Passing argument into function for group_by in dplyr

Question

I am trying to use group_by within a function call in dplyr (R) and I am getting unexpected results. Here is an example of what I am trying to do:

df = data.frame(a = c(0,0,1,1), b = c(0,1,0,1), c = c(1,2,3,4))

result1 = df %>%
  group_by(a,b) %>%
  mutate(d = sum(c))
result1$d

myFunc <- function(df, var) {
  output = df %>%
    group_by(a,!!var) %>%
    mutate(d = sum(c))
  return(output)
}

result2 = myFunc(df,"b")
result2$d

result1$d yields [1,2,3,4] which is what I expected. result2$d yields [3,3,7,7] which I do not want, and I am not sure what is going on.

It works to have b (without quotes) as the function argument, and {{var}} in place of !!var. Unfortunately, in my case, my column names are in string format (but maybe there is a way to transform the string beforehand so that it will work with the {{}} notation?)

@VvdL yes, but you will get an additional column named `\`get(var)\`` in the output. That's not perfect. — Darren Tsai, Jul 22 '22 at 06:57
Does this answer your question? [How to pass column name as argument to function for dplyr verbs?](https://stackoverflow.com/questions/67382081/how-to-pass-column-name-as-argument-to-function-for-dplyr-verbs) — user438383, Jul 22 '22 at 07:18

Darren Tsai · Accepted Answer · 2022-07-22T07:15:49.837

If you want to pass a character object that can refer to a certain column of a data frame, you should use !!sym(var):

myFunc <- function(df, var) {
  output = df %>%
    group_by(a, !!sym(var)) %>%
    mutate(d = sum(c))
  return(output)
}

myFunc(df, "b")

If you want to pass a data-masked argument, you should use {{ var }} or equivalently !!enquo(var):

myFunc <- function(df, var) {
  output = df %>%
    group_by(a, {{ var }}) %>%
    mutate(d = sum(c))
  return(output)
}

myFunc(df, b)

Note that I pass "b" and b respectively into the function in the two different cases.

score 2 · Answer 2 · answered Jul 22 '22 at 07:08

If we want to use quoting and unquoting instead of curlycurly {{}} the we should consider this basic procedure: https://tidyeval.tidyverse.org/dplyr.html

Creating a function around dplyr pipelines involves three steps: abstraction, quoting, and unquoting.

1. Abstraction step:

Here we identify the varying steps. In our case var in group_by:

2. Quoting step:

Identify all the arguments where the user is allowed to refer to data frame columns directly.
The function can’t evaluate these arguments right away.
Instead they should be automatically quoted. Apply enquo() to these arguments

3. Unquoting step:

Identify where these variables are passed to other quoting functions and unquote with !!.
In this case we pass var to group_by():

myFunc <- function(df, var) {
  var <- enquo(var)
  output = df %>%
    group_by(a,!!var) %>%
    mutate(d = sum(c))
  return(output)
}

result2 = myFunc(df,b)

output:

[1] 1 2 3 4

score 0 · Answer 3 · answered Jul 22 '22 at 06:44

0

Just as I post a question, I come across something that works...

myFunc <- function(df, var) {
  output = df %>%
    group_by_at(.vars = c("a",var)) %>%
    mutate(d = sum(c))
  return(output)
}

result2 = myFunc(df,"b")

answered Jul 22 '22 at 06:44

David Mao

43
4

Passing argument into function for group_by in dplyr

3 Answers3