Count in sql with group by - sql

Table name: mytable
Id username pizza-id pizza-size Quantity order-time
--------------------------------------------------------------
1 xyz 2 9 2 09:00 10/08/2014
2 abc 1 11 3 17:45 13/07/2014
This is mytable which has 6 columns. Id is int, username is varchar, order-time is datetime and rest are of integer datatype.
How to count the number of orders with the following pizza quantities: 1, 2, 3, 4, 5, 6,7 and above 7?
Using a T-SQL query.
It would be very helpful If any one could help to me find the solution.

Try this !
SELECT COUNT(ID),CASE WHEN QUANTITY<7 THEN QUANTITY ELSE 'ABOVE7' END AS QUANTITIES
FROM mytable
GROUP BY CASE WHEN QUANTITY<7 THEN QUANTITY ELSE 'ABOVE7' END

Try
Select CASE WHEN Quantity > 7 THEN 'OVER7' ELSE Cast(quantity as varchar) END Quantity,
COUNT(ID) NoofOrders
from mytable
GROUP BY CASE WHEN Quantity > 7 THEN 'OVER7' ELSE Cast(quantity as varchar) END
or
Select
SUM(Case when Quantity = 1 then 1 else 0 end) Orders1,
SUM(Case when Quantity = 2 then 1 else 0 end) Orders2,
SUM(Case when Quantity = 3 then 1 else 0 end) Orders3,
SUM(Case when Quantity = 4 then 1 else 0 end) Orders4,
SUM(Case when Quantity = 5 then 1 else 0 end) Orders5,
SUM(Case when Quantity = 6 then 1 else 0 end) Orders6,
SUM(Case when Quantity = 7 then 1 else 0 end) Orders7,
SUM(Case when Quantity > 7 then 1 else 0 end) OrdersAbove7
from mytable

If the requirement is like count the number of orders with different pizza quantities and represent count of orders as : 1, 2, 3, 4, 5, 6,7 and consider all above order counts in new category : 'above 7' then you can use window function as:
select case when totalorders < = 7 then cast(totalorders as varchar(10))
else 'Above 7' end as totalorders
, Quantity
from
(
select distinct count(*) over (partition by Quantity order by Quantity asc)
as totalorders,
Quantity
from mytable
) T
order by Quantity
DEMO
Edit: if the requirement is like count the number of orders with pizza quantities: 1, 2, 3, 4, 5, 6,7 and consider all other pizza quantities in new category : 'above 7' then you can write as:
select distinct
count(*) over (
partition by Quantity order by Quantity asc
) as totalorders,
Quantity
from (
select
case when Quantity < = 7 then cast(Quantity as varchar(20))
else 'Above 7' end as Quantity, id
from mytable ) T
order by Quantity
DEMO

Related

Adding a dummy identifier to data that varies by position and value

I am working on a project in SQL Server with diagnosis codes and a patient can have up to 4 codes but not necessarily more than 1 and a patient cannot repeat a code more than once. However, codes can occur in any order. My goal is to be able to count how many times a Diagnosis code appears in total, as well as how often it appears in a set position.
My data currently resembles the following:
PtKey
Order #
Order Date
Diagnosis1
Diagnosis2
Diagnosis3
Diagnosis 4
345
1527
7/12/20
J44.9
R26.2
NULL
NULL
367
1679
7/12/20
R26.2
H27.2
G47.34
NULL
325
1700
7/12/20
G47.34
NULL
NULL
NULL
327
1710
7/12/20
I26.2
J44.9
G47.34
NULL
I would think the best approach would be to create a dummy column here that would match up the diagnosis by position. For example, Diagnosis 1 with A, and Diagnosis 2 with B, etc.
My current plan is to rollup the diagnosis using an unpivot:
UNPIVOT ( Diag for ColumnALL IN (Diagnosis1, Diagnosis2, Diagnosis3, Diagnosis4)) as unpvt
However, this still doesn’t provide a way to count the diagnoses by position on a sales order.
I want it to look like this:
Diagnosis
Total Count
Diag1 Count
Diag2 Count
Diag3 Count
Diag4 Count
J44.9
2
1
1
0
0
R26.2
1
1
0
0
0
H27.2
1
0
1
0
0
I26.2
1
1
0
0
0
G47.34
3
1
0
2
0
You can unpivot using apply and aggregate:
select v.diagnosis, count(*) as cnt,
sum(case when pos = 1 then 1 else 0 end) as pos_1,
sum(case when pos = 2 then 1 else 0 end) as pos_2,
sum(case when pos = 3 then 1 else 0 end) as pos_3,
sum(case when pos = 4 then 1 else 0 end) as pos_4
from data d cross apply
(values (diagnosis1, 1),
(diagnosis2, 2),
(diagnosis3, 3),
(diagnosis4, 4)
) v(diagnosis, pos)
where diagnosis is not null;
Another way is to use UNPIVOT to transform the columns into groupable entities:
SELECT Diagnosis, [Total Count] = COUNT(*),
[Diag1 Count] = SUM(CASE WHEN DiagGroup = N'Diagnosis1' THEN 1 ELSE 0 END),
[Diag2 Count] = SUM(CASE WHEN DiagGroup = N'Diagnosis2' THEN 1 ELSE 0 END),
[Diag3 Count] = SUM(CASE WHEN DiagGroup = N'Diagnosis3' THEN 1 ELSE 0 END),
[Diag4 Count] = SUM(CASE WHEN DiagGroup = N'Diagnosis4' THEN 1 ELSE 0 END)
FROM
(
SELECT * FROM #x UNPIVOT (Diagnosis FOR DiagGroup IN
([Diagnosis1],[Diagnosis2],[Diagnosis3],[Diagnosis4])) up
) AS x GROUP BY Diagnosis;
Example db<>fiddle
You can also manually unpivot via UNION before doing the conditional aggregation:
SELECT Diagnosis, COUNT(*) As Total Count
, SUM(CASE WHEN Position = 1 THEN 1 ELSE 0 END) As [Diag1 Count]
, SUM(CASE WHEN Position = 2 THEN 1 ELSE 0 END) As [Diag2 Count]
, SUM(CASE WHEN Position = 3 THEN 1 ELSE 0 END) As [Diag3 Count]
, SUM(CASE WHEN Position = 4 THEN 1 ELSE 0 END) As [Diag4 Count]
FROM
(
SELECT PtKey, Diagnosis1 As Diagnosis, 1 As Position
FROM [MyTable]
UNION ALL
SELECT PtKey, Diagnosis2 As Diagnosis, 2 As Position
FROM [MyTable]
WHERE Diagnosis2 IS NOT NULL
UNION ALL
SELECT PtKey, Diagnosis3 As Diagnosis, 3 As Position
FROM [MyTable]
WHERE Diagnosis3 IS NOT NULL
UNION ALL
SELECT PtKey, Diagnosis4 As Diagnosis, 4 As Position
FROM [MyTable]
WHERE Diagnosis4 IS NOT NULL
) d
GROUP BY Diagnosis
Borrowing Aaron's fiddle, to avoid needing to rebuild the schema from scratch, and we get this:
https://dbfiddle.uk/?rdbms=sqlserver_2019&fiddle=d1f7f525e175f0f066dd1749c49cc46d

Oracle SELECT statement with GROUP BY and multiple WHERE clauses

I'm having trouble with a select query. See sample data below. I want to select the Sku records where there is no stock quantity for warehouse id 1, but there is stock quantity for warehouse id 2 & 3. Not sure what I'm doing wrong?
SAMPLE TABLE DATA
Sku WhseId Qty
============================
ABC-123 1 6
ABC-123 2 3
ABC-123 3 2
XYZ-789 1 0
XYZ-789 2 1
XYZ-789 3 3
DEF-456 1 0
DEF-456 2 0
DEF-456 3 3
QUERY
SELECT Sku, WhseId, Qty
FROM PRODUCTS
WHERE (WhseId = 1 AND Qty < 1)
AND (WhseId = 2 AND Qty > 0
AND (WhseId = 3 AND Qty > 0)
GROUP BY Sku, WhseId, Qty
DESIRED RESULT
Sku WhseId Qty
============================
XYZ-789 1 0
XYZ-789 2 1
XYZ-789 3 3
I think you actually want to use EXISTS for this:
SELECT Sku, WhseId, Qty
FROM PRODUCTS p
WHERE EXISTS
(SELECT 1
FROM PRODUCTS p2
WHERE p.sku = p2.sku
AND p2.whseid = 1
AND p2.qty = 0)
AND EXISTS
(SELECT 1
FROM PRODUCTS p3
WHERE p.sku = p3.sku
AND p3.whseid = 2
AND p3.qty > 0)
AND EXISTS
(SELECT 1
FROM PRODUCTS p4
WHERE p.sku = p4.sku
AND p4.whseid = 3
AND p4.qty > 0)
Use aggregation and a having clause:
SELECT Sku
FROM PRODUCTS
GROUP BY Sku
HAVING SUM(CASE WHEN WhseId = 1 AND Qty < 1 THEN 1 ELSE 0 END) > 0 AND
SUM(CASE WHEN WhseId = 2 AND Qty > 0 THEN 1 ELSE 0 END) > 0 AND
SUM(CASE WHEN WhseId = 3 AND Qty > 0 THEN 1 ELSE 0 END) > 0;
SELECT
Sku,
WhseId,
Qty
FROM
(
SELECT
PRODUCTS.*,
SUM(CASE WHEN WhseId = 1 THEN Qty END) OVER (PARTITION BY Sku) AS whse1_qty,
SUM(CASE WHEN WhseId = 2 THEN Qty END) OVER (PARTITION BY Sku) AS whse2_qty,
SUM(CASE WHEN WhseId = 3 THEN Qty END) OVER (PARTITION BY Sku) AS whse3_qty
FROM
PRODUCTS
)
pivotted
WHERE
whse1_qty < 1
AND whse2_qty > 0
AND whse3_qty > 0
A simple solution:
select sku, whseid, qty
from etst
where sku = 'XYZ-789' and ((whseid = 1 and qty < 1)
or (whseid = 2 and qty > 0)
or (whseid = 3 and qty > 0))
group by sku, whseid, qty;
CREATE VIEW get_skus_2 AS
SELECT Sku
FROM PRODUCTS
WHERE Qty>0 AND WhseId=2;
CREATE VIEW get_skus_3 AS
SELECT Sku
FROM PRODUCTS
WHERE Qty>0 AND WhseId=3;
SELECT Sku s, WhseId, Qty
FROM get_skus_2 g2 JOIN get_skus_3 g3 ON g2.Sku = g3.Sku
WHERE s IN (
SELECT Sku
FROM PRODUCTS
WHERE Qty=0 AND WhseId=1);
How about combining IN with a GROUP BY on Sku?
SELECT Sku, WhseId, Qty
FROM PRODUCTS
WHERE Sku IN (
SELECT Sku
FROM PRODUCTS
WHERE WhseId IN (1, 2, 3)
GROUP BY Sku
HAVING MAX(CASE WHEN WhseId = 1 THEN Qty END) = 0
AND MAX(CASE WHEN WhseId = 2 THEN Qty END) > 0
AND MAX(CASE WHEN WhseId = 3 THEN Qty END) > 0
)
ORDER BY Sku, WhseId;
Result:
Sku WhseId Qty
------- ------ ---
XYZ-789 1 0
XYZ-789 2 1
XYZ-789 3 3
SQL Fiddle

Mutually exclusive counts in SQL

The table that I need to query looks like this
ID - Account - Product
1 - 002 - Bike
2 - 003 - Bike
4 - 003 - Motor
5 - 004 - Car
I need to be able to retrieve the number of accounts that purchased the each of the products and combinations of the products, like this
Bike | Car | Motor | Bike&Car | Bike&Motor | Car&Motor | Bike&Car&Motor
Note that an account that purchased a combination of products will be counted as 1.
Please help me in retrieving this data.
You can do this using two levels of aggregation. One method puts the values on different rows:
select has_bike, has_motor, has_car, count(*)
from (select account,
max(case when product = 'bike' then 1 else 0 end) as has_bike,
max(case when product = 'motor' then 1 else 0 end) as has_motor,
max(case when product = 'car' then 1 else 0 end) as has_car
from t
group by account
) t
group by has_bike, has_motor, has_car;
Or in columns:
select sum(has_bike * (1 - has_motor) * (1 - has_car)) as has_only_bike,
sum((1 - has_bike) * has_motor * (1 - has_car)) as has_only_motor,
sum((1 - has_bike) * (1 - has_motor) * has_car) as has_only_car,
. . .
from (select account,
max(case when product = 'bike' then 1 else 0 end) as has_bike,
max(case when product = 'motor' then 1 else 0 end) as has_motor,
max(case when product = 'car' then 1 else 0 end) as has_car
from t
group by account
) t;
If you only have a limited set of Products, then you can use this:
-- Create sample data
CREATE TABLE #tbl(
ID INT,
Account VARCHAR(10),
Product VARCHAR(10)
);
INSERT INTO #tbl VALUES
(1, '002', 'Bike'),
(2, '003', 'Bike'),
(3, '003', 'Motor'),
(4, '004', 'Car');
WITH Cte AS(
SELECT t1.Account, a.Products
FROM #tbl t1
CROSS APPLY (
SELECT STUFF((
SELECT '&' + t2.Product
FROM #tbl t2
WHERE t2.Account = t1.Account
ORDER BY t2.Product
FOR XML PATH(''), type).value('.[1]','nvarchar(max)'),
1, 1, '') AS Products
) a
GROUP BY t1.Account, a.Products
)
SELECT
Bike = SUM(CASE WHEN Products = 'Bike' THEN 1 ELSE 0 END),
Car = SUM(CASE WHEN Products = 'Car' THEN 1 ELSE 0 END),
Motor = SUM(CASE WHEN Products = 'Motor' THEN 1 ELSE 0 END),
[Bike&Car] = SUM(CASE WHEN Products = 'Bike&Car' THEN 1 ELSE 0 END),
[Bike&Motor] = SUM(CASE WHEN Products = 'Bike&Motor' THEN 1 ELSE 0 END),
[Car&Motor] = SUM(CASE WHEN Products = 'Car&Motor' THEN 1 ELSE 0 END),
[Bike&Car&Motor] = SUM(CASE WHEN Products = 'Bike&Car&Motor' THEN 1 ELSE 0 END)
FROM Cte;
DROP TABLE #tbl; -- Remove sample data
The idea is to generate 1 row for each Account, together with a comma-delimited Products. If you execute the query inside the CTE, you will get:
Account Products
---------- ---------------
002 Bike
003 Bike&Motor
004 Car
With that, you can do a conditional aggregation. The above uses a static solution, if you do not know the number of Products, you may need to come up with a dynamic approach.
ONLINE DEMO

sql subquery that collects from 3 rows

I have a huge database with over 4 million rows that look like that:
Customer ID Shop
1 Asda
1 Sainsbury
1 Tesco
2 TEsco
2 Tesco
I need to count customers that within last 4 weeks had shopped in all 3 shops Tesco Sainsbury and Asda. Can you please advice if its possible to do it with subqueries?
This is an example of a "set-within-sets" subquery. You can solve it with aggregation:
select customer_id
from Yourtable t
where <shopping date within last four weeks>
group by customer_id
having sum(case when shop = 'Asda' then 1 else 0 end) > 0 and
sum(case when shop = 'Sainsbury' then 1 else 0 end) > 0 and
sum(case when shop = 'Tesco' then 1 else 0 end) > 0;
This structure is quite flexible. So if you wanted Asda and Tesco but not Sainsbury, then you would do:
select customer_id
from Yourtable t
where <shopping date within last four weeks>
group by customer_id
having sum(case when shop = 'Asda' then 1 else 0 end) > 0 and
sum(case when shop = 'Sainsbury' then 1 else 0 end) = 0 and
sum(case when shop = 'Tesco' then 1 else 0 end) > 0;
EDIT:
If you want a count, then use this as a subquery and count the results:
select count(*)
from (select customer_id
from Yourtable t
where <shopping date within last four weeks>
group by customer_id
having sum(case when shop = 'Asda' then 1 else 0 end) > 0 and
sum(case when shop = 'Sainsbury' then 1 else 0 end) > 0 and
sum(case when shop = 'Tesco' then 1 else 0 end) > 0
) t

Generating order statistics grouped by order total

Hopefully I can explain this correctly. I have a table of line orders (each line order consists of quantity of item and the price, there are other fields but I left those out.)
table 'orderitems':
orderid | quantity | price
1 | 1 | 1.5000
1 | 2 | 3.22
2 | 1 | 9.99
3 | 4 | 0.44
3 | 2 | 15.99
So to get order total I would run
SELECT SUM(Quantity * price) AS total
FROM OrderItems
GROUP BY OrderID
However, I would like to get a count of all total orders under $1 (just provide a count).
My end result I would like would be able to define ranges:
under $1, $1 - $3, 3-5, 5-10, 10-15, 15.. etc;
and my data to look like so (hopefully):
tunder1 | t1to3 | t3to5 | t5to10 | etc
10 | 500 | 123 | 5633 |
So that I can present a piechart breakdown of customer orders on our eCommerce site.
Now I can run individual SQL queries to get this, but I would like to know what the most efficient 'single sql query' would be. I am using MS SQL Server.
Currently I can run a single query like so to get under $1 total:
SELECT COUNT(total) AS tunder1
FROM (SELECT SUM(Quantity * price) AS total
FROM OrderItems
GROUP BY OrderID) AS a
WHERE (total < 1)
How can I optimize this? Thanks in advance!
select
count(case when total < 1 then 1 end) tunder1,
count(case when total >= 1 and total < 3 then 1 end) t1to3,
count(case when total >= 3 and total < 5 then 1 end) t3to5,
...
from
(
select sum(quantity * price) as total
from orderitems group by orderid
);
you need to use HAVING for filtering grouped values.
try this:
DECLARE #YourTable table (OrderID int, Quantity int, Price decimal)
INSERT INTO #YourTable VALUES (1,1,1.5000)
INSERT INTO #YourTable VALUES (1,2,3.22)
INSERT INTO #YourTable VALUES (2,1,9.99)
INSERT INTO #YourTable VALUES (3,4,0.44)
INSERT INTO #YourTable VALUES (3,2,15.99)
SELECT
SUM(CASE WHEN TotalCost<1 THEN 1 ELSE 0 END) AS tunder1
,SUM(CASE WHEN TotalCost>=1 AND TotalCost<3 THEN 1 ELSE 0 END) AS t1to3
,SUM(CASE WHEN TotalCost>=3 AND TotalCost<5 THEN 1 ELSE 0 END) AS t3to5
,SUM(CASE WHEN TotalCost>=5 THEN 1 ELSE 0 END) AS t5andup
FROM (SELECT
SUM(quantity * price) AS TotalCost
FROM #YourTable
GROUP BY OrderID
) dt
OUTPUT:
tunder1 t1to3 t3to5 t5andup
----------- ----------- ----------- -----------
0 0 0 3
(1 row(s) affected)
WITH orders (orderid, quantity, price) AS
(
SELECT 1, 1, 1.5
UNION ALL
SELECT 1, 2, 3.22
UNION ALL
SELECT 2, 1, 9.99
UNION ALL
SELECT 3, 4, 0.44
UNION ALL
SELECT 4, 2, 15.99
),
ranges (bound) AS
(
SELECT 1
UNION ALL
SELECT 3
UNION ALL
SELECT 5
UNION ALL
SELECT 10
UNION ALL
SELECT 15
),
rr AS
(
SELECT bound, ROW_NUMBER() OVER (ORDER BY bound) AS rn
FROM ranges
),
r AS
(
SELECT COALESCE(rf.rn, 0) AS rn, COALESCE(rf.bound, 0) AS f,
rt.bound AS t
FROM rr rf
FULL JOIN
rr rt
ON rt.rn = rf.rn + 1
)
SELECT rn, f, t, COUNT(*) AS cnt
FROM r
JOIN (
SELECT SUM(quantity * price) AS total
FROM orders
GROUP BY
orderid
) o
ON total >= f
AND total < COALESCE(t, 10000000)
GROUP BY
rn, t, f
Output:
rn f t cnt
1 1 3 1
3 5 10 2
5 15 NULL 1
, that is 1 order from $1 to $3, 2 orders from $5 to $10, 1 order more than $15.