Background
Forgive the title of this question, as I'm not really sure how to describe what I'm trying to do.
I have a SQL table, d, that looks like this:
+--+---+------------+------------+
|id|sex|event_type_1|event_type_2|
+--+---+------------+------------+
|a |m |1 |1 |
|b |f |0 |1 |
|c |f |1 |0 |
|d |m |0 |1 |
+--+---+------------+------------+
The Problem
I'm trying to write a query that yields the following summary of counts of event_type_1 and event_type_2 cut (grouped?) by sex:
+-------------+-----+-----+
| | m | f |
+-------------+-----+-----+
|event_type_1 | 1 | 1 |
+-------------+-----+-----+
|event_type_2 | 2 | 1 |
+-------------+-----+-----+
The thing is, this seems to involve some kind of transposition of the 2 event_type columns into rows of the query result that I'm not familiar with as a novice SQL user.
What I've tried
I've so far come up with the following query:
SELECT event_type_1, event_type_2, count(sex)
FROM d
group by event_type_1, event_type_2
But that only gives me this:
+------------+------------+-----+
|event_type_1|event_type_2|count|
+------------+------------+-----+
|1 |1 |1 |
|1 |0 |1 |
|0 |1 |2 |
+------------+------------+-----+
You can use a lateral join to unpivot the data. Then use conditional aggregate to calculate m and f:
select v.which,
count(*) filter (where d.sex = 'm') as m,
count(*) filter (where d.sex = 'f') as f
from d cross join lateral
(values (d.event_type_1, 'event_type_1'),
(d.event_type_2, 'event_type_2')
) v(val, which)
where v.val = 1
group by v.which;
Here is a db<>fiddle.
Related
Background
I'm a novice Postgres user running a local server on a Windows 10 machine. I've got a dataset g that looks like this:
+--+---------+----------------+
|id|treatment|outcome_category|
+--+---------+----------------+
|a |1 |cardiovascular |
|a |0 |cardiovascular |
|b |0 |metabolic |
|b |0 |sensory |
|c |1 |NULL |
|c |0 |cardiovascular |
|c |1 |sensory |
|d |1 |NULL |
|d |0 |cns |
+--+---------+----------------+
The Problem
I'd like to get a count of outcome_category by outcome_category for those id who are "ever treated" -- defined as "id's who have any row where treatment=1".
Here's the desired result:
+----------------+---------+
|outcome_category| count |
+----------------+---------+
|cardiovascular | 3 |
|sensory | 1 |
|cns | 1 |
+----------------+---------+
It would be fine if the result had to contain metabolic, like so:
+----------------+---------+
|outcome_category|treatment|
+----------------+---------+
|cardiovascular | 3 |
|metabolic | 0 |
|sensory | 1 |
|cns | 1 |
+----------------+---------+
Obviously I don't need the rows to be in any particular order, though descending would be nice.
What I've tried
Here's a query I've written:
select treatment, outcome_category, sum(outcome_ct)
from (select max(treatment) as treatment,
outcome_category,
count(outcome_category) as outcome_ct
from g
group by outcome_category) as sub
group by outcome_category, sub.treatment;
But it's a mishmash result:
+---------+----------------+---+
|treatment|outcome_category|sum|
+---------+----------------+---+
|1 |cardiovascular |3 |
|1 |sensory |2 |
|0 |metabolic |1 |
|1 |NULL |0 |
|0 |cns |1 |
+---------+----------------+---+
I'm trying to identify the "ever exposed" id's using that first line in the subquery: select max(treatment) as treatment. But I'm not quite getting at the rest of it.
EDIT
I realized that the toy dataset g I originally gave you above doesn't correspond to the idiosyncrasies of my real dataset. I've updated g to reflect that many id's who are "ever treated" won't have a non-null outcome_category next to a row with treatment=1.
Interesting little problem. You can do:
select
outcome_category,
count(x.id) as count
from g
left join (
select distinct id from g where treatment = 1
) x on x.id = g.id
where outcome_category is not null
group by outcome_category
order by count desc
Result:
outcome_category count
----------------- -----
cardiovascular 3
sensory 1
cns 1
metabolic 0
See running example at db<>fiddle.
This would appear to be just a simple aggregation,
select outcome_category, Count(*) count
from t
where treatment=1
group by outcome_category
order by Count(*) desc
Demo fiddle
Background
I'm a novice SQL user. Using PostgreSQL 13 on Windows 10 locally, I have a table t:
+--+---------+-------+
|id|treatment|outcome|
+--+---------+-------+
|a |1 |0 |
|a |1 |1 |
|b |0 |1 |
|c |1 |0 |
|c |0 |1 |
|c |1 |1 |
+--+---------+-------+
The Problem
I didn't explain myself well initially, so I've rewritten the goal.
Desired result:
+-----------------------+-----+
|ever treated |count|
+-----------------------+-----+
|0 |1 |
|1 |3 |
+-----------------------+-----+
First, identify id that have ever been treated. Being "ever treated" means having any row with treatment = 1.
Second, count rows with outcome = 1 for each of those two groups. From my original table, the ids who are "ever treated" have a total of 3 outcome = 1, and the "never treated", so to speak, have 1 `outcome = 1.
What I've tried
I can get much of the way there, I think, with something like this:
select treatment, count(outcome)
from t
group by treatment;
But that only gets me this result:
+---------+-----+
|treatment|count|
+---------+-----+
|0 |2 |
|1 |4 |
+---------+-----+
For the updated question:
SELECT ever_treated, sum(outcome_ct) AS count
FROM (
SELECT id
, max(treatment) AS ever_treated
, count(*) FILTER (WHERE outcome = 1) AS outcome_ct
FROM t
GROUP BY 1
) sub
GROUP BY 1;
ever_treated | count
--------------+-------
0 | 1
1 | 3
db<>fiddle here
Read:
For those who got no treatment at all (all treatment = 0), we see 1 x outcome = 1.
For those who got any treatment (at least one treatment = 1), we see 3 x outcome = 1.
Would be simpler and faster with proper boolean values instead of integer.
(Answer to updated question)
here is an easy to follow subquery logic that works with integer:
select subq.ever_treated, sum(subq.count) as count
from (select id, max(treatment) as ever_treated, count(*) as count
from t where outcome = 1
group by id) as subq
group by subq.ever_treated;
I got a table looking like this
+-----+---------+
|Group|Value |
+-----+---------+
|A |1 |
+-----+---------+
|B |2 |
+-----+---------+
|C |1 |
+-----+---------+
|D |3 |
+-----+---------+
And I would like to add a column in my select command that count GROUP based on value, lookin like this:
+-----+---------+---------+
|Group|Value | COUNT |
+-----+---------+---------+
|A |1 |2 |
+-----+---------+---------+
|B |2 |1 |
+-----+---------+---------+
|C |1 |2 |
+-----+---------+---------+
|D |3 |1 |
+-----+---------+---------+
Value 1 got the two groups A and C the other values for each one in this example.
Additional is it possible to consider all values for VALUES and GROUP even if a WHERE filtered out some of them in the select query?
You want a window function:
select t.*, count(*) over (partition by value) as count
from t;
You have a problem if the query has a where clause. The where applies to the window function. So you need a subquery for the count:
select t.*
from (select t.*, count(*) over (partition by value) as count
from t
) t
where . . .;
Or a correlated subquery might be convenient under some circumstances:
select t.*,
(select count(*) from t t2 where t2.value = t.value) as count
from t
where . . .;
I have a doubt on a SQL query:
I have the following result from a query:
select distinct eb.event_type_id, eb.status from eid.event_backlog eb order by 1
|event_type_id|status |
|-------------|----------|
|1 |SUCCESS |
|2 |SUCCESS |
|2 |ERROR |
|3 |SUCCESS |
|3 |ERROR |
|4 |SUCCESS |
i would like to obtain this result doing a distinct on the status:
|event_type_id|count |
|-------------|-------|
|1 |1 |
|2 |2 |
|3 |2 |
|4 |1 |
but the only way that I see to obtain this result is doing the following query:
select
eb.event_type_id,
count(1)
from
(
select
distinct eb.event_type_id, eb.status
from
eid.event_backlog eb
order by
1) eb
group by
eb.event_type_id
I don't like to use an nestled query, there is another way to obtain what i want?
Simply count(distinct eb.status), i.e.
select
eb.event_type_id,
count(distinct eb.status)
from eid.event_backlog eb
group by
eb.event_type_id
I need to get the min and max score of group ids, but only if they are enabled:
cdu_group_sl: cdu_group_cc: cdu_group_ph:
-------------------- -------------------- --------------------
|id |name |enabled | |id |name |enabled | |id |name |enabled |
-------------------- -------------------- --------------------
|1 |sl_1 |1 | |1 |cc_1 |1 | |1 |ph_1 |0 |
|2 |sl_3 |1 | |2 |cc_2 |0 | |2 |ph_2 |1 |
|3 |sl_4 |1 | |3 |cc_3 |1 | |3 |ph_3 |1 |
-------------------- -------------------- --------------------
Scores are found in a separate table:
cdu_user_progress
----------------------------------
|id |group_type |group_id |score |
----------------------------------
|1 |sl |1 |50 |
|1 |cc |1 |10 |
|1 |ph |1 |20 |
|1 |sl |2 |80 |
|1 |sl |3 |20 |
|1 |cc |3 |30 |
|1 |sl |1 |40 |
|1 |ph |1 |50 |
|1 |cc |1 |40 |
|1 |ph |2 |90 |
----------------------------------
I need to get a max and min score for each type of group for only enabled groups (for each type):
---------------------------------------------
|group_type |group_id |min_score |max_score |
---------------------------------------------
|sl |1 |40 |50 |
|sl |2 |80 |80 |
|sl |3 |20 |20 |
|cc |1 |10 |40 |
|cc |3 |30 |30 |
|ph |1 |20 |50 |
|ph |2 |90 |90 |
---------------------------------------------
Any idea what the query might be??? So far I have:
SELECT * FROM cdu_user_progress
JOIN cdu_group_sl ON (cdu_group_sl.id = cdu_user_progress.group_id AND cdu_user_progress.group_type = 'sl')
JOIN cdu_group_cc ON (cdu_group_cc.id = cdu_user_progress.group_id AND cdu_user_progress.group_type = 'cc')
JOIN cdu_group_ph ON (cdu_group_ph.id = cdu_user_progress.group_id AND cdu_user_progress.group_type = 'ph')
WHERE cdu_user_progress.uid = $student->uid
AND (cdu_user_progress.group_type = 'sl' AND cdu_group_sl.enabled = 1)
AND (cdu_user_progress.group_type = 'cc' AND cdu_group_cc.enabled = 1)
AND (cdu_user_progress.group_type = 'ph' AND cdu_group_ph.enabled = 1)
Probably completely wrong...
what about using a union to pick the groups you are interested in - something like:
select group_type, group_id min(score) min_score, max(score) max_score
from (
select id, 'sl' grp from cdu_group_sl where enabled = 1
union all
select id, 'cc' from cdu_group_cc where enabled = 1
union all
select id, 'ph' from cdu_group_ph where enabled = 1
) grps join cdu_user_progress scr
on grps.id = scr.group_id and grps.grp = scr.group_type
group by scr.group_type, scr.group_id
The following is probably the fastest way to do this query. To optimize this, you should have an index on group_id, enabled on each of the three "sl", "cc", and "ph" tables:
select cup.*
from cdu_user_progress cup
where (cup.group_type = 'sl' and
exists (select 1
from cdu_group_sl sl
where sl.id = cup.group_id and
sl.enabled = 1
)
) or
(cup.group_type = 'cc' and
exists (select 1
from cdu_group_cc cc
where cc.id = cup.group_id and
cc.enabled = 1
)
) or
(cup.group_type = 'ph' and
exists (select 1
from cdu_group_ph ph
where ph.id = cup.group_id and
ph.enabled = 1
)
)
As a note, having three tables with the same structure is usually a sign of a poor database schema. These three tables should probably be combined into a single table, which would make this query much easier to write.
If you are just starting up this project, I would recommend refining your data structure. Based on what you showed, you could benefit from only one cdu_groups table with a reference to a new cdu_group_types table, and removing the group_type column from cdu_user_progress.
If this is an established project, where changing the structure would be too disruptive... then one of the other answers showing a query would be a better/easier fit.
Otherwise, you could simplify things with restructured tables and end up with a query like:
SELECT group_type,
group_id,
MIN(score) as min_score,
MAX(score) as max_score
FROM cdu_user_progress c
INNER JOIN cdu_groups g
ON c.group_id=g.id
INNER JOIN cdu_group_types t
ON g.group_type_id=t.id
WHERE enabled=1
GROUP BY group_type, group_id
This is shown, with expected results, in this SQLFiddle. With this structure you can add new group types as you want (and also cut down on amount of tables and joins). Tables would be (simplified in this code below, no FKs or anything):
CREATE TABLE cdu_user_progress
(id INT, group_id INT, score INT)
CREATE TABLE cdu_group_types
(id INT, group_type VARCHAR(3))
CREATE TABLE cdu_groups
(id INT, group_type_id INT, name VARCHAR(10), enabled BIT NOT NULL DEFAULT 1)
Granted moving data to a new structure may be a pain or not reasonable... but wanted to throw this out there as a possibility or just something to chew on.