Tidy evaluation programming with dplyr::case_when

Question

I try to write a simple function wrapping around the dplyr::case_when() function. I read the programming with dplyr documentation on https://cran.r-project.org/web/packages/dplyr/vignettes/programming.html but can't figure out how this works with the case_when() function.

I have the following data:

data <- tibble(
   item_name = c("apple", "bmw", "bmw")
)

And the following list:

cat <- list(
   item_name == "apple" ~ "fruit",
   item_name == "bmw" ~ "car"
)

Then I would like to write a function like:

category_fn <- function(df, ...){
   cat1 <- quos(...)
   df %>%
     mutate(category = case_when((!!!cat1)))
}

Unfortunately category_fn(data,cat) gives an evaluation error in this case. I would like to obtain the same output as the output obtained by:

data %>% 
   mutate(category = case_when(item_name == "apple" ~ "fruit",
                               item_name == "bmw" ~ "car"))

What is the way to do this?

Answer 1

Here's another tidyverse centric approach

cat <- tribble(
    ~name, ~category,
    "apple", "fruit",
    "bmw", "car"
) %>% 
    str_glue_data("item_name == '{name}' ~ '{category}'")

data %>% 
    mutate(category = case_when(!!! map(cat, rlang::parse_expr)))

Answer 2

Quote each element of your list first:

cat <- list(
  quo(item_name == "apple" ~ "fruit"),
  quo(item_name == "bmw" ~ "car")
)

Your function does not then have to quote the cat object itself. I have also changed the use of the "everything else" ... argument to refer to the category argument explicitly in the call:

category_fn <- function(df, categories){
  df %>%
    mutate(category = case_when(!!!categories))
}

The output of the function is then as expected:

category_fn(data, cat)
# A tibble: 3 x 2
  item_name category
      <chr>    <chr>
1     apple    fruit
2       bmw      car
3       bmw      car

For completeness, I note that the category list works with your function when defined using the base R quote() function too:

cat <- list(
  quote(item_name == "apple" ~ "fruit"),
  quote(item_name == "bmw" ~ "car")
)
> cat
[[1]]
item_name == "apple" ~ "fruit"

[[2]]
item_name == "bmw" ~ "car"

> category_fn(data, cat)
# A tibble: 3 x 2
  item_name category
      <chr>    <chr>
1     apple    fruit
2       bmw      car
3       bmw      car