Pass a variable name to a user written function that uses dyplr - r

Question

I am trying to write a function that index variables names.
In particular, in my function, I use mutate to encode a variable that I have without changing its name. Does anyone knows how I can index a variable on the left end side of mutate?
Here is an example
library(tydiverse)
# first create relevant dataset
iris <- iris%>% group_by(Species) %>% mutate(mean_Length=mean(Sepal.Length))
# second create my function
userfunction <- function(var){
newdata <- iris %>%
select(mean_Length,{var}) %>% distinct() %>%
mutate(get(var)= # this is what causes my function to fail. How can i refer to the `var` here?
factor(get(var),get(var))) %>%
arrange(get(var)) #
return(newdata)
}
# this function produces the following error # Error: unexpected '}' in "}"
#note that if I change the reference to its original string the function works
userfunction2 <- function(var){
newdata <- iris %>%
select(mean_Length,{var}) %>% distinct() %>%
mutate(Species= # without reference it works, but I am unable to use the function for multiple variables.
factor(get(var),get(var))) %>%
arrange(get(var)) #
return(newdata)
}
encodedata<- userfunction2("Species")
Thanks a lot in advance for your help
Best

Answer 1

Here is a working example that goes into a similar direction as Limey's answer:
iris <- datasets::iris %>%
group_by(Species) %>%
mutate(mean_Length=mean(Sepal.Length)) %>%
ungroup()
userfunction <- function(var){
iris %>%
transmute(mean_Length, "temp" = iris[[var]]) %>%
distinct() %>%
mutate("{var}" := factor(temp)) %>%
arrange(temp) %>%
select(-temp)
}
userfunction("Petal.Length")

Answer 2

I don't think var is your problem. I think it's the =. If you you have a enquoted variable on the left hand side of the assignment (which is effectively what you do have with get()), you need :=, not =.
See here for more details.
I would have written your function slightly differently:
userfunction <- function(data, var){
qVar <- enquo(var)
newdata <- data %>%
select(mean_Length, !! qVar) %>% distinct() %>%
mutate(!! qVar := factor(!! qVar, !! qVar)) %>%
arrange(!! qVar)
return(newdata)
}
The inclusion of the data parameter means you can include it in a pipe:
encodedata <- iris %>% userfunction(Species)
encodedata
# A tibble: 3 x 2
# Groups: Species [3]
mean_Length Species
<dbl> <fct>
1 5.01 setosa
2 5.94 versicolor
3 6.59 virginica