I am trying to find the difference of expenses of previous and current month in sql.
I have a table like this
Date Amount Category
2/18/2015 100 Salary
2/12/2015 150 Rent
2/21/2015 200 Allowances
1/4/2015 200 Salary
1/17/2015 50 Rent
1/20/2015 100 Allowances
Now I want a result like this
Category CurrentMonthAmount PreviousMonthAmount Difference
Salary 100 200 100
Rent 150 50 100
Allowances 200 100 100
Try using conditional Aggregate
;WITH cte
AS (SELECT Category,
Max(CASE WHEN Month([date]) = Month(Getdate()) and year([date]) =year(getdate()) THEN amount END) CurrentMonthAmount,
Max(CASE WHEN Month([date]) = Month(Getdate()) - 1 and year([date]) =year(getdate()) THEN amount END) PreviousMonthAmount
FROM Yourtable
GROUP BY Category)
SELECT Category,
CurrentMonthAmount,
PreviousMonthAmount,
[Difference]=Abs(CurrentMonthAmount - PreviousMonthAmount)
FROM cte
SQLFIDDLE DEMO
Are you trying to do the computations within your SQL only or via some scripts like PHP.? Furthermore, can you state if you are choosing specific records for this operation (specific rows i mean). Give some more clarification
Related
I am using SQL and I would like this number '1000' to appear once per month. I have a record set which has the first of every month appearing multiple times. I would like the number '1000' to appear once only and then '0' for the remaining records until the next month appears. I would like the below please- maybe a case type statement/order parition by? I am using SQL Server 2018 ##SQLSERVER. Please see table below of how i would like the data to appear.
Many Thanks :)
Date
Amount
01/01/2022
1000
01/01/2022
0
01/01/2022
0
01/02/2022
1000
01/02/2022
0
01/02/2022
0
01/03/2022
1000
01/03/2022
0
Solution for your problem:
WITH CT1 AS
(
SELECT *,
ROW_NUMBER() OVER(PARTITION BY CONCAT(MONTH([Date]),YEAR([Date])) ORDER BY [Date]) as rn
FROM your_table
)
SELECT [Date],
CASE WHEN rn = 1 THEN 1000 ELSE 0 END AS Amount
FROM CT1;
Working Example: DB<>Fiddle Link
Given just a list of dates you could use row_number and a conditional expression to arbitrarily assign one row of each month a value of 1000
select *,
Iif(Row_Number() over(partition by Month(date) order by (select null)) = 1, 1000, 0) Amount
from t
order by [date], Amount desc;
I have a table that contains Transactions of Customers.
I should Find Customers That had have at least 2 transaction with amount>20000 in Three consecutive days each month.
For example , Today is 2022/03/12 , I should Gather Data Of Transactions From 2022/02/13 To 2022/03/12, Then check These Data and See If a Customer had at least 2 Transaction With Amount>=20000 in Three consecutive days.
For Example, Consider Below Table:
Id
CustomerId
Transactiondate
Amount
1
1
2022-01-01
50000
2
2
2022_02_01
20000
3
3
2022_03_05
30000
4
3
2022_03_07
40000
5
2
2022_03_07
20000
6
4
2022_03_07
30000
7
4
2022_03_07
30000
The Out Put Should be : CustomerId =3 and CustomerId=4
I write query that Find Customer For Special day , but i don't know how to find these customers in one month with out using loop.
the query for special day is:
With cte (select customerid, amount, TransactionDate,Dateadd(day,-2,TransactionDate) as PrevDate
From Transaction
Where TransactionDate=2022-03-12)
Select CustomerId,Count(*)
From Cte
Where
TransactionDate>=Prevdate and TransactionDate<=TransactionDate
And Amount>=20000
Group By CustomerId
Having count(*)>=2
Hi there are many options how to achieve this.
I think that easies (from perfomance maybe not) is using LAG function:
WITH lagged_days AS (
SELECT
ISNULL(LAG(Transactiondate) OVER(PARTITION BY CustomerID ORDER BY id),
LEAD(Transactiondate) OVER(PARTITION BY CustomerID ORDER BY id)) lagged_dt
,*
FROM Transaction
), valid_cust_base as (
SELECT
*
FROM lagged_days
WHERE DATEPART(MONTH, lagged) = DATEPART(MONTH, Transactiondate)
AND datediff(day, Transactiondate, lagged_dt) <= 3
AND Amount >= 20000
)
SELECT
CustomerID
FROM valid_cust_base
GROUP BY CustomerID
HAVING COUNT(*) >= 2
First I have created lagged TransactionDate over customer (I assume that id is incremental). Then I have Selected only transactions within one month, with amount >= 20000 and where date difference between transaction is less then 4 days. Then just select customers who had more than 1 transaction.
In LAG First value is always missing per Customer missing, but you still need to be able say: 1st and 2nd transaction are within 3 days. Thats why I am replacing first NULL value with LEAD. It doesn't matter if you use:
ISNULL(LAG(Transactiondate) OVER(PARTITION BY CustomerID ORDER BY id),
LEAD(Transactiondate) OVER(PARTITION BY CustomerID ORDER BY id)) lagged_dt
OR
ISNULL(LEAD(Transactiondate) OVER(PARTITION BY CustomerID ORDER BY id),
LAG(Transactiondate) OVER(PARTITION BY CustomerID ORDER BY id)) lagged_dt
The main goal is to have for each transaction closest TransactionDate.
Company_Name Amount Cumulative Total
---------------------------------------------
Company 6 100 100
Company 6 200 300
Company 6 150 450
Company 7 700 700
Company 7 1100 1800
Company 7 500 2300
How can I do cumulative sum group by company as shown in this example?
First, you need a column that specifies the ordering, because SQL tables represent unordered sets. Let me assume you have such a column.
Then the function is sum() as a window function:
select t.*,
sum(amount) over (partition by company order by <ordering col>)
from t;
Note: This does not return 0 for the "first" row for each company, so it really is a cumulative sum. For your logic, you need an additional conditional:
select t.*,
(case when row_number() over (partition by company order by <ordering col>) = 1
then 0
else sum(amount) over (partition by company order by <ordering col>)
end)
from t;
Let's assume there is a table as below structure
select Year, Month , customer, Category, Amount
from claim
I want to apply a discount for each month as shown in the table (green columns):
if the 'Cus X' total sales for brand and generic categories in JAN is greater than 15000, then apply a discount for only 'Brand' category of 2%
if it is greater than 20000 then apply a discount of 3%
and the same thing for other months and customers.
Is it possible to do that in SQL with a subquery or some functions that can help?
Please advise
You can use case .. when statement and analytical function as follows:
select Year, Month , customer, Category, Amount,
Case when category = 'Brand'
then
Case when total_sales > 15000 then '2%'
When total_sales > 20000 then '3%'
End
End as disc,
Case when category = 'Brand'
then
Case when total_sales > 15000 then 2*amount/100
When total_sales > 20000 then 3*amount/100
End
End disc_amount
From
(select Year, Month , customer, Category, Amount,
sum(case when category in ('Brand', 'Generic') then amount else 0 end)
over (partition by year, month, customer) as total_sales
from claim)
This is the input table:
Customer_ID Date Amount
1 4/11/2014 20
1 4/13/2014 10
1 4/14/2014 30
1 4/18/2014 25
2 5/15/2014 15
2 6/21/2014 25
2 6/22/2014 35
2 6/23/2014 10
There is information pertaining to multiple customers and I want to get a rolling sum across a 3 day window for each customer.
The solution should be as below:
Customer_ID Date Amount Rolling_3_Day_Sum
1 4/11/2014 20 20
1 4/13/2014 10 30
1 4/14/2014 30 40
1 4/18/2014 25 25
2 5/15/2014 15 15
2 6/21/2014 25 25
2 6/22/2014 35 60
2 6/23/2014 10 70
The biggest issue is that I don't have transactions for each day because of which the partition by row number doesn't work.
The closest example I found on SO was:
SQL Query for 7 Day Rolling Average in SQL Server
but even in that case there were transactions made everyday which accomodated the rownumber() based solutions
The rownumber query is as follows:
select customer_id, Date, Amount,
Rolling_3_day_sum = CASE WHEN ROW_NUMBER() OVER (partition by customer_id ORDER BY Date) > 2
THEN SUM(Amount) OVER (partition by customer_id ORDER BY Date ROWS BETWEEN 2 PRECEDING AND CURRENT ROW)
END
from #tmp_taml9
order by customer_id
I was wondering if there is way to replace "BETWEEN 2 PRECEDING AND CURRENT ROW" by "BETWEEN [DATE - 2] and [DATE]"
One option would be to use a calendar table (or something similar) to get the complete range of dates and left join your table with that and use the row_number based solution.
Another option that might work (not sure about performance) would be to use an apply query like this:
select customer_id, Date, Amount, coalesce(Rolling_3_day_sum, Amount) Rolling_3_day_sum
from #tmp_taml9 t1
cross apply (
select sum(amount) Rolling_3_day_sum
from #tmp_taml9
where Customer_ID = t1.Customer_ID
and datediff(day, date, t1.date) <= 3
and t1.Date >= date
) o
order by customer_id;
I suspect performance might not be great though.