mytable:
and result i want:
but i can't query do you help me?
As I understand your requirement you want pivoting of your data.
Try this:
select tmn_code,
max(case when bank_type=1 then totalamount end) as bank_1_total_amount,
max(case when bank_type=1 then totalpay end) as bank_1_totalpay,
max(case when bank_type=2 then totalamount end) as bank_2_total_amount,
max(case when bank_type=2 then totalpay end) as bank_2_totalpay
from your_table group by tmn_code;
Related
Below is the my base table
I need to create view like below format based on my base table.
Here Deposit_Acc_Count is combination of (Type -> SB,RD, FD) and Loan_Acc_Count is (Type ->LO) same as for amount.
Can anyone help me to achieve this.
You can use conditional aggregation while grouping by br_code and cif columns such as
SELECT br_code, cif,
COUNT(CASE WHEN type IN ('SB','RD', 'FD') THEN Amt END) AS deposit_acc_count,
SUM(CASE WHEN type IN ('SB','RD', 'FD') THEN Amt ELSE 0 END) AS deposit_acc_amt,
COUNT(CASE WHEN type = 'LO' THEN Amt END) AS loan_acc_count,
SUM(CASE WHEN type = 'LO' THEN Amt ELSE 0 END) AS loan_acc_amt,
COUNT(*) AS total_count,
SUM(amt) AS total_amt
FROM t
GROUP BY br_code, cif
Demo
I have here a sample table data which i want to use pivot and make my DedCode data into column.
the AMount example is already computed to its total but how can i count the number of employee if it is same with branch,deptcode and emptype.
my sample table data.
expected output:
You can use conditional aggregation:
select branch, deptcode, emptype, sum(empcount) as empcount,
sum(case when dedcode = 'PHIC' then amount else 0 end) as phic,
sum(case when dedcode = 'SLOAN' then amount else 0 end) as sloan,
sum(case when dedcode = 'VLOAN' then amount else 0 end) as vloan
from t
group by branch, deptcode, emptype;
I have a data like this:
And I want this - I am trying with PIVOT but not getting the expected results:
Query is
SELECT AttendeeID,[Quantity1],[PROD1],[Quantity2],[PROD2],[Quantity3],[PROD3] FROM
(SELECT * ,
row_number() over(partition by AttendeeID order by AttendeeID)rn
from #ProductTestingwithPosition2) TT
PIVOT
(MAX(product) for ProductPosition in ([PROD1],[PROD2],[PROD3])) AS Tab2
PIVOT
(sum(Quantity) for QuantityPosition in ([Quantity1],[Quantity2],[Quantity3])) AS Tab3
I am getting this output:
Just use conditional aggregation:
SELECT AttendeeID,
MAX(CASE WHEN ProductPosition = 'PROD1' THEN product END) as prod1,
MAX(CASE WHEN QuantityPosition = 'QUANTITY1' THEN quantity END) as quantity1,
MAX(CASE WHEN ProductPosition = 'PROD2' THEN product END) as prod2,
MAX(CASE WHEN QuantityPosition = 'QUANTITY2' THEN quantity END) as quantity2,
MAX(CASE WHEN ProductPosition = 'PROD3' THEN product END) as prod3,
MAX(CASE WHEN QuantityPosition = 'QUANTITY3' THEN quantity END) as quantity3
FROM (SELECT ptp.* ,
row_number() over (partition by AttendeeID, ProductPosition order by AttendeeID) as seqnum
FROM #ProductTestingwithPosition2 ptp
) ptp
GROUP BY AttendeeID, seqnum;
PIVOT -- in addition to being non-standard -- is very finicky. Conditional aggregation is much more powerful and less prone to errors.
I have Table a(Dimension table) and Table B(Fact table) stores transaction shopper history.
Table a : shopped id(surrogate key) created for unique combination(any of column 2,colum3,column4 repeated it will have same shopper id)
Table b is transaction data.
I am trying to identify New customers and repeated customers for each week, expected output is below.
I am thinking following SQL Statement
Select COUNT(*) OVER (PARTITION BY shopperid,weekdate) as total_new_shopperid for Repeated customer,
for Identifying new customer(ie unique) in same join condition, I am stuck on window function..
thanks,
Sam
You can use the DENSE_RANK analytical function along with aggregate function as follows:
SELECT WEEK_DATE,
COUNT(DISTINCT CASE WHEN DR = 1 THEN SHOPPER_ID END) AS TOTAL_NEW_CUSTOMER,
SUM(CASE WHEN DR = 1 THEN AMOUNT END) AS TOTAL_NEW_CUSTOMER_AMT,
COUNT(DISTINCT CASE WHEN DR > 1 THEN SHOPPER_ID END) AS TOTAL_REPEATED_CUSTOMER,
SUM(CASE WHEN DR > 1 THEN AMOUNT END) AS TOTAL_REPEATED_CUSTOMER_AMT
FROM
(
select T.*,
DENSE_RANK() OVER (PARTITION BY SHOPPER_ID ORDER BY WEEK_DATE) AS DR
FROM YOUR_TABLE T);
GROUP BY WEEK_DATE;
Cheers!!
Tejash's answer is fine (and I'm upvoting it).
However, Oracle is quite efficient with aggregation, so two levels of aggregation might have better performance (depending on the data):
select week_date,
sum(case when min_week_date = week_date then 1 else 0 end) as new_shoppers,
sum(case when min_week_date = week_date then amount else 0 end) as new_shopper_amount,
sum(case when min_week_date > week_date then 1 else 0 end) as returning_shoppers,
sum(case when min_week_date > week_date then amount else 0 end) as returning_amount
from (select shopper_id, week_date,
sum(amount) as amount,
min(week_date) over (partition by shopper_id) as min_week_date
from t
group by shopper_id, week_date
) sw
group by week_date
order by week_date;
Note: If this has better performance, it is probably due to the elimination of count(distinct).
I would like a cross table from the following table.
The cross table should look like this
A pivot table does not seem to solve the problem, because only one column can be used at a time. But in our case we are dealing with 4 different columns. (payment, month, year and free of charge)
I solved the problem by splitting these 4 columns into four different pivot tables, using temporary tables and finally reassembling the obtained data. But this is very complicated, long and confusing, in short not very nice...
The years and months should be shown in ascending form, exactly as you can see in the cross table above.
I have been looking for a solution for quite a while but I can't find the same problem anywhere.
If someone would give me a short, elegant solution I would be very grateful.
Under http://www.sqlfiddle.com/#!18/7216f/2 you can see the problem definition.
Thank you!
You can rank records by date in a subquery with row_number(), and then pivot with conditional aggregation:
select
ClientId,
max(case when rn = 1 then Payment end) Payment1,
max(case when rn = 2 then Payment end) Payment2,
max(case when rn = 3 then Payment end) Payment3,
max(case when rn = 1 then [Month] end) Month1,
max(case when rn = 2 then [Month] end) Month2,
max(case when rn = 3 then [Month] end) Month3,
max(case when rn = 1 then [Year] end) Year1,
max(case when rn = 2 then [Year] end) Year2,
max(case when rn = 3 then [Year] end) Year3,
max(case when rn = 1 then FreeOfCharge end) FreeOfCharge1,
max(case when rn = 2 then FreeOfCharge end) FreeOfCharge2,
max(case when rn = 3 then FreeOfCharge end) FreeOfCharge3
from (
select
t.*,
row_number() over(partition by ClientId order by [Year], [Month]) rn
from mytable t
) t
group by ClientId
You can join the table with itself a few times, as in:
with p as (
select
*, row_number() over(partition by clientid order by year, month) as n
from Payment
)
select
p1.clientid,
p1.payment, p2.payment, p3.payment,
p1.month, p2.month, p3.month,
p1.year, p2.year, p3.year,
p1.freeofcharge, p2.freeofcharge, p3.freeofcharge
from p p1
left join p p2 on p2.clientid = p1.clientid and p2.n = 2
left join p p3 on p3.clientid = p1.clientid and p3.n = 3
where p1.n = 1
See Fiddle.