Sql ISNULL condition in Sql Pivot and Sql case - sql

I searched for many solutions on SO and elsewhere but couldn't quite understand how to write a query for my problem.
Anyway my query looks like below
SELECT * FROM
(
SELECT Id, Date, Name, Amount,
CASE
WHEN DATEDIFF(DAY,Date,GETDATE()) <=0
THEN 'Current'
WHEN DATEDIFF(DAY,Date,GETDATE()) <30
THEN 'Due30'
WHEN DATEDIFF(DAY,Date,GETDATE()) <60
THEN 'Due60'
ELSE 'Due90'
END AS [Age]
FROM Statement
WHERE (Amount <> 0)
) AS S
PIVOT
(
SUM(Amount)
FOR[Age] IN ([Current],[Due30],[Due60],[Due90])
) P
and the result looks like this
Id Date Name Current Due30 Due60 Due90
----------- ---------- --------------------------------------------
1 2016-04-03 Alan NULL NULL NULL 110.00
2 2016-05-02 TC NULL NULL 30.00 NULL
where should i insert IsNull condition to be able to remove the null in the result and add a zero there.
I tried inserting IsNull in the pivot query but we all know that is not meant to work

You have to add it repetitively in the final SELECT, when you replace the SELECT * (which should only exist in ad-hoc queries or EXISTS tests) with the column list:
SELECT
Id,
Date,
Name,
COALESCE([Current],0) as [Current],
COALESCE(Due30,0) as Due30,
COALESCE(Due60,0) as Due60,
COALESCE(Due90,0) as Due90
FROM
(
SELECT Id, Date, Name, Amount,
CASE
WHEN DATEDIFF(DAY,Date,GETDATE()) <=0
THEN 'Current'
WHEN DATEDIFF(DAY,Date,GETDATE()) <30
THEN 'Due30'
WHEN DATEDIFF(DAY,Date,GETDATE()) <60
THEN 'Due60'
ELSE 'Due90'
END AS [Age]
FROM Statement
WHERE (Amount <> 0)
) AS S
PIVOT
(
SUM(Amount)
FOR[Age] IN ([Current],[Due30],[Due60],[Due90])
) P
I've also used COALESCE since it's generally the preferred option (ANSI standard, extends to more than two arguments, applies normal type precedence rules) instead of ISNULL.

SELECT Id
, [Date]
, Name
, [Current] = SUM(CASE WHEN val <= 0 THEN Amount ELSE 0 END)
, Due30 = SUM(CASE WHEN val < 30 THEN Amount ELSE 0 END)
, Due60 = SUM(CASE WHEN val < 60 THEN Amount ELSE 0 END)
, Due90 = SUM(CASE WHEN val >= 60 THEN Amount ELSE 0 END)
FROM dbo.[Statement] t
CROSS APPLY (
SELECT val = DATEDIFF(DAY, [Date], GETDATE())
) s
WHERE Amount <> 0
GROUP BY Id, [Date], Name

Related

CASE WHEN condition with MAX() function

There are a lot questions on CASE WHEN topic, but the closest my question is related to this How to use CASE WHEN condition with MAX() function query which has not been resolved.
Here is some of my sample data:
date
debet
2022-07-15
57190.33
2022-07-14
815616516.00
2022-07-15
40866.67
2022-07-14
1221510.00
So, I want to all records for the last two dates and three additional columns: sum(sales) for the previous day, sum for the current day and the difference between them:
SELECT
[debet],
[date] ,
SUM( CASE WHEN [date] = MAX(date) THEN [debet] ELSE 0 END ) AS sum_act,
SUM( CASE WHEN [date] = MAX(date) - 1 THEN [debet] ELSE 0 END ) AS sum_prev ,
(
SUM( CASE WHEN [date] = MAX(date) THEN [debet] ELSE 0 END )
-
SUM( CASE WHEN [date] = MAX(date) - 1 THEN [debet] ELSE 0 END )
) AS diff
FROM
Table
WHERE
[date] = ( SELECT MAX(date) FROM Table WHERE date < ( SELECT MAX(date) FROM Table) )
OR
[date] = ( SELECT MAX(date) FROM Table WHERE date = ( SELECT MAX(date) FROM Table ) )
GROUP BY
[date],
[debet]
Further, of course, it informs that I can't use the aggregate function inside CASE WHEN. Now I use this combination: sum(CASE WHEN [date] = dateadd(dd,-3,cast(getdate() as date)) THEN [debet] ELSE 0 END). But here every time I need to make an adjustment for weekends and holidays. The question is, is there any other way than using 'getdate' in 'case when' Statement to get max date?
Expected result:
date
sum_act
sum_prev
diff
2022-07-15
97190.33
0.00
97190.33
2022-07-14
0.00
508769.96
-508769.96
You can use dense_rank() to filter the last 2 dates in your table. After that you can use either conditional case expression with sum() to calculate the required value
select [date],
sum_act = sum(case when rn = 1 then [debet] else 0 end),
sum_prev = sum(case when rn = 2 then [debet] else 0 end),
diff = sum(case when rn = 1 then [debet] else 0 end)
- sum(case when rn = 2 then [debet] else 0 end)
from
(
select *, rn = dense_rank() over (order by [date] desc)
from tbl
) t
where rn <= 2
group by [date]
db<>fiddle demo
Two steps:
Get the sums for the last three dates
Show the results for the last two dates.
Well, we could also get all daily sums in step 1, but we just need the last three in order to calculate the sums for the last two days, so why aggregate more data than necessary?
Here is the query. You may have to put the date column name in brackets in SQL Server, as date is a keyword in SQL.
select top(2)
date,
sum_debit_current,
sum_debit_previous,
sum_debit_current - sum_debit_previous as diff
(
select
date,
sum(debet) as sum_debit_current,
lag(sum(debet)) over (order by date) as sum_debit_previous
from table
where date in (select distinct top(3) date from table order by date desc)
group by date
)
order by date desc;
(SQL Server uses TOP(n) instead of standard SQL FETCH FIRST 3 ROWS and while SELECT DISTINCT TOP(3) date looks like "get the top 3 rows, then apply distinct on their date", it is really "apply distinct on the dates, then get the top 3" like in standard SQL.)

Using a case column within another case in select clause

I have a select clause with a case statement and I need to create another case statement comparing the column created by the previous case statement. Something like this:
select client
,discount
,(case when sales_avg>10000 then 30
when sales_avg>5000 then 20
else 0 end) discount_rule
,(case when discount < discount_rule then 1 else 0 end) status
from sales;
I get a message that discount_rule is unknown. How can I accomplish that?
You can use a Common Table Expression (CTE) and reference a CTE within a CTE as:
with CTE_discount_rule as
(
select client,
discount,
(case when sales_avg>10000 then 30
when sales_avg>5000 then 20
else 0 end) as discount_rule
from sales
),
CTE_Final_Status as
(
select client,
discount,
discount_rule,
(case when discount < discount_rule then 1 else 0 end) as status
from CTE_discount_rule
)
select * from CTE_Final_Status;
The simplest way is to use a subquery that returns the column discount_rule:
select t.client, t.discount, t.discount_rule,
case
when discount < discount_rule then 1
else 0
end status
from (
select client, discount,
case
when sales_avg > 10000 then 30
when sales_avg > 5000 then 20
else 0
end discount_rule
from sales
) t

MSSQL Group by and Select rows from grouping

I'm trying to figure out if what I'm trying to do is possible. Instead of resorting to multiple queries on a table, I wanted to group the records by business date and id then group by the id and select one date for a field and another date for the other field.
SELECT
*
{AMOUNT FROM DATE}
{AMOUNT FROM OTHER DATE}
FROM (
SELECT
date,
id,
SUM(amount) AS amount
FROM
table
GROUP BY id, date
AS subquery
GROUP BY id
It seems that you're looking to do a pivot query. I usually use cross tabs for this. Based on the query you posted, it could look like:
SELECT
id,
SUM(CASE WHEN date = '20190901' THEN amount ELSE 0 END) AmountFromSept01,
SUM(CASE WHEN date = '20191001' THEN amount ELSE 0 END) AmountFromOct01
FROM (
SELECT
date,
id,
SUM(amount) AS amount
FROM
table
GROUP BY id, date
)AS subquery
GROUP BY id;
You could also use a CTE.
WITH CTE AS(
SELECT
date,
id,
SUM(amount) AS amount
FROM
table
GROUP BY id, date
)
SELECT
id,
SUM(CASE WHEN date = '20190901' THEN amount ELSE 0 END) AmountFromSept01,
SUM(CASE WHEN date = '20191001' THEN amount ELSE 0 END) AmountFromOct01
FROM CTE
GROUP BY id;
Or even be a rebel and do the operation directly.
SELECT
id,
SUM(CASE WHEN date = '20190901' THEN amount ELSE 0 END) AmountFromSept01,
SUM(CASE WHEN date = '20191001' THEN amount ELSE 0 END) AmountFromOct01
FROM CTE
GROUP BY id;
However, some people have tested for performance and found that pre-aggregating can improve performance.
If I understand you correctly, then you're just trying to pivot, but only with two particular dates:
select id,
date1 = sum(iif(date = '2000-01-01', amount, null)),
date2 = sum(iif(date = '2000-01-02', amount, null))
from [table]
group by id

Divide and sum in SQL

I got this code and in this code I do a sum of the slow and fast driver. My Problem is I must divide this sum with the normal driver. I donĀ“t know how I can do a division in this statement:
Select *
FROM (
Select date as Datetime, tevent.name as Event, level = case
when levelname = 'High' then 'High'
when levelname = 'Normal' then 'Normal'
when shiftname = 'Low' then 'Low'
end, SUM(value) as sum
from tCount inner join tEvent ON tCount.eventid = tevent.id
where Name in ('Drive Fast', 'Drive Slow')
and date > getdate() -1
and tevent.Name in ('E01','E02','E03','E04','E05','E06','E07','E08')
and CalName = 'Drive'
group by tevent.name, date, levelname
) as s
PIVOT
(
SUM(sum)
FOR Event IN (E01,E02,E03,E04,E05,E06,E07,E08)
) as p
order by Datetime, level
And Then I put the same Select statement with the normal driver :
... from tCount inner join tEvent ON tCount.eventid = tevent.id
where Name in ('drive normal') ...
And I would like to make a division like this:
(Sum('drive fast' + 'drive slow')/Sum('drive normal')) * 100
There is a simpler way to include different cases in different sums inside a SQL statement: sum a case, like in the below calculation of percent:
Select ...
, SUM(case Name
when 'drive fast' then Value
when 'drive slow' then value
else 0 end)
/ SUM(case Name
when 'drive normal' then value
else 0 end) * 100 as percentage
from ...
where ...
group by ...;
As I lack data to test this code, I created a query on the CARS table SAS delivers as training material, implementing the same principle.
select Cylinders
, sum(case origin when 'USA' then EngineSize
when 'Asia' then EngineSize
else 0.0 end)
/ sum(case origin when 'Europe' then EngineSize
else 0.0 end)
* 100 as percentage
from sasHelp.cars
where Cylinders in (4, 5, 6, 12)
group by Cylinders

Work out percentage count using SQL CASE statement

I have the following code which tells me which line items are in and out of SLA.
How can I turn that into a %, so for example when I add them together it will show 98% SLA Met.
,CASE
WHEN m.COMPLETED_DT is NULL THEN ''
WHEN m.COMPLETED_DT <= m.SLA_ADJUSTED_DT THEN 'SLA Met'
WHEN m.SLA_ADJUSTED_DT IS NULL THEN 'SLA Met'
ELSE 'SLA Missed' END AS "SLA Desc"
If I had the result already, I think it would look something like...
SELECT (count(*) * 100 / (select count(*) FROM testtable)) AS YesSLA
FROM testtable where SLA='Yes';
I am not sure how to integrate that with my current statement, I don't believe I can reference the AS SLA Desc in a new statement.
Does this do what you want?
select 100 * avg(case when m.completed_dt <= m.SLA_ADJUSTED_DT or m.SLA_ADJUSTED_DT is null
then 1.0 else 0
end)
from testtable
where SLA = 'Yes';
The code below calculates the % met SLA out of 100 by counting only values that met SLA and then dividing by the total opportunities.
DECLARE #Data TABLE (COMPLETED_DT DATETIME, SLA_ADJUSTED_DT DATETIME)
INSERT #Data VALUES ('5/5/2014', '5/6/2014'), ('5/6/2014', '5/6/2014'), ('5/7/2014', '5/6/2014')
SELECT
CONVERT(FLOAT, SUM(CASE WHEN COMPLETED_DT <= SLA_ADJUSTED_DT THEN 1 ELSE 0 END)) * 100 / COUNT(1) AS [% Met SLA]
FROM #Data
Output
% Met SLA
----------------------
66.6666666666667