Find top 1-on-1 online tutors for Coding, Math, Science, AP and 50+ subjects
Tutoring
Tutors by Subject
Computer Science
Math
AP (Advanced Placement)
Courses
Coding Classes for Kids
Robotics Classes for Kids
Design Classes for Kids
Resources
AP (Advanced Placement)
Calculators
Length Calculators
Weight Calculators
Tools
Tutorials
Scratch Tutorial
Learn
Math Tutorials
AP Statistics Tutorials
Python Tutorials
Blog
Chapters
Python sets are a grouping of distinct objects. It is a group of elements that is neither ordered nor immutable. The set() function or curly braces can be used to create sets. A set’s components can be of any data type, including strings, integers, and even other sets.
The fact that a set forbids duplicate elements is one of its primary characteristics. A set won’t change if an element is already there; adding it again won’t. Additionally, sets do not keep the elements they contain in any particular order. This means that the order in which the elements are added to the set does not matter.
B. Difference between sets and other data structures
Although sets resemble other data structures like lists and tuples, there are some significant differences between them. The biggest distinction is that lists and tuples support duplicate elements, whereas sets do not. Lists and tuples are ordered, whereas sets are unordered. Tuples are immutable, whereas sets are also mutable, meaning they can be changed after creation.
C. How sets are used in Python
In Python, sets are used to carry out set operations such as union, intersection, and difference. Algorithms and calculations in mathematics frequently use set operations. Duplicates can also be eliminated from a list or tuple using sets.
Looking to Learn Python? Explore Wiingy’s Online Python Tutoring. Learn from Top Coders and Software Developers.
A. Literal notation
Sets can be created using curly braces {} with elements separated by commas. Here is an example of creating a set with integers:
my_set = {1, 2, 3, 4, 5}
B. Using the set() constructor
Another way to create a set is by using the set() constructor function. The constructor function can take any iterable as an argument and returns a set containing all the unique elements in the iterable. Here is an example of creating a set using the constructor function:
my_set = set([1, 2, 3, 4, 5])
C. Creating an empty set
To create an empty set, you cannot use empty curly braces as they will be interpreted as an empty dictionary. Instead, you can use the set() constructor function to create an empty set:
my_set = set()
You can determine the size of a set by using the len() function. The len() function returns the number of elements in a set. Here is an example of using the len() function to determine the size of a set:
my_set = {1, 2, 3, 4, 5} print(len(my_set)) # Output: 5
Checking if an element is in a set
You can check if an element is in a set by using the in keyword. The in keyword returns True if the element is in the set and False otherwise. Here is an example of checking if an element is in a set:
my_set = {1, 2, 3, 4, 5} print(3 in my_set) # Output: True print(6 in my_set) # Output: False
A. Operators vs. Methods
Sets support both operators and methods for performing operations on them. Operators are symbols that perform an operation on two or more sets, while methods are functions that are called on a single set to modify it or perform an operation on it.
B. Available Operators and Methods
The following are the available operators and methods for sets in Python:
C. Examples of using operators and methods
Here are some examples of using operators and methods with sets:
set1 = {1, 2, 3, 4} set2 = {3, 4, 5, 6} # Using union operator union_set = set1 | set2 print(union_set) # Output: {1, 2, 3, 4, 5, 6}
# Using intersection method
intersection_set = set1.intersection(set2) print(intersection_set)
# Output: {3, 4}
# Using difference operator
difference_set = set1 - set2 print(difference_set)
# Output: {1, 2}
# Using symmetric difference
method symmetric_difference_set = set1.symmetric_difference(set2) print(symmetric_difference_set)
# Output: {1, 2, 5, 6}
# Using subset operator
print(set1 < set2)
# Output: False
# Using issubset method
print(set1.issubset(set2))
# Output: False
# Using disjoint operator
print(set1.isdisjoint(set2))
# Output: False
A. Adding an element to a set
To add an element to a set, you can use the add() method. The add() method adds an element to the set if it is not already present in the set.
my_set = {1, 2, 3} my_set.add(4) print(my_set)
# Output: {1, 2, 3, 4}
B. Removing an element from a set
To remove an element from a set, you can use the remove() method. The remove() method removes the element from the set if it is present in the set, and raises a KeyError if the element is not in the set.
my_set = {1, 2, 3} my_set.remove(2) print(my_set)
# Output: {1, 3}
C. Updating a set with another set
To update a set with another set, you can use the update() method. The update() method adds all the elements from the given set(s) to the original set.
my_set = {1, 2, 3} my_set.update({3, 4, 5}) print(my_set) # Output: {1, 2, 3, 4, 5}
D. Clearing a set
To remove all the elements from a set, you can use the clear() method. The clear() method removes all the elements from the set and makes it an empty set.
my_set = {1, 2, 3} my_set.clear() print(my_set)
# Output: set()
Augmented assignment operators are shorthand notations for performing an operation and assigning the result back to the original variable. For example, the following statement is equivalent to x = x + 1:
x += 1
The following are the available augmented assignment operators for sets in Python:
set1 = {1, 2, 3} set2 = {3, 4, 5} set1 |= set2 print(set1) # Output: {1, 2, 3, 4, 5}
set1 = {1, 2, 3} set2 = {3, 4, 5} set1 &= set2 print(set1) # Output: {3}
set1 = {1, 2, 3} set2 = {3, 4, 5} set1 -= set2 print(set1)
# Output: {1, 2}
set1 = {1, 2, 3} set2 = {3, 4, 5} set1 ^= set2 print(set1) # Output: {1, 2, 4, 5}
B. Examples of using methods for augmented assignment
The following are the available methods for performing augmented assignment on sets in Python:
set1 = {1, 2, 3} set2 = {3, 4, 5} set1.update(set2) print(set1)
# Output: {1, 2, 3, 4, 5}
set1 = {1, 2, 3} set2 = {3, 4, 5} set1.intersection_update(set2) print(set1) # Output: {3}
set1 = {1, 2, 3} set
A. Intersection, Union, and Difference
Sets in Python have three methods for performing the basic set operations – union, intersection, and difference.
set1 = {1, 2, 3} set2 = {3, 4, 5} set3 = set1.union(set2) print(set3) # Output: {1, 2, 3, 4, 5}
set1 = {1, 2, 3} set2 = {3, 4, 5} set3 = set1.intersection(set2) print(set3) # Output: {3}
set1 = {1, 2, 3} set2 = {3, 4, 5} set3 = set1.difference(set2) print(set3) # Output: {1, 2}
B. Symmetric Difference and Disjoint
Sets in Python have two methods for performing symmetric difference and disjoint operations.
set1 = {1, 2, 3} set2 = {3, 4, 5} set3 = set1.symmetric_difference(set2) print(set3) # Output: {1, 2, 4, 5}
set1 = {1, 2, 3} set2 = {4, 5, 6} print(set1.isdisjoint(set2)) # Output: True
C. Subsets, Supersets, and Proper Subsets
Sets in Python have three methods for checking if a set is a subset, superset, or proper subset of another set.
set1 = {1, 2, 3} set2 = {1, 2} print(set2.issubset(set1)) # Output: True
set1 = {1, 2, 3} set2 = {1, 2} print(set1.issuperset(set2)) # Output: True
set1 = {1, 2, 3} set2 = {1, 2} print(set2.ispropersubset(set1)) # Output: True
D. Copying a Set
To create a copy of a set, you can use the copy() method or the set() constructor.
set1 = {1, 2, 3} set2 = set1.copy() set3 = set(set1) print(set2) # Output: {1, 2, 3} print(set3) # Output: {1, 2, 3}
A. Definition of frozen sets
Frozen sets are immutable collections of unique elements that are hashable, which means they can be used as elements of a set, but they cannot be modified once they are created. Frozen sets are created using the frozenset() constructor.
fset = frozenset([1, 2, 3]) print(fset) # Output: frozenset({1, 2, 3})
B. Creating frozen sets
Frozen sets can be created from other sets or any iterable using the frozenset() constructor.
set1 = {1, 2, 3} fset = frozenset(set1) print(fset) # Output: frozenset({1, 2, 3})
C. Differences between frozen sets and sets
Frozen sets differ from sets in that they are immutable and hashable, which means they can be used as keys in dictionaries and elements of other sets.
fset = frozenset([1, 2, 3]) d = {fset: 'hello'} print(d)
# Output: {frozenset({1, 2, 3}): 'hello'}
Since frozen sets cannot be modified, they do not have any methods for adding, removing, or updating elements like sets do.
A. Basic syntax
Set comprehensions provide a concise way to create sets in Python. The basic syntax of a set comprehension is similar to that of a list comprehension, except that it is enclosed in curly braces instead of square brackets.
set1 = {x for x in range(10)} print(set1)
# Output: {0, 1, 2, 3, 4, 5, 6, 7, 8, 9}
B. Creating sets with set comprehensions
Set comprehensions can be used to create sets from any iterable, including other sets.
set1 = {x**2 for x in range(10)} print(set1)
# Output: {0, 1, 4, 9, 16, 25, 36, 49, 64, 81}
set2 = {x for x in set1 if x % 2 == 0} print(set2)
# Output: {0, 64, 4, 36, 16, 8}
C. Using set comprehensions with conditionals
Set comprehensions can also be used with conditionals to filter elements.
set1 = {x for x in range(10) if x % 2 == 0} print(set1)
# Output: {0, 2, 4, 6, 8}
A. Removing duplicates from a list
One common application of sets in Python is to remove duplicates from a list. We can easily convert a list to a set to remove duplicates, and then convert it back to a list if necessary.
list1 = [1, 2, 3, 2, 1, 4, 5] set1 = set(list1) list2 = list(set1) print(list2) # Output: [1, 2, 3, 4, 5]
B. Finding common elements in multiple lists
Sets can also be used to find common elements in multiple lists. We can convert each list to a set and then take the intersection of the sets to find the common elements.
list1 = [1, 2, 3, 4, 5] list2 = [4, 5, 6, 7, 8] set1 = set(list1) set2 = set(list2) common = set1.intersection(set2) print(common) # Output: {4, 5}
C. Checking for membership in a set
Sets are also useful for checking if an element is in a collection. Since sets use hash tables for fast membership testing, they are very efficient for large collections.
set1 = {1, 2, 3, 4, 5} if 3 in set1: print('3 is in the set') # Output: 3 is in the set
D. Performing set operations on large datasets
Sets are also useful for performing set operations like union, intersection, and difference on large datasets. Since sets are implemented using hash tables, they are very efficient for these types of operations.
set1 = {1, 2, 3, 4, 5} set2 = {4, 5, 6, 7, 8} union = set1.union(set2) intersection = set1.intersection(set2) difference = set1.difference(set2) print(union) # Output: {1, 2, 3, 4, 5, 6, 7,8}
Python sets provide a powerful and efficient way to work with collections of unique elements. They are useful in a variety of programming tasks, from removing duplicates to performing set operations on large datasets. Understanding how to create, modify, and operate on sets is an important part of becoming a proficient Python programmer.
Looking to Learn Python? Explore Wiingy’s Online Python Tutoring. Learn from Top Coders and Software Developers.
A: Sets in Python are an unordered collection of unique elements. They are defined using the set() constructor or with literal notation {}.
A: There are two types of sets in Python: mutable sets and immutable sets (frozen sets). Mutable sets can be modified, while frozen sets cannot.
A: Python sets are good for a variety of programming tasks, such as removing duplicates from a list, finding common elements in multiple lists, checking for membership in a set, and performing set operations on large datasets.
A: No, {} is not a set in Python. It is the literal notation for an empty dictionary. To create an empty set, you should use set() instead.