Sets in Python
In the world of programming, data structures play a crucial role in organizing and managing data efficiently. One such data structure that Python offers is the set. Sets are versatile and powerful containers that are commonly used to work with collections of unique elements. In this blog post, we will dive deep into sets in Python, exploring their properties, methods, and practical use cases.
A Sets in Python is an unordered collection of unique elements. Unlike lists or tuples, which allow duplicate values, sets only store distinct values. This property makes sets particularly useful when you need to work with unique items or perform operations like intersection, union, and difference.
In the below PDF we discuss about Sets in Python in detail in simple language, Hope this will help in better understanding.
Creating Sets:
Creating a set in Python is straightforward. You can use curly braces {} or the set() constructor to initialize an empty set. To create a set with initial elements, simply provide them as a comma-separated list within curly braces. Let’s look at some examples:
# Creating an empty set empty_set = set() # Creating a set with elements fruits = {"apple", "banana", "cherry"} # Using the set() constructor colors = set(["red", "green", "blue"])
Sets Operations :
- Adding Elements                                                                 You can add elements to a set using the add() method:
fruits.add("orange")
- Removing Elements                                                               To remove elements from a set, you can use the remove() method. It will raise a KeyError if the element is not present in the set. Alternatively, you can use the discard() method, which won’t raise an error if the element is not found:
fruits.remove("banana") fruits.discard("watermelon")Â
- Set Operations:Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Â Sets support various operations that are common in mathematics. These include:
- Union: union() or |
- Intersection: intersection() or &
- Difference: difference() or –
- Symmetric Difference: symmetric_difference() or ^
- Subset: issubset()
- Superset: issuperset()
- Here’s an example demonstrating some of these operations:
set1 = {1, 2, 3, 4} set2 = {3, 4, 5, 6} # Union union_set = set1.union(set2) # Intersection intersection_set = set1.intersection(set2) # Difference difference_set = set1.difference(set2) # Symmetric Difference symmetric_difference_set = set1.symmetric_difference(set2) # Subset is_subset = set1.issubset(set2) # Superset is_superset = set1.issuperset(set2
Related Question
A set in Python is an unordered collection of unique elements. It is defined by enclosing a comma-separated sequence of elements within curly braces {}.
You can create an empty set using the set() constructor: my_set = set().
You can add elements to a set using the add() method. For example: my_set.add(42).
 No, a set in Python cannot contain duplicate elements. It automatically removes duplicates
The main difference is that a set contains unique elements in an unordered fashion, while a list can contain duplicate elements in a specific order.
You can use the in keyword to check if an element is in a set. For example: if 42 in my_set:
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