I have table of customers operations:
date, client_id, gender
1 1 M
1 1 M
1 2 M
1 2 M
1 3 F
2 1 M
2 1 M
2 1 M
2 2 M
2 2 M
2 3 F
2 3 F
2 4 F
2 5 M
2 5 M
etc
Desired output is:
date, amount of males, (also need amount of females)
1 2 1
2 3 2
I need to group it by date, so i did it, then my goal is to find amount of each gender in each grouped group.
so i tried to do this to count amount of males:
sum(case when gender = 'M' then 1 else NULL end) as 'M%'
but its counted clients id 1 and 2 two times each, but i need to count it distinct.
On example above i expect this to return 2 because 2 male. But it return 4 because distinct construction doesnt work.
I tried this but it doesnt work and count '1' in result:
sum(distinct case when gender = 'M' then 1 else NULL end) as 'M%'
It's easier to count from the distinct rows of the table.
Also, use SQLite's feature to treat boolean expressions as 1 for true and 0 for false so you can sum them instead of using CASE expressions:
SELECT date,
SUM(gender = 'M') [amount of males],
SUM(gender = 'F') [amount of females]
FROM (SELECT DISTINCT date, client_id, gender FROM tablename)
GROUP BY date
See the demo.
You seem to want conditional count(distinct):
select date,
count(distinct case when gender = 'M' then client_id end) as count_m,
count(distinct case when gender = 'F' then client_id end) as count_f
from t
group by date;
Related
I have a table which stores purchase info from sellers and table contains rating to every purchase out of 5 stars. I want to have output Group By sellers and Each sellers good(Above 3) and bad(Below 4) ratings count
PurchaseId SellerId PurchaseRating
1 ABC 2
2 ABC 5
3 DEF 1
4 XYZ 2
5 DEF 4
7 ABC 3
OUTPUT
SellerId TotalOrders AvgRating Above3*(4&5) Below4*(1 to 3)
ABC 3 3.3 1 2
DEF 2 2.5 1 1
XYZ 1 2 0 1
For first 3 columns I am getting result using this
Select SellerId, Count(P.Id) TotalOrders, Avg(PurchaseRating) AvgRating,
CASE WHEN P.PurchaseRating >= 4 THEN 1 ELSE 0 END AS Above3*(4&5)
from
[dbo].[AmazonAbeOrdersPurchaseInfo] P
Where PurchaseRating is not null
Group by P.SellerId
order by TotalOrders desc
Unable to identify how to include case in group by clause.
You are trying to do conditional aggreation. The important thing is that you want the conditional expression inside the aggregate function:
select
sellerId,
count(*) totalOrders,
avg(purchaseRating) avgRating,
sum(case when purchaseRating > 3 then 1 else 0 end) above3,
sum(case when purchaseRating < 4 then 1 else 0 end) below4
from [dbo].[AmazonAbeOrdersPurchaseInfo]
where purchaseRating is not null
group by sellerId
order by totalOrders desc
Can anyone help me with the sql and sqlite query for the below condition. To be specific, i wanted to show the merged count of 2 categories.
**Table**
Category Sub_category
A 1
A 2
A 2
B 1
C 1
C 1
C 2
D 1
D 1
D 1
D 2
D 3
**Required Output**
Category Sub_category Count **condition(not part of o/p just instruction)**
A 1 1 -
A 2+ 2 -
B 1 1 -
C 1 2 -
C 2+ 1 -
D 1 3 -
D 2+ 1 should contain the count of 2 and more
i am able to achieve the same using below:
select Category,
count(CASE WHEN Sub_category = 1 THEN Sub_category END) AS '1',
count(CASE WHEN Sub_category >= 2 THEN Sub_category END) AS '2+'
from table
however output is little different hence looking for the first output only.
**Output**
Category 1 2+
A 1 2
B 1 0
C 1 2
D 3 2
Thanks in advance!
You want:
select Category,
(case when sub_category = 1 then '1' else '2+' end) as sub_category,
count(*)
from table
group by Category,
(case when sub_category = 1 then '1' else '2+' end);
That is, you want to put the sub category groups on rows, not as columns.
You are just missing one column. Add the last count without a filtering to get the total:
select Category,
count(CASE WHEN Sub_category = 1 THEN Sub_category END) AS '1',
count(CASE WHEN Sub_category >= 2 THEN Sub_category END) AS '2+',
count(*)
from table
group by Category, count(CASE WHEN Sub_category = 1 THEN Sub_category END), count(CASE WHEN Sub_category >= 2 THEN Sub_category END), count(*)
I have 2 tables I'm trying to join in a select query.
Table 1: Store, primary_key(id,store_num)
store_id store_num due_date manager_id
1 100 06-30-2024 user1
2 108 06-30-2018 user2
3 109 13-31-2014 user3
Table 2: Department, where status(A-applied,p-Pending)
store_id store_num dept_num status
1 100 201 A
1 100 202 A
1 100 203 P
1 100 204 A
1 100 205 P
1 100 206 A
Expecting to select store_id, store_num, due_date, manager_id, Applied count, pending count. The result is something looks like this.
store_id store_num due_date manager_id applied_count pending_count
1 100 06-30-2024 user1 4 2
I tried it and got where I am able to join and get it in multiple rows, But counts not working out for me. can some one help me how I can get the counts
select
store.store_id,
store.store_num,
store.due_date,
store.manager_id,
dept.status
from store as store
inner join department as dept on store.store_id = dept.store_id
and store.store_num = dept.store_num
Your query is half way done. You need to do an aggregation to get the values in different columns. This is a conditional aggregation, as shown here:
select s.store_id, s.store_num, s.due_date, s.manager_id,
sum(case when d.status = 'A' then 1 else 0 end) as Active_Count,
sum(case when d.status = 'P' then 1 else 0 end) as Pending_Count
from store s inner join
department as dept
on s.store_id = d.store_id and s.store_num = d.store_num
group by store.store_id, store.store_num, store.due_date, store.manager_id;
The expression:
sum(case when d.status = 'A' then 1 else 0 end) as Active_Count,
Is counting the rows where status = 'A'. It does so by assigning such rows a value of 1 and then summing up that value.
In the example table below, I'm trying to figure out a way to sum amount over id for all marks where mark 'C' doesn't exist within an id. When mark 'C' does exist in an id, I want the sum of amounts over that id, excluding the amount against mark 'A'. As illustration, my desired output is at the bottom. I've considered using partitions and the EXISTS command, but I'm having trouble conceptualizing the solution. If any of you could take a look and point me in the right direction, it would be greatly appreciated :)
sample table:
id mark amount
------------------
1 A 1
2 A 3
2 B 2
3 A 2
4 A 1
4 B 3
5 A 1
5 C 3
6 A 2
6 C 2
desired output:
id sum(amount)
-----------------
1 1
2 5
3 2
4 4
5 3
6 2
select
id,
case
when count(case mark when 'C' then 1 else null end) = 0
then
sum(amount)
else
sum(case when mark <> 'A' then amount else 0 end)
end
from sampletable
group by id
Here is my effort:
select id, sum(amount) from table t where not t.id = 'A' group by id
having id in (select id from table t where mark = 'C')
union
select id, sum(amount) from table t where t.id group by id
having id not in (select id from table t where mark = 'C')
SELECT
id,
sum(amount) AS sum_amount
FROM atable t
WHERE mark <> 'A'
OR NOT EXISTS (
SELECT *
FROM atable
WHERE id = t.id
AND mark = 'C'
)
GROUP BY
id
;
If I have a table
AgentID | IsNew | TeamID
1 N 1
2 Y 2
3 Y 2
4 N 2
5 Y 1
I want to return the following from a query:
Team | CountIsNew = N | CountIsNew = Y
1 1 1
2 1 2
Is there a way I can do this?
Using Oracle 10
SELECT team, SUM(DECODE(IsNew, 'N', 1, 0)), SUM(DECODE(IsNew, 'Y', 1, 0))
FROM mytable
GROUP BY
team
SELECT TeamId
, SUM(CASE WHEN IsNew = 'N' THEN 1 ELSE 0 END) AS CountIsNotNew
, SUM(CASE WHEN IsNew = 'Y' THEN 1 ELSE 0 END) AS CountIsNew
FROM Agent
GROUP BY TeamId
Yet another way - COUNT doesn't count NULLs (except for COUNT(*)):
SELECT TeamId,
COUNT(DECODE(IsNew,'N',1)) CountIsNotNew,
COUNT(DECODE(IsNew,'Y',1)) CountIsNew
FROM Agent
GROUP BY TeamId;
Or, if you prefer CASE:
SELECT TeamId,
COUNT(CASE IsNew WHEN 'N' THEN 1 END) CountIsNotNew,
COUNT(CASE IsNew WHEN 'Y' THEN 1 END) CountIsNew
FROM Agent
GROUP BY TeamId;
(note: the "1"s could be any literal value)