How to GROUP EIDs by dates where Date between 2014-01-15 and 2014-03-18
| ID |EID | DATE | Status | |
|----------|--------------|---------|-----|
| 9 |9991 | 2014-03-16 | OUT | |
| 8 |9997 | 2014-03-18 | IN | |
| 7 |9997 | 2014-03-16 | OUT | |
| 6 |9999 | 2014-02-16 | IN | |
| 5 |9999 | 2014-02-16 | OUT | |
| 4 |9996 | 2014-03-18 | IN | |
| 3 |9996 | 2014-03-16 | OUT | |
| 2 |9997 | 2014-01-18 | IN | |
| 1 |9997 | 2014-01-15 | OUT | |
Output should be like:
|
|EID |in date | OUT date| DAYS OUT |
|------|--------------|--------- |------ ----|
| 9997 | 2014-03-18 | 2014-03-16| 2 |
| 9997 | 2014-01-18 | 2014-01-15| 3 |
| 9999 | 2014-02-16 | 2014-02-16| 0 |
| 9996 | 2014-03-18 | 2014-03-16| 2 |
| 9991 | | 2014-03-16| |
Thank you
Here is one method that assumes that they are interleaved, so no two ins or outs are together:
select eid,
max(case when status = 'in' then date end) as in_date,
max(case when status = 'out' then date end) as out_date,
datediff(day,
max(case when status = 'in' then date end),
max(case when status = 'out' then date end)
) as days_diff
from (select t.*, row_number() over (partition by eid, status order by date) as seqnum
from t
) t
group by eid, seqnum;
I think that you have already done it but, have you tried to do the sentence like:
SELECT [here you format as you wish] FROM [your table] WHERE date BETWEEN '2014-01-15' AND '2014-03-18' GROUP BY date
or
SELECT [here you format as you wish] FROM [your table] WHERE dateIn >= '2014-01-15' AND dateOut <= '2014-03-18' GROUP BY dateIn
Can you share your full table?
Related
Product:
+--------------+-----------+------------+------------+
| Product_code | Prod Name | Status | Date |
+--------------+-----------+------------+------------+
| A | AA1 | New | 12/3/2019 |
| A | AA2 | Expiry | 7/20/2017 |
| A | AA1 | Others | 8/15/2018 |
| A | AA1 | Others_Loy | 7/10/2019 |
| B | BB2 | Expiry | 8/20/2017 |
| B | BB1 | Others | 8/15/2019 |
| B | BB3 | New | 7/15/2020 |
| C | CC1 | Others | 4/27/2020 |
| D | DD1 | New | 12/31/2017 |
| D | DD3 | Expiry | 2/15/2020 |
+--------------+-----------+------------+------------+
expected result: Max_date(within 24 months from min_date)
+--------------+------------+------------+------------+------------+------------+-------+
| Product_code | Min_date | Min_status | Max_date | Max_status | count_Prod | Label |
+--------------+------------+------------+------------+------------+------------+-------+
| A | 7/20/2017 | Expiry | 7/10/2019 | Others_Loy | 3 | 1 |
| B | 8/20/2017 | Expiry | 8/15/2019 | Others | 2 | 1 |
| C | 4/27/2020 | Others | 4/27/2020 | Others | 1 | 0 |
| D | 12/31/2017 | New | 12/31/2017 | New | 1 | 0 |
+--------------+------------+------------+------------+------------+------------+-------+
I want pull the records from Min_date based on prod_code,
then Max_date need to compute from Min_date to next 24 months (within 24 months time period) and count_prod within that
, Label need to update if count_prod more than one within the 24 months time period.
Trying this sql datbase:
You haven't tagged the database, so this is basically pseudo-code. In particular, date functionality varies significantly among databases:
select product_code,
min_date, max(case when date = min_date then status end) as min_status,
max_date, max(case when date = max_date then status end) as max_status,
sum(case when date >= max_date - interval '2 year' then 1 else 0 end) as count_prod,
(case when sum(case when date >= max_date - interval '2 year' then 1 else 0 end) > 1
then 1 else 0
end) as label
from (select t.*,
min(date) over (partition by product_code) as min_date,
max(date) over (partition by product_code) as max_date
from t
) t
group by product_code;
You need to adjust this for the database you are using.
I want to calculate the number of people who also had occurrence the previous day on a daily basis, but I'm not sure how to do this?
Sample Table:
| ID | Date |
+----+-----------+
| 1 | 1/10/2020 |
| 1 | 1/11/2020 |
| 2 | 2/20/2020 |
| 3 | 2/20/2020 |
| 3 | 2/21/2020 |
| 4 | 2/23/2020 |
| 4 | 2/24/2020 |
| 5 | 2/22/2020 |
| 5 | 2/23/2020 |
| 5 | 2/24/2020 |
+----+-----------+
Desired Output:
| Date | Count |
+-----------+-------+
| 1/11/2020 | 1 |
| 2/21/2020 | 1 |
| 2/23/2020 | 1 |
| 2/24/2020 | 2 |
+-----------+-------+
Edit: Added desired output. The output count should be unique to the ID, not the number of date occurrences. i.e. an ID 5 can appear on this list 10 times for dates 2/23/2020 and 2/24/2020, but that would count as "1".
Use lag():
select date, count(*)
from (select t.*, lag(date) over (partition by id order by date) as prev_date
from t
) t
where prev_date = dateadd(day, -1, date)
group by date;
input :
+------+------------+--------------+------------+
| NAME | Date | Amount_start | Amount_END |
+------+------------+--------------+------------+
| AAA | 2016-10-06 | 20 | 4 |
| AAA | 2016-10-07 | 30 | 6 |
| AAA | 2016-10-08 | 7 | 8 |
| AAA | 2016-10-09 | 380 | 9 |
| ... | ... | ... | ... |
| ZZZ | 2016-10-06 | 10 | 20 |
| ZZZ | 2016-10-07 | 11 | 6 |
+------+------------+--------------+------------+
output:
+------+--------------+------------+
| NAME | Amount_start | Amount_END |
+------+--------------+------------+
| AAA | 20 | 9 |
| ... | ... | ... |
| ZZZ | 10 | 6 |
+------+--------------+------------+
output : In one row need to take Amount_start of starting date and
Amount_end of End date of that employee
Just use row_number() and conditional aggregation:
select t.name,
max(case when seqnum_a = 1 then amount_start end) as amount_start,
max(case when seqnum_d = 1 then amount_end end) as amount_end
from (select t.*,
row_number() over (partition by name order by date asc) as seqnum_a,
row_number() over (partition by name order by date desc) as seqnum_d
from t
) t
group by name;
I have a table that looks like the following.
What I want is the the rows in continuation of each other to be grouped together - for each "ID".
The column IsContinued marks if the next row should be combined with the current row
My data looks like this:
+-----+--------+-------------+-----------+----------+
| ID | Period | IsContinued | StartDate | EndDate |
+-----+--------+-------------+-----------+----------+
| 123 | 1 | 1 | 20180101 | 20180404 |
+-----+--------+-------------+-----------+----------+
| 123 | 2 | 1 | 20180501 | 20180910 |
+-----+--------+-------------+-----------+----------+
| 123 | 3 | 0 | 20181001 | 20181201 |
+-----+--------+-------------+-----------+----------+
| 123 | 4 | 1 | 20190105 | 20190228 |
+-----+--------+-------------+-----------+----------+
| 123 | 5 | 0 | 20190401 | 20190430 |
+-----+--------+-------------+-----------+----------+
| 456 | 2 | 1 | 20180201 | 20180215 |
+-----+--------+-------------+-----------+----------+
| 456 | 3 | 0 | 20180301 | 20180401 |
+-----+--------+-------------+-----------+----------+
| 456 | 4 | 0 | 20180501 | 20180530 |
+-----+--------+-------------+-----------+----------+
| 456 | 5 | 0 | 20180701 | 20180705 |
+-----+--------+-------------+-----------+----------+
The end result I want is this:
+-----+-------------+-----------+-----------+----------+
| ID | PeriodStart | PeriodEnd | StartDate | EndDate |
+-----+-------------+-----------+-----------+----------+
| 123 | 1 | 3 | 20180101 | 20181201 |
+-----+-------------+-----------+-----------+----------+
| 123 | 4 | 5 | 20190105 | 20190430 |
+-----+-------------+-----------+-----------+----------+
| 456 | 2 | 3 | 20180201 | 20180401 |
+-----+-------------+-----------+-----------+----------+
| 456 | 4 | 4 | 20180501 | 20180530 |
+-----+-------------+-----------+-----------+----------+
| 456 | 5 | 5 | 20180701 | 20180705 |
+-----+-------------+-----------+-----------+----------+
DDL Statement:
CREATE TABLE #Period (ID INT, PeriodNr INT, IsContinued INT, STARTDATE DATE, ENDDATE DATE)
INSERT INTO #Period VALUES (123,1,1,'20180101', '20180404'),
(123,2,1,'20180501', '20180910'),
(123,3,0,'20181001', '20181201'),
(123,4,1,'20190105', '20190228'),
(123,5,0,'20190401', '20190430'),
(456,2,1,'20180201', '20180215'),
(456,3,0,'20180301', '20180401'),
(456,4,0,'20180501', '20180530'),
(456,5,0,'20180701', '20180705')
The code should be run on SQL Server 2016
Thanks!
Here is one approach:
with removeFluff as
(
SELECT *
FROM (
SELECT ID, PeriodNr, IsContinued, STARTDATE, ENDDATE, LAG(IsContinued,1,2) OVER (PARTITION BY ID ORDER BY PERIODNR) Lag
FROM #Period
) A
WHERE (IsContinued <> Lag) OR (IsContinued + Lag = 0)
)
,getValues as
(
SELECT ID,
CASE WHEN LAG(IsContinued) OVER (PARTITION BY ID ORDER BY PeriodNr) = 1 THEN LAG(PeriodNr) OVER (PARTITION BY ID ORDER BY PeriodNr) ELSE PeriodNr END PeriodStart,
PeriodNr PeriodEnd,
CASE WHEN LAG(IsContinued) OVER (PARTITION BY ID ORDER BY PeriodNr) = 1 THEN LAG(STARTDATE) OVER (PARTITION BY ID ORDER BY PeriodNr) ELSE STARTDATE END StartDate,
EndDate,
IsContinued
FROM removeFluff r
)
SELECT ID, PeriodStart, PeriodEnd, StartDate, EndDate
FROM getValues
WHERE IsContinued = 0
Output:
ID PeriodStart PeriodEnd StartDate EndDate
123 1 3 2018-01-01 2018-12-01
123 4 5 2019-01-05 2019-04-30
456 2 3 2018-02-01 2018-04-01
456 4 4 2018-05-01 2018-05-30
456 5 5 2018-07-01 2018-07-05
Method:
removeFluff cte removes lines that are unimportant. Theses are the records that don't start or end a segment (line 2 in your sample data)
Now that the fluff is removed, we know that either:
A.) The line is complete on it's own (LAG(IsContinued) ... = 0), ie. previous line is complete
B.) The line needs the "start" info from the previous line (LAG(IsContinued) ... = 1)
We apply these two cases in the CASE expression of the getValues cte
Last, the results are narrowed to only the important rows in the final select with IsContinued = 0. This is because we have used LAG to get "start" data on the "end" data row, so we only want to select the end rows
I have a table with 5 columns like this:
| ID | NAME | PO_NUMBER | DATE | STATS |
| 1 | Jhon | 160101-001 | 2016-01-01 | 7 |
| 2 | Jhon | 160101-002 | 2016-01-01 | 7 |
| 3 | Jhon | 160102-001 | 2016-01-02 | 7 |
| 4 | Jane | 160101-001 | 2016-01-01 | 7 |
| 5 | Jane | 160102-001 | 2016-01-02 | 7 |
| 6 | Jane | 160102-002 | 2016-01-02 | 7 |
| 7 | Jane | 160102-003 | 2016-01-02 | 7 |
I need to display all values, but stats fields without duplicate according from date field.
Like this
| ID | NAME | PO_NUMBER | DATE | STATS |
| 1 | Jhon | 160101-001 | 2016-01-01 | 7 |
| 2 | Jhon | 160101-002 | 2016-01-01 | null |
| 3 | Jhon | 160102-001 | 2016-01-02 | 7 |
| 4 | Jane | 160101-001 | 2016-01-01 | 7 |
| 5 | Jane | 160102-001 | 2016-01-02 | 7 |
| 6 | Jane | 160102-002 | 2016-01-02 | null |
| 7 | Jane | 160102-003 | 2016-01-02 | null |
I've had trouble getting the hoped. Thanks
From your sample data, it appears you only want to show the stats for po_number ending with 001. If so, this should be the easiest approach:
select id, name, po_number, date,
case when right(po_number, 3) = '001' then stats else null end as stats
from yourtable
If instead you want to order by the po_number, then here's one option using row_number:
select id, name, po_number, date,
case when rn = 1 then stats else null end as stats
from (
select *, row_number() over (partition by name, date order by po_number) as rn
from yourtable
) t
SQL Fiddle Demo
since you are using SQL 2012, you can use the LEAD() or LAG() window function to compare the DATE value
select *,
STATS = case when t.DATE = LAG(DATE) OVER(ORDER BY ID)
then NULL
else STATS
end
from yourtable t
Use below code
;with temp as (
select id,name ,PO_NUMBER ,DATE, STATS,
LAG (STATS, 1, 0)
OVER (PARTITION BY name ,PO_NUMBER ,DATE ORDER BY id) AS PrevSTATS
from tableName
)
select id,name ,PO_NUMBER ,DATE,
case when STATS = PrevSTATS then null
else STATS end as STATS
from temp