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Sets Datatype in Python

Set datatype in Python is mutable, iterable and does not have any duplicate elements. It is an unordered collection of elements which means that a set is a collection that stores elements of different data types. Remember that, set doesn’t index them in a particular order. Let us look at some of the properties of set in python. Sets are usually used to perform some mathematical functions such as union, interest, etc.

  • In the set, elements don’t have a specific order.
  • Set can’t have duplicates. Each item is unique.
  • Set elements are immutable. They can’t accept changes once added.
  • But the set is mutable. Set allows addition and deletion operations.

One of the major advantages of using sets in Python is that unlike some other datatypes like lists, set in Python contains a highly optimized method for the sole purpose of checking whether a particular element is included in a set or not.

Also, since sets in Python are mutable, we can add and remove elements from a set, however every element that is added in the set must be unique and immutable, that is, you cannot change elements once they have been added.

In this module, we will learn all about sets in order to get started with it, following is the list of all the topics that we will be covering, in case you need to jump to a specific one.

So, without any further delay, let’s get started.

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Instantiate a Set

1. Using comma to separate and curly braces to group elements.

myset = {“apple”, “banana”, “cherry”}
print(myset)

Output:

{‘cherry’, ‘banana’, ‘apple’}

2. Using the inbuilt Set() method with the elements that we want to add as the parameters.

myset = set((“apple”, “banana”, “cherry”)) # note the double round-brackets
print(myset)

Output:

{‘cherry’, ‘banana’, ‘apple’}

Remember that once a set is created you can’t change that you can only add elements. You can remove and then add element but cannot change the existing element. Now let us see how to add items in a python set.

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Set operations

Adding elements in set

1. Using add() method with the element as parameter in the method:

myset = {“apple”, “banana”, “cherry”}
myset.add(“orange”)
print(myset)

Output:

{‘cherry’, ‘orange’, ‘banana’, ‘apple’}

2. Using update()

myset = {“apple”, “banana”, “cherry”}
myset.update([“orange”, “mango”, “grapes”])
print(myset)

Output:

{‘cherry’, ‘mango’, ‘banana’, ‘apple’, ‘orange’, ‘grapes’}

Removing elements from sets

Remove operation can be performed by using the following methods
1. Using remove() method:

myset = {“apple”, “banana”, “cherry”}
myset.remove(“banana”)
print(myset)

output:

{‘cherry’, ‘apple’}

Note: If the item to be removed does not exist, remove() will raise an error
2. Using discard():

myset = {“apple”, “banana”, “cherry”}
myset.discard(“banana”)
print(myset)

Output:

{‘cherry’, ‘apple’}

Note: If the item to be removed does not exist, discard() will not raise an error.
3. Using pop():
Remember that pop() will remove the last item of the set. Since set is unordered, we should avoid performing pop() in set.

myset = {“apple”, “banana”, “cherry”}
x = myset.pop()
print(x)
print(myset)

Output:

{‘banana’, ‘apple’}

Printing the length of a set

To print the length of the set we can simply use the inbuilt len() method as shown below:

myset = {“apple”, “banana”, “cherry”}
print(len(myset))

Output:

3

Emptying a set completely

To clear a set completely we can use either clear() method or del() method.
1. Using clear()

myset = {“apple”, “banana”, “cherry”}
myset.clear()
print(myset)

2. Using del():

myset = {“apple”, “banana”, “cherry”}
del myset
print(myset)

Output:

Traceback (most recent call last):
File “”, line 1, in
NameError: name ‘myset’ is not defined

As discussed above, Sets in Python are used to carry out mathematical set operations such as union, intersection, etc. Let’s see a few examples of these mathematical operations.

Sets Union

To perform union, we use “|” operator. We can also use an inbuilt method called union(), which will give the same result.

The result of the union of two sets, say set A and set B, is a set containing the elements of both the sets.

The following code block shows the union of set A and set B using Sets in Python.

Set_A = {1,2,3,4,5}
Set_B = {4,5,6,7}
print(Set_A | Set_B)

Output:

{1, 2, 3, 4, 5, 6}
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Set Intersection

To perform intersection, we use & operator. We can also use the inbuilt method named as intersection() to get the same result.

The intersection of two sets, say Set A and Set B can results in a set that contains the elements that are common in both the sets, that is the overlapping part in the diagram below.

Set Intersection
The following code block shows the union of set A and set B using Sets in Python.

Set_A = {1,2,3,4,5}
Set_B = {4,5,6,7}
print (Set_A & Set_B)

Output:

{4, 5}

Common set methods

 

Method Description
update() It updates the set with the union of this set and others
add() It adds an element to the set
clear() It removes all the elements from the set
copy() It returns a copy of the set
difference() It returns a set containing the difference between two or more sets
difference_update() It removes the items in this set that are also included in another, specified set
discard() It removes the specified item
remove() It removes the specified element
pop() It removes an element from the set
intersection() It returns a set, that is the intersection of two other sets
intersection_update() It removes the items in this set that are not present in other, specified set(s)
isdisjoint() It returns whether two sets have a intersection or not
issubset() It returns whether another set contains this set or not
issuperset() It returns whether this set contains another set or not
symmetric_difference() It returns a set with the symmetric differences of two sets
symmetric_difference() It returns a set with the symmetric differences of two sets
union() or | It returns a set containing the union of sets
intersection or & It returns a set comprising common elements in both the sets

Now that we are familiar with the set and its operations, we will be discussing another very important datatype which is nothing but a dictionary in the next module. See you there!

Further, check our Python course for certification and prepare yourself with our free Python interview questions listed by the experts.

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