Best way to parse a big and intricated Json file with OpenRefine (or R)

Question

I know how to parse json cells in Open refine, but this one is too tricky for me.

I've used an API to extract the calendar of 4730 AirBNB's rooms, identified by their IDs.

Here is an example of one Json file : https://fr.airbnb.com/api/v2/calendar_months?key=d306zoyjsyarp7ifhu67rjxn52tv0t20&currency=EUR&locale=fr&listing_id=4212133&month=11&year=2016&count=12&_format=with_conditions

For each ID and each day of the year from now until november 2017, i would like to extract the availability of this rooms (true or false) and its price at this day.

I can't figure out how to parse out these informations. I guess that it implies a series of nested forEach, but i can't find the right way to do this with Open Refine.

I've tried, of course,

forEach(value.parseJson().calendar_months, e, e.days) 

The result is an array of arrays of dictionnaries that disrupts me.

Any help would be appreciate. If the operation is too difficult in Open Refine, a solution with R (or Python) would also be fine for me.

Answer 1

Rather than just creating your Project as text, and working with GREL to parse out...

The best way is just select the JSON record part that you want to work with using our visual importer wizard for JSON files and XML files (you can even use a URL pointing to a JSON file as in your example). (A video tutorial shows how here: https://www.youtube.com/watch?v=vUxdB-nl0Bw )

1. Select the JSON part that contains your records that you want to parse and work with (this can be any repeating part, just select one of them and OpenRefine will extract all the rest)

2. Limit the amount of data rows that you want to load in during creation, or leave default of all rows.

3. Click Create Project and now your in Rows mode. However if you think that Records mode might be better suited for context, just import the project again as JSON and then select the next outside area of the content, perhaps a larger array that contains a key field, etc. In the example, the key field would probably be the Date, and why I highlight the whole record for a given date. This way OpenRefine will have Keys for each record and Records mode lets you work with them better than Row mode.

Feel free to take this example and make it better and even more helpful for all , add it to our Wiki section on How to Use

Answer 2

I think you are on the right track. The output of:

forEach(value.parseJson().calendar_months, e, e.days) 

is hard to read because OpenRefine and JSON both use square brackets to indicate arrays. What you are getting from this expression is an OR array containing twelve items (one for each month of the year). The items in the OR array are JSON - each one an array of days in the month.

To keep the steps manageable I'd suggest tackling it like this:

First use

forEach(value.parseJson().calendar_months,m,m.days).join("|")

You have to use 'join' because OR can't store OR arrays directly in a cell - it has to be a string.

Then use "Edit Cells->Split multi-valued cells" - this will get you 12 rows per ID, each containing a JSON expression. Now for each ID you have 12 rows in OR

Then use:

forEach(value.parseJson(),d,d).join("|")

This splits the JSON down into the individual days

Then use "Edit Cells->Split multi-valued cells" again to split the details for each day into its own cell.

Using the JSON from example URL above - this gives me 441 rows for the single ID - each contains the JSON describing the availability & price for a single day. At this point you can use the 'fill down' function on the ID column to fill in the ID for each of the rows.

You've now got some pretty easy JSON in each cell - so you can extract availability using

value.parseJson().available

etc.