SELECT

Previously, we touched upon the importance of the SELECT statement. Every time you want to retrieve data from a database, SELECT is your go-to command. It's the gateway to accessing and manipulating the data stored in your tables.

When you use SELECT in its most basic form, with an asterisk (*), you're asking the database to return all the columns from a table. It's like saying, "Give me everything you've got!" For example:

SELECT *
FROM table_name;

This is incredibly useful when you need a broad overview of the data. However, what if you're only interested in specific pieces of information? That's where specifying individual columns comes in handy.

Selecting Specific Columns

Suppose we're only interested in two columns from our table. We can specify these columns by their names, separated by a comma. This makes our query more efficient and our results more readable.

SELECT column1, column2
FROM table_name;

Notice how we moved FROM to a new line. This is purely for readability. In SQL, line breaks don't affect the functionality of your query. You could write the entire query in one line if you prefer, and it would still run perfectly.

Activity

Now it's time to put theory into practice! Let's dive into a hands-on activity to reinforce our understanding.

Selecting Specific Columns

Select the name and genre columns from the movies table.

SELECT name, genre
FROM movies;

This will retrieve only the name and genre of each movie, making our results more focused and easier to analyze.

name	genre
Avatar	action
Jurassic World	action
The Avengers	action
The Dark Knight	action
Star Wars: Episode I - The Phantom Menace	action
Star Wars	action
...	...

Adding More Columns

Now, let's expand our query to include a third column.

Edit your query so that it returns the name, genre, and year columns from the movies table. Update your code to:

SELECT name, genre, year
FROM movies;

This modification allows us to see not only the name and genre of each movie but also the year it was released, giving us a richer dataset to work with.

name	genre	year
Avatar	action	2009
Jurassic World	action	2015
The Avengers	action	2012
The Dark Knight	action	2008
Star Wars: Episode I - The Phantom Menace	action	1999
Star Wars	action	1977
...	...	...