Pass a df and variable argument in a function in R - r

Question

How can I write a function with a df and variable argument, evaluating both? I read several posts and blog-posts from r-bloggers and I think I have some problem with the lazy-evaluation, but now I'm terribly confused.
This is my function:
RAM_char_func <- function(dataset, char_var){
a <- dataset[ , c("id", char_var)]
b <- a[[id]][is.na(a[[char_var]]) %in% FALSE]
c <- a[a[[id]] %in% b , ]
c
}
I get this:
Warning
Unknown or uninitialised column: 'char_var'.
This should give me a table (c) with two columns and based on the char_var n-amount lines. while the code works outside the function, I cannot manage to get it working inside the function. I also tried the tidyverse-idea with select and filter, but that doesnt work, too.
I'm using R 3.5.1 with Mac OS X (High Sierra, 10.13.6) and R Studio (latest version).
dataframe
df <- data.frame(id = c(1:10),
var_10 = c(101:110),
var_25 = c("a", "b", NA, "c", NA, "d", NA, "e", "f", NA),stringsAsFactors = F)
df
Code Outside of the function is:
a <- df[ , c("id", "v_25")]
a
b <- a$id[is.na(a$v_25) %in% FALSE]
b
c <- a[a$id %in% b , ]
c
or
library(tidyverse)
df %>%
select(id, var_25) %>%
filter(is.na(var_25) %in% FALSE)

Answer 1

Here is one way to solve your issue:
library(tidyverse)
library(rlang)
remove.na <- function(data, col){
symcol <- enquo(col)
data %>% select(id, !!symcol) %>% filter(!is.na(!!symcol))
}
df %>% remove.na(var_25)
# id var_25
# 1 1 a
# 2 2 b
# 3 4 c
# 4 6 d
# 5 8 e
# 6 9 f
all_equal(df %>% select(id, var_25) %>% filter(!is.na(var_25)), df %>% remove.na(var_25))
[1] TRUE

Answer 2

In the spirit of "teach a man how to fish", you can use the reprex package to be sure you're running your buggy code in a clean environment, and the error will be very explicit (you can also just run the code in a new session as long as you don't have a messy Rprofile file) :
library(reprex)
reprex({
df <- data.frame(id = c(1:10),
var_10 = c(101:110),
var_25 = c("a", "b", NA, "c", NA, "d", NA, "e", "f", NA),stringsAsFactors = F)
RAM_char_func <- function(dataset, char_var){
a <- dataset[ , c("id", char_var)]
b <- a[[id]][is.na(a[[char_var]]) %in% FALSE]
c <- a[a[[id]] %in% b , ]
c
}
RAM_char_func(df,"var_25")
})
If you use Rstudio it will show the output in the Viewer tab, and the error that I get is :
> Error in (function(x, i, exact) if (is.matrix(i)) as.matrix(x)[[i]] else .subset2(x, : objet 'id' introuvable
(sorry for the french)
It tells you object id can't be found, then you can check why your code is trying to access an object named id and you'll find easily the mistake in the 2nd instruction of your function.
If finding the sinful line is hard for you, try running traceback() right after the error or call debugonce(RAM_char_func) then RAM_char_func(df,"var_25") and browse until you find the line which fails.

Answer 3

your function contained an error. [[id]] must be [["id"]]
RAM_char_func <- function(dataset, char_var){
a <- dataset[ , c("id", char_var)]
b <- a[["id"]][is.na(a[[char_var]]) %in% FALSE]
c <- a[a[["id"]] %in% b , ]
c
}
data:
df <- data.frame(id = c(1:10),
var_10 = c(101:110),
var_25 = c("a", "b", NA, "c", NA, "d", NA, "e", "f", NA),stringsAsFactors = F)
call your function:
RAM_char_func(dataset=df,char_var="var_25")
# id var_25
#1 1 a
#2 2 b
#4 4 c
#6 6 d
#8 8 e
#9 9 f