I have a table in which I want to calculate some row values based on another row value conditionally.
The table looks like this
LevelID StepID Amt Type BItem PItem
-------------------------------------------------
6 3 18000 Fixed BS
6 3 10 Percent BS UA
6 3 10 Percent BS TA
6 3 3.5 Percent BS Tx
7 3 24000 Fixed BS
7 3 10 Percent BS UA
7 3 10 Percent BS TA
7 3 3.5 Percent BS Tx
The aim is to calculate the Amt value of rows with Type = 'Percent' Where Bitem = PItem and LevelID and StepID are the same for both BItem and PItem
So a sample output would be
LevelID StepID Amt Type BItem PItem Total
----------------------------------------------------------
6 3 18000 Fixed BS 18,000
6 3 10 Percent BS UA 1,800
6 3 10 Percent BS TA 1,800
6 3 3.5 Percent BS Tx 630
7 3 24000 Fixed BS 24,000
7 3 10 Percent BS UA 2,400
7 3 10 Percent BS TA 2,400
7 3 3.5 Percent BS Tx 840
I have been trying different SQL statements, but haven't got any reasonable output yet
To look up values, use a correlated subquery:
SELECT *,
CASE Type
WHEN 'Fixed' THEN Amt
ELSE (SELECT B.Amt * ATable.Amt / 100
FROM ATable AS B
WHERE B.Type = 'Fixed'
AND B.LevelID = ATable.LevelID
AND B.StepID = ATable.StepID
AND B.PItem = ATable.BItem)
END AS Total
FROM ATable;
Related
I have two tables
Table 'Sales Line' (SL)
Date "Entry No" Item Qty
(PK)
01/01/2018 1 ABC 1
01/02/2018 2 ABC 2
03/02/2018 3 DEF 1
04/06/2018 4 DEF 3
01/01/2019 5 DEF 1
06/06/2019 6 ABC 2
Table 'Cost Breakdown' (CB)
"SL Entry No" Cost
(FK)
1 10
1 15
2 5
3 25
4 10
4 10
5 5
6 5
6 10
Expected result:
Item Tot_Qty Tot_Cost
ABC 3 30
DEF 4 45
Note that I'm only interested on transaction in 2018 only.
How do I aggregate Tot_Qty and Tot_Cost ? Thank you
With query suggested by #GMB, the result is :
Item Tot_Qty Tot_Cost
ABC 4 30
DEF 7 45
so, line from SL will be repeated as many as correponding number of lines in CB.
You can join both tables, filter on the date, and aggregate by item:
select sl.item, sum(sl.qty) tot_qty, sum(sl.qty * cb.cost) tot_cost
from sales_line sl
inner join cost_breakdown cb on cb.sl_entry_no = sl.entry_no
where sl.date >= '20180101' and sl.date < '20190101'
group by sl.item
I am trying to build a query to create a basket analysis of products based on their type grouping. They have two levels of grouping beyond the product ids.
Dept level
1
2
3
4
and buying group level
MA
M
MC
WA
W
WC
KA
KC
K
the hierarchy is
1 > W, WC
2 > M, MC
3 > K, KC
4 > MA, KA, WA
right now the query I have
Select
i.buying_group,
Sum(d.sales),
Sum(d.units),
count(distinct d.trans_nbr) transaction_count
From
sales_details d, item_data i, (select trans_nbr from sales_details where item_dept = 1 group by trans_nbr) main_group
Where
d.trans_nbr = main_group.trans_nbr
d.item_nbr = i.item_nbr
group by i.buying_group;
Right now I get the data that I need for most of the buying groups but because this is being run at the dept level it does not give me the correct basket information for W and WC. Is there a way to do this at the dept level that would show if the customer bought something from either of these groups and had the other in their basket without double counting it?
the results at the moment are something like this
buyyin_group Sum(sales) Sum(units) transaction_count
MA 100 5 4
M 75 3 3
MC 56 1 1
WA 48 3 2
W 250 6 6
WC 200 9 9
KA 164 7 5
KC 400 12 7
K 521 14 12 `
Hi I have a table below;
ID length
1 1050
1 1000
1 900
1 600
2 545
2 434
3 45
3 7
4 5
I need an SQL code to make the below table
ID IDK length
1 1 1050
1 2 1000
1 3 900
1 4 600
2 1 545
2 2 434
3 1 45
3 2 7
4 1 5
IDK is the new column to reindexing the same ID according to ascending order of length.
Thank you very much
This is a pain in MS Access. Here is one way using a correlated subquery:
select t.*,
(select count(*)
from foo as t2
where t2.id = t.id and t2.length >= t.length
) as idk
from foo as t;
I have the following data in SQL Server
St 1 2 3 4 5 6 7 8
===========================================
603 2 5 1.5 3 0 0 0 0
603 0 0 0 0 2 1 3 5
As I insert the data by batches, each batch only has 4 columns each and I want to collate the data to the following
St 1 2 3 4 5 6 7 8
===========================================
603 2 5 1.5 3 2 1 3 5
but most of the threads I see here are about concatenating strings of a single column.
Anyone has any idea on how to collate or even merge different rows into a single row.
You can use the group by and Sum key word of the t-SQL
SELECT SUM(COL1) , SUM(COL2)..... FROM tbl GROUP BY ST
You can use the GROUP BY clause and aggregate with SUM fields 1-8 :
SELECT St, SUM(1), SUM(2),.. FROM tbl GROUP BY St
RSC by comparing values from tab.col1 , tab.col2 ,tab.col3 ,tab.col4 to Result.INTR
Tab table has 1000s of rows
If any of the col1 to 4 has NULL then return 1
Col1 will hold values pertaining to RID = 10
Col2 will hold values pertaining to RID = 20
Col3 will hold values pertaining to RID = 30
Col4 will hold values pertaining to RID = 40
For eg:
if tab.col1 is 3 then 4
if tab.col2 is 'R' then 3
if tab.col3 is 1900 then it query should give 4
if 1945 then 3
if 1937 then 3 (lower bound is less than and upper bound is greater than equal to)
if tab.col4 is 6 then 5
and so on.....
Result table
RID INTR RSC
----- ----- -----
10 1 0
10 2 1
10 3 4
10 4 2
20 I 4
20 R 3
20 U 1
30 1900 5
30 1900-1937 4
30 1937-1967 3
30 1967 3
40 3-4 2
40 1-3 1
40 4 5
Check CASE and DECODE functions of Oracle.Google and check some examples.You will be able to implement your requirement with them.
For example check this one http://www.club-oracle.com/forums/case-and-decode-two-powerfull-constructs-of-sql-t181/
You would do this like:
select (case when tab.col1 = 3 then 4
when tab.col2 = 'R' then 3
when tab.col3 = 1900 then 4
when tab.col3 in (1945, 1937) then 3
when tab.col4 = 6 then 5
. . .
Try something like:
select t1.RSC, t2.RSC, t3.RSC, t4.RSC
from your_table tab join Result t1 on t1.RID=10 and t1.INTR=tab.col1
join Result t2 on t2.RID=20 and t2.INTR=tab.col2
join Result t3 on t3.RID=30 and t3.INTR >= regexp_substr(tab.col3, '^\d*') and t3.INTR <= regexp_substr(tab.col3, '\d*$')
join Result t4 on t4.RID=40 and t4.INTR >= regexp_substr(tab.col4, '^\d*') and t4.INTR <= regexp_substr(tab.col4, '\d*$')