CREATE TABLE person ( ID INT, Name VARCHAR (20), Home VARCHAR (30), Age INT (2), Occupation VARCHAR (45), Gender VARCHAR (6), Salary INT, PRIMARY KEY (ID) ); CREATE TABLE Phone ( ID number, brand varchar2(40), model varchar2(49), screensize number); INSERT INTO person VALUES (1, 'Maisha', 'Dhaka', 25, 'Teacher', 'Female', 50000); INSERT INTO person VALUES (2, 'Saad', 'Dhaka', 56, 'Service', 'Male', 60000); INSERT INTO person VALUES (3, 'Rakeen', 'Ctg', 71, 'Retired', 'Male', 10000); INSERT INTO person VALUES (6, 'Ilma', 'Gazipur', 54, 'Doctor', 'Female', 55000); INSERT INTO person VALUES (7, 'Rajib', 'Gazipur', 65, 'Musician', 'Male', 5000); INSERT INTO person VALUES (8, 'Raisa', 'Dhaka', 56, 'Engineer', 'Female', 60000); INSERT INTO person VALUES (9, 'Sakib', 'Ctg', 23, 'Student', 'Male', 1000); INSERT INTO person VALUES (10, 'Mosaddek', 'Comilla', 32, 'Teacher', 'Male', 45000); INSERT INTO person VALUES (11, 'Jarin', 'Comilla', 51, 'Farmer', 'Female', 20000); INSERT INTO person VALUES (12, 'Rudaba', 'Khulna', 15, 'Student', 'Female', 1500); INSERT INTO person VALUES (13, 'Sami', 'Ctg', 25, 'Business', 'Male', 100000); INSERT INTO person VALUES (14, 'Nihal', 'Comilla', 52, 'Doctor', 'Male', 70000); INSERT INTO person VALUES (15, 'Rafid', 'Gazipur', 53, 'Teacher', 'Male', 50000); INSERT INTO person VALUES (16, 'Medha', 'Dhaka', 35, 'Musician', 'Female', 50000); INSERT INTO person VALUES (17, 'Sakib', 'Khulna', 43, 'Service', 'Male', 50000); INSERT INTO person VALUES (18, 'Zobaeir', 'Khulna', 34, 'Service', 'Male', 45000); INSERT INTO person VALUES (19, 'Shahriyar', 'Ctg', 16, 'Student', 'Male', 500); INSERT INTO person VALUES (20, 'Mahir', 'Comilla', 32, 'Business', 'Male', 120000); INSERT INTO person VALUES (21, 'Mushfiqur', 'Ctg', 25, 'Musician', 'Male', 100000); INSERT INTO person VALUES (22, 'Najish', 'Gazipur', 14, 'Student', 'Male', 400); INSERT INTO person VALUES (23, 'Bandhan', 'Dhaka', 25, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (24, 'Shadman', 'Ctg', 28, 'Teacher', 'Male', 80000); INSERT INTO person VALUES (25, 'Faria', 'Dhaka', 25, 'Engineer', 'Female', 50000); INSERT INTO person VALUES (26, 'Taki', 'Dhaka', 26, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (27, 'Tanzir', 'Dhaka', 45, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (28, 'Alvi', 'Ctg', 23, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (29, 'Nasib', 'Dhaka', 21, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (30, 'Mim', 'Dhaka', 75, 'Teacher', 'Female', 40000); INSERT INTO person VALUES (31, 'Ornob', 'Dhaka', 43, 'Student', 'Male', 50000); INSERT INTO person VALUES (32, 'Shuvo', 'Dhaka', 2, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (33, 'Anika', 'Dhaka', 56, 'Engineer', 'Female', 50000); INSERT INTO person VALUES (34, 'Ikra', 'Ctg', 78, 'Teacher', 'Female', 50000); INSERT INTO person VALUES (35, 'Ojhor', 'Dhaka', 12, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (36, 'Saadman', 'Dhaka', 32, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (37, 'Nafiz', 'Dhaka', 15, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (38, 'Arman', 'Dhaka', 55, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (39, 'Faysal', 'Dhaka', 23, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (40, 'Syed', 'Dhaka', 22, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (41, 'Abidure', 'Dhaka', 21, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (42, 'Nafisa', 'Dhaka', 24, 'Engineer', 'Female', 50000); INSERT INTO person VALUES (44, 'Abu', 'Ctg', 25, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (45, 'Maruf', 'Dhaka', 26, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (46, 'Omar', 'Dhaka', 27, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (47, 'Mahdia', 'Dhaka', 28, 'Engineer', 'Female', 50000); INSERT INTO person VALUES (48, 'Nazneen', 'Dhaka', 29, 'Engineer', 'Female', 50000); INSERT INTO person VALUES (49, 'Ahikul', 'Dhaka', 30, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (50, 'Asif', 'Dhaka', 31, 'Musician', 'Male', 50000); INSERT INTO person VALUES (51, 'Abir', 'Ctg', 32, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (52, 'Afrin', 'Dhaka', 22, 'Engineer', 'Female', 50000); INSERT INTO person VALUES (53, 'Evan', 'Dhaka', 78, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (55, 'Muhib', 'Ctg', 66, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (56, 'Zizan', 'Dhaka', 90, 'Musician', 'Male', 40000); INSERT INTO person VALUES (57, 'Tansi', 'Dhaka', 44, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (58, 'Mumu', 'Ctg', 87, 'Engineer', 'Female', 1000); INSERT INTO person VALUES (59, 'Elma', 'Dhaka', 25, 'Teacher', 'Female', 9000); INSERT INTO person VALUES (60, 'Emon', 'Dhaka', 33, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (61, 'Tanzil', 'Dhaka', 89, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (62, 'Nafi', 'Dhaka', 75, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (63, 'Azraf', 'Ctg', 54, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (64, 'Istiaque', 'Dhaka', 44, 'Engineer', 'Male', 1000); INSERT INTO person VALUES (65, 'Ashraf', 'Dhaka', 32, 'Engineer', 'Male', 100); INSERT INTO person VALUES (66, 'Rubaiat', 'Dhaka', 45, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (67, 'Rafsan', 'Dhaka', 2, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (68, 'Preetu', 'Dhaka', 12, 'Engineer', 'Female', 50000); INSERT INTO person VALUES (69, 'Abdullah', 'Dhaka', 34, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (70, 'Shafi', 'Dhaka', 65, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (71, 'Nova', 'Ctg', 25, 'Engineer', 'Female', 200); INSERT INTO person VALUES (72, 'Rokoni', 'Dhaka', 61, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (73, 'Alsaad', 'Dhaka', 40, 'Teacher', 'Male', 10000); INSERT INTO person VALUES (74, 'Muhtasim', 'Dhaka', 39, 'Engineer', 'Male',3000); INSERT INTO person VALUES (75, 'Galib', 'Jashore', 34, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (76, 'Keya', 'Dhaka', 45, 'Engineer', 'Female', 50000); INSERT INTO person VALUES (77, 'Aunkon', 'Dhaka', 65, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (78, 'Sabbir', 'Dhaka', 53, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (80, 'Shams Shuvo', 'Dhaka', 21, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (81, 'Priota', 'Dhaka', 16, 'Engineer', 'Female', 50000); INSERT INTO person VALUES (82, 'Tameem', 'Comilla', 18, 'Engineer', 'Male', 50000); INSERT INTO person VALUES (83, 'Ibrahim', 'Dhaka', 19, 'Engineer', 'Male', 10);

The SQL file contains the necessary DDL statements to create and store values inside the table. The table is as follows: PERSON (ID, name, hometown, age, occupation, gender, salary)

Now, execute the following queries:

Categorize the average salary of female persons based on occupation where the salary is at least 10000. (hint: having clause) OCCUPATION AVERAGE Doctor Engineer Farmer Musician Teacher 55000 42600 20000 50een 37250 10. Count the number of people who don't live in Dhaka and have average salary more than 30000. Show their home district and count. HOME COUNT Ctg Comilla Jashore Khulna 14 5 1 3