Python Sets

Python Set is an unordered collection of data types that is iterable, mutable, and has no duplicate elements. The order of elements in a set is undefined though it may consist of various elements. The major advantage of using a set, as opposed to a list, is that it has a highly optimized method for checking whether a specific element is contained in the set. Here, we will see what is a set in Python and also see different examples of set Python.

Creating a Set in Python

Python Sets can be created by using the built-in set() function with an iterable object or a sequence by placing the sequence inside curly braces, separated by a ‘comma’.

Note: A Python set cannot have mutable elements like a list or dictionary, as it is immutable. 

# Creating a Set
set1 = set()
print("Initial blank Set: ")
print(set1)

# Creating a Set with the use of a String
set1 = set("GeeksForGeeks")
print("\nSet with the use of String: ")
print(set1)

String = 'GeeksForGeeks'
set1 = set(String)
print("\nSet with the use of an Object: ")
print(set1)

# Creating a Set with the use of a List
set1 = set(["Geeks", "For", "Geeks"])
print("\nSet with the use of List: ")
print(set1)

# Creating a Set with the use of a tuple
t = ("Geeks", "for", "Geeks")
print("\nSet with the use of Tuple: ")
print(set(t))

# Creating a Set with the use of a dictionary
d = {"Geeks": 1, "for": 2, "Geeks": 3}
print("\nSet with the use of Dictionary: ")
print(set(d))

Ouput

Initial blank Set: 
set()

Set with the use of String: 
{'e', 'G', 's', 'F', 'o', 'r', 'k'}

Set with the use of an Object: 
{'e', 'G', 's', 'F', 'o', 'r', 'k'}

Set with the use of List: 
{'For', 'Geeks'}

Set with the use of Tuple: 
{'for', 'Geeks'}

Set with the use of Dictionary: 
{'for', 'Geeks'}

Time complexity: O(n), where n is the length of the input string, list, tuple or dictionary.
Auxiliary space: O(n), where n is the length of the input string, list, tuple or dictionary.

A Python set contains only unique elements but at the time of set creation, multiple duplicate values can also be passed. Order of elements in a Python set is undefined and is unchangeable. Type of elements in a set need not be the same, various mixed-up data type values can also be passed to the set. 

# Creating a Set with a List of Numbers
# (Having duplicate values)
set1 = set([1, 2, 4, 4, 3, 3, 3, 6, 5])
print("\nSet with the use of Numbers: ")
print(set1)

# Creating a Set with a mixed type of values
# (Having numbers and strings)
set1 = set([1, 2, 'Geeks', 4, 'For', 6, 'Geeks'])
print("\nSet with the use of Mixed Values")
print(set1)

Set with the use of Numbers: 
{1, 2, 3, 4, 5, 6}

Set with the use of Mixed Values
{1, 2, 4, 6, 'Geeks', 'For'}

Creating a Python Set with Another Method

In this example, a set is created by using curly braces {} notation, containing the number 1,2 and 3. Set data structure in Python or unordered set in Python are unordered collections of unique elements, making them suitable for tasks requiring uniqueness and set operations in Python.

# Another Method to create sets in Python3
# Set containing numbers
my_set = {1, 2, 3}

print(my_set)

{1, 2, 3}

Adding Elements to a Set in Python

Below are some of the approaches by which we can add elements to a set in Python:

• Using add() Method
• Using update() Method

Using add() Method

Elements can be added to the Sets in Python by using the built-in add() function. Only one element at a time can be added to the set by using add() method, loops are used to add multiple elements at a time with the use of add() method.

Note: Lists cannot be added to a set as elements because Lists are not hashable whereas Tuples can be added because tuples are immutable and hence Hashable. 

# Creating a Set
set1 = set()
print("Initial blank Set: ")
print(set1)

# Adding element and tuple to the Set
set1.add(8)
set1.add(9)
set1.add((6, 7))
print("\nSet after Addition of Three elements: ")
print(set1)

# Adding elements to the Set
# using Iterator
for i in range(1, 6):
    set1.add(i)
print("\nSet after Addition of elements from 1-5: ")
print(set1)

Initial blank Set: 
set()

Set after Addition of Three elements: 
{8, 9, (6, 7)}

Set after Addition of elements from 1-5: 
{1, 2, 3, (6, 7), 4, 5, 8, 9}

Using update() Method

For the addition of two or more elements, Update() method is used. The update() method accepts lists, strings, tuples as well as other Python hash set as its arguments. In all of these cases, duplicate elements are avoided.

# Addition of elements to the Set
# using Update function
set1 = set([4, 5, (6, 7)])
set1.update([10, 11])
print("\nSet after Addition of elements using Update: ")
print(set1)

Set after Addition of elements using Update: 
{4, 5, (6, 7), 10, 11}

Accessing a Set in Python

Set items cannot be accessed by referring to an index, since sets are unordered the items has no index. But you can loop through the Python hash set items using a for loop, or ask if a specified value is present in a set, by using the in keyword.

# Creating a set
set1 = set(["Geeks", "For", "Geeks."])
print("\nInitial set")
print(set1)

# Accessing element using
# for loop
print("\nElements of set: ")
for i in set1:
    print(i, end=" ")

# Checking the element
# using in keyword
print("\n")
print("Geeks" in set1)

Output

Initial set
{'Geeks.', 'For', 'Geeks'}

Elements of set: 
Geeks. For Geeks 

True

Removing Elements from the Set in Python

Below are some of the ways by which we can remove elements from the set in Python:

• Using remove() Method or discard() Method
• Using pop() Method
• Using clear() Method

Using remove() Method or discard() Method

Elements can be removed from the Sets in Python by using the built-in remove() function but a KeyError arises if the element doesn’t exist in the hashset Python. To remove elements from a set without KeyError, use discard(), if the element doesn’t exist in the set, it remains unchanged.

# Creating a Set
set1 = set([1, 2, 3, 4, 5, 6,
            7, 8, 9, 10, 11, 12])
print("Initial Set: ")
print(set1)

# Removing elements from Set  using Remove() method
set1.remove(5)
set1.remove(6)
print("\nSet after Removal of two elements: ")
print(set1)

# Removing elements from Set using Discard() method
set1.discard(8)
set1.discard(9)
print("\nSet after Discarding two elements: ")
print(set1)

# Removing elements from Set using iterator method
for i in range(1, 5):
    set1.remove(i)
print("\nSet after Removing a range of elements: ")
print(set1)

Initial Set: 
{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}

Set after Removal of two elements: 
{1, 2, 3, 4, 7, 8, 9, 10, 11, 12}

Set after Discarding two elements: 
{1, 2, 3, 4, 7, 10, 11, 12}

Set after Removing a range of elements: 
{7, 10, 11, 12}

Using pop() Method

Pop() function can also be used to remove and return an element from the set, but it removes only the last element of the set. 

Note: If the set is unordered then there’s no such way to determine which element is popped by using the pop() function. 

# Python program to demonstrate
# Deletion of elements in a Set

# Creating a Set
set1 = set([1, 2, 3, 4, 5, 6,
            7, 8, 9, 10, 11, 12])
print("Initial Set: ")
print(set1)

# Removing element from the
# Set using the pop() method
set1.pop()
print("\nSet after popping an element: ")
print(set1)

Initial Set: 
{1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}

Set after popping an element: 
{2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12}

Using clear() Method

To remove all the elements from the set, clear() function is used. 

#Creating a set
set1 = set([1,2,3,4,5])
print("\n Initial set: ")
print(set1)


# Removing all the elements from 
# Set using clear() method
set1.clear()
print("\nSet after clearing all the elements: ")
print(set1)

 Initial set: 
{1, 2, 3, 4, 5}

Set after clearing all the elements: 
set()

Frozen Sets in Python

Frozen sets in Python are immutable objects that only support methods and operators that produce a result without affecting the frozen set or sets to which they are applied. While elements of a set can be modified at any time, elements of the frozen set remain the same after creation. 

If no parameters are passed, it returns an empty frozenset.  

# Python program to demonstrate
# working of a FrozenSet

# Creating a Set
String = ('G', 'e', 'e', 'k', 's', 'F', 'o', 'r')

Fset1 = frozenset(String)
print("The FrozenSet is: ")
print(Fset1)

# To print Empty Frozen Set
# No parameter is passed
print("\nEmpty FrozenSet: ")
print(frozenset())

The FrozenSet is: 
frozenset({'F', 's', 'o', 'G', 'r', 'e', 'k'})

Empty FrozenSet: 
frozenset()

Typecasting Objects into Sets

In this example, lists, strings and dictionaries are converted into sets using the set() constructor, eliminating duplicates in lists and extracting unique elements in strings and dictionary keys.

# Typecasting list into set
my_list = [1, 2, 3, 3, 4, 5, 5, 6, 2]
my_set = set(my_list)
print("my_list as a set: ", my_set)

# Typecasting string into set
my_str = "GeeksforGeeks"
my_set1 = set(my_str)
print("my_str as a set: ", my_set1)

# Typecasting dictionary into set
my_dict = {1: "One", 2: "Two", 3: "Three"}
my_set2 = set(my_dict)
print("my_dict as a set: ", my_set2)

my_list as a set:  {1, 2, 3, 4, 5, 6}
my_str as a set:  {'G', 'f', 'r', 'e', 'k', 'o', 's'}
my_dict as a set:  {1, 2, 3}

Example: Implementing All Functions

In this example, a series of functions demonstrate common operations on sets in Python. These include creating a set, adding and removing elements, clearing the set, performing set union, intersection, difference, symmetric difference, subset, and superset operations.

def create_set():
    my_set = {1, 2, 3, 4, 5}
    print(my_set)


def add_element():
    my_set = {1, 2, 3, 4, 5}
    my_set.add(6)
    print(my_set)


def remove_element():
    my_set = {1, 2, 3, 4, 5}
    my_set.remove(3)
    print(my_set)


def clear_set():
    my_set = {1, 2, 3, 4, 5}
    my_set.clear()
    print(my_set)


def set_union():
    set1 = {1, 2, 3}
    set2 = {4, 5, 6}
    my_set = set1.union(set2)
    print(my_set)


def set_intersection():
    set1 = {1, 2, 3, 4, 5}
    set2 = {4, 5, 6, 7, 8}
    my_set = set1.intersection(set2)
    print(my_set)


def set_difference():
    set1 = {1, 2, 3, 4, 5}
    set2 = {4, 5, 6, 7, 8}
    my_set = set1.difference(set2)
    print(my_set)


def set_symmetric_difference():
    set1 = {1, 2, 3, 4, 5}
    set2 = {4, 5, 6, 7, 8}
    my_set = set1.symmetric_difference(set2)
    print(my_set)


def set_subset():
    set1 = {1, 2, 3, 4, 5}
    set2 = {2, 3, 4}
    subset = set2.issubset(set1)
    print(subset)


def set_superset():
    set1 = {1, 2, 3, 4, 5}
    set2 = {2, 3, 4}
    superset = set1.issuperset(set2)
    print(superset)


if __name__ == '__main__':
    create_set()
    add_element()
    remove_element()
    clear_set()
    set_union()
    set_intersection()
    set_difference()
    set_symmetric_difference()
    set_subset()
    set_superset()

{1, 2, 3, 4, 5}
{1, 2, 3, 4, 5, 6}
{1, 2, 4, 5}
set()
{1, 2, 3, 4, 5, 6}
{4, 5}
{1, 2, 3}
{1, 2, 3, 6, 7, 8}
True
True

Advantages of Set in Python

• Unique Elements: Sets can only contain unique elements, so they can be useful for removing duplicates from a collection of data.
• Fast Membership Testing: Sets are optimized for fast membership testing, so they can be useful for determining whether a value is in a collection or not.
• Mathematical Set Operations: Sets support mathematical set operations like union, intersection, and difference, which can be useful for working with sets of data.
• Mutable: Sets are mutable, which means that you can add or remove elements from a set after it has been created.

Disadvantages of Sets in Python

• Unordered: Sets are unordered, which means that you cannot rely on the order of the data in the set. This can make it difficult to access or process data in a specific order.
• Limited Functionality: Sets have limited functionality compared to lists, as they do not support methods like append() or pop(). This can make it more difficult to modify or manipulate data stored in a set.
• Memory Usage: Sets can consume more memory than lists, especially for small datasets. This is because each element in a set requires additional memory to store a hash value.
• Less Commonly Used: Sets are less commonly used than lists and dictionaries in Python, which means that there may be fewer resources or libraries available for working with them. This can make it more difficult to find solutions to problems or to get help with debugging.

Overall, sets can be a useful data structure in Python, especially for removing duplicates or for fast membership testing. However, their lack of ordering and limited functionality can also make them less versatile than lists or dictionaries, so it is important to carefully consider the advantages and disadvantages of using sets when deciding which data structure to use in your Python program.

Set Methods in Python

Recent Articles on Python Sets

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• Set update() in Python to do union of n arrays

Useful Links

• Output of Python programs – Sets
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