📚 What Are Data Structures in Python?

Data structures are essential for organizing and manipulating data efficiently. Python provides built-in structures like lists, tuples, dictionaries, and sets, each with unique use cases.

📋 Lists: Ordered & Mutable

  • Key Features:
    • Allows duplicate elements
    • Accessible via indexes (0-based)
    • Supports dynamic resizing
  • Example:
fruits = ["apple", "banana", "cherry"]
fruits.append("orange")  # Add an element
print(fruits[1])         # Access by index
Python_List

🧩 Tuples: Ordered & Immutable

  • Key Features:
    • Cannot be modified after creation
    • Faster than lists for fixed data
    • Useful for protecting data integrity
  • Example:
coordinates = (10, 20)
# coordinates[1] = 30  # This will raise an error
Python_Tuple

📦 Dictionaries: Key-Value Pairs

  • Key Features:
    • Unordered collection (pre Python 3.7)
    • Fast lookup via keys
    • Flexible for dynamic data mapping
  • Example:
student = {"name": "Alice", "age": 25}
print(student["name"])  # Access by key
Python_Dictionary

🧹 Sets: Unordered & Unique Elements

  • Key Features:
    • Stores unique values only
    • Supports mathematical set operations (e.g., union, intersection)
    • Ideal for membership testing
  • Example:
unique_numbers = {1, 2, 3, 4, 4}  # Duplicates are removed
print(unique_numbers)
Python_Set

🧠 When to Use Which Structure?

Scenario Best Choice
Storing a list of items List
Immutable data collection Tuple
Associating keys with values Dictionary
Removing duplicates Set

🌐 Expand Your Knowledge

For deeper insights into Python programming fundamentals, visit our Python Programming Basics Tutorial.

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