CODEWITHSUNDEEP
rdplyrpurrr
user51462
user51462

Reputation: 2072

R - Passing arguments to `dplyr::select()` inside a wrapper

I have a wrapper function which uses dplyr::select(), however when I attempt to use it to select columns by name, it throws an object * not found error. I know it has something to do with the way select() uses quasiquotation but I don't know exactly why.

Here is my attempt using as_mapper:

fun1 = as_mapper(~select(.x, .y))
fun1(iris, Species)

Error in .f(.x[[i]], ...) : object 'Species' not found

Using base function notation:

fun2 = function(dat, x) {select(substitute(dat), substitute(x))} 
fun2(iris, Species:Sepal.Length)

Error in UseMethod("select_") : 
  no applicable method for 'select_' applied to an object of class "name"

I would be grateful if someone could shed some light on why these errors are occurring.

Upvotes: 0

Views: 92

Answers (1)

al-obrien
al-obrien

Reputation: 1423

I believe this is related to non-standard evaluation (NSE) in R. Why dont you try using rlang to work with dplyr functions, as referenced here.

library(magrittr)
 fun2 <-  function(dat, x) {
   x <- rlang::enquo(x)
   dplyr::select(dat,!!x)
 } 

fun2(iris, Species:Sepal.Length) %>% tibble::tibble()

# A tibble: 150 x 1
   .$Species $Petal.Width $Petal.Length $Sepal.Width $Sepal.Length
   <fct>            <dbl>         <dbl>        <dbl>         <dbl>
 1 setosa             0.2           1.4          3.5           5.1
 2 setosa             0.2           1.4          3             4.9
 3 setosa             0.2           1.3          3.2           4.7
 4 setosa             0.2           1.5          3.1           4.6
 5 setosa             0.2           1.4          3.6           5  
 6 setosa             0.4           1.7          3.9           5.4
 7 setosa             0.3           1.4          3.4           4.6
 8 setosa             0.2           1.5          3.4           5  
 9 setosa             0.2           1.4          2.9           4.4
10 setosa             0.1           1.5          3.1           4.9
# ... with 140 more rows

I would also like to point out that @MrFlick is also correct and the new interpolation method through the curly-curly operator is a nice shortcut

Upvotes: 1

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