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Question
Explain the following SQL function using a suitable example.
TRIM()
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Solution
TRIM(): It removes the leading and trailing spaces from the given string.
Example: SELECT TRIM(‘ Welcome world ‘);
Output: Welcome world
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______ keyword is used to find out the number of values in a column?
Which of the following belongs to an "aggregate function"?
Consider the table STUDENT given below:
| RollNo | Name | Class | DOB | Gender | City | Marks |
| 1 | Anand | XI | 6/6/97 | M | Agra | 430 |
| 2 | Chetan | XII | 7/5/94 | M | Mumbai | 460 |
| 3 | Geet | XI | 6/5/97 | F | Agra | 470 |
| 4 | Preeti | XII | 8/8/95 | F | Mumbai | 492 |
| 5 | Saniyal | XII | 8/10/95 | M | Delhi | 360 |
| 6 | Maakhiy | XI | 12/12/94 | F | Dubai | 256 |
| 7 | Neha | X | 8/12/95 | F | Moscow | 324 |
| 8 | Nishant | X | 12/6/95 | M | Moscow | 429 |
State the command that will give the output as:
| Name |
| Anand |
| Chetan |
| Geet |
| Preeti |
(i) select Name from student where Class ='XI' and Class='XII';
(ii) select name from student where not Class='XI' and Class='XII';
(iii) select name from student where City="Agra" or City="Mumbai";
(iv) select name from student where City in("Agra", "Mumbai");
Choose the correct option:
Consider the table STUDENT given below:
| RollNo | Name | Class | DOB | Gender | City | Marks |
| 1 | Anand | XI | 6/6/97 | M | Agra | 430 |
| 2 | Chetan | XII | 7/5/94 | M | Mumbai | 460 |
| 3 | Geet | XI | 6/5/97 | F | Agra | 470 |
| 4 | Preeti | XII | 8/8/95 | F | Mumbai | 492 |
| 5 | Saniyal | XII | 8/10/95 | M | Delhi | 360 |
| 6 | Maakhiy | XI | 12/12/94 | F | Dubai | 256 |
| 7 | Neha | X | 8/12/95 | F | Moscow | 324 |
| 8 | Nishant | X | 12/6/95 | M | Moscow | 429 |
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(i) Select Gender, avg(Marks) from STUDENT where Class= "XI" group by Gender;
(ii) Select Gender, avg(Marks) from STUDENT group by Gender where Class="XI";
(iii) Select Gender, avg(Marks) group by Gender from STUDENT having Class="XI";
(iv) Select Gender, avg(Marks) from STUDENT group by Gender having Class = "XI";
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| 1 | Abhishek | XI | M | Agra | 430 |
| 2 | Prateek | XII | M | Mumbai | 440 |
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| 4 | Nancy | XII | F | Mumbai | 492 |
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| 6 | Anchal | XI | F | Dubai | 256 |
| 7 | Mehar | X | F | Moscow | 324 |
| 8 | Nishant | X | M | Moscow | 429 |
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