I have a postgres query like this
select application.status as status, count(*) as "current_month" from application
where to_char(application.created, 'mon') = to_char('now'::timestamp - '1 month'::interval, 'mon')
and date_part('year',application.created) = date_part('year', CURRENT_DATE)
and application.job_status != 'expired'
group by application.status
it returns the table below that has the number of applications grouped by status for the current month. However I want to subtract a total count of a seperate but related query from the internal review number only. I want to count the number of rows with type = abc within the same table and for the same date range and then subtract that amount from the internal review number (Type is a seperate field). Current_month_desired is how it should look.
status
current_month
current_month_desired
fail
22
22
internal_review
95
22
pass
146
146
UNTESTED: but maybe...
The intent here is to use an analytic and case expression to conditionally sum. This way, the subtraction is not needed in the first place as you are only "counting" the values needed.
SELECT application.status as status
, sum(case when type = 'abc'
and application.status ='internal_review' then 0
else 1 end) over (partition by application.status)) as
"current_month"
FROM application
WHERE to_char(application.created, 'mon') = to_char('now'::timestamp - '1 month'::interval, 'mon')
and date_part('year',application.created) = date_part('year', CURRENT_DATE)
and application.job_status != 'expired'
GROUP BY application.status
Related
I have a dataset of sales. To summarize, the structure is
client_id
date_purchase
There might be several purchases done by the same customer on different dates. There can also be several purchases done on the same date (by different or the same customer).
My goal is to get the number of customers, for any given day, that made 2 or more purchases between that day and 90 days prior.
That is, the expected output is
date_purchase
number_of_customers
2022-12-19
200
2022-12-18
194
(...)
Please note this calculates, for any given date, the number of customer with 2+ purchases between that date and 90 days prior.
I know it has something to do with a window function. But so far I have not found a way to calculate, for every window of 90 days, how many customers have done 2+ purchases.
I've tried several window functions with no success:
partition by date_purchase
range between interval '90 days' preceding and current row
So far I can't get to calculate correctly the number for each date.
Window function doesn't seem to be relevant here because there is no relationship between the rows of the same window. A simple query or a self-join query should provide the expected result.
Assuming that client_id and date_purchase are two columns of my_table :
1. Query for a given date reference_date :
SELECT a.reference_date AS date_purchase, count(*) AS number_of_customers
FROM ( SELECT reference_date , client_id
FROM my_table
WHERE date_purchase <= reference_date AND date_purchase >= reference_date - INTERVAL '90 days'
GROUP BY client_id
HAVING count(*) >= 2
) AS a
2. Query for a given interval of dates reference_date => reference_date + INTERVAL '20 days' :
SELECT a.date AS date_purchase, count(*) AS number_of_customers
FROM ( SELECT ref.date, t.client_id
FROM my_table AS t
INNER JOIN generate_series(reference_date, reference_date + INTERVAL '20 days', '1 day') AS ref(date)
ON t.date_purchase <= ref.date AND t.date_purchase >= ref.date - INTERVAL '90 days'
GROUP BY ref.date, t.client_id
HAVING count(*) >= 2
) AS a
GROUP BY a.date
ORDER BY a.date
3. Query for all the date_purchase in mytable :
SELECT a.date AS date_purchase, count(*) AS number_of_customers
FROM ( SELECT ref.date, t.client_id
FROM my_table AS t
INNER JOIN (SELECT DISTINCT date_purchase AS date FROM my_table) AS ref
ON t.date_purchase <= ref.date AND t.date_purchase >= ref.date - INTERVAL '90 days'
GROUP BY ref.date, t.client_id
HAVING count(*) >= 2
) AS a
GROUP BY a.date
ORDER BY a.date
I tried this but it said that ERROR: subquery must return only one column
Select date_trunc('week', kyc.kyc_verify_date::timestamptz) as "week",
COUNT(*) filter (where kyc.status = 4) AS "A1",
COUNT(CASE WHEN kyc.status = 5
THEN
(Select date_trunc('week', kyc.last_update_time::timestamptz) AS "week",
count(*) filter (where kyc.status = 5)
From kyc
Group by 1)
END) AS "A2"
from KYC
Where kyc.kyc_verify_date >= date_trunc('week', CURRENT_TIMESTAMP - interval '4 week')
and kyc.kyc_verify_date < date_trunc('week', CURRENT_TIMESTAMP)
Group by 1
i do this query to get the result that if status = 4 will take the date is kyc_verify_date,
but if status = 5 will take the date is last_update_time
What should I have to change in this query? or is there any way better?
A case expression returns a single value. Since you need 2 values from it you will need to repeat the expression.
I'm currently writing an application which shows the growth of the total number of events in my table over time, I currently have the following query to do this:
query = session.query(
count(Event.id).label('count'),
extract('year', Event.date).label('year'),
extract('month', Event.date).label('month')
).filter(
Event.date.isnot(None)
).group_by('year', 'month').all()
This results in the following output:
Count
Year
Month
100
2021
1
50
2021
2
75
2021
3
While this is okay on it's own, I want it to display the total number over time, so not just the number of events that month, so the desired outpout should be:
Count
Year
Month
100
2021
1
150
2021
2
225
2021
3
I read on various places I should use a window function using SqlAlchemy's over function, however I can't seem to wrap my head around it and every time I try using it I get the following error:
sqlalchemy.exc.ProgrammingError: (psycopg2.errors.GroupingError) column "event.id" must appear in the GROUP BY clause or be used in an aggregate function
LINE 1: SELECT count(event.id) OVER (PARTITION BY event.date ORDER...
^
[SQL: SELECT count(event.id) OVER (PARTITION BY event.date ORDER BY EXTRACT(year FROM event.date), EXTRACT(month FROM event.date)) AS count, EXTRACT(year FROM event.date) AS year, EXTRACT(month FROM event.date) AS month
FROM event
WHERE event.date IS NOT NULL GROUP BY year, month]
This is the query I used:
session.query(
count(Event.id).over(
order_by=(
extract('year', Event.date),
extract('month', Event.date)
),
partition_by=Event.date
).label('count'),
extract('year', Event.date).label('year'),
extract('month', Event.date).label('month')
).filter(
Event.date.isnot(None)
).group_by('year', 'month').all()
Could someone show me what I'm doing wrong? I've been searching for hours but can't figure out how to get the desired output as adding event.id in the group by would stop my rows from getting grouped by month and year
The final query I ended up using:
query = session.query(
extract('year', Event.date).label('year'),
extract('month', Event.date).label('month'),
func.sum(func.count(Event.id)).over(order_by=(
extract('year', Event.date),
extract('month', Event.date)
)).label('count'),
).filter(
Event.date.isnot(None)
).group_by('year', 'month')
I'm not 100% sure what you want, but I'm assuming you want the number of events up to that month for each month. You're going to first need to calculate the # of events per month and also sum them with the postgresql window function.
You can do that with in a single select statement:
SELECT extract(year FROM events.date) AS year
, extract(month FROM events.date) AS month
, SUM(COUNT(events.id)) OVER(ORDER BY extract(year FROM events.date), extract(month FROM events.date)) AS total_so_far
FROM events
GROUP BY 1,2
but it might be easier to think about if you split it into two:
SELECT year, month, SUM(events_count) OVER(ORDER BY year, month)
FROM (
SELECT extract(year FROM events.date) AS year
, extract(month FROM events.date) AS month
, COUNT(events.id) AS events_count
FROM events
GROUP BY 1,2
)
but not sure how to do that in SqlAlchemy
I'm having some major issues with the following query formation:
I have projects with start and end dates
Name Start End
---------------------------------------
Project 1 2020-08-01 2020-09-10
Project 2 2020-01-01 2025-01-01
and I'm trying to count the monthly working days within each project with the following subquery
select datetrunc('month', days) as d_month, count(days) as d_count
from generate_series(greatest('2020-08-01'::date, p.start), least('2020-09-14'::date, p.end), '1 day'::interval) days
where extract(DOW from days) not IN (0, 6)
group by d_month
where p.start is from the aliased main query and the dates are hard-coded for now, this correctly gives me the following result:
{"d_month"=>2020-08-01 00:00:00 +0000, "d_count"=>21}
{"d_month"=>2020-09-01 00:00:00 +0000, "d_count"=>10}
However subqueries can't return multiple values. The date range for the query is dynamic, so I would either need to somehow return the query as:
Name Start End 2020-08-01 2020-09-01 ...
-------------------------------------------------------------------------
Project 1 2020-08-01 2020-09-10 21 8
Project 2 2020-01-01 2025-01-01 21 10
Or simply return the whole subquery as JSON, but it doesn't seem to working either.
Any idea on how to achieve this or whether there are simpler solutions for this?
The most correct solution would be to create an actual calendar table that holds every possible day of interest to your business and, at a minimum for your purpose here, marks work days.
Ideally you would have columns to hold fiscal quarters, periods, and weeks to match your industry. You would also mark holidays. Joining to this table makes these kinds of calculations a snap.
create table calendar (
ddate date not null primary key,
is_work_day boolean default true
);
insert into calendar
select ts::date as ddate,
extract(dow from ts) not in (0,6) as is_work_day
from generate_series(
'2000-01-01'::timestamp,
'2099-12-31'::timestamp,
interval '1 day'
) as gs(ts);
Assuming a calendar table is not within scope, you can do this:
with bounds as (
select min(start) as first_start, max("end") as last_end
from my_projects
), cal as (
select ts::date as ddate,
extract(dow from ts) not in (0,6) as is_work_day
from bounds
cross join generate_series(
first_start,
last_end,
interval '1 day'
) as gs(ts)
), bymonth as (
select p.name, p.start, p.end,
date_trunc('month', c.ddate) as month_start,
count(*) as work_days
from my_projects p
join cal c on c.ddate between p.start and p.end
where c.is_work_day
group by p.name, p.start, p.end, month_start
)
select jsonb_object_agg(to_char(month_start, 'YYYY-MM-DD'), work_days)
|| jsonb_object_agg('name', name)
|| jsonb_object_agg('start', start)
|| jsonb_object_agg('end', "end") as result
from bymonth
group by name;
Doing a pivot from rows to columns in SQL is usually a bad idea, so the query produces json for you.
I'm trying to calculate monthly retention rate in Amazon Redshift and have come up with the following query:
Query 1
SELECT EXTRACT(year FROM activity.created_at) AS Year,
EXTRACT(month FROM activity.created_at) AS Month,
COUNT(DISTINCT activity.member_id) AS active_users,
COUNT(DISTINCT future_activity.member_id) AS retained_users,
COUNT(DISTINCT future_activity.member_id) / COUNT(DISTINCT activity.member_id)::float AS retention
FROM ads.fbs_page_view_staging activity
LEFT JOIN ads.fbs_page_view_staging AS future_activity
ON activity.mongo_id = future_activity.mongo_id
AND datediff ('month',activity.created_at,future_activity.created_at) = 1
GROUP BY Year,
Month
ORDER BY Year,
Month
For some reason this query returns zero retained_users and zero retention. I'd appreciate any help regarding why this may be happening or maybe a completely different query for monthly retention would work.
I modified the query as per another SO post and here it goes:
Query 2
WITH t AS (
SELECT member_id
,date_trunc('month', created_at) AS month
,count(*) AS item_transactions
,lag(date_trunc('month', created_at)) OVER (PARTITION BY member_id
ORDER BY date_trunc('month', created_at))
= date_trunc('month', created_at) - interval '1 month'
OR NULL AS repeat_transaction
FROM ads.fbs_page_view_staging
WHERE created_at >= '2016-01-01'::date
AND created_at < '2016-04-01'::date -- time range of interest.
GROUP BY 1, 2
)
SELECT month
,sum(item_transactions) AS num_trans
,count(*) AS num_buyers
,count(repeat_transaction) AS repeat_buyers
,round(
CASE WHEN sum(item_transactions) > 0
THEN count(repeat_transaction) / sum(item_transactions) * 100
ELSE 0
END, 2) AS buyer_retention
FROM t
GROUP BY 1
ORDER BY 1;
This query gives me the following error:
An error occurred when executing the SQL command:
WITH t AS (
SELECT member_id
,date_trunc('month', created_at) AS month
,count(*) AS item_transactions
,lag(date_trunc('m...
[Amazon](500310) Invalid operation: Interval values with month or year parts are not supported
Details:
-----------------------------------------------
error: Interval values with month or year parts are not supported
code: 8001
context: interval months: "1"
query: 616822
location: cg_constmanager.cpp:145
process: padbmaster [pid=15116]
-----------------------------------------------;
I have a feeling that Query 2 would fare better than Query 1, so I'd prefer to fix the error on that.
Any help would be much appreciated.
Query 1 looks good. I tried similar one. See below. You are using self join on table (ads.fbs_page_view_staging) and the same column (created_at). Assuming mongo_id is unique, the datediff('month'....) will always return 0 and datediff ('month',activity.created_at,future_activity.created_at) = 1 will always be false.
-- Count distinct events of join_col_id that have lapsed for one month.
SELECT count(distinct E.join_col_id) dist_ct
FROM public.fact_events E
JOIN public.dim_table Z
ON E.join_col_id = Z.join_col_id
WHERE datediff('month', event_time, sysdate) = 1;
-- 2771654 -- dist_ct