Data_Structures and loops in python lang

python topics which covers data structure & loops

1. Data Structures and Loops in Python 🔹 Understanding the basics with examples

2. What are Data Structures? - A way to organize and store data in Python - Common Data Structures: • List → ordered, changeable, allows duplicates • Tuple → ordered, unchangeable, allows duplicates • Set → unordered, no duplicates • Dictionary → key-value pairs

3. Python Lists fruits = ["apple", "banana", "mango", "apple"] print(fruits) ✅ Ordered ✅ Mutable (can change) ✅ Allows duplicates

4. Looping through a List for fruit in fruits: print(fruit) ➡ Loops allow us to repeat actions without writing code multiple times.

5. Python Tuples numbers = (10, 20, 30, 10) print(numbers) ✅ Ordered ✅ Immutable (cannot change) ✅ Allows duplicates

6. Looping through a Tuple (While Loop) i = 0 while i < len(numbers): print(numbers[i]) i += 1 ➡ while loop continues until condition becomes False.

7. Python Sets colors = {"red", "blue", "green", "red"} print(colors) ✅ Unordered ✅ No duplicates

8. Looping through a Set for color in colors: print(color) ➡ Order is not guaranteed in sets.

9. Python Dictionaries student = {"name": "Alice", "age": 21, "course": "CS"} print(student) ✅ Stores data in key-value pairs ✅ Keys are unique

10. Looping through a Dictionary for key, value in student.items(): print(key, ":", value) ➡ Useful for structured data.

11. Example – Squaring Numbers nums = [1, 2, 3, 4, 5] squares = [] for n in nums: squares.append(n ** 2) print("Squares:", squares) 🎯 Combines list + loop to solve a problem.

12. Summary - Data Structures help store data effectively. - Loops make code shorter and more efficient. - Together, they form the core of Python programming. ✨ End of Presentation ✨