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== PERCENTILE_CONT(x) examines the percent rank values in each group until it finds one that is greater than or equal to x==

PERCENTILE_CONT(x) operate in the reverse sense of PERCENT_RANK().



<source lang="sql">
SQL>
SQL>
SQL> -- create demo table
SQL> create table Employee(
2 ID VARCHAR2(4 BYTE) NOT NULL,
3 First_Name VARCHAR2(10 BYTE),
4 Last_Name VARCHAR2(10 BYTE),
5 Start_Date DATE,
6 End_Date DATE,
7 Salary Number(8,2),
8 City VARCHAR2(10 BYTE),
9 Description VARCHAR2(15 BYTE)
10 )
11 /
Table created.
SQL>
SQL> -- prepare data
SQL> insert into Employee(ID, First_Name, Last_Name, Start_Date, End_Date, Salary, City, Description)
2 values ("01","Jason", "Martin", to_date("19960725","YYYYMMDD"), to_date("20060725","YYYYMMDD"), 1234.56, "Toronto", "Programmer")
3 /
1 row created.
SQL> insert into Employee(ID, First_Name, Last_Name, Start_Date, End_Date, Salary, City, Description)
2 values("02","Alison", "Mathews", to_date("19760321","YYYYMMDD"), to_date("19860221","YYYYMMDD"), 6661.78, "Vancouver","Tester")
3 /
1 row created.
SQL> insert into Employee(ID, First_Name, Last_Name, Start_Date, End_Date, Salary, City, Description)
2 values("03","James", "Smith", to_date("19781212","YYYYMMDD"), to_date("19900315","YYYYMMDD"), 6544.78, "Vancouver","Tester")
3 /
1 row created.
SQL> insert into Employee(ID, First_Name, Last_Name, Start_Date, End_Date, Salary, City, Description)
2 values("04","Celia", "Rice", to_date("19821024","YYYYMMDD"), to_date("19990421","YYYYMMDD"), 2344.78, "Vancouver","Manager")
3 /
1 row created.
SQL> insert into Employee(ID, First_Name, Last_Name, Start_Date, End_Date, Salary, City, Description)
2 values("05","Robert", "Black", to_date("19840115","YYYYMMDD"), to_date("19980808","YYYYMMDD"), 2334.78, "Vancouver","Tester")
3 /
1 row created.
SQL> insert into Employee(ID, First_Name, Last_Name, Start_Date, End_Date, Salary, City, Description)
2 values("06","Linda", "Green", to_date("19870730","YYYYMMDD"), to_date("19960104","YYYYMMDD"), 4322.78,"New York", "Tester")
3 /
1 row created.
SQL> insert into Employee(ID, First_Name, Last_Name, Start_Date, End_Date, Salary, City, Description)
2 values("07","David", "Larry", to_date("19901231","YYYYMMDD"), to_date("19980212","YYYYMMDD"), 7897.78,"New York", "Manager")
3 /
1 row created.
SQL> insert into Employee(ID, First_Name, Last_Name, Start_Date, End_Date, Salary, City, Description)
2 values("08","James", "Cat", to_date("19960917","YYYYMMDD"), to_date("20020415","YYYYMMDD"), 1232.78,"Vancouver", "Tester")
3 /
1 row created.
SQL>
SQL>
SQL>
SQL> -- display data in the table
SQL> select * from Employee
2 /
ID FIRST_NAME LAST_NAME START_DAT END_DATE SALARY CITY DESCRIPTION
---- ---------- ---------- --------- --------- ---------- ---------- ---------------
01 Jason Martin 25-JUL-96 25-JUL-06 1234.56 Toronto Programmer
02 Alison Mathews 21-MAR-76 21-FEB-86 6661.78 Vancouver Tester
03 James Smith 12-DEC-78 15-MAR-90 6544.78 Vancouver Tester
04 Celia Rice 24-OCT-82 21-APR-99 2344.78 Vancouver Manager
05 Robert Black 15-JAN-84 08-AUG-98 2334.78 Vancouver Tester
06 Linda Green 30-JUL-87 04-JAN-96 4322.78 New York Tester
07 David Larry 31-DEC-90 12-FEB-98 7897.78 New York Manager
08 James Cat 17-SEP-96 15-APR-02 1232.78 Vancouver Tester
8 rows selected.
SQL>
SQL>
SQL>
SQL> SELECT
2 PERCENTILE_CONT(0.6) WITHIN GROUP (ORDER BY SUM(salary) DESC)
3 AS percentile_cont,
4 PERCENTILE_DISC(0.6) WITHIN GROUP (ORDER BY SUM(salary) DESC)
5 AS percentile_disc
6 FROM employee
7 GROUP BY city;
PERCENTILE_CONT PERCENTILE_DISC
--------------- ---------------
10023.36 12220.56
SQL>
SQL>
SQL>
SQL> -- clean the table
SQL> drop table Employee
2 /
Table dropped.
SQL></source>

== select percentile_cont(0.5) within group (order by salary desc )==



<source lang="sql">
SQL> CREATE TABLE EMP(
2 EMPNO NUMBER(4) NOT NULL,
3 ENAME VARCHAR2(10),
4 JOB VARCHAR2(9),
5 MGR NUMBER(4),
6 HIREDATE DATE,
7 SAL NUMBER(7, 2),
8 COMM NUMBER(7, 2),
9 DEPTNO NUMBER(2)
10 );
Table created.

SQL> INSERT INTO EMP VALUES(2, "Jack", "Tester", 6,TO_DATE("20-FEB-1981", "DD-MON-YYYY"), 1600, 300, 30);
1 row created.
SQL> INSERT INTO EMP VALUES(3, "Wil", "Tester", 6,TO_DATE("22-FEB-1981", "DD-MON-YYYY"), 1250, 500, 30);
1 row created.
SQL> INSERT INTO EMP VALUES(4, "Jane", "Designer", 9,TO_DATE("2-APR-1981", "DD-MON-YYYY"), 2975, NULL, 20);
1 row created.
SQL> INSERT INTO EMP VALUES(5, "Mary", "Tester", 6,TO_DATE("28-SEP-1981", "DD-MON-YYYY"), 1250, 1400, 30);
1 row created.
SQL> INSERT INTO EMP VALUES(7, "Chris", "Designer", 9,TO_DATE("9-JUN-1981", "DD-MON-YYYY"), 2450, NULL, 10);
1 row created.
SQL> INSERT INTO EMP VALUES(8, "Smart", "Helper", 4,TO_DATE("09-DEC-1982", "DD-MON-YYYY"), 3000, NULL, 20);
1 row created.
SQL> INSERT INTO EMP VALUES(9, "Peter", "Manager", NULL,TO_DATE("17-NOV-1981", "DD-MON-YYYY"), 5000, NULL, 10);
1 row created.
SQL> INSERT INTO EMP VALUES(10, "Take", "Tester", 6,TO_DATE("8-SEP-1981", "DD-MON-YYYY"), 1500, 0, 30);
1 row created.

SQL> INSERT INTO EMP VALUES(13, "Fake", "Helper", 4,TO_DATE("3-DEC-1981", "DD-MON-YYYY"), 3000, NULL, 20);
1 row created.

SQL>
SQL> select percentile_cont(0.5)
2 within group (order by sal desc ) median_sal
3 from emp;
Enter...
2450
1 row selected.
SQL>
SQL> drop table emp;
Table dropped.
SQL></source>

== Take a probability value (between 0 and 1) and returns a percentile value (for a continuous distribution)==

The general format for this function is:
PERCENTILE_CONT (expr) WITHIN GROUP (ORDER BY expr [DESC |ASC]) OVER (query_partition_clause)]



<source lang="sql">
SQL>
SQL> -- create demo table
SQL> create table myTable(
2 id NUMBER(2),
3 value NUMBER(6,2)
4 )
5 /
Table created.
SQL>
SQL> -- prepare data
SQL> insert into myTable(ID, value)values (1,9);
1 row created.
SQL> insert into myTable(ID, value)values (2,2.11);
1 row created.
SQL> insert into myTable(ID, value)values (3,3.44);
1 row created.
SQL> insert into myTable(ID, value)values (4,-4.21);
1 row created.
SQL> insert into myTable(ID, value)values (5,10);
1 row created.
SQL> insert into myTable(ID, value)values (6,3);
1 row created.
SQL> insert into myTable(ID, value)values (7,-5.88);
1 row created.
SQL> insert into myTable(ID, value)values (8,123.45);
1 row created.
SQL> insert into myTable(ID, value)values (9,98.23);
1 row created.
SQL> insert into myTable(ID, value)values (10,938.23);
1 row created.
SQL> insert into myTable(ID, value)values (11,984.23);
1 row created.
SQL> insert into myTable(ID, value)values (12,198.23);
1 row created.
SQL> insert into myTable(ID, value)values (13,928.87);
1 row created.
SQL> insert into myTable(ID, value)values (14,25.37);
1 row created.
SQL> insert into myTable(ID, value)values (15,918.3);
1 row created.
SQL> insert into myTable(ID, value)values (16,9.23);
1 row created.
SQL> insert into myTable(ID, value)values (17,8.23);
1 row created.
SQL>
SQL> select * from myTable
2 /
ID VALUE
---------- ----------
1 9
2 2.11
3 3.44
4 -4.21
5 10
6 3
7 -5.88
8 123.45
9 98.23
10 938.23
11 984.23
ID VALUE
---------- ----------
12 198.23
13 928.87
14 25.37
15 918.3
16 9.23
17 8.23
17 rows selected.
SQL>
SQL>
SQL>
SQL> SELECT PERCENTILE_CONT (0.2) WITHIN GROUP (ORDER BY id )
2 from myTable;
PERCENTILE_CONT(0.2)WITHINGROUP(ORDERBYID)
------------------------------------------
4.2
SQL>
SQL>
SQL>
SQL> -- clean the table
SQL> drop table myTable
2 /
Table dropped.
SQL>
SQL></source>

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