How to flatten a deeply and irregularly nested list/dataframe/JSON in R

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How to flatten a deeply and irregularly nested list/dataframe/JSON in R



I would like convert json file to dataframe (without any nested list inside a dataframe)


temp <- jsonlite::fromJSON(txt ="https://unstats.un.org/SDGAPI/v1/sdg/GeoArea/Tree")




1 Answer
1



Unnesting recursively:


library(tidyr)
library(purrr)
library(dplyr)

recursive_unnest <- function(.data)
recursive_unnest(temp)

# Observations: 489
# Variables: 16
# $ geoAreaCode <int> 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1,...
# $ geoAreaName <chr> "World", "World", "World", "World", "World", "World", "World", "Worl...
# $ type <chr> "Region", "Region", "Region", "Region", "Region", "Region", "Region"...
# $ geoAreaCode1 <int> 10, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2, 2...
# $ geoAreaName1 <chr> "Antarctica", "Africa", "Africa", "Africa", "Africa", "Africa", "Afr...
# $ type1 <chr> "Country", "Region", "Region", "Region", "Region", "Region", "Region...
# $ geoAreaCode2 <int> NA, 15, 15, 15, 15, 15, 15, 15, 202, 202, 202, 202, 202, 202, 202, 2...
# $ geoAreaName2 <chr> NA, "Northern Africa", "Northern Africa", "Northern Africa", "Northe...
# $ type2 <chr> NA, "Region", "Region", "Region", "Region", "Region", "Region", "Reg...
# $ geoAreaCode3 <int> NA, 12, 818, 434, 504, 729, 788, 732, 14, 14, 14, 14, 14, 14, 14, 14...
# $ geoAreaName3 <chr> NA, "Algeria", "Egypt", "Libya", "Morocco", "Sudan", "Tunisia", "Wes...
# $ type3 <chr> NA, "Country", "Country", "Country", "Country", "Country", "Country"...
# $ geoAreaCode4 <int> NA, NA, NA, NA, NA, NA, NA, NA, 86, 108, 174, 262, 232, 231, 260, 40...
# $ geoAreaName4 <chr> NA, NA, NA, NA, NA, NA, NA, NA, "British Indian Ocean Territory", "B...
# $ type4 <chr> NA, NA, NA, NA, NA, NA, NA, NA, "Country", "Country", "Country", "Co...
# $ children <lgl> NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, ...





I really appreciate your help, especially Recall function is my first time to hear about it. May I ask why you use .data instead of data, and .x instead of x. What is the secret behind using dot with argument? Thanks
– Mohamed
Aug 10 at 7:27






.data: no secret, it's just an arbitrary valid variable name. .x is slightly different though: in the tidyverse, typically in the map family of functions, you can pass functions as arguments, and there is a shorthand syntax for anonymous function, basically ~ .x + 1 is a replacement for function(.x) .x + 1, you can read more in help("map") for instance
– Aurèle
Aug 10 at 9:04


.data


.x


map


~ .x + 1


function(.x) .x + 1


help("map")






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