how to use tidyeval functions with loops?

Consider this simple example

library(dplyr)

dataframe <- data_frame(id = c(1,2,3,4),
                        group = c('a','b','c','c'),
                        value = c(200,400,120,300))


> dataframe
# A tibble: 4 x 3
     id group value
  <dbl> <chr> <dbl>
1     1     a   200
2     2     b   400
3     3     c   120
4     4     c   300

and this tidyeval function that uses dplyr to aggregate my dataframe according to some input column.

func_tidy <- function(data, mygroup){
  quo_var <- enquo(mygroup)

  df_agg <- data %>% 
    group_by(!!quo_var) %>% 
    summarize(mean = mean(value, na.rm = TRUE),
              count = n()) %>% 
    ungroup()

  df_agg
}

now, this works

> func_tidy(dataframe, group)
# A tibble: 3 x 3
  group  mean count
  <chr> <dbl> <int>
1     a   200     1
2     b   400     1
3     c   210     2

but doing the same thing from within a loop FAILS

for(col in c(group)){
  func_tidy(dataframe, col)
}
 Error in grouped_df_impl(data, unname(vars), drop) : Column `col` is unknown

What is the problem here? How can I use my tidyeval function in a loop?

Thanks!

Solution

For looping through column names you will need to use character strings.

for(col in "group")

When you pass this variable to your function, you will need to convert it from a character string to a symbol using rlang::sym. You use !! to unquote so the expression is evaluated.

So your loop would look like (I add a print to see the output):

for(col in "group"){
    print( func_tidy(dataframe, !! rlang::sym(col) ) )
}

# A tibble: 3 x 3
  group  mean count
  <chr> <dbl> <int>
1     a   200     1
2     b   400     1
3     c   210     2