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Basics

30 Bra Queries

1. Retrieving Data From All Columns

This is a very basic query to display all data from a table. Notice that this query only has one character after SELECT: "*" (this denotes all columns). Therefore, you don't need to list the names of the columns. Of course, remember to write FROM and the name of the table from which you want to retrieve data. In this example, we are retrieving data from the table animal.
SELECT *
FROM animal;

2. Retrieving Data From Certain Columns

The query above displays all of the data from the table animal. If you would like to only retrieve data from certain columns, list them after SELECT. In this example, we are retrieving data from the id and name columns.
SELECT id, name
FROM animal;

3. Filtering Data Using WHERE Clause

In addition to retrieving data from certain columns, you can also filter data by listing conditions after WHERE. In this example, there is one condition: age>=2. We are looking for records with a value of 2 or more in the column age.
SELECT id, name, age
FROM animal
WHERE age>=2;

4. Filtering Data Using Conditions Joined by AND Operator

If you want to filter data using more than one condition, you can use AND. In this example, we are looking for records with a value of 2 or more in the column age and 'dog' in the column name.
SELECT id, name, age
FROM animal
WHERE age >= 2 AND name = 'dog';

5. Filtering Data Using Conditions Joined by OR Operator

If only one of the conditions needs to be met, you can use OR. In this example, we are looking for records with a value of 2 or more in the column age or 'dog' in the column name.
SELECT id, name, age
FROM animal
WHERE age >= 2 OR name = 'dog';

6. Using DISTINCT to Retrieve Non-Repeated Records

You can place DISTINCT after SELECT to retrieve only one of each type of record. In this example, we want to retrieve records from columns name and color. If the values from these columns are the same in more than one record (e.g., there is more than one yellow T-shirt in the table), the query returns only one of those records.
SELECT DISTINCT name, color
FROM clothing;

7. Retrieving Data Without NULL in a Certain Column

If you want to retrieve data only from rows without NULL in a certain column, use IS NOT NULL. In this example, the value in the column color may not be NULL. So, only records with a value stored in the column color will be returned. A similar operator to IS NOT NULL is IS NULL, which checks if a value is equal to NULL.
SELECT name, color
FROM clothing
WHERE color IS NOT NULL;

8. Sorting Data According to One Column

To sort data according to a column, place the column name after ORDER BY. The default sorting method is alphabetical, but you can also display rows in descending order by adding DESC after the name of the column. In this example, we want to sort the data in columns id and name according to the column name.
SELECT id, name
FROM animal
ORDER BY name;

9. Sorting Data According to More Than One Column

You can also sort data according to more than one column. In this example, the records are first sorted according to the column name in descending order and next according to the column id in ascending order. If the query finds records with the same name (e.g., all records with 'dog' in column name), it sorts these records in ascending order according to id.
SELECT id, name
FROM animal
ORDER BY name DESC, id;

10. Searching for Values Matching a Certain Pattern

You can use LIKE to retrieve data that matches a certain pattern. In this example, we want to retrieve records from columns id and name that store a string containing the character "e" in the column name (e.g., records with names like elephant, bee, etc.)
SELECT id, name
FROM animal
WHERE name LIKE '%e%';

11. Joining Values From Text Columns Into One String

The CONCAT function joins strings. In this example, the strings stored in the columns category and name are returned as a single column of strings with a space between the value in the column category and the value in the column name.
SELECT CONCAT(category, ' ', name)
FROM tab;

12. Using Mathematical Operators

You can write queries to calculate values by using mathematical operators like "+," "-," "*," and "/." In this example, we want to calculate the discounted price by subtracting the value in the column discount from the value in the column price.
SELECT price - discount
FROM product;

13. Adding Data From Different Tables

You can join records from different tables using the operator UNION ALL. Remember that the records must be the same data type. In this example, we want to retrieve all rows with last names from the table customer and all rows with last names from the table employee. It will retrieve all last names, even if they are repeated. If we want to select all last names without repeats, we would use UNION instead of UNION ALL.
SELECT last_name FROM customer
UNION ALL
SELECT last_name FROM employee;

14. Finding the Intersection of Sets of Data

INTERSECT returns the intersection of two sets of data. In this example, we only want to retrieve the last names listed in both tables. To see what is different between the sets, use the operators MINUS or EXCEPT.
If you'd like to know more about set operators and see the visual explanation of this concept, .
SELECT last_name FROM customer
INTERSECT
SELECT last_name FROM employee;

15. Joining Data From Different Tables

You can join tables using JOIN, including INNER JOIN, LEFT JOIN, RIGHT JOIN, FULL JOIN, and CROSS JOIN (please see the courses listed at the end of this article for more information). In this example, we want to join data from the tables customer and city. INNER JOIN needs to come after FROM and the name of the first table, customer. After INNER JOIN, place the name of the second table, city. The records with data from both tables are matched by ON with the condition to join. The records in the table city are matched to the records from the table customer if they have the same value in the column id in the table customer and in the column customer_id in the table city.
SELECT customer.last_name, city.name
FROM customer
INNER JOIN city
ON customer.id = city.customer_id;

16. Using Aliases of Tables and Columns

If you join tables, it is a good idea to use aliases for table and column names. In this example, we want to join two tables, customer and city, and name them c and t, respectively. We define these new names in FROM or JOIN, using AS. Similarly, we rename the columns last_name in the table customer and name in the table city as lname and city, respectively.
SELECT c.last_name AS lname, t.name AS city
FROM customer AS c
INNER JOIN city AS t
ON c.id = t.customer_id;

17. Counting the Number of Rows in a Table

COUNT counts the number of rows. In this example, it returns the number of values from the column id stored in the table product (the number of all products).
SELECT COUNT(id)
FROM product;

18. Calculating the Average of the Values in a Column

You can calculate the average of the values in a column using AVG. In this example, the query returns the average price of all products in the table product.
SELECT AVG(price)
FROM product;

19. Calculating the Sum of the Values in a Column

SUM calculates the sum of the values in a column. In this example, it returns the value of all of the products.
SELECT SUM(price)
FROM product;

20. Finding the Minimum Value in a Column

You can find the minimum value stored in a column using MIN. In this example, the query returns the minimum price among the products.
SELECT MIN(price)
FROM product;

21. Finding the Maximum Value in a Column

You can find the maximum value stored in a column using MAX. In this example, the query returns the maximum price among the products.
SELECT MAX(price)
FROM product;

22. Calculating the Aggregate Value for Groups of Records

GROUP BY puts rows into groups to calculate a value. In this example, we use COUNT to calculate the number of rows (the number of products) in each group (category). The columns in SELECT have to put in the GROUP BY clause. GROUP BY can be used in the same way with other aggregate functions like MAX, MIN, AVG, and SUM.
SELECT category, COUNT(id)
FROM product
GROUP BY category;

23. Filtering Rows Using Aggregate Functions

You can filter records after calculating values for each group using HAVING. In this example, we want to retrieve categories with an average price of products less than 56.50.
SELECT category, AVG(price)
FROM product
GROUP BY category
HAVING AVG(price) < 56.50;

24. Removing Data From a Table

DELETE FROM removes all data from a table. In this example, we want to delete all data from the table product.
DELETE FROM product;

25. Removing Records Meeting a Certain Condition From a Table

You can remove records meeting a certain condition using WHERE. In this example, we want to remove records from the table product with id equal to 5.
DELETE FROM product
WHERE id = 5;

26. Inserting Data Into a Table

You can add a new record to a table using INSERT INTO. After INSERT INTO, put the name of the table and then in brackets the names of the columns of the table. After that, put VALUES and then in the brackets the values for the columns. In this example, we want to insert 25 into id, 'sofa' into name, and 'furniture' into category in the table product.
INSERT INTO product(id, name, category)
VALUES(25, 'sofa', 'furniture');

27. Updating a Column in a Table

UPDATE allows you to modify data in the records. After UPDATE, put the name of the table, then SET, and then the name of the column to modify with "=" and new value to insert. This query modifies all values in the column. In this example, we want to change all values in the column company to 'ABC'.
UPDATE product SET company = 'ABC';

28. Updating a Column by Filtering Records

However, if you don't want to change all values in a column, you can add WHERE with a condition. In the condition, you can specify which records to modify. In this example, we want to change values in the column name to 'armchair' only for records with id=25.
UPDATE product
SET name = 'armchair'
WHERE id = 25;

29. Creating a Table

You can create a table using CREATE TABLE. After CREATE TABLE, put the name of the table and define in brackets the names of the columns and their data types. In this example, we want to create the table tab with two columns: id with integer as the data type and name limited to a maximum of 50 characters.
CREATE TABLE tab(id int, name varchar(50));
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30. Deleting a Table

You can delete a table using DROP TABLE. Simply put the name of the table you want to delete after DROP TABLE. In this example, we want to delete the table tab.
DROP TABLE tab;
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