Extract portion of nested tibbles? - r

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