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SQL Exercises, Practice, Solution - Aggregate Functions

SQL [25 exercises with solution]

1. From the following table, write a SQL query to calculate total purchase amount of all orders. Return total purchase amount.   Go to the editor

Sample table: orders


Sample Output:

sum
17541.18

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2. From the following table, write a SQL query to calculate the average purchase amount of all orders. Return average purchase amount.   Go to the editor

Sample table: orders


Sample Output:

avg
1461.7650000000000000

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3. From the following table, write a SQL query that counts the number of unique salespeople. Return number of salespeople.   Go to the editor

Sample table: orders


Sample Output:

count
6

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4. From the following table, write a SQL query to count the number of customers. Return number of customers.   Go to the editor

Sample table: customer


Sample Output:

count
8

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5. From the following table, write a SQL query to determine the number of customers who received at least one grade for their activity.   Go to the editor

Sample table: customer


Sample Output:

count
7

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6. From the following table, write a SQL query to find the maximum purchase amount.    Go to the editor

Sample table: orders


Sample Output:

max
5760.00

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7. From the following table, write a SQL query to find the minimum purchase amount.   Go to the editor

Sample table: orders


Sample Output:

min
65.26

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8. From the following table, write a SQL query to find the highest grade of the customers in each city. Return city, maximum grade.    Go to the editor

Sample table: customer


Sample Output:

city		max
London		300
Paris		300
New York	200
California	200
Berlin		100
Moscow		200

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9. From the following table, write a SQL query to find the highest purchase amount ordered by each customer. Return customer ID, maximum purchase amount.   Go to the editor

Sample table: orders


Sample Output:

customer_id	max
3007		2400.60
3008		250.45
3002		5760.00
3001		270.65
3009		2480.40
3004		1983.43
3003		75.29
3005		948.50

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10. From the following table, write a SQL query to find the highest purchase amount ordered by each customer on a particular date. Return, order date and highest purchase amount.   ;Go to the editor

Sample table: orders


Sample Output:

customer_id	ord_date	max
3002		2012-10-05	65.26
3003		2012-08-17	75.29
3005		2012-10-05	150.50
3007		2012-07-27	2400.60
3009		2012-08-17	110.50
3001		2012-09-10	270.65
3002		2012-09-10	5760.00
3005		2012-09-10	948.50
3009		2012-10-10	2480.40
3008		2012-06-27	250.45
3004		2012-10-10	1983.43
3002		2012-04-25	3045.60

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11. From the following table, write a SQL query to determine the highest purchase amount made by each salesperson on '2012-08-17'. Return salesperson ID, purchase amount   Go to the editor

Sample table: orders


Sample Output:

salesman_id	max
5003		110.50
5007		75.29

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12. From the following table, write a SQL query to find the highest order (purchase) amount by each customer on a particular order date. Filter the result by highest order (purchase) amount above 2000.00. Return customer id, order date and maximum purchase amount.   Go to the editor

Sample table: orders


Sample Output:

customer_id	ord_date	max
3007		2012-07-27	2400.60
3002		2012-09-10	5760.00
3009		2012-10-10	2480.40
3002		2012-04-25	3045.60

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13. From the following table, write a SQL query to find the maximum order (purchase) amount in the range 2000 - 6000 (Begin and end values are included.) by combination of each customer and order date. Return customer id, order date and maximum purchase amount.  Go to the editor

Sample table: orders


Sample Output:

customer_id	ord_date	max
3007		2012-07-27	2400.60
3002		2012-09-10	5760.00
3009		2012-10-10	2480.40
3002		2012-04-25	3045.60

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14. From the following table, write a SQL query to find the maximum order (purchase) amount based on the combination of each customer and order date. Filter the rows for maximum order (purchase) amount is either 2000, 3000, 5760, 6000. Return customer id, order date and maximum purchase amount.  Go to the editor

Sample table: orders


Sample Output:

customer_id	ord_date	max
3002		2012-09-10	5760.00

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15. From the following table, write a SQL query to determine the maximum order amount for each customer. The customer ID should be in the range 3002 and 3007(Begin and end values are included.). Return customer id and maximum purchase amount.  Go to the editor

Sample table: orders


Sample Output:

customer_id	max
3002		5760.00
3007		2400.60
3004		1983.43
3003		75.29
3005		948.50

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16. From the following table, write a SQL query to find the maximum order (purchase) amount for each customer. The customer ID should be in the range 3002 and 3007(Begin and end values are included.). Filter the rows for maximum order (purchase) amount is higher than 1000. Return customer id and maximum purchase amount.  Go to the editor

Sample table: orders


Sample Output:

customer_id	max
3002		5760.00
3007		2400.60
3004		1983.43

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17. From the following table, write a SQL query to determine the maximum order (purchase) amount generated by each salesperson. Filter the rows for the salesperson ID is in the range 5003 and 5008 (Begin and end values are included.). Return salesperson id and maximum purchase amount.  Go to the editor

Sample table: orders


Sample Output:

salesman_id	max
5005		270.65
5003		2480.40
5007		75.29
5006		1983.43

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18. From the following table, write a SQL query to count all the orders generated on '2012-08-17'. Return number of orders.   Go to the editor

Sample table: orders


Sample Output:

count
2

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19. From the following table, write a SQL query to count the number of salespeople in a city. Return number of salespeople.   Go to the editor

Sample table: salesman


Sample Output:

count
6

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20. From the following table, write a SQL query to count the number of orders based on the combination of each order date and salesperson. Return order date, salesperson id.  Go to the editor

Sample table: orders


Sample Output:

ord_date	salesman_id	count
2012-07-27	5001		1
2012-08-17	5007		1
2012-04-25	5001		1
2012-09-10	5002		1
2012-10-05	5002		1
2012-10-10	5003		1
2012-09-10	5005		1
2012-08-17	5003		1
2012-06-27	5002		1
2012-09-10	5001		1
2012-10-05	5001		1
2012-10-10	5006		1

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21. From the following table, write a SQL query to calculate the average product price. Return average product price.  Go to the editor

Sample table: item_mast


Sample Output:

Average Price
1435.0000000000000000

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22. From the following table, write a SQL query to count the number of products whose price are higher than or equal to 350. Return number of products.  Go to the editor

Sample table: item_mast


Sample Output:

Number of Products
8

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23. From the following table, write a SQL query to compute the average price for unique companies. Return average price and company id.  Go to the editor

Sample table: item_mast


Sample Output:

Average Price			Company ID
250.0000000000000000		14
650.0000000000000000		12
3200.0000000000000000		15
5000.0000000000000000		11
1475.0000000000000000		13
500.0000000000000000		16

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24. From the following table, write a SQL query to compute the sum of the allotment amount of all departments. Return sum of the allotment amount.   Go to the editor

Sample table: emp_department


Sample Output:

sum
450000

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25. From the following table, write a SQL query to count the number of employees in each department. Return department code and number of employees.  Go to the editor

Sample table: emp_details


Sample Output:

emp_dept		count
27			2
57			5
47			3
63			3

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Practice Online


More to Come !

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

Do not submit any solution of the above exercises at here, if you want to contribute go to the appropriate exercise page.



SQL: Tips of the Day

SQL Server SELECT into existing table.

INSERT INTO dbo.TABLETWO
SELECT col1, col2
  FROM dbo.TABLEONE
 WHERE col3 LIKE @search_key

This assumes there's only two columns in dbo.TABLETWO - you need to specify the columns otherwise:

INSERT INTO dbo.TABLETWO
  (col1, col2)
SELECT col1, col2
  FROM dbo.TABLEONE
 WHERE col3 LIKE @search_key

Database: SQL Server

Ref: https://bit.ly/3y6tpA3