Passing column names through multiple functions with dplyr - r

Question

I wrote a simple function to create tables of percentages in dplyr:
library(dplyr)
df = tibble(
Gender = sample(c("Male", "Female"), 100, replace = TRUE),
FavColour = sample(c("Red", "Blue"), 100, replace = TRUE)
)
quick_pct_tab = function(df, col) {
col_quo = enquo(col)
df %>%
count(!! col_quo) %>%
mutate(Percent = (100 * n / sum(n)))
}
df %>% quick_pct_tab(FavColour)
# Output:
# A tibble: 2 x 3
FavColour n Percent
<chr> <int> <dbl>
1 Blue 58 58
2 Red 42 42
This works great. However, when I tried to build on top of this, writing a new function that calculated the same percentages with grouping, I could not figure out how to use quick_pct_tab within the new function - after trying multiple different combinations of quo(col), !! quo(col) and enquo(col), etc.
bygender_tab = function(df, col) {
col_enquo = enquo(col)
# Want to replace this with
# df %>% quick_pct_tab(col)
gender_tab = df %>%
group_by(Gender) %>%
count(!! col_enquo) %>%
mutate(Percent = (100 * n / sum(n)))
gender_tab %>%
select(!! col_enquo, Gender, Percent) %>%
spread(Gender, Percent)
}
> df %>% bygender_tab(FavColour)
# A tibble: 2 x 3
FavColour Female Male
* <chr> <dbl> <dbl>
1 Blue 52.08333 63.46154
2 Red 47.91667 36.53846
From what I understand non-standard evaluation in dplyr is deprecated so it would be great to learn how to achieve this using dplyr > 0.7. How do I have to quote the col argument to pass it through to a further dplyr function?

Answer 1

We need to do !! to trigger the evaluation of the 'col_enquo'
bygender_tab = function(df, col) {
col_enquo = enquo(col)
df %>%
group_by(Gender) %>%
quick_pct_tab(!!col_enquo) %>% ## change
select(!! col_enquo, Gender, Percent) %>%
spread(Gender, Percent)
}
df %>%
bygender_tab(FavColour)
# A tibble: 2 x 3
# FavColour Female Male
#* <chr> <dbl> <dbl>
#1 Blue 54.54545 41.07143
#2 Red 45.45455 58.92857
Using the OP's function, the output is
# A tibble: 2 x 3
# FavColour Female Male
#* <chr> <dbl> <dbl>
#1 Blue 54.54545 41.07143
#2 Red 45.45455 58.92857
Note that the seed was not set while creating the dataset
Update
with rlang version 0.4.0 (ran with dplyr - 0.8.2), we can also use the {{...}} to do quote, unquote, substitution
bygender_tabN = function(df, col) {
df %>%
group_by(Gender) %>%
quick_pct_tab({{col}}) %>% ## change
select({{col}}, Gender, Percent) %>%
spread(Gender, Percent)
}
df %>%
bygender_tabN(FavColour)
# A tibble: 2 x 3
# FavColour Female Male
# <chr> <dbl> <dbl>
#1 Blue 50 46.3
#2 Red 50 53.7
-checking output with previous function (set.seed was not provided)
df %>%
bygender_tab(FavColour)
# A tibble: 2 x 3
# FavColour Female Male
# <chr> <dbl> <dbl>
#1 Blue 50 46.3
#2 Red 50 53.7