Grouping by similar values in multiple columns - sql

Question

I have a table of entities with an id, and a category (few different values with NULL allowed) from 3 different years (category can be different from 1 year to another), in 'wide' table format:
| ID | CATEG_Y1 | CATEG_Y2 | CATEG_Y3 |
+-----+----------+----------+----------+
| 1 | NULL | B | C |
| 2 | A | A | C |
| 3 | B | A | NULL |
| 4 | A | C | B |
| ... | ... | ... | ... |
I would like to simply count the number of entities by category, grouped by category, independently for the year:
+-------+----+----+----+
| CATEG | Y1 | Y2 | Y3 |
+-------+----+----+----+
| A | 6 | 4 | 5 | <- 6 entities w/ categ_y1, 4 w/ categ_y2, 5 w/ categ_y3
| B | 3 | 1 | 10 |
| C | 8 | 4 | 5 |
| NULL | 3 | 3 | 3 |
+-------+----+----+----+
I guess I could do it by grouping values one column after the other and UNION ALL the results, but I was wondering if there was a more rapid & convenient way, and if it can be generalized if I have more columns/years to manage (e.g. 20-30 different values)

Answer 1

A bit clumsy, but probably someone has a better idea. Query first collects all diferent categories (the union-query in the from part), and then counts the occurences with dedicated subqueries in the select part. One could omit the union-part if there is a table already defining the available categories (I suppose categ_y1 is a foreign key to such a primary category table). Hope there are not to many typos:
select categories.cat,
(select count(categ_y1) from table ty1 where select categories.cat = categ_y1) as y1,
(select count(categ_y2) from table ty2 where select categories.cat = categ_y2) as y2,
(select count(categ_y3) from table ty3 where select categories.cat = categ_y3) as y3
from ( select categ_y1 as cat from table t1
union select categ_y2 as cat from table t2
union select categ_y3 as cat from table t3) categories

Answer 2

Use jsonb functions to transpose the data (from the question) to this format:
select categ, jsonb_object_agg(key, count) as jdata
from (
select value as categ, key, count(*)
from my_table t,
jsonb_each_text(to_jsonb(t)- 'id')
group by 1, 2
) s
group by 1
order by 1;
categ | jdata
-------+-----------------------------------------------
A | {"categ_y1": 2, "categ_y2": 2}
B | {"categ_y1": 1, "categ_y2": 1, "categ_y3": 1}
C | {"categ_y2": 1, "categ_y3": 2}
| {"categ_y1": 1, "categ_y3": 1}
(4 rows)
For a known (static) number of years you can easily unpack the jsonb column:
select categ, jdata->'categ_y1' as y1, jdata->'categ_y2' as y2, jdata->'categ_y3' as y3
from (
select categ, jsonb_object_agg(key, count) as jdata
from (
select value as categ, key, count(*)
from my_table t,
jsonb_each_text(to_jsonb(t)- 'id')
group by 1, 2
) s
group by 1
) s
order by 1;
categ | y1 | y2 | y3
-------+----+----+----
A | 2 | 2 |
B | 1 | 1 | 1
C | | 1 | 2
| 1 | | 1
(4 rows)
To get fully dynamic solution you can use the function create_jsonb_flat_view() described in Flatten aggregated key/value pairs from a JSONB field.

Answer 3

I would do this as using union all followed by aggregation:
select categ, sum(categ_y1) as y1, sum(categ_y2) as y2,
sum(categ_y3) as y3
from ((select categ_y1, 1 as categ_y1, 0 as categ_y2, 0 as categ_y3
from t
) union all
(select categ_y2, 0 as categ_y1, 1 as categ_y2, 0 as categ_y3
from t
) union all
(select categ_y3, 0 as categ_y1, 0 as categ_y2, 1 as categ_y3
from t
)
)
group by categ ;