Say that I have this list:
listexample = list(books = list(list(
title="Book 1",
entry = "entry 1",
publisher = "Books Unlimited",
authors = list(
list(name="bob", location="north dakota"),
list(name="susan", location="california"),
list(name="tim")),
isbn = "1358",
universities = list(
list(univ="univ1"),
list(univ="univ2"))
),
list(
title="Book 2",
entry = "entry 2",
publisher = "Books Unified",
authors = list(
list(name="tom", location="north dakota"),
list(name="sally", location="california"),
list(name="erica", location="berlin")),
isbn = "1258",
universities = list(
list(univ="univ5"),
list(univ="univ2"),
list(univ="univ99"),
list(univ="univ2"),
list(univ="univ3"))
)
),
misc = list(name="Jim Smith", location="Alaska"))
How can I create a dataframe (or tibble is also fine) where each row is an author? I want to completely ignore the second element of the main list (misc). I also want to ignore universities, isbn, and publisher. I still want to keep title, name, location, as well as books (the name of the first element of the main list).
I know that rrapply can be used to iteratively do things, but I am not sure if it is appropriate in this case.
library(rrapply)
rrapply(listexample, how = "bind")
1
You can use unnest_longer and unnest_wider from tidyr.
listexample |>
tibble::enframe() |>
dplyr::filter(name == "books") |>
tidyr::unnest_longer(value) |>
tidyr::unnest_wider(value) |>
dplyr::select(title, authors) |>
tidyr::unnest_longer(authors) |>
tidyr::unnest_wider(authors)
You can run the code adding one line at a time to see what everything does. In short, we turn the list into a two-row tibble (row one is books, row two is misc), then expand the nested information.
Read the tidyr “rectangling” vignette for more information. In fact, you can probably reduce the code here by using tidyr::hoist().