a) Write SQL queries for the following. 1) Display details of those patients whose age is either 25 or 36 or 29 without using comparison operator.
a) Write SQL queries for the following.
1) Display details of those patients whose age is either 25 or 36 or 29 without using comparison operator.
2) Display first name and last name of those doctors whose salary is less than or equal to 77,000 and greater than or equal to 50,000 using between operator.
3) Display details of those doctors who neither belong to Isb nor Rwp nor Multan without using in and like operator.
4) Display full name of doctors whose first name is other than Tania.
5) Display first name of doctors whose first name contains any of vowels (a,e,i,o,u).
6) Display names of those patients whose name’s second letter is neither ‘a’ nor ‘d’
7) Display details of those male patients whose age is 25 or 36.
8) Display details of those patients whose name contains less than 5 characters.
9) Display first 4 doctors who are earning least salary.
10) Display details of all patients in such a way that female patients are shown before male patients.
11) Display the unique cities from doctor table.
12) Display all patients.
13) Display details of all those doctors whose salary is greater than 50000 or live in Rwp
14) Display names of those patients whose names starts with either ‘a’ or ‘b’ or‘d’ and don’t ends on‘s’.
15) Display 1/4 records of patients.
b) Assume the schema given above and identify the following queries are executable or not. If yes then draw their results, if not then mention their errors.
1) Select * from patient where age between not 25 and 31;
2) Select D_Fname+’ ‘+D_Lname as [name] from doctor where D_Fname like ‘_[^ubs]%’ ;
3) Select P_Name, gender from patient where age in(25,29,38) or gender=’Mle’ ;
4) Select D_Id from doctor where salary >60000 and <80000;
5) Select * from doctor where city=’sib’ or city=’wrp’ ;
![Patient
Doctor
P ld
PName
Gender Age
1
Aqib
Male
25
D ld
DEname D Lname Salary City
Saima
Female 36
1
Laiba
Hafeez
50000 | Rwp
3
Fatima
Female
29
2
Sameer
Khan
80000 Isb
4
Nouman
Male
31
Muneeb
Male
40
3
Talib
Ali
62000 Işb
6.
Tariq
Male
38
Saleem
Iqbal
77000 Multan
7
Ikram
Male
26
Tania
Abbas
85000 Lahore
8
Sadia
Female 27
Huda
Ahmad
68000 | Rwp
4.
9,](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F10a14dbb-ffb9-42ed-85ee-e50e96b88231%2F2bc2de9d-a349-4cde-b6d6-83af431fa2d9%2Fchlkdxj_processed.jpeg&w=3840&q=75)
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