I have Table
1 2013-10-01 08:21 Null Null Null
1 2013-10-01 14:30 Null Null Null
2 2013-10-01 08:31 Null Lt Null
2 2013-10-01 14:31 EO Null Null
3 2013-10-01 14:30 EO Null Ab here
this Table is Result from this query
SELECT m.ID,L.Log_D,W.Sat,L.C,
(CASE WHEN convert(time,L.Log_D)>'08:31:00' and convert(time,L.Log_D)<'10:30:00' and L.C =1 then 'Lt'end )as Late,
(CASE WHEN convert(time,L.Log_D)<'13:30:00' and L.C =2 then 'Ab'end )as EarlyOut,
(CASE WHEN DATENAME(DAY, day( L.Log_D)) =2 THEN 'Ab' END) as Counte
from WorkPeriod W,LogT L,MinimumInfoT m where day(L.Log_D) =1
and month(L.Log_D) =10
and year(L.Log_D) =2013
and W.id=54
and m.Branch_ID=35
and L.C in(1,2)
and M.ID =L.EmpId
and W.id =m.W_Period
group by m.ID,L.Log_D,W.Sat,L.C
order by m.ID
I need the Absent Column Display as 'Ab' when the count Of the Day is less then 2 for each Id is that possible any help will be appreciated
You can use a Window Function to do this:
CASE WHEN COUNT(*) OVER (PARTITION BY m.ID) < 2 THEN 'ab' ELSE NULL END as Counte
This will get a count of records for each distinct m.ID. If the count for the current m.ID is less than 2, then it spits out ab.
Related
I've this sp, which return a list of data, for each "month" (i.e. each row is a month). Somethings like that:
SELECT
*,
(CAST(t1.NumActivities AS DECIMAL) / t1.NumVisits) * 100 AS PercAccepted,
(CAST(t1.Accepted AS DECIMAL) / t1.Estimated) * 100 AS PercValue
FROM
(SELECT
MONTH(DateVisit) AS Month,
COUNT(*) AS NumVisits,
SUM(CASE WHEN DateActivity is not null THEN 1 ELSE 0 END) AS NumActivities,
SUM(Estimate) AS Estimated,
SUM(CASE WHEN DateActivity is not null THEN Estimate ELSE 0 END) AS Accepted
FROM [dbo].[Activities]
WHERE
DateVisit IS NOT NULL
AND (#year IS NULL OR YEAR(DateVisit) = #year)
AND (#clinicID IS NULL OR ClinicID = #clinicID)
GROUP BY MONTH(DateVisit)) t1
This is a result:
Month NumVisits NumActivities Estimated Accepted PercAccepted PercValue
1 5 1 13770.00 2520.00 20.00000000000 18.30065359477124
2 2 2 7900.00 7900.00 100.00000000000 100.00000000000000
3 1 0 2730.00 0.00 0.00000000000 0.00000000000000
8 1 1 3000.00 3000.00 100.00000000000 100.00000000000000
But as you can see, I could "miss" some Month (for example, here April "4" is missed).
Is it possible to insert, for the missing month/row, an empty (0) record? Such as:
Month NumVisits NumActivities Estimated Accepted PercAccepted PercValue
1 5 1 13770.00 2520.00 20.00000000000 18.30065359477124
2 2 2 7900.00 7900.00 100.00000000000 100.00000000000000
3 1 0 2730.00 0.00 0.00000000000 0.00000000000000
4 0 0 0 0 0 0
...
Here is a example with sample data:
CREATE TABLE #Report
(
Id INT,
Name nvarchar(max),
Percentage float
)
INSERT INTO #Report VALUES (1,'ONE',2.01)
INSERT INTO #Report VALUES (2,'TWO',3.01)
INSERT INTO #Report VALUES (5,'Five',5.01)
;WITH months(Month) AS
(
SELECT 1
UNION ALL
SELECT Month+1
FROM months
WHERE Month < 12
)
SELECT *
INTO #AllMonthsNumber
from months;
Your select query:
The left join will gives you the NULL for other months so just use ISNULL('ColumnName','String_to_replace')
\/\/\/\/
SELECT Month, ISNULL(Name,0), ISNULL(Percentage,0)
FROM AllMonthsNumber A
LEFT JOIN #Report B
ON A.Month = B.Id
EDIT:
Yes you can do it without creating AllMonthNumber Table:
You can use master..spt_values (found here) system table which contains the numbers so just with some where condition.
SELECT Number as Month, ISNULL(B.Name,0), ISNULL(Percentage,0)
FROM master..spt_values A
LEFT JOIN #Report B ON A.Number = B.Id
WHERE Type = 'P' AND number BETWEEN 1 AND 12
I would like to know how can i modify my code for considering all the same values of suppose 10 as UP till the time it is incrementing and then down for decrement and SAME if there is no change till the time there is no variation in the value (increment, decrement, same).
Here is my code :
;with etape1 as
(
select ROW_NUMBER() OVER(ORDER BY mnth) AS id,* from [InsideTSQL2008].[alioune].[Sales]
)
,
etape2 as
(
select
a.id, b.mnth AS START , a.mnth AS FINISH ,
a.qty - b.qty AS TREND
FROM
etape1 a
LEFT JOIN etape1 b
on a.id = b.id+1
)
select * from etape2;
My Result is :
id START FINISH TREND
1 NULL 2007-12-01 NULL
2 2007-12-01 2008-01-01 10
3 2008-01-01 2008-02-01 10
4 2008-02-01 2008-03-01 10
5 2008-03-01 2008-04-01 10
6 2008-04-01 2008-05-01 0
7 2008-05-01 2008-06-01 -10
8 2008-06-01 2008-07-01 -10
9 2008-07-01 2008-08-01 -10
10 2008-08-01 2008-09-01 -10
11 2008-09-01 2008-10-01 10
12 2008-10-01 2008-11-01 -10
13 2008-11-01 2008-12-01 20
14 2008-12-01 2009-01-01 10
15 2009-01-01 2009-02-01 10
16 2009-02-01 2009-03-01 -40
My final result as required should be like :
Start End Trend
200712 200712 unknown
200801 200804 UP
200805 200805 SAME
200806 200809 DOWN
200810 200810 UP
200811 200811 DOWN
200812 200812 UP
200903 200903 DOWN
200904 200905 SAME
200906 200907 UP
Any help would be really helpful; Thanks
Took me a few goes (and a few hours), but I think I have what you want:
DECLARE #Sales AS TABLE (mnth datetime, qty int)
INSERT INTO #Sales
SELECT '2016-01-01', 10 UNION ALL
SELECT '2016-02-01', 20 UNION ALL
SELECT '2016-03-01', 30 UNION ALL
SELECT '2016-04-01', 40 UNION ALL
SELECT '2016-05-01', 40 UNION ALL
SELECT '2016-06-01', 30 UNION ALL
SELECT '2016-07-01', 20 UNION ALL
SELECT '2016-08-01', 30 UNION ALL
SELECT '2016-09-01', 40 UNION ALL
SELECT '2016-10-01', 45 UNION ALL
SELECT '2016-11-01', 50
;WITH etape1 AS (
SELECT ROW_NUMBER() OVER(ORDER BY mnth) AS id, * FROM #Sales
)
, etape2 AS (
SELECT id, lag(mnth) OVER (ORDER BY id) AS START, mnth AS FINISH, CASE WHEN qty - LAG(qty) OVER (ORDER BY id) < 0 THEN -1 WHEN qty - LAG(qty) OVER (ORDER BY id) > 0 THEN 1 ELSE 0 END AS TREND
FROM etape1
)
, etape3 AS (
SELECT id, START, FINISH, TREND, lag(TREND) OVER (ORDER BY id) AS PrevTrend
FROM etape2
)
, etape4 AS (
SELECT id, START, FINISH, TREND, SUM(CASE WHEN TREND = PREVTREND THEN 0 ELSE 1 END) OVER (ORDER BY id ROWS UNBOUNDED PRECEDING) AS Change
FROM etape3
)
SELECT MIN(START) AS START, MAX(FINISH) AS FINISH, CASE WHEN MIN(TREND) IS NULL THEN 'Unknown' WHEN MIN(TREND) < 0 THEN 'Down' WHEN MIN(TREND) > 0 THEN 'Up' WHEN MIN(Start) is NULL THEN 'Unknown' ELSE 'Same' END AS TREND
FROM etape4
GROUP BY Change
ORDER BY START
Results are:
START FINISH TREND
NULL 2016-01-01 Unknown
2016-01-01 2016-04-01 Up
2016-04-01 2016-05-01 Same
2016-05-01 2016-07-01 Down
2016-07-01 2016-11-01 Up
I have this table - Name : Mytable:
Amount Desc Month Sym code ID
$32,323.00 Bla1 1 121 3 2424221
$4,242.00 Bla1 1 121 3 2424221
$3,535.00 Bla1 1 121 1 3230824
$4,984.00 Bla2 1 433 1 3230824
$47,984.00 Bla2 2 433 1 3230824
$41.00 Bla2 2 433 1 3230824
$3,472.00 Bla6 1 D2 27 2297429
$3,472.00 Bla6 1 D2 27 2297429
$3,239.00 Bla6 2 D2 27 2297429
$4,249.00 Bla8 2 114 24 3434334
ID and Month Stands for for a paycheck. There are 6 paychecks : 1 + 3230824, 2+3230824 etc.
And I want to generate a pivot like this:
Jan Feb
count amount count amount
121 2 40100$ 0 0
433 1 52968$ 1 48025$
D2 1 6944$ 1 3239$
114 0 0 1 4249$
Explanation: 121 is two in Jan because ID = 2424221 got it twice and 3230824 got it one time. The number of of "occurrences" in the paychecks is two.
But, In the amount I sum every thing To get the total sum of money in the paycheck for that Sym.
Same, 433 got the value of 1 in Feb for example because only 3230824 got it (twice).
I started writing this:
SELECT *
FROM (
SELECT
[Sym] as Sym, [Month] as [month], [Amount] as Amount
FROM Mytable
) as T
PIVOT
(
Sum(Amount)
FOR [Month] IN ([1],[2])
)AS piv
Well, The amounts are correct But I don't know how can I pull this count as I explained near the amount in the pivot table.
SELECT
[Sym],
COALESCE(SUM(CASE WHEN [1] IS NULL THEN NULL ELSE [Cnt] END), 0) [Jan Count],
COALESCE(SUM(CASE WHEN [1] IS NULL THEN NULL ELSE [1] END), 0) [Jan Amount],
COALESCE(SUM(CASE WHEN [2] IS NULL THEN NULL ELSE [Cnt] END), 0) [Feb Count],
COALESCE(SUM(CASE WHEN [2] IS NULL THEN NULL ELSE [2] END), 0) [Feb Amount]
FROM (
SELECT
mt1.[Sym] as Sym, mt1.[Month] as [month], mt1.[Amount] as Amount, mt2.[Cnt]
FROM Mytable mt1
JOIN (SELECT COUNT(DISTINCT [ID]) [Cnt], [Sym], [Month]
FROM MyTable
GROUP BY [Sym], [Month]) mt2
ON mt1.[Sym] = mt2.[Sym] AND mt1.[Month] = mt2.[Month]
) as T
PIVOT
(
Sum(Amount)
FOR [Month] IN ([1],[2])
)AS piv
GROUP BY [Sym]
SQL Fiddle
Let's assume I have a table which has columns From and To which are dates and a bit type column which identifies whether it is a cancel (1 = cancel). Also an Id which is a PK and CancelId which references what is cancelled.
Let's say I have records which look like:
Id From To IsCancel CancelId
1 2015-01-01 2015-01-31 0 NULL
2 2015-01-03 2015-01-09 1 1
3 2015-01-27 2015-01-31 1 1
I am expecting the result to show what intervals of then non-cancel records are still uncancelled:
Id From To
1 2015-01-01 2015-01-02
1 2015-01-10 2015-01-26
I can make it so it would split each record into dates, then subtract cancelled dates from the records then merge the intervals but since I have quite a lot of records, I find this very inefficient and am pretty sure that I am overlooking something simple.
The task you want to achieve is non trivial. A possible solution involves placing all From / To dates in an ordered sequence. The following UNPIVOT operation:
SELECT ID, EventDate, StartStop,
ROW_NUMBER() OVER (ORDER BY ID, EventDate, StartStop) AS EventRowNum,
IsCancel
FROM
(SELECT ID, IsCancel, [From], [To]
FROM Event) Src
UNPIVOT (
EventDate FOR StartStop IN ([From], [To])
) AS Unpvt
produces this result set:
ID EventDate StartStop EventRowNum IsCancel
--------------------------------------------------
1 2015-01-01 From 1 0
2 2015-01-03 From 2 1
2 2015-01-09 To 3 1
3 2015-01-27 From 4 1
3 2015-01-31 To 5 1
1 2015-01-31 To 6 0
Using a CTE, you can subsequently simulate LEAD function (available from SQL Server 2012 onwards) in order to place in a single record the current and the next date from the sequence above:
;WITH StretchEventDates AS
(
-- above query goes here
), CTE AS
(
SELECT s.ID, s.EventDate, s.StartStop, s.IsCancel,
sLead.EventDate As LeadEventDate, sLead.StartStop AS LeadStartStop, sLead.IsCancel AS LeadIsCancel
FROM StretchEventDates AS s
LEFT JOIN StretchEventDates AS sLead ON s.EventRowNum + 1 = sLead.EventRowNum
)
The above produces the following result set:
ID EventDate StartStop IsCancel LeadEventDate LeadStartStop LeadIsCancel
--------------------------------------------------------------------------------------
1 2015-01-01 From 0 2015-01-03 From 1
2 2015-01-03 From 1 2015-01-09 To 1
2 2015-01-09 To 1 2015-01-27 From 1
3 2015-01-27 From 1 2015-01-31 To 1
3 2015-01-31 To 1 2015-01-31 To 0
1 2015-01-31 To 0 NULL NULL NULL
Using CASE statements you can filter these records in order to get the desired output.
Putting it all together:
;WITH StretchEventDates AS
(
SELECT ID, EventDate, StartStop,
ROW_NUMBER() OVER (ORDER BY EventDate, StartStop) AS EventRowNum,
IsCancel
FROM
(SELECT ID, IsCancel, [From], [To]
FROM Event) Src
UNPIVOT (
EventDate FOR StartStop IN ([From], [To])
) AS Unpvt
), CTE AS
(
SELECT s.ID, s.EventDate, s.StartStop, s.IsCancel,
sLead.EventDate As LeadEventDate, sLead.StartStop AS LeadStartStop, sLead.IsCancel AS LeadIsCancel
FROM StretchEventDates AS s
LEFT JOIN StretchEventDates AS sLead ON s.EventRowNum + 1 = sLead.EventRowNum
), CTE_FINAL AS
(SELECT *,
CASE WHEN StartStop = 'From' AND IsCancel = 0 THEN EventDate
WHEN StartStop = 'To' AND IsCancel = 1 THEN DATEADD(d, 1, EventDate)
END AS [From],
CASE WHEN LeadStartStop = 'From' AND LeadIsCancel = 1 THEN DATEADD(d, -1, LeadEventDate)
WHEN LeadStartStop = 'To' AND LeadIsCancel = 0 THEN LeadEventDate
END AS [To]
FROM CTE
)
SELECT ID, [From], [To]
FROM CTE_FINAL
WHERE [From] IS NOT NULL AND [To] IS NOT NULL AND [From] <= [To]
You may have to add additional CASEs in the query above to handle additional combinations of 'cancelations' following 'non-canceled' (and vice-versa) events.
With the data provided in the OP the above yields the following output:
ID From To
---------------------------
1 2015-01-01 2015-01-02
2 2015-01-10 2015-01-26
I have a table like this
MonthYear JobType JobID
01-2014 FullTime 1
01-2014 PartTime 2
02-2014 FullTime 3
03-2014 FullTime 4
04-2014 PartTime 5
04-2014 PartTime 6
04-2014 FullTime 7
I want to select the count of each job type grouped by MonthYear as follows.
MonthYear FullTime PartTime
01-2014 1 1
02-2014 1 0
03-2014 1 0
04-2014 1 2
Can anyone suggest how to achieve this?
Thanks.
SELECT MonthYear,
SUM(CASE WHEN JobType='FullTime' THEN 1 ELSE 0 END) as FullTime ,
SUM(CASE WHEN JobType='PartTime' THEN 1 ELSE 0 END) as PartTime
FROM t
GROUP BY MonthYear
Pivot solution:
SELECT
[MonthYear],
[FullTime],
[PartTime]
FROM
(values
('01-2014', 'FullTime',1),
('01-2014', 'PartTime',2),
('02-2014', 'FullTime',3),
('03-2014', 'FullTime',4),
('04-2014', 'PartTime',5),
('04-2014', 'PartTime',6),
('04-2014', 'FullTime',7)) x(MonthYear, JobType, JobID)
PIVOT (count(JobType)
for JobType
in([FullTime],[PartTime])
)as p
ORDER BY MonthYear