I have the following sample table (provided with single ID for simplicity - need to perform the same logic across all IDs)
ID Visit_date
-----------------
ABC 8/7/2019
ABC 9/10/2019
ABC 9/12/2019
ABC 10/1/2019
ABC 10/1/2019
ABC 10/8/2019
ABC 10/15/2019
ABC 10/17/2019
ABC 10/24/2019
Here is what I need to get the sample output
Mark the first visit as 1 in the "new_visit" column
Compare the subsequent dates with the 1st date until it exceeds 21 days condition. Example Sep 10 is compared to Aug 7 and it doesn’t fall within 21 days of Aug 7, therefore this is considered as another new_visit, so mark new_visit as 1
Then we compare Sep 10 with the subsequent dates with 21 days criteria and mark all of them as follow_up of Sep 10 visit. Eg. Sep 12, Oct 1 are within 21 days of Sep 10; hence they are considered as follow up visits, so mark "follow_up" as 1
When the subsequent date exceeds 21 days criteria of the previous new visit (e.g. Oct 8 compared to Sep 10) then Oct 8 will be considered a new visit & mark "New_visit" as 1 and the subsequent dates will be compared against Oct 8
Sample Output :
Dates New_Visit Follow_up
-----------------------------
8/7/2019 1
9/10/2019 1
9/12/2019 1
10/1/2019 1
10/1/2019 1
10/8/2019 1
10/15/2019 1
10/17/2019 1
10/24/2019 1
You need a recursive query for this.
You would enumerate the rows, then walk through the dataset by ascending date, while keeping track of the first visit date of each group; when the interval since the last first visit exceeds 21 days, the date of the first visit resets, and a new group starts.
with
data as (
select t.*, row_number() over(partition by id order by date) rn
from mtytable t
),
cte as (
select id, visit_date, visit_date first_visit_date
from data
where rn = 1
union all
select c.id, d.visit_date, case when d.visit_date > datead(day, 21, c.first_visit_date) then d.visit_date else c.first_visit_date end
from cte c
inner join data d on d.id = c.id and d.rn = c.rn + 1
)
select
id,
date,
case when visit_date = first_visit_date then 1 else 0 end as is_new
case when visit_date = first_visit_date then 0 else 1 end as is_follow_up
from cte
If a patient may have more than 100 visits, then you need to add option (maxrecursion 0) at the very end of the query.
You need a recursive CTE to handle this. This is the idea, although the exact syntax might vary by database:
with recursive t as (
select id, date,
row_number() over (partition by id order by date) as seqnum
from yourtable
),
recursive cte as (
select id, date, visit_start as date, 1 as is_new_visit
from t
where id = 1
union all
select cte.id, t.date,
(case when t.date < visit_start + interval '21 day'
then cte.visit_start else t.date
end) as visit_start,
(case when t.date < cte.visit_start + interval '21 say'
then 0 else 1
end) as is_new_visit
from cte join
t
on t.id = cte.id and t.seqnum = cte.seqnum + 1
)
select *
from cte
where is_new_visit = 1;
Related
I have below table which has customer's transaction details.
Tranactaction date
CustomerID
1/27/2022
1
1/29/2022
1
2/27/2022
1
3/27/2022
1
3/29/2022
1
3/31/2022
1
4/2/2022
1
4/4/2022
1
4/6/2022
1
In this table consecutive transactions occurred in every two days considered as a segment.
For example, Transactions between Jan 27th and Jan 29th considered as segment 1 & Transactions between Mar 29th and Apr 6th considered as Segment 2. I need to rank the transactions per segment with date order. If a transaction not fall under any segment by default the rank is 1. Expected output is below.
Segment Rank
Tranactaction date
CustomerID
1
1/27/2022
1
2
1/29/2022
1
1
2/27/2022
1
1
3/27/2022
1
2
3/29/2022
1
3
3/31/2022
1
4
4/2/2022
1
5
4/4/2022
1
6
4/6/2022
1
Can somebody guide how to achieve this in T-sql?
Using lag() to check for change in TransDate that is within 2 days and groups together (as a segment). After that use row_number() to generate the required sequence
with
cte as
(
select *,
g = case when datediff(day,
lag(t.TransDate) over (order by t.TransDate),
t.TransDate
) <= 2
then 0
else 1
end
from tbl t
),
cte2 as
(
select *, grp = sum(g) over (order by TransDate)
from cte
)
select *, row_number() over (partition by grp order by TransDate)
from cte2
db<>fiddle demo
I have the following table on SQL Server:
ID
FROM
TO
OFFER NUMBER
1
2022.01.02
9999.12.31
1
1
2022.01.02
2022.02.10
2
2
2022.01.05
2022.02.15
1
3
2022.01.02
9999.12.31
1
3
2022.01.15
2022.02.20
2
3
2022.02.03
2022.02.25
3
4
2022.01.16
2022.02.05
1
5
2022.01.17
2022.02.13
1
5
2022.02.05
2022.02.13
2
The range includes the start date but excludes the end date.
The date 9999.12.31 is given (comes from another system), but we could use the last day of the current quarter instead.
I need to find a way to determine the number of days when the customer sees exactly one, two, or three offers. The following picture shows the method upon id 3:
The expected results should be like (without using the last day of the quarter):
ID
# of days when the customer sees only 1 offer
# of days when the customer sees 2 offers
# of days when the customer sees 3 offers
1
2913863
39
0
2
41
0
0
3
2913861
24
17
4
20
0
0
5
19
8
0
I've found this article but it did not enlighten me.
Also I have limited privileges that is I am not able to declare a variable for example so I need to use "basic" TSQL.
Please provide a detailed explanation besides the code.
Thanks in advance!
The following will (for each ID) extract all distinct dates, construct non-overlapping date ranges to test, and will count up the number of offers per range. The final step is to sum and format.
The fact that the start dates are inclusive and the end dates are exclusive while sometimes non-intuitive for the human, actually works well in algorithms like this.
DECLARE #Data TABLE (Id INT, FromDate DATETIME, ToDate DATETIME, OfferNumber INT)
INSERT #Data
VALUES
(1, '2022-01-02', '9999-12-31', 1),
(1, '2022-01-02', '2022-02-10', 2),
(2, '2022-01-05', '2022-02-15', 1),
(3, '2022-01-02', '9999-12-31', 1),
(3, '2022-01-15', '2022-02-20', 2),
(3, '2022-02-03', '2022-02-25', 3),
(4, '2022-01-16', '2022-02-05', 1),
(5, '2022-01-17', '2022-02-13', 1),
(5, '2022-02-05', '2022-02-13', 2)
;
WITH Dates AS ( -- Gather distinct dates
SELECT Id, Date = FromDate FROM #Data
UNION --(distinct)
SELECT Id, Date = ToDate FROM #Data
),
Ranges AS ( --Construct non-overlapping ranges (The ToDate = NULL case will be ignored later)
SELECT ID, FromDate = Date, ToDate = LEAD(Date) OVER(PARTITION BY Id ORDER BY Date)
FROM Dates
),
Counts AS ( -- Calculate days and count offers per date range
SELECT R.Id, R.FromDate, R.ToDate,
Days = DATEDIFF(DAY, R.FromDate, R.ToDate),
Offers = COUNT(*)
FROM Ranges R
JOIN #Data D ON D.Id = R.Id
AND D.FromDate <= R.FromDate
AND D.ToDate >= R.ToDate
GROUP BY R.Id, R.FromDate, R.ToDate
)
SELECT Id
,[Days with 1 Offer] = SUM(CASE WHEN Offers = 1 THEN Days ELSE 0 END)
,[Days with 2 Offers] = SUM(CASE WHEN Offers = 2 THEN Days ELSE 0 END)
,[Days with 3 Offers] = SUM(CASE WHEN Offers = 3 THEN Days ELSE 0 END)
FROM Counts
GROUP BY Id
The WITH clause introduces Common Table Expressions (CTEs) which progressively build up intermediate results until a final select can be made.
Results:
Id
Days with 1 Offer
Days with 2 Offers
Days with 3 Offers
1
2913863
39
0
2
41
0
0
3
2913861
24
17
4
20
0
0
5
19
8
0
Alternately, the final select could use a pivot. Something like:
SELECT Id,
[Days with 1 Offer] = ISNULL([1], 0),
[Days with 2 Offers] = ISNULL([2], 0),
[Days with 3 Offers] = ISNULL([3], 0)
FROM (SELECT Id, Offers, Days FROM Counts) C
PIVOT (SUM(Days) FOR Offers IN ([1], [2], [3])) PVT
ORDER BY Id
See This db<>fiddle for a working example.
Find all date points for each ID. For each date point, find the number of overlapping.
Refer to comments within query
with
dates as
(
-- get all date points
select ID, theDate = FromDate from offers
union -- union to exclude any duplicate
select ID, theDate = ToDate from offers
),
cte as
(
select ID = d.ID,
Date_Start = d.theDate,
Date_End = LEAD(d.theDate) OVER (PARTITION BY ID ORDER BY theDate),
TheCount = c.cnt
from dates d
cross apply
(
-- Count no of overlapping
select cnt = count(*)
from offers x
where x.ID = d.ID
and x.FromDate <= d.theDate
and x.ToDate > d.theDate
) c
)
select ID, TheCount, days = sum(datediff(day, Date_Start, Date_End))
from cte
where Date_End is not null
group by ID, TheCount
order by ID, TheCount
Result :
ID
TheCount
days
1
1
2913863
1
2
39
2
1
41
3
1
2913861
3
2
29
3
3
12
4
1
20
5
1
19
5
2
8
To get to the required format, use PIVOT
dbfiddle demo
I have dates and some value, I would like to sum values within 7-day cycle starting from the first date.
date value
01-01-2021 1
02-01-2021 1
05-01-2021 1
07-01-2021 1
10-01-2021 1
12-01-2021 1
13-01-2021 1
16-01-2021 1
18-01-2021 1
22-01-2021 1
23-01-2021 1
30-01-2021 1
this is my input data with 4 groups to see what groups will create the 7-day cycle.
It should start with first date and sum all values within 7 days after first date included.
then start a new group with next day plus anothe 7 days, 10-01 till 17-01 and then again new group from 18-01 till 25-01 and so on.
so the output will be
group1 4
group2 4
group3 3
group4 1
with match_recognize would be easy current_day < first_day + 7 as a condition for the pattern but please don't use match_recognize clause as solution !!!
One approach is a recursive CTE:
with tt as (
select dte, value, row_number() over (order by dte) as seqnum
from t
),
cte (dte, value, seqnum, firstdte) as (
select tt.dte, tt.value, tt.seqnum, tt.dte
from tt
where seqnum = 1
union all
select tt.dte, tt.value, tt.seqnum,
(case when tt.dte < cte.firstdte + interval '7' day then cte.firstdte else tt.dte end)
from cte join
tt
on tt.seqnum = cte.seqnum + 1
)
select firstdte, sum(value)
from cte
group by firstdte
order by firstdte;
This identifies the groups by the first date. You can use row_number() over (order by firstdte) if you want a number.
Here is a db<>fiddle.
I need to compare side by side the companies values by current year vs last year and current month with same month of the previous year.
I use this query to get the values
SELECT STORE, SUM(TOTAL) as VAL, DATE FROM MYTABLE
WHERE DATE=CURRENT_DATE GROUP BY STORE ORDER BY STORE
below the results
STORE | VAL | DATE
1 10 CURRENT_DATE (2018-27-03)
1 20 2018-26-03
1 30 2018-25-03
2 20 CURRENT_DATE (2018-27-03)
2 20 2018-26-02
and i need this
STORE | VALUE CURRENT YEAR | VALUE LAST YEAR
1 60 30 (CALCULATED)
2 40 50 (CALCULATED)
STORE | VALUE CURRENT MONTH | VALUE SAME MONTH OF LAST YEAR
1 60 30 (CALCULATED)
2 20 50 (CALCULATED)
Thank you
You could just join two sub-selects together.
E.g with this DDL and Data
CREATE TABLE MYTABLE (STORE int, VAL int, D DATE);
INSERT INTO MYTABLE VALUES
( 1, 10, '2018-03-27')
,( 1, 20, '2018-03-26')
,( 1, 10, '2018-02-25')
,( 1, 35, '2017-03-25')
,( 2, 20, '2018-03-27')
,( 2, 15, '2017-03-26');
This will get you current month and last month last year values
SELECT C.*, LY.VAL_CURR_MONTH_LY
FROM (
SELECT STORE, SUM(VAL) as VAL_CURR_MONTH
FROM MYTABLE WHERE INT(D)/100=INT(CURRENT_DATE)/100
GROUP BY STORE ) AS C
LEFT JOIN
(SELECT STORE
, SUM(VAL) AS VAL_CURR_MONTH_LY
FROM MYTABLE
WHERE INT(D)/100 = INT(CURRENT_DATE)/100 -100
GROUP BY STORE ) LY
ON
C.STORE = LY.STORE
Then this for years
SELECT C.*, LY.VAL_LY
FROM (
SELECT STORE, SUM(VAL) as VAL_CURR_YEAR
FROM MYTABLE WHERE INT(D)/10000=INT(CURRENT_DATE)/10000
GROUP BY STORE ) AS C
LEFT JOIN
(SELECT STORE
, SUM(VAL) AS VAL_LY
FROM MYTABLE
WHERE INT(D)/10000 = INT(CURRENT_DATE)/10000 -1
GROUP BY STORE ) LY
ON
C.STORE = LY.STORE
P.S. there are many other ways to manipulate dates, but casting to INT is maybe one of the easier ways
Also, here is a more flexible way to get the "Same Month of Last Year" value. A similar method can get "last Year" values.
SELECT T.*
, AVG(VAL) OVER(
PARTITION BY STORE
ORDER BY YEAR_MONTH
RANGE BETWEEN 101 PRECEDING AND 100 PRECEDING
) AS SAME_MONTH_PREV_YEAR
FROM
( SELECT STORE
, INTEGER(D)/100 AS YEAR_MONTH
, SUM(VAL) AS VAL
FROM
MYTABLE T
GROUP BY
STORE
, INTEGER(D)/100
) AS T
;
Gives
STORE YEAR_MONTH VAL SAME_MONTH_PREV_YEAR
----- ---------- --- --------------------
1 201703 35 NULL
1 201802 10 NULL
1 201803 30 35
2 201703 15 NULL
2 201803 20 15
It is better to avoid functions on table columns in where clauses. Check following SQLs which are based on P. Vernon sample table.
Note: These SQLs are for DB2 LUW 11.1
For month:
SELECT STORE,
SUM(CASE WHEN YEAR(D) = year(current date) THEN val
ELSE 0 END) as VAL_CURR_MONTH,
SUM(CASE WHEN YEAR(D) = year(current date) - 1 THEN vaL
ELSE 0 END) as VAL_CURR_MONTH_LY
FROM MYTABLE
WHERE D between first_day(current date) and last_day(current date)
or D between first_day(current date - 1 year) and last_day(current date - 1 year)
GROUP BY STORE
ORDER BY STORE
For year:
SELECT STORE, SUM(CASE WHEN YEAR(D) = year(current date) THEN val
ELSE 0 END) as VAL_CY,
SUM(CASE WHEN YEAR(D) = year(current date) - 1 THEN vaL
ELSE 0 END) as VAL_LY
FROM MYTABLE
WHERE D between first_day(current date - (month(current date) - 1) months)
and last_day(current date + (12 - month(current date)) months)
or D between first_day(current date - (month(current date) - 1) months - 1 year)
and last_day(current date + (12 - month(current date)) months - 1 year)
GROUP BY STORE
ORDER BY STORE
Lets assume that we have the ORACLE table of the following format and data:
TIMESTAMP MESSAGENO ORGMESSAGE
------------------------- ---------------------- -------------------------------------
27.04.13 1 START PERIOD
27.04.13 3 10
27.04.13 4 5
28.04.13 5 6
28.04.13 3 20
29.04.13 4 25
29.04.13 5 26
30.04.13 2 END PERIOD
30.04.13 1 START PERIOD
01.05.13 3 10
02.05.13 4 15
02.05.13 5 16
03.05.13 3 30
03.05.13 4 35
04.05.13 5 36
05.05.13 2 END PERIOD
I want to select sum of all the ORGMESSAGE for all the period (window between START PERIOD and END PERIOD) grouped by MESSAGENO.
Exapmle output would be:
PERIOD START PERIOD END MESSAGENO SUM
------------ ------------- -------- ----
27.04.13 30.04.13 3 25
27.04.13 30.04.13 4 30
27.04.13 30.04.13 5 32
30.04.13 05.05.13 3 45
30.04.13 05.05.13 4 50
30.04.13 05.05.13 5 52
I am guessing that use of ORACLE Analityc function woulde be suitable but really dont know how and where to start.
Thanks in advance for any help.
If we assume that the period starts and ends match, then a simple way to find the matching messages is to count the preceding number of starts. This is a cumulative sum and it is easy in Oracle. The rest is just aggregation:
select min(timestamp) as periodstart, max(timestamp) as periodend, messageno, count(*)
from (select om.*,
sum(case when messageno = 1 then 1 else 0 end) over (order by timestamp) as grp
from orgmessages om
) om
where messageno not in (1, 2)
group by grp, messageno;
Note that this method (as with the others) really wants the timestamp to be unique on each record. In the data presented, these solutions will work. But if you have multiple starts and ends on the same day, none of them will work assuming that timestamp only has the date.
First find all period ends per period start. Then join with your table to group and sum.
select
dates.start_date,
dates.end_date,
messageno,
sum(to_number(orgmessage)) as period_sum
from mytable
join
(
select start_dates.timestmp as start_date, min(end_dates.timestmp) as end_date
from (select * from mytable where orgmessage = 'START PERIOD') start_dates
join (select * from mytable where orgmessage = 'END PERIOD') end_dates
on start_dates.timestmp < end_dates.timestmp
group by start_dates.timestmp
) dates on mytable.timestmp between dates.start_date and dates.end_date
where mytable.orgmessage not like '%PERIOD%'
group by dates.start_date, dates.end_date, messageno
order by dates.start_date, dates.end_date, messageno;
SQL fiddle: http://www.sqlfiddle.com/#!4/365de/15.
please, try this one, replace rrr with your table name
select periodstart, periodend, messageno, sum(to_number(orgmessage)) s
from (select TIMESTAMP periodstart,
(select min (TIMESTAMP) from rrr r2 where orgmessage = 'END PERIOD' and r2.TIMESTAMP > r.TIMESTAMP) periodend
from rrr r
where orgmessage = 'START PERIOD'
) borders, rrr r
where r.TIMESTAMP between borders.periodstart and borders.periodend
and r.orgmessage not in ('END PERIOD', 'START PERIOD')
group by periodstart, periodend, messageno
order by periodstart, periodend, messageno