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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.
What is a Set?
An unordered collection of unique elements
Properties of a set
- The order does not matter
- Contains no duplicate values
What is a Member?
An element of a set
Sets vs Lists
Similarities
- Mutable
- Collect single elements
Differences
- Sets have no index
- Sets are not a sequence
Sets vs Dictionaries
Similarities
- Unordered collection
- Very fast with "look-up" operations
Differences
- Sets have no key-value pairs
- Set "look-up" is a test for membership
- "True or False: does it exist in the set?"
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[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
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