Python Data Structures Guide

Understanding data structures is crucial for writing efficient Python code. Let's explore the most important ones.

Lists

Lists are ordered, mutable collections that can hold multiple items.

Creating lists

fruits = ["apple", "banana", "orange"]

numbers = [1, 2, 3, 4, 5]

mixed = [1, "hello", 3.14, True]

Accessing elements

print(fruits[0]) # "apple"

print(fruits[-1]) # "orange" (last element)

List methods

fruits.append("grape")

fruits.remove("banana")

numbers.sort()

Dictionaries

Dictionaries store key-value pairs and are perfect for mapping relationships.

Creating dictionaries

person = {

"name": "John",

"age": 30,

"city": "New York"

}

Accessing values

print(person["name"]) # "John"

Adding new keys

person["email"] = "john@example.com"

Dictionary methods

person.keys()

person.values()

person.items()

Sets

Sets are unordered collections of unique items. Perfect for membership testing and eliminating duplicates.

Creating sets

colors = {"red", "green", "blue"}

numbers = {1, 2, 2, 3, 3, 3} # {1, 2, 3}

Set operations

colors.add("yellow")

colors.remove("red")

Set operations

set_a = {1, 2, 3}

set_b = {3, 4, 5}

union = set_a | set_b # {1, 2, 3, 4, 5}

intersection = set_a & set_b # {3}

Tuples

Tuples are immutable sequences. Use them when you need to ensure data won't change.

Creating tuples

point = (10, 20)

rgb = (255, 0, 128)

Accessing elements

print(point[0]) # 10

Tuple unpacking

x, y = point

r, g, b = rgb

Choosing the Right Data Structure

**List**: When you need an ordered, mutable collection

**Dictionary**: When you need to map keys to values

**Set**: When you need unique items and fast membership testing

**Tuple**: When you need immutable sequences or hash keys

Master these four data structures and you'll be able to solve most programming problems efficiently!