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DISTINCT

When working with databases, especially large ones, it's often necessary to filter out duplicate entries to get a clear picture of the unique data points. This is where DISTINCT comes into play. It helps us identify and work with unique values in a dataset, making our analysis cleaner and more precise.

In SQL, the DISTINCT keyword is used to return only unique values from a specified column, filtering out all duplicate entries. This can be incredibly useful when you want to understand the variety or range of data within a particular column.

Imagine you have an inventory database that tracks the tools available in a workshop. The table might look something like this:

sql
SELECT tools
FROM inventory;

This query could produce a result like:

tools
Hammer
Nails
Nails
Nails

As you can see, "Nails" appears multiple times. If we want to know just the unique tools available, we can use DISTINCT:

sql
SELECT DISTINCT tools
FROM inventory;

Now, the result would be:

tools
Hammer
Nails

By using DISTINCT, we quickly filter out the duplicates and see that the unique tools in our inventory are "Hammer" and "Nails".

Filtering the results of a query is an essential skill in SQL. It allows you to get a clearer view of your data without having to scan through every single row, which can be especially cumbersome in large datasets.

Activity

Let's put this into practice with a hands-on activity!

Identify Unique Genres

Open your SQL editor and type the following query:

sql
SELECT DISTINCT genre
FROM movies;

This query will return a list of unique genres from the movies table. Analyzing these unique genres can help you understand the variety of movies available.

genre
action
comedy
horror
romance
drama
NULL

Identify Unique Years

Now, let's modify the query to find unique years instead of genres. Change your code to:

sql
SELECT DISTINCT year
FROM movies;

This query will give you a list of unique years in which movies were released, providing a historical perspective on your movie database.

year
2009
2015
2012
2008
1999
1997
2006