SQL SELECT

🎬 Scenario: Analyzing Netflix Hit Series#

You’ve just been hired as a Data Analyst at Netflix! Your first task is to extract insights on the platform’s most successful series.

Your manager, Alex, has asked:

We need a report on our top-performing series, including their ratings, genres, and total viewership. Can you retrieve this data?

To get started, take a look at the netflix_series table, which contains key details:

1. The Basics: SELECT *#

The SELECT statement is the foundation of SQL. It’s how we retrieve data from a database.

Syntax

SELECT * FROM table_name;

Example Query

SELECT * FROM netflix_series;

Output Example

What’s Happening?

• SELECT * means “Show me everything in this table.”
• While SELECT * works, in real-world data analysis, we often only need specific columns.

2. Selecting Specific Columns#

Instead of retrieving all columns, you can specify which columns you need.

Syntax

SELECT column1, column2 FROM table_name;

Example Query

SELECT title, genre, rating FROM netflix_series;

Output Example

Why is this better than SELECT *?

• Faster Execution – Only pulls needed columns, reducing unnecessary data.
• More Readable – Avoids cluttering the results with extra columns.

3. Using Aliases (AS) for Readability#

Your manager wants to create a report where column names are more readable.
SQL allows you to rename columns using AS.

Syntax

SELECT column_name AS new_name FROM table_name;

Example Query

1SELECT title AS "Show Name", 
2       genre AS "Category", 
3       rating AS "IMDb Score"
4FROM netflix_series;

Output Example

Why Use Aliases?

• Makes reports more readable for non-technical users.
• Useful when working with complex queries that involve calculations or joins.

✍️ SQL Exercises#

Exercise 1: Renaming Columns for a Netflix Series Report#

Your manager wants a list of Netflix series along with their release year and total viewership. However, the column names should be more readable for a company report.

Rename the columns as follows:

• title → “Series Name”
• release_year → “Years Released”
• total_views_millions → “Total Views (Millions)”

Write an SQL query to retrieve the requested data.

Expected Output:

Write an SQL query to return the requested data.