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Python Sets

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Introducing Python Sets

5:56 with AJ Tran

A set is an unordered collection of unique elements. Sets can be used like a Venn Diagram to compare and contrast the membership of elements in two or more collections.

[MUSIC] 0:00
Hi, my name is AJ, and I'm an instructor at Treehouse. 0:09
My pronouns include he, and they. 0:14
In this workshop, you're gonna learn about a new type of Python data structure, 0:17
the set. 0:22
What exactly is a set? 0:24
A set is a collection type with two basic properties. 0:26
First, the order of elements does not matter. 0:31
Second, all of the elements have unique values. 0:35
In other words, a set contains no duplicate values. 0:40
When an element is in a set, we say that it is a member of that set. 0:45
Membership is an important distinguishing feature of sets, and 0:51
we will be exploring this concept throughout the workshop. 0:55
The concepts of sets and 1:00
membership come from a branch of mathematics called set theory. 1:01
You don't have to be a math expert to understand how to use these in Python. 1:06
We'll start by visualizing set membership with diagrams. 1:11
On a diagram, a set is represented by a circle. 1:17
Let's imagine a set of fruit, apples, bananas, oranges, lemons, and limes. 1:21
So the order of the fruit does not matter. 1:29
In fact, if I change the order and then talk about limes, oranges, apples, 1:32
lemons, and then bananas, I'm still talking about the same set of fruit. 1:37
The set contains unique elements. 1:43
All of our fruits are distinctly different from each other. 1:46
This also means that a set cannot contain duplicate data. 1:50
If someone asks you to name five fruits, 1:54
you wouldn't say bananas five times, one is enough. 1:57
Since bananas are already in the set, it cannot be added again. 2:02
You may have already encountered sets in the form of Venn diagrams. 2:07
A Venn diagram allows us to visually compare and 2:12
contrast the elements that exist in two or more sets. 2:15
It's made of two or more overlapping circles. 2:19
And the overlapping area are where the elements or 2:22
members that both sets have in common. 2:26
Coffee and tea are both drinks that are made with hot water. 2:29
But coffee comes from roasting the seed of the coffee plant, which we call beans. 2:35
And tea comes from curing the leaves of the tea plant. 2:40
Both coffee and tea can have sugar, milk or cream. 2:44
Most importantly, both drinks have caffeine. 2:49
Venn diagrams can be used with more than two sets. 2:54
Let's imagine sets of ingredients of three foods from around the world. 2:58
Burrito, panini, and banh mi. 3:03
That's a lot of ingredients to keep track of. 3:06
Reorganizing all of this data into a Venn diagram will make the information easier 3:09
to understand. 3:14
Elements go into different circles based on their membership. 3:16
And the intersections contain the elements that the sets have in common 3:20
with each other. 3:25
And notice how the values are not duplicated, we just need one of each. 3:27
Now we can make comparisons about these foods to learn about what ingredients they 3:33
do and do not have in common. 3:38
Using a Venn diagram is a good way to visually analyze the differences and 3:41
similarities between multiple collections of data. 3:45
In Python, we can use sets so 3:50
that our programs can think in the same way that we do when we use a Venn diagram. 3:51
A lot of programming involves taking an input of raw data and 3:59
then processing it to output useful information. 4:03
So it's important to understand the different ways to structure data in order 4:06
to process it. 4:11
In Python, you've learned about how to use lists and tuples to collect 4:13
sequences of data, and dictionaries to collect data and key-value pairs. 4:18
Sets share characteristics of both lists and dictionaries. 4:25
Like lists, sets are mutable collections of single elements. 4:31
Mutable means that the data can be changed after its creation. 4:36
Unlike lists, however, 4:40
sets have no index because they're not a sequence. 4:43
That makes sets more similar to dictionaries, 4:49
which are also unordered collections. 4:52
In Python, both sets and dictionaries are highly optimized for look-up operations. 4:56
In a dictionary, you can look up a key to get a value like finding somebody's name 5:03
and then getting their phone number when you look in an address book. 5:07
But sets do not contain key-value pairs. 5:12
Instead with sets, we look up an element to check if it does, 5:15
or does not exist in the set. 5:20
This concept is called membership testing. 5:22
And we'll learn more about how to do this later. 5:25
Many programming languages have an implementation of sets to make it easy to 5:28
compare and contrast collections. 5:32
And they are all based in the mathematical field of set theory. 5:34
But don't worry about the math. 5:38
I've got real-world examples to explain these concepts in Python. 5:40
In the next video, we'll start by making our first sets. 5:44
And by the end of this workshop, 5:49
you will be a member of the set of Pythonistas who understand sets. 5:51