Today, I wrapped up learning about Sets and explored more about data structures in Python.

🔹 What are Sets?
• Unordered collections of unique elements.
• Defined using curly braces {}.
• No duplicates allowed.

fruits = {"apple", "banana", "cherry", "apple"}
print(fruits) # {'apple', 'banana', 'cherry'}

🔑 Common Set Operations

a = {1, 2, 3}
b = {3, 4, 5}

print(a.union(b)) # {1, 2, 3, 4, 5}
print(a.intersection(b)) # {3}
print(a.difference(b)) # {1, 2}
print(a.symmetric_difference(b)) # {1, 2, 4, 5}

✅ Sets are very useful for mathematical operations, filtering, and removing duplicates.

🔹 Why Use Sets?
• Fast membership testing (in operator).
• Automatically remove duplicates.
• Great for mathematical/logical operations.

🔹 Data Structures Recap in Python

1. List → Ordered, mutable.
2. Tuple → Ordered, immutable.
3. Set → Unordered, unique items.
4. Dictionary → Key-value pairs.

Each data structure has its own strengths depending on the use case (speed, immutability, uniqueness, etc.).

🎯 Reflection

Sets introduced me to powerful operations for handling unique data. Understanding Python’s core data structures is essential because they form the foundation of problem-solving, algorithms, and real-world applications.

⚡ Next up: I’ll dive into libraries and explore advanced coding practices.

Python #100DaysOfCode #LearningJourney #DataStructures