Add a new row for each jsonb value pairs

Question

I have this table from were I'm running a query:

CREATE TABLE IF NOT EXISTS public.preprocess_things
(
    preprocess_id integer NOT NULL DEFAULT nextval('preprocess_things_preprocess_id_seq'::regclass),
    arrive_date date NOT NULL,
    arrive_location character varying COLLATE pg_catalog."default" NOT NULL,
    data jsonb NOT NULL,
    CONSTRAINT preprocess_things_pkey PRIMARY KEY (preprocess_id),
    CONSTRAINT preprocess_things_arrive_date_arrive_location_bo_key UNIQUE (arrive_date, arrive_location)
)

The query that I'm running is this:

SELECT DATE_TRUNC('month', arrive_date) AS grouped_date,
  LOWER(arrive_location) AS location,
  json_build_object(
    '1', SUM((data->'1')::int),
    '2', SUM((data->'2')::int),
    '3', SUM((data->'3')::int),
    '4', SUM((data->'4')::int),
    '5', SUM((data->'5')::int)
    ) AS data
FROM preprocess_things
GROUP BY grouped_date,
  location

The current result is:

grouped_date	location	data
2018-06-01 00:00:00	location_00	{"1" : 1, "2" : null, "3" : null, "4" : 1, "5" : 8}
2018-05-01 00:00:00	location_00	{"1" : null, "2" : 9, "3" : 10, "4" : 8, "5" : 3}

I would like to apply another SELECT, that adds a row for each value pair that does not have a null value, where the key goes to the thing_type column and the value goes to the total column; like this:

grouped_date	location	thing_type	total
2018-06-01 00:00:00	location_00	1	1
2018-06-01 00:00:00	location_00	4	1
2018-06-01 00:00:00	location_00	5	8
2018-05-01 00:00:00	location_00	2	9
2018-05-01 00:00:00	location_00	3	10
2018-05-01 00:00:00	location_00	4	8
2018-05-01 00:00:00	location_00	5	3

The fiddle db can be found here.

UPDATE:

Thanks to @Gerard H. Pille, I tweak a little bit he's response to this:

SELECT
  DATE_TRUNC('month', arrive_date) AS grouped_date,
  LOWER(arrive_location) AS location,
  x.key::int thing_type, sum(x.value::int) total
FROM preprocess_things
JOIN  jsonb_each(data) x ON (x.key::int = ANY('{1,2,3}'::int[]))
GROUP BY grouped_date,  location, x.key::int
ORDER BY grouped_date,  location, x.key::int;

Since there are some cases were I just need a selection of the thing_type and not all of them to be calculated, the only problem is by adding the JOIN and compare the query speed is not that good.

Answer 1

SELECT
  DATE_TRUNC('month', arrive_date) AS grouped_date,
  LOWER(arrive_location) AS location,
  x.key::int  thing_type, sum(x.value::int) total
    FROM preprocess_things,
         jsonb_each(data) x
  GROUP BY grouped_date,  location, x.key::int
  order by grouped_date,  location, x.key::int;

see db<>fiddle