I want to count number of month for particular user from subscription table. for example user_id = 1 occur 10 times in subscription table like in January it appears 2 time and in February = 0 and again in march = 1 like that
user_id type started_on ended_on
2 P 2009-10-21 2010-03-18
2 F 2010-03-18 2010-03-20
2 P 2010-03-20 2012-05-19
2 F 2012-05-19 till now
This is pretty basic SQL, I reccomend you read some manual before asking it here. About the Aggregate functions for example. But there you go:
If you want one user:
SELECT
count(distinct month)
FROM
subscription
WHERE
user_id=your_user_id_number
If you want every user's:
SELECT
count(distinct month),
user_id
FROM
subscription
GROUP BY
user_id
Edit:
Ok, so you want the month difference between two date columns, here is how you do it with age():
SELECT user_id, extract(YEAR from age(coalesce(ended_on,current_date),started_on)) * 12 + extract(MONTH FROM age(coalesce(ended_on,current_date),started_on))
FROM subscription
Related
I have two tables.
In first table "customers" I have 3 colums, first column is "id" (unique for every customer) and in second column is "date_created" (the date when the customer file was created). Dates are ranging in format 'yyyy-mm-dd' from 2007 till date. The third column is "client_name" (the name of client to which customer belongs)
the second table is "payments" table with 3 colums, "id" (unique for every customer), in second column is "amount" of payment and in third column is "date_payment".
What I would like to achieve is next. From the first table I would like to choose files, created within a date range (for example from 2018-06-01 till 31.12.2018) and get sum of payment from second table after one month of creation, etc.. till month 36. Interval is attached for every particular claim, so it is different for every separate claim. The purpose of this is to get success rates from on month of creation, 2 month from creation, till month 36...
The result would be:
interval client_name sum
1 Boden 100
2 Boden 220
etc... till 36
Close results i get with next query but it is very time consuming, so I would need some quicker solution that would return results for 36 month intervals for every each claim.
select customers.client_name, sum(payments.amount) as sum_amount
from customers
left join payments on customers.id=payments.id
where customers.date_created >= '2018-06-01' and customersdate_created <= '2018-12-31'
and date_payment <= date(date_created + interval '1 month)
and client_name ilike '%Boden%'
group by customers.client_name
Can anyone help, please?
UPDATE
Nobody answered but I kind of figure it out myself. Solution below:
select customers.client_name, sum(payments.amount) as sum_amount, 1 as sortorder
from customers
left join payments on customers.id=payments.id
where customers.date_created >= '2018-06-01' and customersdate_created <= '2018-12-31'
and date_payment <= date(date_created + interval '1 month)
and client_name ilike '%Boden%'
group by customers.client_name
UNION
select customers.client_name, sum(payments.amount) as sum_amount, 2 as sortorder
from customers
left join payments on customers.id=payments.id
where customers.date_created >= '2018-06-01' and customersdate_created <= '2018-12-31'
and date_payment <= date(date_created + interval '2 month)
and client_name ilike '%Boden%'
group by customers.client_name
I want to count %days when a user was active. A query like this
select
a.id,
a.created_at,
CURRENT_DATE - a.created_at::date as days_since_registration,
NOW() as current_d
from public.accounts a where a.id = 3257
returns
id created_at days_since_registration current_d tot_active
3257 2022-04-01 22:59:00.000 1 2022-04-02 12:00:0.000 +0400 2
The person registered less than 24 hours ago (less than a day ago), but there are two distinct dates between the registration and now. Hence, if a user was active one hour before midnight and one hour after midnight, he is two days active in less than a day (active 200% of days)
What is the right way to count distinct dates and get 2 for a user, who registered at 23:00:00 two hours ago?
WITH cte as (
SELECT 42 as userID,'2022-04-01 23:00:00' as d
union
SELECT 42,'2022-04-02 01:00:00' as d
)
SELECT
userID,
count(d),
max(d)::date-min(d)::date+1 as NrOfDays,
count(d)/(max(d)::date-min(d)::date+1) *100 as PercentageOnline
FROM cte
GROUP BY userID;
output:
userid
count
nrofdays
percentageonline
42
2
2
100
I am trying to get a list of:
all months in a specified year that,
have at least 2 unique rows based on their date
and ignore specific column values
where I got to is:
SELECT DATE_PART('month', "orderDate") AS month, count(*)
FROM public."Orders"
WHERE "companyId" = 00001 AND "orderNumber" != 1 and DATE_PART('year', ("orderDate")) = '2020' AND "orderNumber" != NULL
GROUP BY month
HAVING COUNT ("orderDate") > 2
The HAVING_COUNT sort of works in place of DISTINCT insofar as I can be reasonably sure that condition filters the condition of data required.
However, being able to use DISTINCT based on a given date within a month would return a more reliable result. Is this possible with Postgres?
A sample line of data from the table:
Sample Input
"2018-12-17 20:32:00+00"
"2019-02-26 14:38:00+00"
"2020-07-26 10:19:00+00"
"2020-10-13 19:15:00+00"
"2020-10-26 16:42:00+00"
"2020-10-26 19:41:00+00"
"2020-11-19 20:21:00+00"
"2020-11-19 21:22:00+00"
"2020-11-23 21:10:00+00"
"2021-01-02 12:51:00+00"
without the HAVING_COUNT this produces
month
count
7
1
10
2
11
3
Month 7 can be discarded easily as only 1 record.
Month 10 is the issue: we have two records. But from the data above, those records are from the same day. Similarly, month 11 only has 2 distinct records by day.
The output should therefore be ideally:
month
count
11
2
We have only two distinct dates from the 2020 data, and they are from month 11 (November)
I think you just want to take the distinct count of dates for each month:
SELECT
DATE_PART('month', orderDate) AS month,
COUNT(DISTINCT orderDate::date) AS count
FROM Orders
WHERE
companyId = 1 AND
orderNumber != 1 AND
DATE_PART('year', orderDate) = '2020'
GROUP BY
DATE_PART('month', orderDate)
HAVING
COUNT(DISTINCT orderDate::date) > 2;
I need to find the number of users that were invoiced for an amount greater than 0 in the previous month and were not invoiced in the current month. This calcualtion is to be done for 12 months in a single query. Output should be as below.
Month Count
01/07/2019 50
01/08/2019 34
01/09/2019 23
01/10/2019 98
01/11/2019 10
01/12/2019 5
01/01/2020 32
01/02/2020 65
01/03/2020 23
01/04/2020 12
01/05/2020 64
01/06/2020 54
01/07/2020 78
I am able to get the value only for one month. I want to get it for all months in a single query.
This is my current query:
SELECT COUNT(DISTINCT TWO_MONTHS_AGO.USER_ID), TWO_MONTHS_AGO.MONTH AS INVOICE_MONTH
FROM (
SELECT USER_ID, LAST_DAY(invoice_ct_dt)) AS MONTH
FROM table a AS ID
WHERE invoice_amt > 0
AND LAST_DAY(invoice_ct_dt)) = ADD_MONTHS(LAST_DAY(CURRENT_DATE - 1), - 2)
GROUP BY user_id
) AS TWO_MONTHS_AGO
LEFT JOIN (
SELECT user_id,LAST_DAY(invoice_ct_dt)) AS MONTH
FROM table a AS ID
AND LAST_DAY(invoice_ct_dt)) = ADD_MONTHS(LAST_DAY(CURRENT_DATE - 1), - 1)
GROUP BY USER_ID
) AS ONE_MONTH_AGO ON TWO_MONTHS_AGO.USER_ID = ONE_MONTH_AGO.USER_ID
WHERE ONE_MONTH_AGO.USER_ID IS NULL
GROUP BY INVOICE_MONTH;
Thank you in advance.
Lona
Probably lots of different approaches but the way I would do it is as follows:
Summarise data by user and month for the last 13 months (you need 12 months plus the previous month to that first month
Compare "this" month (that has data) to "next" month and select records where there is no "next" month data
Summarise this dataset by month and distinct userid
For example, assuming a table created as follows:
create table INVOICE_DATA (
USERID varchar(4),
INVOICE_DT date,
INVOICE_AMT NUMBER(10,2)
);
the following query should give you what you want - you may need to adjust it depending on whether you are including this month, or only up to the end of last month, in your calculation, etc.:
--Summarise data by user and month
WITH MONTH_SUMMARY AS
(
SELECT USERID
,TO_CHAR(INVOICE_DT,'YYYY-MM') "INVOICE_MONTH"
,TO_CHAR(ADD_MONTHS(INVOICE_DT,1),'YYYY-MM') "NEXT_MONTH"
,SUM(INVOICE_AMT) "MONTHLY_TOTAL"
FROM INVOICE_DATA
WHERE INVOICE_DT >= TRUNC(ADD_MONTHS(current_date(),-13),'MONTH') -- Last 13 months of data
GROUP BY 1,2,3
),
--Get data for users with invoices in this month but not the next month
USER_DATA AS
(
SELECT USERID, INVOICE_MONTH, MONTHLY_TOTAL
FROM MONTH_SUMMARY MS_THIS
WHERE NOT EXISTS
(
SELECT USERID
FROM MONTH_SUMMARY MS_NEXT
WHERE
MS_THIS.USERID = MS_NEXT.USERID AND
MS_THIS.NEXT_MONTH = MS_NEXT.INVOICE_MONTH
)
AND MS_THIS.INVOICE_MONTH < TO_CHAR(current_date(),'YYYY-MM') -- Don't include this month as obviously no next month to compare to
)
SELECT INVOICE_MONTH, COUNT(DISTINCT USERID) "USER_COUNT"
FROM USER_DATA
GROUP BY INVOICE_MONTH
ORDER BY INVOICE_MONTH
;
I have a table of events, called tbl_events that looks something like this:
PersonID Date
1 30/03/2015
1 22/04/2015
1 30/06/2015
2 18/07/2016
2 09/12/2016
2 28/04/2017
3 01/10/2014
3 28/11/2016
3 28/11/2016
3 16/01/2017
4 13/04/2017
4 09/05/2017
I want to be able to group these events up by the start date of each 'sequence', with a sequence being defined as a run of events from the first identified to the last identified for each PersonID. The last event in a sequence is defined as the event where thereafter there are no subsequent events for that PersonID for a year.
The result of this I would expect to look like is below:
PersonID FirstDate Sequence Events
1 30/03/2015 1 3
2 18/07/2016 1 3
3 01/10/2014 1 1
3 28/11/2016 2 3
4 13/04/2017 1 2
I am able to identify the sequences in Excel and pivot the data, but I need to be able to do this in SQL.
Here is the formula I have used in Excel to generate the sequence number (I am populating cell C3, with column A being PersonID and B being Date):
=+IF(A2<>A3,1,IF((B3-B2)<365,C2,C2+1))
I have joined the table back on itself using ROW_NUMBER to get the difference between the Date and the previous event date for that ID, but I'm not really sure where to go from there.
Any help is much appreciated.
My solution is based on the sample data you've provided along with your excel formula.
-- easily consumable sample data
DECLARE #tbl_events TABLE (PersonId int, [date] date)
INSERT #tbl_events VALUES
(1,'20150330'),(1,'20150422'),(1,'20150630'),(2,'20160718'),(2,'20161209'),(2,'20170428'),
(3,'20141001'),(3,'20161128'),(3,'20161128'),(3,'20170116'),(4,'20170413'),(4,'20170509');
-- Solution
WITH groupings AS
(
SELECT
PersonId,
FirstDate = MIN([date]) OVER (PARTITION BY personId ORDER BY [date]),
NextDate = LAG([date],1,[date]) OVER (PARTITION BY personId ORDER BY [date]),
[date],
grouper =
DATEDIFF(DAY, MIN([date]) OVER (PARTITION BY personId ORDER BY [date]), [date]) / 365
FROM #tbl_events
),
Prep AS
(
SELECT
PersonId,
firstDate = IIF(grouper = 0, FirstDate, IIF(FirstDate = NextDate, [date],NextDate))
FROM groupings
)
SELECT
PersonId,
FirstDate,
[Sequence] = ROW_NUMBER() OVER (PARTITION BY personId ORDER BY FirstDate),
[Events] = COUNT(*)
FROM prep
GROUP BY personId, FirstDate;
Results
PersonId FirstDate Sequence Events
----------- ---------- -------------------- -----------
1 2015-03-30 1 3
2 2016-07-18 1 3
3 2014-10-01 1 1
3 2016-11-28 2 3
4 2017-04-13 1 2
First note all years have 365 days, nonetheless, I'm using 365 to emulate your excel logic; this would need to be updated to account for leap years. Next, like your excel formula - this will only be correct when there are two sequences;
it would not work when, say personId has a date of jan 1 2015, then jan 10 2016, then feb 1 2017.Let us know if we need logic to accommodate for the aforementioned scenarios.
Lastly this solution uses LAG which requires SQL Server 2012+, if you're working with an earlier version of SQL the query will have to be updated accordingly.