Dynamic column names in view (Postgres) - sql

Question

I am currently programming an SQL view which should provide a count of a populated field for a particular month.
This is how I would like the view to be constructed:
Country | (Current Month - 12) Eg Feb 2011 | (Current Month - 11) | (Current Month - 10)
----------|----------------------------------|----------------------|---------------------
UK | 10 | 11 | 23
The number under the month should be a count of all populated fields for a particular country. The field is named eldate and is a date (cast as a char) of format 10-12-2011. I want the count to only count dates which match the month.
So column "Current Month - 12" should only include a count of dates which fall within the month which is 12 months before now. Eg Current Month - 12 for UK should include a count of dates which fall within February-2011.
I would like the column headings to actually reflect the month it is looking at so:
Country | Feb 2011 | March 2011 | April 2011
--------|----------|------------|------------
UK | 4 | 12 | 0
So something like:
SELECT c.country_name,
(SELECT COUNT("C1".eldate) FROM "C1" WHERE "C1".eldate LIKE %NOW()-12 Months% AS NOW() - 12 Months
(SELECT COUNT("C1".eldate) FROM "C1" WHERE "C1".eldate LIKE %NOW()-11 Months% AS NOW() - 11 Months
FROM country AS c
INNER JOIN "site" AS s using (country_id)
INNER JOIN "subject_C1" AS "C1" ON "s"."site_id" = "C1"."site_id"
Obviously this doesn't work but just to give you an idea of what I am getting at.
Any ideas?
Thank you for your help, any more queries please ask.

Answer 1

My first inclination is to produce this table:
+---------+-------+--------+
| Country | Month | Amount |
+---------+-------+--------+
| UK | Jan | 4 |
+---------+-------+--------+
| UK | Feb | 12 |
+---------+-------+--------+
etc. and pivot it. So you'd start with (for example):
SELECT
c.country,
EXTRACT(MONTH FROM s.eldate) AS month,
COUNT(*) AS amount
FROM country AS c
JOIN site AS s ON s.country_id = c.id
WHERE
s.eldate > NOW() - INTERVAL '1 year'
GROUP BY c.country, EXTRACT(MONTH FROM s.eldate);
You could then plug that into one the crosstab functions from the tablefunc module to achieve the pivot, doing something like this:
SELECT *
FROM crosstab('<query from above goes here>')
AS ct(country varchar, january integer, february integer, ... december integer);

Answer 2

You could truncate the dates to make the comparable:
WHERE date_trunc('month', eldate) = date_trunc('month', now()) - interval '12 months'
UPDATE
This kind of replacement for your query:
(SELECT COUNT("C1".eldate) FROM "C1" WHERE date_trunc('month', "C1".eldate) =
date_trunc('month', now()) - interval '12 months') AS TWELVE_MONTHS_AGO
But that would involve a scan of the table for each month, so you could do a single scan with something more along these lines:
SELECT SUM( CASE WHEN date_trunc('month', "C1".eldate) = date_trunc('month', now()) - interval '12 months' THEN 1 ELSE 0 END ) AS TWELVE_MONTHS_AGO
,SUM( CASE WHEN date_trunc('month', "C1".eldate) = date_trunc('month', now()) - interval '11 months' THEN 1 ELSE 0 END ) AS ELEVEN_MONTHS_AGO
...
or do a join with a table of months as others are showing.
UPDATE2
Further to the comment on fixing the columns from Jan to Dec, I was thinking something like this: filter on the last years worth of records, then sum on the appropriate month. Perhaps like this:
SELECT SUM( CASE WHEN EXTRACT(MONTH FROM "C1".eldate) = 1 THEN 1 ELSE 0 END ) AS JAN
,SUM( CASE WHEN EXTRACT(MONTH FROM "C1".eldate) = 2 THEN 1 ELSE 0 END ) AS FEB
...
WHERE date_trunc('month', "C1".eldate) < date_trunc('month', now())
AND date_trunc('month', "C1".eldate) >= date_trunc('month', now()) - interval '12 months'