id item_name cust_id
1 Rolex 5
2 Diamond 33
3 Hublop 1
4 Ring 9
5 Ruby 13
6 Rolex 33
7 Hublop 29
8 Ring 17
9 Belt 21
10 Diamond 9
12 Belt 33
13 Hublop 9
14 Brooch 9
From these table I have to write a query to find those cust_id who have buy all three 'diamond,brooch,ring'
without using intersection ( IN clause will also not work)
You can use sum with a case statement for each item to get how many of that item the client has bought, then filter only customers that have bought at least one of each type of product:
select cust_id from
(select cust_id,
sum(case when item_name = 'Diamond' then 1 else 0 end) as cntDiamond,
sum(case when item_name = 'Brooch' then 1 else 0 end) as cntBrooch,
sum(case when item_name = 'Ring' then 1 else 0 end) as cntRing
from table_name
group by cust_id) as t
where cntDiamond > 0 and cntBrooch > 0 and cntRing > 0
Fiddle
Related
Show two different sum columns based on another column.
For this table:
ID Item Quantity Location
1 1 10 A
2 1 10 B
3 1 10 A
4 2 10 A
5 2 10 A
6 2 10 B
7 3 10 A
8 3 20 A
I need to see the total quantities for both location A and location B (to compare which is higher), but only for items that have a location B:
Expected result:
Item Quantity A Quantity B
1 20 10
2 20 10
I've been trying this but getting errors:
SELECT st.item, st.qty ALIAS(stqty),
(SELECT SUM(dc.qty)
FROM table dc
WHERE st.item = dc.item) ALIAS(dcqty))
FROM table st
WHERE location ='b'
I can do this easily with two queries obviously, but I was hoping for a way to do it in one.
you can use a sum with case statement to do your pivot then a having to exclude rows with no total for b
here is the fiddle
https://www.db-fiddle.com/f/rS8fgvWoFxn879Utc2CKbu/0
select Item,
sum(case when Location = 'A' then Quantity else 0 end),
sum(case when Location = 'B' then Quantity else 0 end)
from myTable
group by Item
having sum(case when Location = 'B' then Quantity else 0 end) > 0
I have a table which has the following columns:
user_id - includes duplicates
product_id - includes duplicates
purchases - number of purchases of given product_id
My table looks somewhat like this:
user_id date product_id purchases
0 1 1 1 4
1 1 2 1 0
2 1 3 2 0
3 1 4 2 0
4 2 1 1 1
5 2 2 1 0
6 2 3 1 1
7 3 1 2 0
8 3 2 3 0
9 4 1 5 1
My goal is to calculate the following metric:
% of products that were purchased at least once, grouped by user
For example: user 1 had 2 products, one of them got purchased at least once, the other one did not get purchased at all. So the metric would be the number of products that got purchased at least once / number of all products per user: 1/2 * 100 = 50%
I have little SQL experience so I do not have any legitimate code that could be corrected.
My desired output would be like this:
user_id total_products products_with_purchases metric
0 1 2 1 50%
1 2 1 1 100%
2 3 2 0 0%
3 4 1 1 100%
I would appreciate seeing a good practice solution to this problem. Many thanks!
select
user_id,
count(distinct product_id) as total_products,
count(distinct case when purchases > 0 then product_id end) as products_with_purchases,
100.00 * count(distinct case when purchases > 0 then product_id end)
/ count(distinct product_id) as metric
from T as t
group by user_id
https://rextester.com/EDSY39439
You can do this all in one query but this is the type of situation where it is easier to understand with sub-queries -- sql optimizer should make it fast.
select
user_id,
total_products,
products_with_purchase,
(products_with_purchase / total_products) * 100 as metric
from (
select -- group by user to get totals
user_id,
count(product_id) as total_products,
sum(case when purchases > 0 then 1 else 0 end) as products_with_purchase
from ( -- group by user and product and get purchase items
SELECT user_id, product_id, sum(purchases) as purchases
FROM table
GROUP BY user_id, product_id
) X
group by user_id
) X2
I Am Mohit Sahni
you can solve the above problem with the below SQL Code:
select
user_id,
count(distinct product_id) as total_products,
sum(case when purchases = 0 then 0 else 1 end) as products_with_purchases,
((sum(case when purchases = 0 then 0 else 1 end))/count(distinct product_id))*100 as metric
from
table
group by
user_id
I have the following table
Cash_table
ID Cash Rates Amount
1 50 3 16
2 100 4 25
3 130 10 7
3 130 10 6
4 13 7 1.8
5 30 8 2.5
5 30 10 1
6 10 5 2
What I want as a result is to cumulate all the entries that have a Count(id)>1 like this:
ID New_Cash New_Rates New_Amount
1 50 3 16
2 100 4 25
3 130 10+10 130/(10+10)
4 13 7 1.8
5 30 8+10 30/(8+10)
6 10 5 2
So I only want to change the rows where Count(id)>1 and leave the rest like it was.
For the rows with count(id)>1 I want to sum up the rates and take the cash and divide it by the sum of the rates. The Rates alone aren't a problem since I can sum them up and group by id and get the desired result.
The problem is with the New_Amount column:
I am trying to do it with a case statement but it isn't working:
select id,
cash as new_cash,
sum(rates) as new_rates,
(case count(id)
when 1 then amount
else cash/sum(nvl(rates,null))
end) as new_amount
from Cash_table
group by id
As the cash value is always the same for an ID, you can group by that as well:
select id,
cash as new_cash,
sum(rates) as new_rates,
case count(id)
when 1 then max(amount)
else cash/sum(rates)
end as new_amount
from cash_table
group by id, cash
order by id
ID NEW_CASH NEW_RATES NEW_AMOUNT
---------- ---------- ---------- ----------
1 50 3 16
2 100 4 25
3 130 20 6.5
4 13 7 1.8
5 30 18 1.66666667
6 10 5 2
The first branch of the case expression needs an aggregate because you aren't grouping by amount; and the sum(nvl(rates,null)) can just be sum(rates). If you're expecting any null rates then you need to decide how you want the amount to be handled, but nvl(rates,null) isn't doing anything.
You can do the same thing without a case expression if you prefer, manipulating all the values - which might be more expensive:
select id,
cash as new_cash,
sum(rates) as new_rates,
sum(amount * rates)/sum(rates) as new_amount
from cash_table
group by id, cash
order by id
I need some help to solve this query. I have a table which contains the ages of the passengers who are going to stay in a room which is mentioned below:
Age RoomId
----- ---
1 1
12 1
8 1
19 1
3 2
12 2
18 2
21 3
Also, I have properties table which contains the maximum age of the child and maximum age of the infant. Based on the age of the passenger, I need to segregate them to adult, child, and infant to each of the properties.
Properties table structure
Property Id Maximum_child_age Maximum_infant_age
-------------------------------------------------
1 11 2
Desired output
RoomId Adult Child Infant PropertyId
--------------------------------
1 2 1 1 1
2 2 1 0 1
3 1 0 0 1
Use conditional aggregation :
SELECT
SUM(CASE WHEN pas.age > ppt.Maximum_child_age THEN 1 ELSE 0 END) AS Adult,
SUM(CASE WHEN pas.age BETWEEN Maximum_infant_age AND ppt.Maximum_child_age THEN 1 ELSE 0 END) AS Child,
SUM(CASE WHEN pas.age < ppt.Maximum_infant_age THEN 1 ELSE 0 END) AS Infant,
ppt.id
FROM
passengers pas
CROSS JOIN properties ppt
GROUP BY ppt.id
Cross join the properties and then do conditional aggregation.
SELECT count(CASE
WHEN pa.ages > pr.maximum_child_age THEN
1
END) adult,
count(CASE
WHEN pa.ages > pr.maximum_infant_age
AND pa.ages <= pr.maximum_child_age THEN
1
END) child,
count(CASE
WHEN pa.ages <= pr.maximum_infant_age THEN
1
END) infant,
pr.propertyid
FROM passengers pa
CROSS JOIN properties pr
GROUP BY pr.propertyid;
I'm looking at auction data in the following form:
product auction_id bid_value is_winning_bid reject_reason
iPhone 123 5 1 0
iPhone 123 3 0 1
iPhone 123 2 0 200
iPad 456 1 0 1
iPad 456 10 0 1
iPhone 789 2 0 200
iPhone 999 10 0 1
I want to count the number of auctions where one of the bids had a reject_reason = 200 and none of the bids has a is_winning_bid = 1, grouped by product.The data set is large so I don't want to have the output grouped by auction_id.
The table above should result in:
product total_auctions count_unfilled_auctions count_unfilled_auctions_200
iPhone 3 2 1
iPad 1 1 0
I think you just need two levels of aggregation, one at the auction level and one at the product level:
select product, count(*) as total_auctions,
sum(1 - has_winning_bid) as unfulfilled_auctions,
sum(case when cnt_reject_200 > 0 and has_winning_bid = 1 then 1 else 0 end) as unfulfilled_auctions_200
from (select auction_id, product,
max(is_winning_bid) as has_winning_bid,
sum(case when reject_reason = 200 then 1 else 0 end) as cnt_reject_200
from auctiondata ad
group by auction_id, product
) ad
group by product;