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I have a deeply nested list that I am trying to extract into a simple df.

Sample List

df <- tibble::tribble( ~division, ~id, ~owners, "Division 2", "8", list(list(commissioner = 0, name = "Jesse H", id = "475A2F18-B6AF-11E6-977B-8468E8194D12", playoff_add_drops_disabled = 0)), "Division 1", "15", list(list(commissioner = 0, name = "Jon O", id = "F37E4A84-673C-11EC-812D-82AF546C6EE5", playoff_add_drops_disabled = 0)), "Division 2", "10", list(list(commissioner = 0, name = "Jim K", id = "1F19EADA-AC9D-11E3-8EB7-031CFC5F1C7D", playoff_add_drops_disabled = 0), list(commissioner = 0, name = "Kevin P", id = "E48FCF2A-ACA5-11E3-854D-2A588E5A61DF", playoff_add_drops_disabled = 0)), "Division 1", "14", list(list(commissioner = 0, name = "Alan C", id = "D97B1226-E9C6-11E8-8119-3A141D7BE3A7", playoff_add_drops_disabled = 0), list(commissioner = 0, name = "Sam L", id = "8CC10D94-E7DF-11EC-9CA5-51CD4E0A8531", playoff_add_drops_disabled = 0)), "Division 1", "9", list(list(commissioner = 0, name = "Don R", id = "4686110A-D916-11EF-8988-87BD04866ADA", playoff_add_drops_disabled = 0)), "Division 1", "17", list(list(logged_in_owner = 1, commissioner = 0, name = "Jason S", id = "2E84EA94-D98A-11EF-A9AB-4A2105866ADA", playoff_add_drops_disabled = 0)), "Division 2", "16", list(list(commissioner = 0, name = "Eric W", id = "E0D804E0-9B59-11ED-BA80-FCF8D3963504", playoff_add_drops_disabled = 0)), "Division 1", "3", list(list(commissioner = 0, name = "James C", id = "1EF701E6-AC9D-11E3-8EB7-031CFC5F1C7D", playoff_add_drops_disabled = 0)), "Division 2", "13", list(list(commissioner = 0, name = "Enrique D", id = "1F2EBB68-AC9D-11E3-8EB7-031CFC5F1C7D", playoff_add_drops_disabled = 0)), "Division 1", "5", list(list(commissioner = 0, name = "Mitch T", id = "1F00CD8E-AC9D-11E3-8EB7-031CFC5F1C7D", playoff_add_drops_disabled = 0)), "Division 2", "1", list(list(commissioner = 1, name = "Fred R", id = "1E34F182-AC9D-11E3-8EB7-031CFC5F1C7D", playoff_add_drops_disabled = 0), list(commissioner = 0, name = "Cam E", id = "E42646B8-ACA5-11E3-854D-2A588E5A61DF", playoff_add_drops_disabled = 0)), "Division 2", "12", list(list(commissioner = 0, name = "Nick D", id = "1F29D4C2-AC9D-11E3-8EB7-031CFC5F1C7D", playoff_add_drops_disabled = 0)), "Division 1", "4", list(list(commissioner = 0, name = "Liam S", id = "389BDCA0-21EC-11EA-AD4E-B4851D7BE3A7", playoff_add_drops_disabled = 0)), "Division 2", "7", list(list(commissioner = 0, name = "David E", id = "3D994500-AE62-11E5-AB74-A57DE140860F", playoff_add_drops_disabled = 0)) )

I want to extract the commissioner and name values and put them in the same level as division and id. I'd like the name column to become owner_name, and have any row that has more than one value be joined with a &. For example on the row with id = "1". owner_name would be "Fred R & Cam E".

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    What should be done with commisioner then? In the described case, commisioner of Fred R is 1 while commisioner of Cam E is 0. Commented Mar 19 at 10:13
  • I assume you want the commissioner column to be handled in the same way as the owner_name column. If not, please specify how the commissioner column should be processed. Commented Mar 19 at 10:25
  • I'd like to see the formula with and without commissioner mapped. Commented Mar 19 at 10:40
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    @Jazzmatazz "extract the commissioner and name values and put them in the same level as division and id" and "any row that has more than one value be joined with a &" is what Darren perfectly answered. How should the commisioner values be combined in one column? Commented Mar 19 at 10:44

1 Answer 1

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You can use various map functions.

library(tidyverse) df %>% mutate(map_dfc(c(commissioner = "commissioner", owner_name = "name"), ~ map_chr(map_depth(owners, 2, .x), paste, collapse = ' & ')), .keep = "unused") # # A tibble: 14 × 4 # division id commissioner owner_name # <chr> <chr> <chr> <chr> # 1 Division 2 8 0 Jesse H # 2 Division 1 15 0 Jon O # 3 Division 2 10 0 & 0 Jim K & Kevin P # 4 Division 1 14 0 & 0 Alan C & Sam L # 5 Division 1 9 0 Don R # 6 Division 1 17 0 Jason S # 7 Division 2 16 0 Eric W # 8 Division 1 3 0 James C # 9 Division 2 13 0 Enrique D # 10 Division 1 5 0 Mitch T # 11 Division 2 1 1 & 0 Fred R & Cam E # 12 Division 2 12 0 Nick D # 13 Division 1 4 0 Liam S # 14 Division 2 7 0 David E
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2 Comments

For my own knowledge.... How would the answer above change if I only wanted to map the owners column, and not commissioner?
You would just need df %>% mutate(owner_name = map_chr(owners, \(x) paste(map_chr(x, ~ .x$name), collapse = " & ")))

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