When working with data, sometimes we need to store unique values only. For example, if you are collecting email IDs from a form and don’t want duplicates, then Sets in Python are the perfect choice.
Let’s explore what Sets are, how they work, their useful functions, and real-life examples.
What is a Set in Python?
A Set is a collection of unordered, unindexed, and unique items.
- No duplicate values allowed
- Items can be of different data types (int, str, float, etc.)
- They are enclosed in
{ }curly brackets
Example:
fruits = {"apple", "banana", "mango", "apple"}
print(fruits) Output:
{'banana', 'apple', 'mango'}
👉 Notice how "apple" is written twice, but stored only once.
Creating Sets
# Empty set
myset = set()
# Set with values
numbers = {1, 2, 3, 4, 5}
# Mixed data
mixed = {1, "hello", 3.14, True}Also Read: Tuples in Python
Useful Set Methods & Functions
Python provides many built-in methods for sets. Let’s explore them with examples.
1. add() – Add a single element
fruits = {"apple", "banana"}
fruits.add("mango")
print(fruits)2. update() – Add multiple elements
fruits = {"apple", "banana"}
fruits.update(["grapes", "orange"])
print(fruits)3. remove() / discard() – Remove an element
fruits = {"apple", "banana", "mango"}
fruits.remove("banana") # error if not present
fruits.discard("grapes") # no error if not present4. pop() – Removes a random element
fruits = {"apple", "banana", "mango"}
fruits.pop()
print(fruits)5. clear() – Empty the set
fruits = {"apple", "banana"}
fruits.clear()
print(fruits) # Output: set()6. union() – Combine sets (like OR)
set1 = {1, 2, 3}
set2 = {3, 4, 5}
print(set1.union(set2))Output:
{1, 2, 3, 4, 5}
7. intersection() – Common values (like AND)
set1 = {1, 2, 3}
set2 = {2, 3, 4}
print(set1.intersection(set2))Output:
{2, 3}
8. difference() – Values only in first set
set1 = {1, 2, 3, 4}
set2 = {3, 4, 5}
print(set1.difference(set2))Output:
{1, 2}
9. symmetric_difference() – Values not common in both
set1 = {1, 2, 3}
set2 = {3, 4, 5}
print(set1.symmetric_difference(set2))Output:
{1, 2, 4, 5}
Read More: Lists in Python
Real-Life Examples of Sets
Example 1: Removing duplicate email IDs
emails = ["a@gmail.com", "b@gmail.com", "a@gmail.com", "c@gmail.com"]
unique_emails = set(emails)
print(unique_emails)
# Output: {'a@gmail.com', 'c@gmail.com', 'b@gmail.com'}Example 2: Finding common students in two courses
python_course = {"Amit", "Neha", "Ravi"}
java_course = {"Ravi", "Neha", "Sonia"}
common = python_course.intersection(java_course)
print("Students in both courses:", common)
# Output: Students in both courses: {'Neha', 'Ravi'}Example 3: Detecting unique website visitors
visitors = ["101", "102", "101", "103", "102", "104"]
unique_visitors = set(visitors)
print(f"Total unique visitors: {len(unique_visitors)}")
# Output: Total unique visitors: 4Final Thoughts
Sets in Python are very useful when:
- You want to store unique items
- You need to perform mathematical set operations (union, intersection, difference)
- You want to quickly remove duplicates
They might not preserve order, but they are fast and powerful when it comes to handling unique collections.
FAQs – Sets in Python
What is the difference between a Set and a List?
Lists allow duplicates and maintain order.
Sets do not allow duplicates and are unordered.
How do you create an empty Set in Python?
You must use set() because {} creates an empty dictionary.
When should I use Sets in Python?
When you want to store only unique values
When performing mathematical operations like union, intersection, or difference
When you want faster membership checking (using
in)
Why are Sets unordered?
Because Python uses a hashing mechanism to store set elements, which makes them unordered but ensures uniqueness and fast lookup.
What’s Next?
In the next post, we’ll learn about the Dictionaries in Python