In the tab above you can see several records in some cases the Material column of the record n is equal to the record n + 1 and in the Material column Desc the record n is equal to the record n + 1.
But it does not make the columns List Price USD and RVS-ZSEG what happens is that I need to make a group by or combine the pairs in some registers but that they become complementary.
For example that in register
1 and 2 would be converted by combining the values of List Price USD and RVS ZSEG should be shown as image below
Try this:
SELECT Material, MaterialDesc
,MAX([D-Chain-Spec(Status)])[D-Chain-Spec(Status)]
,MAX([List Price USD])[List Price USD]
,MAX([RVS - ZSEG])[RVS - ZSEG]
FROM YourTable
GROUP BY Material, MaterialDesc
From what I see you just need a sum on List Price USD and RVS-ZSEG right?
SELECT Material, MaterialDesc,[D-Chain-Spec(Status)]
,SUM([List Price USD]) as [List Price USD]
,SUM([RVS - ZSEG]) as [RVS - ZSEG]
FROM Table
GROUP BY Material, MaterialDesc,[D-Chain-Spec(Status)]
Related
This question already has answers here:
Two SQL LEFT JOINS produce incorrect result
(3 answers)
Closed 12 months ago.
I am having some troubles with a count function. The problem is given by a left join that I am not sure I am doing correctly.
Variables are:
Customer_name (buyer)
Product_code (what the customer buys)
Store (where the customer buys)
The datasets are:
Customer_df (list of customers and product codes of their purchases)
Store1_df (list of product codes per week, for Store 1)
Store2_df (list of product codes per day, for Store 2)
Final output desired:
I would like to have a table with:
col1: Customer_name;
col2: Count of items purchased in store 1;
col3: Count of items purchased in store 2;
Filters: date range
My query looks like this:
SELECT
DISTINCT
C_customer_name,
C.product_code,
COUNT(S1.product_code) AS s1_sales,
COUNT(S2.product_code) AS s2_sales,
FROM customer_df C
LEFT JOIN store1_df S1 USING(product_code)
LEFT JOIN store2_df S2 USING(product_code)
GROUP BY
customer_name, product_code
HAVING
S1_sales > 0
OR S2_sales > 0
The output I expect is something like this:
Customer_name
Product_code
Store1_weekly_sales
Store2_weekly_sales
Luigi
120012
4
8
James
100022
6
10
But instead, I get:
Customer_name
Product_code
Store1_weekly_sales
Store2_weekly_sales
Luigi
120012
290
60
James
100022
290
60
It works when instead of COUNT(product_code) I do COUNT(DSITINCT product_code) but I would like to avoid that because I would like to be able to aggregate on different timespans (e.g. if I do count distinct and take into account more than 1 week of data I will not get the right numbers)
My hypothesis are:
I am joining the tables in the wrong way
There is a problem when joining two datasets with different time aggregations
What am I doing wrong?
The reason as Philipxy indicated is common. You are getting a Cartesian result from your data thus bloating your numbers. To simplify, lets consider just a single customer purchasing one item from two stores. The first store has 3 purchases, the second store has 5 purchases. Your total count is 3 * 5. This is because for each entry in the first is also joined by the same customer id in the second. So 1st purchase is joined to second store 1-5, then second purchase joined to second store 1-5 and you can see the bloat. So, by having each store pre-query the aggregates per customer will have AT MOST, one record per customer per store (and per product as per your desired outcome).
select
c.customer_name,
AllCustProducts.Product_Code,
coalesce( PQStore1.SalesEntries, 0 ) Store1SalesEntries,
coalesce( PQStore2.SalesEntries, 0 ) Store2SalesEntries
from
customer_df c
-- now, we need all possible UNIQUE instances of
-- a given customer and product to prevent duplicates
-- for subsequent queries of sales per customer and store
JOIN
( select distinct customerid, product_code
from store1_df
union
select distinct customerid, product_code
from store2_df ) AllCustProducts
on c.customerid = AllCustProducts.customerid
-- NOW, we can join to a pre-query of sales at store 1
-- by customer id and product code. You may also want to
-- get sum( SalesDollars ) if available, just add respectively
-- to each sub-query below.
LEFT JOIN
( select
s1.customerid,
s1.product_code,
count(*) as SalesEntries
from
store1_df s1
group by
s1.customerid,
s1.product_code ) PQStore1
on AllCustProducts.customerid = PQStore1.customerid
AND AllCustProducts.product_code = PQStore1.product_code
-- now, same pre-aggregation to store 2
LEFT JOIN
( select
s2.customerid,
s2.product_code,
count(*) as SalesEntries
from
store2_df s2
group by
s2.customerid,
s2.product_code ) PQStore2
on AllCustProducts.customerid = PQStore2.customerid
AND AllCustProducts.product_code = PQStore2.product_code
No need for a group by or having since all entries in their respective pre-aggregates will result in a maximum of 1 record per unique combination. Now, as for your needs to filter by date ranges. I would just add a WHERE clause within each of the AllCustProducts, PQStore1, and PQStore2.
I am looking for a way to add up averages in SQL. Here is an example of the data I have:
product avg_price
phone 104.28
car 1000.00
And I'm looking to build something like this:
product avg_price
[all] 544.27
phone 104.28
car 1000.00
The way I'm currently doing it is to store the count and sum in two different columns, such as:
product cnt total
phone 203 20,304.32
car 404 304,323.30
And from that get the average. However, I was wondering if it is possible in SQL to just 'keep the fraction' and be able to add them as needed. For example:
product avg_price
[all] [add the fractions]
phone 20,304.32 / 203
car 304,323.30 / 404
Or do I need to use two columns in order to get an average of multiple aggregated rows?
You don't need 2 columns to get the average, but if you want to display as a fraction then you will need both numbers. They don't need to be in 2 columns though.
select product, sum(total) ||'/'||sum(count)
from table a
join table b on a.product=b.product
union
select product, total ||'/'||count
from table a
join table b on a.product=b.product;
I have a need to create a stock report, where I have article number in one stock table and Invoice number under which they were sold in another table.
Stock Table:
Select * from StockTable
result:
artno opening_Stock stock_received
30271472 1 50
Invoice Table:
Select * from InvoiceTable
result:
itemno invoicenumber QTYSold invoicedate
30271472 Inv_123 10 2018-10-06T00:00:00
30271472 Inv_234 20 2018-10-06T00:00:00
30271472 Inv_345 10 2018-10-06T00:00:00
30271472 Inv_567 10 2018-10-06T00:00:00
The Problem is that in Stock Table StockReceived is 50. Now this 50 Quantity can be sold to difference customers in multiple invoices.
My Objective is to show data in most presentation way and then query for that: a) Some option I can think of is to show all invoice numbers in comma saperated, Using XML Path or COALESCE..
b) Second option is to join two table and for each invoice number generate a new row, but in this case Opening_Stoc and Stock Received value will also repeat for each row.
c) Third is to generate dynamic columns for each invoice. Not even sure how to achive this..
Really confused, can somebody help me suggested the best possible way to present this to business and query to achive the same
Regards
Vipin
I have a query output showing a list of orders. Some orders might occupy more then one record in the query output if those orders consist of sub-orders.Each sub-order occupies a separate line in the output. There is the OrderID column which has the same value for all sub-orders in the output:
OrderID Sub-Order Price
1 1 100
1 2 50
2 1 30
3 1 50
I need to add a column "Discount" to the output and fill it by following rules:
If certain order has one sub-order - the discount is 10% of the Price
If certain order has more than one sub-order, the discount is 20% on all sub-orders'
My query is a UNION of two SELECTs.
I use mssql with ms sql studio
Use CASE and COUNT window function
SELECT OrderID, Sub-Order, Price,
CASE WHEN (count(*) OVER (PARTITION BY OrderID)) > 1
THEN Price * 0.8
ELSE Price * 0.9
END
FROM ( table or <query> )
I am currently trying to split one value with percentage column. But as most of percentages values are 1/3, I am not able to get aboslute 100% with two decimal points in the value. For example:
Product Supplier percentage totalvalue customer_split
decimal(15,14) (decimal(18,2) decimal(18,2)
-------- -------- ------------ --------------- ---------------
Product1 Supplier1 0.33 10.00 3.33
Product1 Supplier2 0.33 10.00 3.33
Product1 Supplier3 0.33 10.00 3.33
So, here we are missing 0.01 in the value column and suppliers would like to put this missing 0.01 value against any one of the supplier randomly. I have been trying to get this done in a two sets of SQLs with temporary tables, but is there any simple way of doing this. If possible how can I get 0.34 in the percentage column itself for one of the above rows? 0.01 is negligible value, but when the value column is 1000000000 it is significant.
It sounds like you're doing some type of "allocation" here. This is a common problem any time you are trying to allocate something from a higher granulartiy to a lower granularity, and you need to be able to re-aggregate to the total value correctly.
This becomes a much bigger problem when dealing with larger fractions.
For example, if I try to divide a total value of, say $55.30 by eight, I get a decimal value of $6.9125 for each of the eight buckets. Should I round one to $6.92 and the rest to $6.91? If I do, I will lose a cent. I would have to round one to $6.93 and the others to $6.91. This gets worse as you add more buckets to divide by.
In addition, when you start to round, you introduce problems like "Should 33.339 be rounded to 33.34 or 33.33?"
If your business logic is such that you just want to take whatever remainder beyond 2 significant digits may exist and add it to one of the dollar values "randomly" so you don't lose any cents, #Diego is on the right track with this.
Doing it in pure SQL is a bit more difficult. For starters, your percentage isn't 1/3, it's .33, which will yield a total value of 9.9, not 10. I would either store this as a ratio or as a high-precision decimal field (.33333333333333).
P S PCT Total
-- -- ------------ ------
P1 S1 .33333333333 10.00
P2 S2 .33333333333 10.00
P3 S3 .33333333333 10.00
SELECT
BaseTable.P, BaseTable.S,
CASE WHEN BaseTable.S = TotalTable.MinS
THEN BaseTable.BaseAllocatedValue + TotalTable.Remainder
ELSE BaseTable.BaseAllocatedValue
END As AllocatedValue
FROM
(SELECT
P, S, FLOOR((PCT * Total * 100)) / 100 as BaseAllocatedValue,
FROM dataTable) BaseTable
INNER JOIN
(SELECT
P, MIN(S) AS MinS,
SUM((PCT * Total) - FLOOR((PCT * Total * 100)) / 100) as Remainder,
FROM dataTable
GROUP BY P) as TotalTable
ON (BaseTable.P = TotalTable.P)
It appears your calculation is an equal distribution based on the total number of products per supplier. If it is, it may be advantageous to remove the percentage and instead just store the count of items per supplier in the table.
If it is also possible to store a flag indicating the row that should get the remainder value applied to it, you could assign based on that flag instead of randomly.
run this, it will give an idea on how you can solve your problem.
I created a table called orders just with an ID to be easy to understand:
create table orders(
customerID int)
insert into orders values(1)
go 3
insert into orders values(2)
go 3
insert into orders values(3)
go 3
these values represent the 33% you have
1 33.33
2 33.33
3 33.33
now:
create table #tempOrders(
customerID int,
percentage numeric(10,2))
declare #maxOrder int
declare #maxOrderID int
select #maxOrderID = max(customerID) from orders
declare #total numeric(10,2)
select #total =count(*) from orders
insert into #tempOrders
select customerID, cast(100*count(*)/#total as numeric(10,2)) as Percentage
from orders
group by customerID
update #tempOrders set percentage = percentage + (select 100-sum(Percentage) from #tempOrders)
where customerID =#maxOrderID
this code will basically calculate the percentage and the order with the max ID, then it gets the diference from 100 to the percentage sum and add it to the order with the maxID (your random order)
select * from #tempOrders
1 33.33
2 33.33
3 33.34
This should be an easy task using Windowed Aggregate Functions. You probably use them already for the calculation of customer_split:
totalvalue / COUNT(*) OVER (PARTITION BY Product) as customer_split
Now sum up the customer_splits and if there's a difference to total value add (or substract) it to one random row.
SELECT
Product
,Supplier
,totalvalue
,customer_split
+ CASE
WHEN COUNT(*)
OVER (PARTITION BY Product
ROWS UNBOUNDED PRECEDING) = 1 -- get a random row, using row_number/order you might define a specific row
THEN totalvalue - SUM(customer_split)
OVER (PARTITION BY Product)
ELSE 0
END
FROM
(
SELECT
Product
,Supplier
,totalvalue
,totalvalue / COUNT(*) OVER (PARTITION BY Product) AS customer_split
FROM dropme
) AS dt
After more than one trial and test i think i found better solution
Idea
Get Count of all(Count(*)) based on your conditions
Get Row_Number()
Check if (Row_Number() value < Count(*))
Then select round(curr_percentage,2)
Else
Get sum of all other percentage(with round) and subtract it from 100
This steps will select current percentage every time EXCEPT Last one will be
100 - the sum of all other percentages
this is part of my code
Select your_cols
,(Select count(*) from [tbl_Partner_Entity] pa_et where [E_ID] =#E_ID)
AS cnt_all
,(ROW_NUMBER() over ( order by pe.p_id)) as row_num
,Case when (
(ROW_NUMBER() over ( order by pe.p_id)) <
(Select count(*) from [tbl_Partner_Entity] pa_et where [E_ID] =#E_ID))
then round(([partnership_partners_perc]*100),2)
else
100-
((select sum(round(([partnership_partners_perc]*100),2)) FROM [dbo].
[tbl_Partner_Entity] PEE where [E_ID] =#E_ID and pee.P_ID != pe.P_ID))
end AS [partnership_partners_perc_Last]
FROM [dbo].[tbl_Partner_Entity] PE
where [E_ID] =#E_ID