming.html to create interactive tidy functions. These rely on environment variables (as the article calls them) such as the following example.

var_summary <- function(data, var) {
  data %>%
    summarise(n = n(), min = min({{ var }}), max = max({{ var }}))
}
mtcars %>% 
  group_by(cyl) %>% 
  var_summary(mpg)
#> `summarise()` ungrouping output (override with `.groups` argument)

However, when I try a similar method using left_join() I receive an error. Reproducible example below.

# A table
foobar <- tribble(~fooname, ~value, "setosa", 20, "versicolor", 30, "virginica", 10)

# A function
foobarjoin <- function(table, joincol){iris %>% left_join(table, by = c("Species" = {{ joincol }}))}

# When I use the function
 foobarjoin(table = foobar, joincol = fooname)

#> Error in standardise_join_by(by, x_names = x_names, y_names = y_names) : 
#>  object 'fooname' not found 

What is the correct way to use environment variables to perform a dplyr join within a custom function?

---

Note that this is not a duplicate question of How to join (merge) data frames (inner, outer, left, right). That question is a vanilla join question. This one is specifically about how to use environment variables within functions to achieve a join.

Answer 1

left_join or joins in general need character values. So change your function to :

library(dplyr)
foobarjoin <- function(table, joincol) {
       iris %>% left_join(table, by = c("Species" = joincol))
}

and you can call it as :

foobarjoin(table = foobar, joincol = "fooname")

#    Sepal.Length Sepal.Width Petal.Length Petal.Width    Species value
#1            5.1         3.5          1.4         0.2     setosa    20
#2            4.9         3.0          1.4         0.2     setosa    20
#3            4.7         3.2          1.3         0.2     setosa    20
#4            4.6         3.1          1.5         0.2     setosa    20
#5            5.0         3.6          1.4         0.2     setosa    20
#6            5.4         3.9          1.7         0.4     setosa    20
#7            4.6         3.4          1.4         0.3     setosa    20
#8            5.0         3.4          1.5         0.2     setosa    20
#...
#...