R - Function to make a binary variable - r

Question

I have some variables which take value between 1 and 5. I would like to code them 0 if they take the value between 1 and 3 (included) and 1 if they take the value 4 or 5.
My dataset looks like this
var1 var2 var3
1 1 NA
4 3 4
3 4 5
2 5 3
So I would like it to be like this:
var1 var2 var3
0 0 NA
1 0 1
0 1 1
0 1 0
I tried to do a function and to call it
making_binary <- function (var){
var <- factor(var >= 4, labels = c(0, 1))
return(var)
}
df <- lapply(df, making_binary)
But I had an error : incorrect labels : length 2 must be 1 or 1
Where did I go wrong?
Thank you very much for your answers!

Answer 1

You can use :
df[] <- +(df == 4 | df == 5)
df
# var1 var2 var3
#1 0 0 NA
#2 1 0 1
#3 0 1 1
#4 0 1 0
Comparison of df == 4 | df == 5 returns logical values (TRUE/FALSE), + here turns those logical values to integer values (1/0) respectively.
If you want to apply this for selected columns you can subset the columns by position or by name.
cols <- 1:3 #Position
#cols <- grep('var', names(df)) #Name
df[cols] <- +(df[cols] == 4 | df[cols] == 5)
As far as your function is concerned you can do :
making_binary <- function (var){
var <- as.integer(var >= 4)
#which is faster version of
#var <- ifelse(var >= 4, 1, 0)
return(var)
}
df[] <- lapply(df, making_binary)
data
df <- structure(list(var1 = c(1L, 4L, 3L, 2L), var2 = c(1L, 3L, 4L,
5L), var3 = c(NA, 4L, 5L, 3L)), class = "data.frame", row.names = c(NA, -4L))

Answer 2

I think ifelse would fit the problem well:
df[] <- lapply(df, function(x) ifelse(x >=1 & x <=3, 0, x))
df
var1 var2 var3
1 0 0 NA
2 4 0 4
3 0 4 5
4 0 5 0
df[] <- lapply(df, function(x) ifelse(x >=4 & x <=5, 1, x))
df
var1 var2 var3
1 0 0 NA
2 1 0 1
3 0 1 1
4 0 1 0
If you need to do the two steps at once, you can look at dplyr::case_when() or data.table::fcase().

Answer 3

You can simply test if the value is larger than 3, which will return TRUE and FALSE and cast this to a number:
+(x>3)
# var1 var2 var3
#[1,] 0 0 NA
#[2,] 1 0 1
#[3,] 0 1 1
#[4,] 0 1 0
In case you want this only for some columns, you have to subset them. E.g. for column 1 and 2:
+(x[1:2]>3)
#+(x[c("var1","var2")]>3) #Alternative
# var1 var2
#[1,] 0 0
#[2,] 1 0
#[3,] 0 1
#[4,] 0 1
Data:
x <- data.frame(var1 = c(1L, 4L, 3L, 2L), var2 = c(1L, 3L, 4L, 5L)
, var3 = c(NA, 4L, 5L, 3L))