How to call column names from an object in dplyr? - r

Question

I am trying to replace all zeros in multiple columns with NA using dplyr.
However, since I have many variables, I do not want to call them all by one, but rather store them in an object that I can call afterwards.
This is a minimal example of what I did:
library(dplyr)
Data <- data.frame(var1=c(1:10), var2=rep(c(0,4),5), var3 = rep(c(2,0,3,4,5),2), var4 = rep(c(7,0),5))
col <- Data[,c(2:4)]
Data <- Data %>%
mutate(across(col , na_if, 0))
However, if I do this, I get the following error message:
Error: Problem with 'mutate()' input '..1'.
x Must subset columns with a valid subscript vector.
x Subscript has the wrong type 'data.frame<
var2: double
var3: double
var4: double>'.
i It must be numeric or character.
i Input '..1' is '(function (.cols = everything(), .fns = NULL, ..., .names = NULL) ...'.
I have tried to change the format of col to a tibble, but that did not help.
Could anyone tell me how to make this work?

Answer 1

In case you wanted to target numeric columns only, then try helper functions like where(), which will select any variable where the function returns TRUE. I suppose the only benefit here is targeting a specific type of variable.
library(dplyr)
# The where() function will select var2, var3, and var4
# Note: var1 is an integer so the function returns FALSE
# Useful when you want to completely ignore a specific type of variable
Data <- data.frame(
var1 = c(1:10),
var2 = rep(c(0, 4),5),
var3 = rep(c(2, 0 ,3, 4, 5), 2),
var4 = rep(c(7, 0), 5)
)
Data %>%
mutate(across(where(is.numeric), ~na_if(., 0)))
Here is the output:
var1 var2 var3 var4
1 1 NA 2 7
2 2 4 NA NA
3 3 NA 3 7
4 4 4 4 NA
5 5 NA 5 7
6 6 4 2 NA
7 7 NA NA 7
8 8 4 3 NA
9 9 NA 4 7
10 10 4 5 NA
The other answer you'll find here is great and allows you to select any arbitrary number of columns.

Answer 2

Here, the col should be names of the Data. As there is a function name with col, we can name the object differently, wrap with all_of and replace the 0 to NA within across
library(dplyr)
col1 <- names(Data)[2:4]
Data <- Data %>%
mutate(across(all_of(col1) , na_if, 0))
-output
Data
# var1 var2 var3 var4
#1 1 NA 2 7
#2 2 4 NA NA
#3 3 NA 3 7
#4 4 4 4 NA
#5 5 NA 5 7
#6 6 4 2 NA
#7 7 NA NA 7
#8 8 4 3 NA
#9 9 NA 4 7
#10 10 4 5 NA
NOTE: Here the OP asked about looping based on either the index or the column names