Using lapply over a list and adding a column with data frame name

Question

I have a list containing two data frames:

sample_list <- list("tables" = data.frame(weight = sample(1:50, 20, replace = T)),
                    "chairs" = data.frame(height = sample(1:50, 20, replace = T)))

I would like to use lapply to run a function over all the data frames in this list. In the output of each function, I need to create another column with the name of the source data frame (see mutate):

lapply(sample_list, function(x) {
  x %>% 
    filter(x >= 20) %>% 
    mutate(groupName = names(x))
})

For some reason, I can't figure out how to make this work. How do I pass the name of the data frame into mutate? Right now it is returning the name of the first column in that data frame, rather than the name of the data frame itself.

Thanks!

Answer 1

We can loop through names of sample_list instead of looping through the list

lapply(names(sample_list), function(x) {
    sample_list[[x]] %>% 
        filter_at(vars(1),~. >= 20) %>% 
        mutate(groupName = x)
})

Update Sep-2021

cleaner way using purrr::map

purrr::map(names(sample_list), ~sample_list[[.x]] %>% 
             filter_at(vars(1),~. >= 20) %>% 
             mutate(groupName = .x)
)