Dplyr Non Standard Evaluation -- Help Needed - r

Question

I am making my first baby steps with non standard evaluation (NSE) in dplyr.
Consider the following snippet: it takes a tibble, sorts it according to the values inside a column and replaces the n-k lower values with "Other".
See for instance:
library(dplyr)
df <- cars%>%as_tibble
k <- 3
df2 <- df %>%
arrange(desc(dist)) %>%
mutate(dist2 = factor(c(dist[1:k],
rep("Other", n() - k)),
levels = c(dist[1:k], "Other")))
What I would like is a function such that:
df2bis<-df %>% sort_keep(old_column, new_column, levels_to_keep)
produces the same result, where old_column column "dist" (the column I use to sort the data set), new_column (the column I generate) is "dist2" and levels_to_keep is "k" (number of values I explicitly retain).
I am getting lost in enquo, quo_name etc...
Any suggestion is appreciated.

Answer 1

You can do:
library(dplyr)
sort_keep=function(df,old_column, new_column, levels_to_keep){
old_column = enquo(old_column)
new_column = as.character(substitute(new_column))
df %>%
arrange(desc(!!old_column)) %>%
mutate(use = !!old_column,
!!new_column := factor(c(use[1:levels_to_keep],
rep("Other", n() - levels_to_keep)),
levels = c(use[1:levels_to_keep], "Other")),
use=NULL)
}
df%>%sort_keep(dist,dist2,3)

Answer 2

Something like this?
old_column = "dist"
new_column = "dist2"
levels_to_keep = 3
command = "df2bis<-df %>% sort_keep(old_column, new_column, levels_to_keep)"
command = gsub('old_column', old_column, command)
command = gsub('new_column', new_column, command)
command = gsub('levels_to_keep', levels_to_keep, command)
eval(parse(text=command))