This is a follow-up to my earlier question, now that the requirements have changed again after the analysts clarified the requirements
I have a dataset like the below using the help I received:
I need to be able to identify row 2, where the TotalWeeks column has reached or exceeded 23 weeks, so I can return the correct ToDate value.
to get that dataset I am using a query like this:
Select
idcol
, FromDate
, ToDate
, NoOfDays
, Weeks
, Linked
, sum(Weeks) over(order by idcol desc) TotalWeeks
from
#tmpAbsences
where
idcol between 1 AND (
Select TOP 1 idcol from #tmpAbsences where Linked=0)
ORDER BY
ToDate DESC
But how could I alwauys identify the record where the TotalWeeks reaches the value I am checking for - either 23 weeks (and less than 28) or greater than or equal to 28 weeks?
thanks
I think you could use the Having clause
Something like
Having (sum(weeks) >= 23 and SUM(weeks) < 28) or sum(weeks) >= 28
Related
I am working on a query to return the next 7 days worth of data every time an event happens indicated by "where event = 1". The goal is to then group all the data by the user id and perform aggregate functions on this data after the event happens - the event is encoded as binary [0, 1].
So far, I have been attempting to use nested select statements to structure the data how I would like to have it, but using the window functions is starting to restrict me. I am now thinking a self join could be more appropriate but need help in constructing such a query.
The query currently first creates daily aggregate values grouped by user and date (3rd level nested select). Then, the 2nd level sums the data "value_x" to obtain an aggregate value grouped by the user. Then, the 1st level nested select statement uses the lead function to grab the next rows value over and partitioned by each user which acts as selecting the next day's value when event = 1. Lastly, the select statement uses an aggregate function to calculate the average "sum_next_day_value_after_event" grouped by user and where event = 1. Put together, where event = 1, the query returns the avg(value_x) of the next row's total value_x.
However, this doesn't follow my time rule; "where event = 1", return the next 7 days worth of data after the event happens. If there is not 7 days worth of data, then return whatever data is <= 7 days. Yes, I currently only have one lead with the offset as 1, but you could just put 6 more of these functions to grab the next 6 rows. But, the lead function currently just grabs the next row without regard to date. So theoretically, the next row's "value_x" could actually be 15 days from where "event = 1". Also, as can be seen below in the data table, a user may have more than one row per day.
Here is the following query I have so far:
select
f.user_id
avg(f.sum_next_day_value_after_event) as sum_next_day_values
from (
select
bld.user_id,
lead(bld.value_x, 1) over(partition by bld.user_id order by bld.daily) as sum_next_day_value_after_event
from (
select
l.user_id,
l.daily,
sum(l.value_x) as sum_daily_value_x
from (
select
user_id, value_x, date_part('day', day_ts) as daily
from table_1
group by date_part('day', day_ts), user_id, value_x) l
group by l.user_id, l.day_ts
order by l.user_id) bld) f
group by f.user_id
Below is a snippet of the data from table_1:
user_id
day_ts
value_x
event
50
4/2/21 07:37
25
0
50
4/2/21 07:42
45
0
50
4/2/21 09:14
67
1
50
4/5/21 10:09
8
0
50
4/5/21 10:24
75
0
50
4/8/21 11:08
34
0
50
4/15/21 13:09
32
1
50
4/16/21 14:23
12
0
50
4/29/21 14:34
90
0
55
4/4/21 15:31
12
0
55
4/5/21 15:23
34
0
55
4/17/21 18:58
32
1
55
4/17/21 19:00
66
1
55
4/18/21 19:57
54
0
55
4/23/21 20:02
34
0
55
4/29/21 20:39
57
0
55
4/30/21 21:46
43
0
Technical details:
PostgreSQL, supported by EDB, version = 14.1
pgAdmin4, version 5.7
Thanks for the help!
"The query currently first creates daily aggregate values"
I don't see any aggregate function in your first query, so that the GROUP BY clause is useless.
select
user_id, value_x, date_part('day', day_ts) as daily
from table_1
group by date_part('day', day_ts), user_id, value_x
could be simplified as
select
user_id, value_x, date_part('day', day_ts) as daily
from table_1
which in turn provides no real added value, so this first query could be removed and the second query would become :
select user_id
, date_part('day', day_ts) as daily
, sum(value_x) as sum_daily_value_x
from table_1
group by user_id, date_part('day', day_ts)
The order by user_id clause can also be removed at this step.
Now if you want to calculate the average value of the sum_daily_value_x in the period of 7 days after the event (I'm referring to the avg() function in your top query), you can use avg() as a window function that you can restrict to the period of 7 days after the event :
select f.user_id
, avg(f.sum_daily_value_x) over (order by f.daily range between current row and '7 days' following) as sum_next_day_values
from (
select user_id
, date_part('day', day_ts) as daily
, sum(value_x) as sum_daily_value_x
from table_1
group by user_id, date_part('day', day_ts)
) AS f
group by f.user_id
The partition by f.user_id clause in the window function is useless because the rows have already been grouped by f.user_id before the window function is applied.
You can replace the avg() window function by any other one, for instance sum() which could better fit with the alias sum_next_day_values
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 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 list of start dates as below -
start dates sorted in descending order
The start dates are always sorted in descending order.
I am looking for a postgresql query that can give the following output -
start dates with groups
Basically i am trying to create groups of dates from the given list such that each date in a group is within 61 days from the date at the top of the corresponding group.
For example -
in the output,
Group 1 has first 4 records because all 4 start dates are within 61
days of record no. 2.
Group 2 contains only record no. 6 since it is more than 61 days
away from record no. 2.
Group 3 contains row no. 7 and 8 since they are more than 61
days away from record no. 6. but within 61 days of each other
P.S. I am new to postgresql and stackoverflow.
Any pointers will be helpfull
Your sample data does not match your sample output.
Your calculations in your sample output are wrong since this counts backwards and March and October both have 31 days.
To recurse properly you need to assign row numbers using dense_rank():
with recursive num as (
select row_number() over (order by start_date desc) as rn,
start_date
from dateslist
),
Then you create groups and find gaps by carrying anchor values forward as you recurse. Since you have the start_date information you can calculate the offset within groups at the same time:
find_gaps as (
select rn as anchor, start_date as anchor_date, rn, start_date, 0 as group_offset
from num
where rn = 1
union all
select case
when f.anchor_date - n.start_date > 61 then n.rn
else f.anchor
end,
case
when f.anchor_date - n.start_date > 61 then n.start_date
else f.anchor_date
end,
n.rn, n.start_date,
case
when f.anchor_date - n.start_date > 61 then n.start_date
else f.anchor_date
end - n.start_date
from find_gaps f
join num n on n.rn = f.rn + 1
)
The final query selects the columns you want for the output and applies a group number.
select start_date,
dense_rank() over (order by anchor) as group_number,
group_offset
from find_gaps
order by start_date desc;
Working Fiddle Demo
I’m having trouble getting my head around this.
I’m looking for a single query, if possible, running PostgreSQL 9.6.6 under pgAdmin3 v1.22.1
I have a table with a date and a row for each event on the date:
Date Events
2018-12-10 1
2018-12-10 1
2018-12-10 0
2018-12-09 1
2018-12-08 0
2018-12-07 1
2018-12-06 1
2018-12-06 1
2018-12-06 1
2018-12-05 1
2018-12-04 1
2018-12-03 0
I’m looking for the longest sequence of dates without a break. In this case, 2018-12-08 and 2018-12-03 are the only dates with no events, there are two dates with events between 2018-12-08 and today, and four between 2018-12-8 and 2018-12-07 - so I would like the answer of 4.
I know I can group them together with something like:
Select Date, count(Date) from Table group by Date order by Date Desc
To get just the most recent sequence, I’ve got something like this- the subquery returns the most recent date with no events, and the outer query counts the dates after that date:
select count(distinct date) from Table
where date>
( select date from Table
group by date
having count (case when Events is not null then 1 else null end) = 0
order by date desc
fetch first row only)
But now I need the longest streak, not just the most recent streak.
Thank you!
Your instinct is a good one in looking at the rows with zero events and working off them. We can use a subquery with a window function to get the "gaps" between zero event days, and then in a query outside it take the record we want, like so:
select *
from (
select date as day_after_streak
, lag(date) over(order by date asc) as previous_zero_date
, date - lag(date) over(order by date asc) as difference
, date_part('days', date - lag(date) over(order by date asc) ) - 1 as streak_in_days
from dates
group by date
having sum(events) = 0 ) t
where t.streak_in_days is not null
order by t.streak_in_days desc
limit 1