How can I make a static column/row in crosstab? See example below; can I have a fixed jan, feb, march, ... columns instead of it generating dynamically?
location jan feb mar apr may jun jul aug sep oct nov dec
london 500 62 200 50 0 60 100 46 89 200 150 210
paris 50 26 20 500 50 70 40 200 0 40 250 50
I want the column (jan, feb, mar, apr, ...) to always show up regardless of their measures zero or have values. Like they are fixed.
Here is the query I'm using:
select sum("AMOUNT"), "REQUESTDATE","description"
from(
SELECT SUM(e.AMOUNT)"AMOUNT",TO_CHAR(REQUESTDATE,'MM')"REQUESTDATE", CA.DESCR "description"
FROM PC_PAYMENTTRXNLOG PC,GLB_TYPE ca, PC_ESERVICEINQUIRY e
where PC.ESERVICE_ID = E.ID
AND trunc(REQUESTDATE) between trunc(to_date('2012-01-01','yyyy-mm-dd')) and trunc(to_date('2012-06-30','yyyy-mm-dd'))
GROUP BY TO_CHAR(REQUESTDATE,'MM'),CA.DESCR
)
group by "REQUESTDATE","description"
and the output
SUM("amount") Requestdate Description
2550405 04 A
2550405 04 B
23893281 05 C
614977 06 A
614977 06 E
2550405 04 C
now after updated the query to be
select sum("AMOUNT"), month,"description"
from(
SELECT SUM(e.AMOUNT)"AMOUNT",TO_CHAR(REQUESTDATE,'MM')"REQUESTDATE", CA.DESCR "description"
FROM PC_PAYMENTTRXNLOG PC,GLB_TYPE ca, PC_ESERVICEINQUIRY e
where PC.ESERVICE_ID = E.ID
AND trunc(REQUESTDATE) between trunc(to_date('2012-01-01','yyyy-mm-dd')) and trunc(to_date('2012-06-30','yyyy-mm-dd'))
GROUP BY TO_CHAR(REQUESTDATE,'MM'),CA.DESCR
)
full outer join (select to_char(date '1970-01-01'
+ numtoyminterval(level - 1, 'month'), 'mm') as month
from dual
connect by level <= 12) on month="REQUESTDATE"
group by month,"description"
when run the query run it displaying all the months regardless of their measures zero or have values.
BUT now the output is like that
location jan feb mar apr may jun jul aug sep oct nov dec
london 500 62 200 50 0 60 100 46 89 200 150 210
paris 50 26 20 500 50 70 40 200 0 40 250 50
null 0 0 0 0 0 0 0 0 0 0 0 0
how i can restrict/hide the last null row?
have not tested it.. but try something like this
select sum("AMOUNT"), month,"description"
from(SELECT SUM(e.AMOUNT)"AMOUNT",TO_CHAR(REQUESTDATE,'MM')"REQUESTDATE", CA.DESCR "description"
FROM PC_PAYMENTTRXNLOG PC,GLB_TYPE ca, PC_ESERVICEINQUIRY e
where PC.ESERVICE_ID = E.ID
AND trunc(REQUESTDATE) between trunc(to_date('2012-01-01','yyyy-mm-dd')) and trunc(to_date('2012-06-30','yyyy-mm-dd'))
GROUP BY TO_CHAR(REQUESTDATE,'MM'),CA.DESCR
)
full outer join (select to_char(date '1970-01-01'
+ numtoyminterval(level - 1, 'month'), 'mm') as month
from dual
connect by level <= 12) on month="REQUESTDATE"
group by month,"description"
click here for SQL Fiddle demo to generate 1 to 12 in Oracle
Once you have generated this.. full outer join Your main query with this series query and take month from series query as I did in main query.
Using this query you will get all the data for all months with null values in measure.
For Description column - iReport set property's isRemoveLineWhenBlank and isBlankWhenNull to True, This will remove the null value being printed in iReport
For Measure use Print when expression in such a way, when ever description is null then return false. So this will prevent the value 0 being printed in iReport.
Related
I have orders table with two columns sales_amt, Disc_Amt. I want to find the each month total sales amount having discounts and without discount
Table:
month
sales_amt
Disc_Amt
Jan
20
Jan
30
Feb
5
2
Feb
30
Feb
10
5
Mar
80
10
Mar
20
Result required:
month
Sales_Amount_Without_Discount
Sales_Amount_With_Discount
Jan
50
0
Feb
30
15
Mar
80
20
I tried with the below query
Select
month(invoice_date),
sales_amt as Sales_Amount_Without_Discount,
Sales_Amount_Without_Discount = (select
sales_amt
from
orders
where
disc_amt > '0'
)
from
orders
Group by
month(invoice_date)
Currently I am getting result as below
month
Sales_Amount_Without_Discount
Sales_Amount_With_Discount
Jan
50
110
Feb
30
110
Mar
80
110
Thank you
You can do this by putting a case expression within your SUM(), e.g.
SELECT MONTH(invoice_date),
Sales_Amount_Without_Discount = SUM(sales_amt),
Sales_Amount_With_Discount = SUM(CASE WHEN Disc_Amt > 0 THEN sales_amt ELSE 0 END)
FROM orders
GROUP BY
MONTH(invoice_date);
This may already be answered, but I can't figure out the correct search terms for what I need. We store values by Year / Period for the Beginning of Month (BOM). The BOM for one month is the same value as End of Month (EOM) for the previous month. I need a way to report this as such.
So 2018-02 BOM = 2018-01 EOM.
I thought I might be able to use something simple, but it does not account for the month/year wrap at 12 months as those fields are numerical.
select yr as YEAR, (pd-1) as PERIOD, sum(BOM) as EOM
from Table1
where type = '3'
group by yr, pd
order by yr desc, pd desc
This works for the middle months, but not for January, which becomes 2018-0 instead of 2017-12.
Example Data
Yr Pd Type BOM
18 02 3 100
18 02 3 100
18 02 2 200
18 02 2 100
18 01 3 100
18 01 3 100
18 01 2 200
18 01 2 100
18 01 3 100
18 01 2 300
17 12 3 100
17 12 3 200
17 12 2 300
17 12 3 200
17 12 2 100
17 11 3 300
17 11 2 400
17 11 3 400
17 11 2 100
So the results I am looking for would be:
Yr Pd EOM
18 01 200
17 12 300
17 11 500
17 10 700
I'm working in System iNavigator currently, but hoping to move this into an externally connected Excel query at some point.
Your DB2 database should be able to use CASE WHEN
Which can be used to calculate the year and the month, depending on the month.
For example:
select
CASE WHEN pd = 1 THEN yr - 1 ELSE yr END as Yr,
CASE WHEN pd = 1 THEN 12 ELSE pd - 1 END as Pd,
SUM(BOM) as EOM
from Table1
where type = '3'
group by yr, pd
order by yr desc, pd desc
We have thousands of record in our data and want to count date wise jobs with category through single query. It is Possible?
Display required as under
TypesJobs 01 02 03 04 05 06 07
A 2 1 6 4 1 3 4
B 10 12 8 10 12 9 13
C 3 5 4 3 2 5 4
Here Types of jobs count for a day in date column 01, 02, 03 are date range of the month
You can use conditional aggregation, something like this:
select typesjobs,
sum(case when month(datecol) = 1 then 1 els e0 end) as month_01,
sum(case when month(datecol) = 2 then 1 els e0 end) as month_02,
. . .
from t
where <date condition here>
group by typesjobs;
I have a table with the following ddl.
CREATE TABLE "LEDGER"
("FY" NUMBER,
"FP" VARCHAR2(20 BYTE),
"FUND" VARCHAR2(20 BYTE),
"TYPE" VARCHAR2(2 BYTE),
"AMT" NUMBER
)
The table contains the following data.
REM INSERTING into LEDGER
SET DEFINE OFF;
Insert into LEDGER (FY,FP,FUND,TYPE,AMT) values (15,'03','A','03',1);
Insert into LEDGER (FY,FP,FUND,TYPE,AMT) values (15,'04','A','03',2);
Insert into LEDGER (FY,FP,FUND,TYPE,AMT) values (16,'04','A','03',3);
Insert into LEDGER (FY,FP,FUND,TYPE,AMT) values (12,'05','A','04',6);
based on the partition of fy,fp,fund and type I would like to write a query to keep a running count from the beginning of fp(fp though it is a varchar it represents a number in the month. i.E 2 equals february and 3 equals march etc.) to a hard number of 14. So taking a closer look at the data you will notice that in FY 15 the max period is 04 so i must add another 10 periods to my report to get my report to have the full 14 periods. here is the expected output.
here is what i tried, but I'm just simply stumbling all together on this.
WITH fy_range AS
(
SELECT MIN (fy) AS min_fy
, MAX (fy) AS max_fy
FROM ledger
),all_fys AS
(
SELECT min_fy + LEVEL - 1 AS fy
FROM fy_range
CONNECT BY LEVEL <= max_fy + 1 - min_fy
)
,all_fps AS
(
SELECT TO_CHAR (LEVEL, 'FM00') AS fp
FROM dual
CONNECT BY LEVEL <= 14
)
SELECT
FUND
,G.TYPE
,G.FY
,G.FP
,LAST_VALUE(G.AMT ignore nulls) OVER (PARTITION BY G.FUND ORDER BY Y.FY P.FP ) AS AMT
FROM all_fys y
CROSS JOIN all_fps p
LEFT OUTER JOIN LEDGER G PARTITION BY(FUND)
ON g.fy = y.fy
AND g.fp = p.fp;
but I end up with a bunch of nulls and some strange results.
This may not be the most efficient solution, but it is easy to understand and maintain. First (in the most deeply nested subquery) we find the min FP for each combination of FY, FUND and TYPE. Then we use a CONNECT BY query to fill all the FP for all FY, FUND, TYPE combinations (up to the hard upper limit of 14). Then we left-outer-join to the original data in the LEDGER table. So far we densified the data. In the final query (the join) we also add the column for the cumulative sum - that part is easy after we densified the data.
TYPE is an Oracle keyword, so it is probably best not to use it as a column name. It is also best not to use double-quoted table and column names (I had to use upper case everywhere because of that). I also made sure to convert from varchar2 to number and back to varchar2 - we shouldn't rely on implicit conversions.
select S.FY, to_char(S.FP, 'FM09') as FP, S.FUND, S.TYPE,
sum(L.AMT) over (partition by S.FY, S.FUND, S.TYPE order by S.FP) as CUMULATIVE_AMT
from (
select FY, MIN_FP + level - 1 as FP, FUND, TYPE
from (
select FY, min(to_number(FP)) as MIN_FP, FUND, TYPE
from LEDGER
group by FY, FUND, TYPE
)
connect by level <= 15 - MIN_FP
and prior FY = FY
and prior FUND = FUND
and prior TYPE = TYPE
and prior sys_guid() is not null
) S left outer join LEDGER L
on S.FY = L.FY and S.FP = L.FP and S.FUND = L.FUND and S.TYPE = L.TYPE
;
Output:
FY FP FUND TYPE CUMULATIVE_AMT
--- --- ---- ---- --------------
12 05 A 04 6
12 06 A 04 6
12 07 A 04 6
12 08 A 04 6
12 09 A 04 6
12 10 A 04 6
12 11 A 04 6
12 12 A 04 6
12 13 A 04 6
12 14 A 04 6
15 03 A 03 1
15 04 A 03 3
15 05 A 03 3
15 06 A 03 3
15 07 A 03 3
15 08 A 03 3
15 09 A 03 3
15 10 A 03 3
15 11 A 03 3
15 12 A 03 3
15 13 A 03 3
15 14 A 03 3
16 04 A 03 3
16 05 A 03 3
16 06 A 03 3
16 07 A 03 3
16 08 A 03 3
16 09 A 03 3
16 10 A 03 3
16 11 A 03 3
16 12 A 03 3
16 13 A 03 3
16 14 A 03 3
I have this query
With
NoOfOrder as
(
SELECT Apr,May,Jun,Jul,Aug,Sep,Oct,Nov,Dec,Jan,Feb,Mar
FROM
(
select LEFT(datename(month,InvoiceDate),3) mon,InvoiceNo as InvoiceNo
from tbl_InvoiceMain ,tbl_OrderMain,tbl_CompanyMaster
where tbl_InvoiceMain.OrderID = tbl_OrderMain.OrderID
and (CAST(tbl_InvoiceMain.InvoiceDate AS date) BETWEEN tbl_CompanyMaster.YearStart AND tbl_CompanyMaster.YearEnd)
) P
PIVOT (count(InvoiceNo)for mon in (Jan,Feb,Mar,Apr,May,Jun,Jul,Aug,Sep,Oct,Nov,Dec)) PV
),
OnTime as
(
SELECT Apr,May,Jun,Jul,Aug,Sep,Oct,Nov,Dec,Jan,Feb,Mar
FROM
(
select LEFT(datename(month,InvoiceDate),3) mon,InvoiceNo as InvoiceNo
from tbl_InvoiceMain ,tbl_OrderMain,tbl_CompanyMaster
where tbl_InvoiceMain.OrderID = tbl_OrderMain.OrderID
and (CAST(tbl_InvoiceMain.InvoiceDate AS date) BETWEEN tbl_CompanyMaster.YearStart AND tbl_CompanyMaster.YearEnd)
and CAST(tbl_InvoiceMain.InvoiceDate AS date) <= CAST(tbl_OrderMain.ScheduledDispatchDate AS date)
) P
PIVOT (count(InvoiceNo)for mon in (Jan,Feb,Mar,Apr,May,Jun,Jul,Aug,Sep,Oct,Nov,Dec)) PV
)
Select * From NoOfOrder
union all
Select * From OnTime
It gives this result:
Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar
18 35 39 52 32 47 47 22 14 0 0 0
9 10 16 22 6 11 19 10 5 0 0 0
Here is my expected result
Apr May Jun Jul Aug Sep Oct Nov Dec Jan Feb Mar
NoOfOrder 18 35 39 52 32 47 47 22 14 0 0 0
OnTimeDelivered 9 10 16 22 6 11 19 10 5 0 0 0
DeliverPerformance% 50.00 28.57 41.03 42.31 18.75 23.40 40.43 45.45 35.71 0.00 0.00 0.00
The formula for DeliverPerformance is:
DeliverPerformance% = (OnTimeDelivered/NoOfOrder) X 100
How do I achieve this result on the next row?
for reference you check my question in good format
enter link description here
My immediate suggestion is to combine everything first prior to pivoting the results.
Your first query might look like this:
SELECT
LEFT(datename(month, InvoiceDate), 3) InvMon,
SUM(1) AS NoOfOrder,
SUM(CASE WHEN CAST(tbl_InvoiceMain.InvoiceDate AS date) <= CAST(tbl_OrderMain.ScheduledDispatchDate AS date) THEN 1 ELSE 0 END) OnTimeDelivered
FROM tbl_InvoiceMain, tbl_OrderMain, tbl_CompanyMaster
WHERE tbl_InvoiceMain.OrderID = tbl_OrderMain.OrderID
AND (CAST(tbl_InvoiceMain.InvoiceDate AS date) BETWEEN tbl_CompanyMaster.YearStart AND tbl_CompanyMaster.YearEnd)
GROUP BY LEFT(datename(month, InvoiceDate), 3)
Note that I'm always counting every invoice record and optionally counting the "on time" invoices with that CASE statement and the respective SUM functions.
My next thought is to put that query in a CTE and then the statement that uses that CTE will do the additional calculation like so:
SELECT InvMon, NoOfOrder, OnTimeDelivered, ((OnTimeDelivered / NoOfOrder) * 100) DeliverPerformance ...
And finally, that's what I pivot.