Data Structures in Python

Python'sTreasure Chest: Data Structures

Imagine your closet. Some sections are for hanging clothes, others for shoes, and maybe a drawer for accessories.

In Python, data structures help us organize and store data just like that closet, but for information!

1. What are Data Structures?

Definition: Data structures are specific ways of storing and organizing data in a computer. Why?:They ensure efficient access and modification.

list_of_numbers = [1, 2, 3,4,5, 6

2.Python'sBuilt-in Data Structures

Lists: Ordered collections (e.g., [1, 2, 3]). Tuples: Immutable ordered collections (e.g., (1, 2, 3)). Dictionaries: Key-value pairs (e.g., {"name": "Alex" , "age": 25}). Sets: Unordered collections of unique elements (e.g., {1, 2, 3}).

3. Diving Deep: Lists

Lists are versatile and can store mixed types of data.

fruits = ["apple" , "banana", "cherry"] fruits.append("date") print(fruit)

["apple" , "banana", "cherry","date"]

Output

4. Unlocking Power: Dictionaries

Dictionaries let us store data in key-value pairs.

5.Why Use Specific DataStructures?

Efficiency: Some structures, like dictionaries, offer faster data access. Organization: Tuples can ensure data doesn't accidentally get changed. Flexibility: Lists allow us to easily add, remove, or modify items.

In Summary:

Python offers a rich set of data structures to help us store and manage data efficiently. Choosing the right one can make our code faster, cleaner, and more robust.