Help in Pivot Query- To change the column data to rows data!

Question

Hello Gurus -
I have to change the row to Column -
When i use the query -
select NVL (T2.NAME, ' Grand Total') AS State,count(T2.NAME) as Total
from Defect T1,statedef T2,repoproject T3
WHERE T1.STATE=T2.ID AND T1.repoproject = T3.dbid AND T3.name like '%Compass Juice' GROUP BY ROLLUP (T2.NAME)
Then i have got the following data -
STATE          TOTAL
Analysis     17
Closed          1302
Development     9
Duplicate     24
Failed          2
OnHold          4
Opened          146
QA          1
ReadyForQA     1
Withdrawn      335
Grand Total     1841
But i want the data in following format -
State Analysis     Closed     Development      Duplicate     Failed     OnHold     Opened     QA     ReadyForQA     Withdrawn     GrandTotal
Total 17     1302     9          24          2     4     146     1     1          335          1841
Kindly help me with this. I searched the forum and saw the usage of Max and NVL, Decode but i am unable to understand it to use in my query. kindly help me with this.

Answer 1

Hi,
In 11g you can use pivot.
[http://www.oracle.com/technology/pub/articles/oracle-database-11g-top-features/11g-pivot.html]
example
SQL> desc customers
Name                                      Null?    Type
CUST_ID                                            NUMBER(10)
CUST_NAME                                          VARCHAR2(20)
STATE_CODE                                         VARCHAR2(2)
TIMES_PURCHASED                                    NUMBER(3)
When this table is selected:
select cust_id, state_code, times_purchased
from customers
order by cust_id;
The output is:
CUST_ID STATE_CODE TIMES_PURCHASED
      1 CT                       1
      2 NY                      10
      3 NJ                       2
      4 NY                       4
... and so on ...
Note how the data is represented as rows of values: For each customer, the record shows the customer's home state and how many times the customer purchased something from the store. As the customer purchases more items from the store, the column times_purchased is updated.
Now consider a case where you want to have a report of the purchase frequency each state�that is, how many customers bought something only once, twice, thrice and so on, from each state. In regular SQL, you can issue the following statement:
select state_code, times_purchased, count(1) cnt
from customers
group by state_code, times_purchased;
Here is the output:
ST TIMES_PURCHASED        CNT
CT               0         90
CT               1        165
CT               2        179
CT               3        173
CT               4        173
CT               5        152
... and so on ...
This is the information you want but it's a little hard to read. A better way to represent the same data may be through the use of crosstab reports, in which you can organized the data vertically and states horizontally, just like a spreadsheet:
Times_purchased
             CT           NY         NJ      ... and so on ...
1             0            1          0      ...
2            23          119         37      ...
3            17           45          1      ...
... and so on ...
Prior to Oracle Database 11g, you would do that via some sort of a decode function for each value and write each distinct value as a separate column. The technique is quite nonintuitive however.
Fortunately, you now have a great new feature called PIVOT for presenting any query in the crosstab format using a new operator, appropriately named pivot. Here is how you write the query:
select * from (
   select times_purchased, state_code
   from customers t
pivot
   count(state_code)
   for state_code in ('NY','CT','NJ','FL','MO')
order by times_purchased
Here is the output:
. TIMES_PURCHASED       'NY'       'CT'       'NJ'       'FL'       'MO'
              0      16601         90          0          0          0
              1      33048        165          0          0          0
              2      33151        179          0          0          0
              3      32978        173          0          0          0
              4      33109        173          0          1          0
... and so on ...