Handling nested JSON data in R for API responses - best practices and tips
I'm collaborating on a project where I can't seem to get I'm confused about I've been struggling with this for a few days now and could really use some help..... Currently developing a Shiny application that interacts with an external API returning nested JSON data, and I'm finding the data manipulation in R a bit challenging. The JSON response looks something like this: ```json { "results": [ { "id": 1, "name": "Item A", "details": { "description": "Description of Item A", "price": 10.5 } }, { "id": 2, "name": "Item B", "details": { "description": "Description of Item B", "price": 20.0 } } ] } ``` To extract the relevant fields like `id`, `name`, and `price`, I initially tried using `jsonlite::fromJSON()`, but it returns a rather complex structure. Here's what I attempted: ```r library(jsonlite) api_response <- fromJSON("http://api.example.com/data") ``` After this, I ended up with a list instead of a tidy data frame. I used `dplyr::bind_rows()` but faced trouble flattening the nested `details` object. My next thought was to manually create a data frame, which felt inefficient. Here's the attempt: ```r results_df <- data.frame( id = api_response$results$id, name = api_response$results$name, price = sapply(api_response$results$details, function(x) x$price) ) ``` While this works, it seems a bit cumbersome. At this stage, I wish to know if there’s a more elegant solution to directly access the nested fields or a recommended approach for dealing with such scenarios in R. Are there any packages or functions that could simplify this process, especially for larger datasets? Alternatively, how can I structure my code to ensure better performance with larger JSON responses? Has anyone else encountered this? I'm coming from a different tech stack and learning R. Thanks for taking the time to read this! Any help would be greatly appreciated! For context: I'm using R on Windows 10. Thanks, I really appreciate it!