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SQL Exercises, Practice, Solution - Using Boolean and Relational operators

SQL [12 exercises with solution]

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1. Customers with Grade > 100

From the following table, write a SQL query to locate the details of customers with grade values above 100. Return customer_id, cust_name, city, grade, and salesman_id. 

Sample table: customer

 customer_id |   cust_name    |    city    | grade | salesman_id 
-------------+----------------+------------+-------+-------------
        3002 | Nick Rimando   | New York   |   100 |        5001
        3007 | Brad Davis     | New York   |   200 |        5001
        3005 | Graham Zusi    | California |   200 |        5002
        3008 | Julian Green   | London     |   300 |        5002
        3004 | Fabian Johnson | Paris      |   300 |        5006
        3009 | Geoff Cameron  | Berlin     |   100 |        5003
        3003 | Jozy Altidor   | Moscow     |   200 |        5007
        3001 | Brad Guzan     | London     |       |        5005

Click me to see the solution with visual presentation

2. New York Customers with Grade > 100

From the following table, write a SQL query to find all the customers in ‘New York’ city who have a grade value above 100. Return customer_id, cust_name, city, grade, and salesman_id.  

Sample table: customer

 customer_id |   cust_name    |    city    | grade | salesman_id 
-------------+----------------+------------+-------+-------------
        3002 | Nick Rimando   | New York   |   100 |        5001
        3007 | Brad Davis     | New York   |   200 |        5001
        3005 | Graham Zusi    | California |   200 |        5002
        3008 | Julian Green   | London     |   300 |        5002
        3004 | Fabian Johnson | Paris      |   300 |        5006
        3009 | Geoff Cameron  | Berlin     |   100 |        5003
        3003 | Jozy Altidor   | Moscow     |   200 |        5007
        3001 | Brad Guzan     | London     |       |        5005

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3. New York or Grade > 100

From the following table, write a SQL query to find customers who are from the city of New York or have a grade of over 100. Return customer_id, cust_name, city, grade, and salesman_id.  

Sample table: customer

 customer_id |   cust_name    |    city    | grade | salesman_id 
-------------+----------------+------------+-------+-------------
        3002 | Nick Rimando   | New York   |   100 |        5001
        3007 | Brad Davis     | New York   |   200 |        5001
        3005 | Graham Zusi    | California |   200 |        5002
        3008 | Julian Green   | London     |   300 |        5002
        3004 | Fabian Johnson | Paris      |   300 |        5006
        3009 | Geoff Cameron  | Berlin     |   100 |        5003
        3003 | Jozy Altidor   | Moscow     |   200 |        5007
        3001 | Brad Guzan     | London     |       |        5005

Click me to see the solution with visual presentation

4. New York or Not Grade > 100

From the following table, write a SQL query to find customers who are either from the city 'New York' or who do not have a grade greater than 100. Return customer_id, cust_name, city, grade, and salesman_id.  

Sample table: customer

 customer_id |   cust_name    |    city    | grade | salesman_id 
-------------+----------------+------------+-------+-------------
        3002 | Nick Rimando   | New York   |   100 |        5001
        3007 | Brad Davis     | New York   |   200 |        5001
        3005 | Graham Zusi    | California |   200 |        5002
        3008 | Julian Green   | London     |   300 |        5002
        3004 | Fabian Johnson | Paris      |   300 |        5006
        3009 | Geoff Cameron  | Berlin     |   100 |        5003
        3003 | Jozy Altidor   | Moscow     |   200 |        5007
        3001 | Brad Guzan     | London     |       |        5005

Click me to see the solution with visual presentation

5. Not New York and Not Grade > 100

From the following table, write a SQL query to identify customers who are not from the city of 'New York' and do not have a grade value greater than 100. Return customer_id, cust_name, city, grade, and salesman_id.

Sample table: customer

 customer_id |   cust_name    |    city    | grade | salesman_id 
-------------+----------------+------------+-------+-------------
        3002 | Nick Rimando   | New York   |   100 |        5001
        3007 | Brad Davis     | New York   |   200 |        5001
        3005 | Graham Zusi    | California |   200 |        5002
        3008 | Julian Green   | London     |   300 |        5002
        3004 | Fabian Johnson | Paris      |   300 |        5006
        3009 | Geoff Cameron  | Berlin     |   100 |        5003
        3003 | Jozy Altidor   | Moscow     |   200 |        5007
        3001 | Brad Guzan     | London     |       |        5005

Click me to see the solution with visual presentation

6. Exclude Specific Orders

From the following table, write a SQL query to find details of all orders excluding those with ord_date equal to '2012-09-10' and salesman_id higher than 5005 or purch_amt greater than 1000.Return ord_no, purch_amt, ord_date, customer_id and salesman_id.  

Sample table : orders

ord_no      purch_amt   ord_date    customer_id  salesman_id
----------  ----------  ----------  -----------  -----------
70001       150.5       2012-10-05  3005         5002
70009       270.65      2012-09-10  3001         5005
70002       65.26       2012-10-05  3002         5001
70004       110.5       2012-08-17  3009         5003
70007       948.5       2012-09-10  3005         5002
70005       2400.6      2012-07-27  3007         5001
70008       5760        2012-09-10  3002         5001
70010       1983.43     2012-10-10  3004         5006
70003       2480.4      2012-10-10  3009         5003
70012       250.45      2012-06-27  3008         5002
70011       75.29       2012-08-17  3003         5007
70013       3045.6      2012-04-25  3002         5001

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7. Salespeople with Commission Range 0.10-0.12

From the following table, write a SQL query to find the details of those salespeople whose commissions range from 0.10 to0.12. Return salesman_id, name, city, and commission. 

Sample table : salesman

 salesman_id |    name    |   city   | commission 
-------------+------------+----------+------------
        5001 | James Hoog | New York |       0.15
        5002 | Nail Knite | Paris    |       0.13
        5005 | Pit Alex   | London   |       0.11
        5006 | Mc Lyon    | Paris    |       0.14
        5007 | Paul Adam  | Rome     |       0.13
        5003 | Lauson Hen | San Jose |       0.12

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8. Orders with Amount < 200 or Exclusions

From the following table, write a SQL query to find details of all orders with a purchase amount less than 200 or exclude orders with an order date greater than or equal to '2012-02-10' and a customer ID less than 3009. Return ord_no, purch_amt, ord_date, customer_id and salesman_id.

Sample table : orders

ord_no      purch_amt   ord_date    customer_id  salesman_id
----------  ----------  ----------  -----------  -----------
70001       150.5       2012-10-05  3005         5002
70009       270.65      2012-09-10  3001         5005
70002       65.26       2012-10-05  3002         5001
70004       110.5       2012-08-17  3009         5003
70007       948.5       2012-09-10  3005         5002
70005       2400.6      2012-07-27  3007         5001
70008       5760        2012-09-10  3002         5001
70010       1983.43     2012-10-10  3004         5006
70003       2480.4      2012-10-10  3009         5003
70012       250.45      2012-06-27  3008         5002
70011       75.29       2012-08-17  3003         5007
70013       3045.6      2012-04-25  3002         5001

Click me to see the solution with visual presentation

9. Conditional Orders Exclusions

From the following table, write a SQL query to find all orders that meet the following conditions. Exclude combinations of order date equal to '2012-08-17' or customer ID greater than 3005 and purchase amount less than 1000.

Sample table : orders

ord_no      purch_amt   ord_date    customer_id  salesman_id
----------  ----------  ----------  -----------  -----------
70001       150.5       2012-10-05  3005         5002
70009       270.65      2012-09-10  3001         5005
70002       65.26       2012-10-05  3002         5001
70004       110.5       2012-08-17  3009         5003
70007       948.5       2012-09-10  3005         5002
70005       2400.6      2012-07-27  3007         5001
70008       5760        2012-09-10  3002         5001
70010       1983.43     2012-10-10  3004         5006
70003       2480.4      2012-10-10  3009         5003
70012       250.45      2012-06-27  3008         5002
70011       75.29       2012-08-17  3003         5007
70013       3045.6      2012-04-25  3002         5001

Click me to see the solution with visual presentation

10. Orders with Achieved Percentage > 50%

Write a SQL query that displays order number, purchase amount, and the achieved and unachieved percentage (%) for those orders that exceed 50% of the target value of 6000.  

Sample table: orders

ord_no      purch_amt   ord_date    customer_id  salesman_id
----------  ----------  ----------  -----------  -----------
70001       150.5       2012-10-05  3005         5002
70009       270.65      2012-09-10  3001         5005
70002       65.26       2012-10-05  3002         5001
70004       110.5       2012-08-17  3009         5003
70007       948.5       2012-09-10  3005         5002
70005       2400.6      2012-07-27  3007         5001
70008       5760        2012-09-10  3002         5001
70010       1983.43     2012-10-10  3004         5006
70003       2480.4      2012-10-10  3009         5003
70012       250.45      2012-06-27  3008         5002
70011       75.29       2012-08-17  3003         5007
70013       3045.6      2012-04-25  3002         5001

Click me to see the solution with visual presentation

11. Employees with Last Name Dosni or Mardy

From the following table, write a SQL query to find the details of all employees whose last name is ‘Dosni’ or ‘Mardy’. Return emp_idno, emp_fname, emp_lname, and emp_dept.  

Sample table : emp_details

 EMP_IDNO EMP_FNAME       EMP_LNAME         EMP_DEPT
--------- --------------- --------------- ----------
   127323 Michale         Robbin                  57
   526689 Carlos          Snares                  63
   843795 Enric           Dosio                   57
   328717 Jhon            Snares                  63
   444527 Joseph          Dosni                   47
   659831 Zanifer         Emily                   47
   847674 Kuleswar        Sitaraman               57
   748681 Henrey          Gabriel                 47
   555935 Alex            Manuel                  57
   539569 George          Mardy                   27
   733843 Mario           Saule                   63
   631548 Alan            Snappy                  27
   839139 Maria           Foster                  57

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12. Employees in Department 47 or 63

rom the following table, write a SQL query to find the employees who work at depart 47 or 63. Return emp_idno, emp_fname, emp_lname, and emp_dept.  

Sample table : emp_details

 EMP_IDNO EMP_FNAME       EMP_LNAME         EMP_DEPT
--------- --------------- --------------- ----------
   127323 Michale         Robbin                  57
   526689 Carlos          Snares                  63
   843795 Enric           Dosio                   57
   328717 Jhon            Snares                  63
   444527 Joseph          Dosni                   47
   659831 Zanifer         Emily                   47
   847674 Kuleswar        Sitaraman               57
   748681 Henrey          Gabriel                 47
   555935 Alex            Manuel                  57
   539569 George          Mardy                   27
   733843 Mario           Saule                   63
   631548 Alan            Snappy                  27
   839139 Maria           Foster                  57

Click me to see the solution with result

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Query visualizations are generated using Postgres Explain Visualizer (pev).

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