Converting nested JSON to data frame - r

Question

I am trying to convert a heavily nested json into a proper data frame (proper by tidy standards). An MWE of the json is copied at the end of the question, as I wanted to make sure it captured every element of the json.
I've tried:
library(jsonlite)
library(tidyverse)
dat <- jsonlite::fromJSON('data_toy.json') %>% pluck(1) %>% imap_dfr(~mutate(.x, department = .y))
but this returns:
Error: Columns `time_spent`, `school_breakdown`, `reason_for_taking_course`, `student_years`, `interest_before` must be 1d atomic vectors or lists
I've also tried:
dat <- jsonlite::fromJSON('data_toy.json', simplifyVector = FALSE,
simplifyDataFrame = FALSE, flatten=FALSE)
dat.df <- map_df(dat, ~{
flatten_df(.x[[1]]) %>%
dplyr::mutate(department = names(.x)[1])
})
but this returns:
Error in bind_rows_(x, .id) : Argument 3 must be length 1, not 0
How can I convert this to a data frame?
Data file (data_toy.json):
{
"department": {
"BME": [
{
"course_name": "BMD_ENG_250-0_20: Thermodynamics",
"instructor": "Neha Kamat",
"time_spent": {},
"school_breakdown": {
"Education & SP": 0,
"Communication": 0,
"Graduate School": 0,
"KGSM": 0
},
"reason_for_taking_course": {
"Distribution requirement": 0,
"Major/Minor requirement": 53
},
"student_years": {
"Freshman": 5,
"Sophomore": 37
},
"interest_before": {
"1-Not interested at all": 1,
"2": 5
},
"comments": [
"is amazing and you will love her!",
"Prof. is so nice"
],
"instructor_gender": "F"
},
{
"course_name": "BMD_ENG_250-0_20: Thermodynamics",
"instructor": "Neha Kamat",
"time_spent": {},
"school_breakdown": {
"Education & SP": 0,
"Communication": 0,
"Graduate School": 0,
"KGSM": 0
},
"reason_for_taking_course": {
"Distribution requirement": 0,
"Major/Minor requirement": 53
},
"student_years": {
"Freshman": 5,
"Sophomore": 37
},
"interest_before": {
"1-Not interested at all": 1,
"2": 5
},
"comments": [
"is amazing and you will love her!",
"Prof. is so nice"
],
"instructor_gender": "F"
}
],
"LING": [
{
"course_name": "BMD_ENG_250-0_20: Thermodynamics",
"instructor": "Neha Kamat",
"time_spent": {},
"school_breakdown": {
"Education & SP": 0,
"Communication": 0,
"Graduate School": 0,
"KGSM": 0
},
"reason_for_taking_course": {
"Distribution requirement": 0,
"Major/Minor requirement": 53
},
"student_years": {
"Freshman": 5,
"Sophomore": 37
},
"interest_before": {
"1-Not interested at all": 1,
"2": 5
},
"comments": [
"is amazing and you will love her!",
"Prof. is so nice"
],
"instructor_gender": "F"
},
{
"course_name": "BMD_ENG_250-0_20: Thermodynamics",
"instructor": "Neha Kamat",
"time_spent": {},
"school_breakdown": {
"Education & SP": 0,
"Communication": 0,
"Graduate School": 0,
"KGSM": 0
},
"reason_for_taking_course": {
"Distribution requirement": 0,
"Major/Minor requirement": 53
},
"student_years": {
"Freshman": 5,
"Sophomore": 37
},
"interest_before": {
"1-Not interested at all": 1,
"2": 5
},
"comments": [
"is amazing and you will love her!",
"Prof. is so nice"
],
"instructor_gender": "F"
}
]
}
}

Answer 1

Using flatten = TRUE seems to be the key here:
dat <- jsonlite::fromJSON('data_toy.json', flatten = TRUE)[[1]]
dat %>% bind_rows() %>% mutate(department = rep(names(dat), map_dbl(dat, nrow)))