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- Introducing Python Sets 5:56
- Practice Files
- The First Property: No Order 3:58
- The Second Property: No Duplicates 7:24
- Immutable Data Types 7:45
- The Set Constructor Function 10:38
- Sets Simplify Data Processing 5:03
- Set Mutability: Adding Elements 4:44
- Set Mutability: Deleting Elements 11:33
- Set Membership & Relationship 11:03
- Set Operations: Union & Intersection 6:55
- Set Operations: Symmetric Difference & Difference 5:55
- Exercise 7:03
- Conclusion
Preview
Video Player
00:00
00:00
00:00
- 2x 2x
- 1.75x 1.75x
- 1.5x 1.5x
- 1.25x 1.25x
- 1.1x 1.1x
- 1x 1x
- 0.75x 0.75x
- 0.5x 0.5x
Sets can be useful when trying to remove duplicates from a list.
Code Snippets
# Sort and Deduplicate a list (not using sets)
numbers = [3,1,2,2,1,3,3,1,2]
unique_numbers = []
# enumerate will track the index while looping
for index, number in enumerate(sorted(numbers)):
if index == 0:
unique_numbers.append(number)
elif number == unique_numbers[-1]:
pass
else:
unique_numbers.append(number)
print(unique_numbers)
#=> [1,2,3]
# Sort and Deduplicate a list (using sets)
numbers = [3,1,2,2,1,3,3,1,2]
unique_numbers = sorted(set(numbers))
print(unique_numbers)
#=> [1,2,3]
Extra Credit
Here are more "constructor" functions that convert sets into other collection types:
list() - convert a set into a list. Elements may be in random order.
tuple() - convert a set into a tuple. Elements may be in random order.
frozenset() - convert a set into a frozen set. A frozenset is an immutable set. As a list is to a tuple, a set is to a frozenset.
Frozensets are not commonly used so I will mention some examples here as a technical note.
- Frozensets can be used as dictionary keys, ie. the dictionary key is like an "unordered tuple."
- Frozensets are used in the Python source code for tests and documenting implementation details.
- Frozensets can be practical for unit testing, eg. to test that the keys of a dictionary are equal to an expected, immutable frozenset of keys.
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It is a common pattern in programming
to take one data type and
0:01
convert it into another data type.
0:04
Sets fit into this pattern when
it comes to pre-processing data.
0:07
For example,
let's take a list of random integers
0:13
where some of the values
are repeated in the list.
0:17
So we've got some threes,
some ones, some twos, and
0:28
they're in no particular order here.
0:31
Now, imagine trying to remove
the duplicates from this list
0:37
without using sets.
0:42
We can work through this together,
0:44
we can pseudocode the steps
required to remove the duplicates.
0:46
Pause me, and I'll let you try it first,
and then I'll show you how I did it.
1:04
How did it go?
1:13
Was it challenging?
1:14
Here's what I came up with.
1:16
My strategy is to iterate
through the list of integers and
1:19
then collect the unique
values into a new list.
1:23
First I sort the original list.
1:26
It's easier to process data if you sort
it first before doing more calculations.
1:28
Then I loop through the sorted list.
1:34
Since the list is sorted, every time
the loop moves to the next element,
1:39
I can compare it to the previous element.
1:43
On each step of the loop, for the first
step I just put that number into a new
1:47
list because there's nothing to
compare when it's just the first one.
1:52
For every next number, I compare it
to the last number in the new list.
1:57
If the values are equal then I can pass,
I don't need to do anything.
2:03
If the values are not equal, then I
put that number in the new list, and
2:08
what happens is that I can end with
a list of no duplicate numbers.
2:12
You can check my teacher's notes
to see my implementation code.
2:17
That was quite the mental exercise.
2:22
Fortunately, it's not as
complicated with sets.
2:24
Let's scroll back up to see
our list of numbers again.
2:29
This time, let's just pass that list
into the set constructor function.
2:33
And we'll print this out as well.
2:40
So for now, I've printed out a set
of the numbers, we can see one,
2:52
two and three,
all of the duplicates are just gone.
2:57
I can use the sorted function
to convert it back into a list.
3:03
So here, Let's say
3:08
numbers equals a set of numbers.
3:13
First we convert our list into a set,
3:18
then numbers equals sorted numbers,
3:22
we convert our set back into a list.
3:26
Now watch what happens
when I print out numbers.
3:30
I have a list of one, two, and three.
3:37
It's in order.
3:42
And it's all of the unique numbers
there are no duplicates here.
3:43
These two functions, sorted and
set can also be chained together
3:49
very easily to clean any list of
duplicated data in one line of code.
3:54
I'll show you what that looks like.
4:00
So we can say unique numbers
4:04
equals sorted set of numbers,
4:09
we can print our unique numbers.
4:13
And in the console,
I can run my script again to get 1, 2 and
4:18
3, my list of unique numbers
in a very pythonic manner.
4:24
So, we've just learned how to use the set
constructor function to make an empty set.
4:33
And to make a set from an iterable and
4:39
we explored more in-depth about how
using sets can simplify data processing.
4:41
when duplicates need to be
removed from a collection.
4:46
Now, we're ready to learn about set
specific methods and operations.
4:51
In the next video,
we will learn the basics of adding and
4:56
removing elements from a set.
5:00
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