Extracting JSON data with asymetric content from a dataframe column in R - r

Question

I loaded a table from a database which contains a column that has JSON data in each row.
The table looks something like the example below. (I was not able to replicate the data.frame I have, due to the format of the column data)
dataframe_example <- data.frame(id = c(1,2,3),
name = c("name1","name2","name3"),
JSON_col = c({"_inv": [10,20,30,40]}, "_person": ["_personid": "green"],
{"_inv": [15,22]}, "_person": ["_personid": "blue"],
{"_inv": []}, "_person": ["_personid": "red"]))
I have the following two issues:
Some of the items (e.g. "_inv") sometimes have the full 4 numeric entries, sometimes less, and sometimes nothing. Some of the other items (e.g. "_person") usually contain another header, but only one character data point.
My goal is to preserve the existing dataframes colums (such as id and name) and spread the data in the json column such that I have new columns containing each point of information. The target dataframe would look a little like this:
data.frame(id = c(1,2,3),
name = c("name1","name2","name3"),
`_inv_1` = c(10,15,NA),
`_inv_2` = c(20,22,NA),
`_inv_3` = c(30,NA,NA),
`_inv_4` = c(40,NA,NA),
`_person_id` = c("green","blue","red"))
Please bear in mind that I have very little experience handling JSON data and no experience dealing with uneven JSON data.
Using purrr I got:
frame <- purrr::map(dataframe_example$JSON_col, jsonlite::fromJSON)
This gave me a large list with n elements, where n is the length of the original dataframe. The "Name" item contains n lists [[1]], each one with its own type of object, ranging from double to data.frame. The double object contain four numeric observations, (such as _inv), some of the objects are lists themselves (such as _person), which further contains "_personid" and then a single entry. The dataframe contains the datetime stamps for each observation in the JSON data. (each _inv item has a timestamp)
Is there a way to obtain the solution above, either by extracting the data from my "frame" object, or an altogether different solution?

Answer 1

library(tidyverse)
library(jsonlite)
#>
#> Attaching package: 'jsonlite'
#> The following object is masked from 'package:purrr':
#>
#> flatten
dataframe_example <-
data.frame(
id = c(1, 2, 3),
name = c("name1", "name2", "name3"),
JSON_col = c(
"{\"_inv\": [10,20,30,40], \"_person\": {\"_personid\": \"green\"}}",
"{\"_inv\": [15,22], \"_person\": {\"_personid\": \"blue\"}}",
"{\"_inv\": [], \"_person\": {\"_personid\": \"red\"}}"
)
)
dataframe_example %>%
as_tibble() %>%
mutate(
JSON_col = JSON_col %>% map(parse_json)
) %>%
unnest_wider(JSON_col) %>%
unnest(`_inv`) %>%
unnest(`_inv`) %>%
unnest(`_person`) %>%
unnest(`_person`) %>%
group_by(id, name) %>%
mutate(inv_id = row_number()) %>%
pivot_wider(names_from = inv_id, values_from = `_inv`, names_prefix = "_inv_")
#> # A tibble: 2 x 7
#> # Groups: id, name [2]
#> id name `_person` `_inv_1` `_inv_2` `_inv_3` `_inv_4`
#> <dbl> <chr> <chr> <int> <int> <int> <int>
#> 1 1 name1 green 10 20 30 40
#> 2 2 name2 blue 15 22 NA NA
Created on 2021-11-25 by the reprex package (v2.0.1)