Extract portion of nested tibbles?

Question

I've got a pile of nested tibbles that are from the tidyrss package. The data looks like this:

What I'm trying to do is take the four common items from each tibble and tidy them, so that the output looks like this:

item_title	item_link	item_description	item_pub_date
title from article 1	some url	longer text	posix date
title from article 2	some url	longer text	posix date
title from article 3	some url	longer text	posix date
title from article 4	some url	longer text	posix date

Thus far I've tried unlist() and deframe() and both of those just make a general mess of things - and an added twist is not all the list items are tibbles. Some are functions, and I want to ignore those. What's the best tidyverse approach to tackle this task?

Answer 1

map_dfr seems to do what you want! It loops over a list and applies a function to each one - in this case, the only "function" we want to apply is returning the data frame/tibble, but that also allows us to skip the functions:

clean_feed_df <- list(
  data.frame(item_title=sample(letters, 3), 
             item_link=sample(letters, 3),
             item_desc=sample(letters, 3),
             item_date=sample(letters, 3)),
  data.frame(item_title=as.character(sample(1:100, 5)), 
             item_link=as.character(sample(1:100, 5)),
             item_desc=as.character(sample(1:100, 5)),
             item_date=as.character(sample(1:100, 5))),
  function(x)sum(x)
)

map_dfr(clean_feed_df, function(rssentry){
  if(is(rssentry, "data.frame")){
    return(rssentry)
  }
})

which returns

  item_title item_link item_desc item_date
1          s         s         u         i
2          x         d         o         x
3          t         x         d         h
4         40        51        21        91
5          4        25        37        34
6          5        44        18        71
7         65        70        83        90
8         32        85        76        89