How to separate column values by condition (pivot) to fill one row

Question

I have two tables that I'd like do a full outer join where the resulting view separates the values table into two separate columns with one row for each name_id. I have made one approach with a CASE expression to select by type and then use it with pandas to fill in the values and return distinct name_ids.

Name Table

name_id	name
1	foo
2	bar
3	doo
4	sue

Values Table

name_id	value	type
1	90	red
2	95	blue
3	33	red
3	35	blue
4	60	blue
4	20	red

This is a condensed version. In my full table, I need to do this twice with two separate value tables sorted by type, red/blue and control/placebo.

Simple Join

SELECT names_table.name_id, name, value, type
FULL OUTER JOIN values_table
ON names_table.name_id = values_table.name_id
WHERE type in ('red', 'blue')

name_id	name	value	type
1	foo	90	red
2	bar	95	blue
3	doo	33	red
3	doo	35	blue
4	sue	60	blue
4	sue	20	red

Current work around result which I then fix with python and pandas

SELECT names_table.name_id, name, value, type
CASE 
    WHEN type = 'red' THEN value END red,
CASE 
    WHEN type = 'blue' THEN value END blue
FROM names_table
FULL OUTER JOIN values_table
ON names_table.name_id = values_table.name_id

name_id	name	blue	red
1	foo	Null	90
2	bar	95	Null
3	doo	35	Null
3	doo	Null	33
4	sue	60	Null
4	sue	Null	20

This is my desired output below, where I would have the types as columns and just rows for unique name_ids but with value tables 1 and 2.

Desired Output

name_id	name	blue	red
1	foo	Null	90
2	bar	95	Null
3	doo	35	33
4	sue	60	20

Answer 1

I have two tables that I'd like do a full outer join ...

Why would you? Better explain what you actually want to do instead of the assumed tool to implement it.

Simple pivoting with the aggregate FILTER clause. See:

• Aggregate columns with additional (distinct) filters

SELECT name_id, n.name, v.blue, v.red
FROM  (
   SELECT name_id
        , min(value) FILTER (WHERE type = 'blue') AS blue
        , min(value) FILTER (WHERE type = 'red')  AS red
   FROM   values_table
   GROUP  BY 1
   ) v
LEFT   JOIN names_table n USING (name_id);

Produces your desired result.

db<>fiddle here

The LEFT JOIN includes result rows even if no name is found. A FULL [OUTER] JOIN would add names in the result that have no values at all. I think you really want a LEFT [OUTER] JOIN or even a plain [INNER] JOIN.

You can just switch the JOIN type to adapt to your actual requirements. The identical column name "name_id" allows to join with a USING clause. The unqualified name_id in the outer SELECT works for any join type.

Note how I aggregate first and join later. Typically substantially faster. See:

• Query with LEFT JOIN not returning rows for count of 0

If there can be duplicate values for "red" or "blue", you'll have to define how to deal with those.

For more involved queries consider crosstab(). See:

• PostgreSQL Crosstab Query