Postgres calculate average using distinct IDs‚ values also distinct - sql

Question

I have a postgres query that is supposed to calculate an average value based on a set of values. This set of values should be based on DISTINCT ID's.
The query is the following:
#{context.answers_base}
SELECT
stores.name as store_name,
answers_base.question_name as question_name,
answers_base.question_id as question_id,
(sum(answers_base.answer_value) / NULLIF(count(answers_base.answer_id),0)) as score, # <--- this line is calculating wrong
sum(answers_base.answer_value) as score_sum,
count(answers_base.answer_id) as question_answer_count,
count(DISTINCT answers_base.answer_id) as answer_count
FROM answers_base
INNER JOIN stores ON stores.id = answers_base.store_id
WHERE answers_base.answer_value IS NOT NULL AND answers_base.question_type_id = :question_type_id
AND answers_base.scale = TRUE
#{context.filter_answers}
GROUP BY stores.name, answers_base.question_name, answers_base.question_id, answers_base.sort_order
ORDER BY stores.name, answers_base.sort_order
The thing is, that on the indicated line (sum(answers_base.answer_value) / NULLIF(count(answers_base.answer_id),0)) some values are counted more than once.
Part of the solution is making it DISTINCT based on ID, like so:
(sum(answers_base.answer_value) / NULLIF(count(DISTINCT answers_base.answer_id),0))
This will result in an average that divided by the right number, but here the sum it's dividing is still wrong.
Doing the following (make sum() DISTINCT) does not work, for the reason that values are not unique. The values are either 0 / 25 / 50 / 75 / 100, so different IDs might contain 'same' values.
(sum(DISTINCT answers_base.answer_value) / NULLIF(count(DISTINCT answers_base.answer_id),0))
How would I go about making this work?
Here are simplified versions of the table structures.
Table Answer
ID
answer_date
1
Feb 01, 2022
2
Mar 02, 2022
3
Mar 13, 2022
4
Mar 21, 2022
Table AnswerRow
ID
answer_id
answer_value
1
1
25
2
1
50
3
1
50
4
2
75
5
2
100
6
2
0
7
3
25
8
4
25
9
4
100
10
4
50
Answer 1' answer_rows:
25 + 50 + 50 -> average = 125 / 3
Answer 2' answer_rows:
75 + 100 + 0 -> average = 175 / 3
Answer 3' answer_rows:
25 -> average = 25 / 1
Answer 4' answer_rows:
25 + 100 + 50 -> average = 175 / 3
For some reason, we get duplicate answer_rows in the calculation.
Example of the problem; for answer_id=1 we have the following answer_rows in the calculation, giving us a different average:
ID
answer_id
answer_value
1
1
25
2
1
50
3
1
50
3
1
50
3
1
50
3
1
50
Result: 25 + 50 + 50 + 50 + 50 + 50 -> 275 / 6
Desired result: 25 + 50 + 50 -> 125 / 3
Making answer_row_id distinct (see beginning of post) makes it possible for me to get:
25 + 50 + 50 + **50 + 50 + 50** -> 275 / **3**
But not
25 + 50 + 50 -> 275 / 3
What I would like to achieve is having a calculation that selects answer_row distinctly based on its ID, and those answer_rows will be used both for calculation x and y in calculation average -> x / y.
answers_base is the following (simplified):
WITH answers_base as (
SELECT
answers.id as answer_id,
answers.store_id as store_id,
answer_rows.id as answer_row_id,
question_options.answer_value as answer_value
FROM answers
INNER JOIN answer_rows ON answers.id = answer_rows.answer_id
INNER JOIN stores ON stores.id = answers.store_id
WHERE answers.status = 0
)

Answer 1

I think this would be best solved with a window function. Something along the lines of
SELECT
ROW_NUMBER() OVER (PARTITION BY answer_rows.id ORDER BY answer_rows.created_at DESC) AS duplicate_answers
...
WHERE
answer_rows.duplicate_answers = 1
This would filter out multiple rows with the same id, and only keep one entry. (I chose the "first by created_at", but you could change this to whatever logic suits you best.)
A benefit to this approach is that it makes the rationale behind the logic clear, contained and re-usable.