在apply中的函数中使用dplyr :: group_by

Question

i'd like to produce nice summaries for a selection of grouping variables in my dataset, where for each group i would show the top 6 frequencies and their associated proportions. I can get this for a single grouping variable using the syntax:

my_db %>% 
group_by(my_var) %>% 
summarise(n=n()) %>% 
mutate(pc=scales::percent(n/sum(n))) %>% 
arrange(desc(n)) %>% 
head()

How do i modify this expression so it can be used in an apply function?

For example using mtcars, I've tried something like this:

apply(mtcars[c(2:4,11)], 2, 
   function(x) {
    group_by(!!x) %>% 
      summarise(n=n()) %>% 
      mutate(pc=scales::percent(n/sum(n))) %>% 
      arrange(desc(n)) %>% head()
      }
    )

but it doesn't work. Any idea how i can achieve this?

Answer 1

You should apply using the colnames(dat) to get the correct groupings:

dat <- mtcars[c(2:4,11)]



grp <- function(x) {
  group_by(dat,!!as.name(x)) %>%
  summarise(n=n()) %>% 
  mutate(pc=scales::percent(n/sum(n))) %>% 
  arrange(desc(n)) %>% head()
}


lapply(colnames(dat), grp)

Answer 2

apply(mtcars[c(2:4,11)], 2, 
      function(x) { 
    mtcars %>%
    group_by(x= !!x) %>% 
      summarise(n=n()) %>% 
      mutate(pc=scales::percent(n/sum(n))) %>% 
      arrange(desc(n)) %>% head()
  }
)

you just need the parent df to evaluation