Section 3: Data Structures

Lesson 1: Lists and Tuples

1.1 Creating and Manipulating Lists

Lists in Python are versatile data structures that can hold a collection of items. They are mutable, meaning you can modify their elements.

Example:

# Creating and manipulating lists

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

# Accessing elements

print(fruits[0])      # Output: apple

# Modifying elements

fruits[1] = "grape"

print(fruits)         # Output: ['apple', 'grape', 'orange']

# Adding elements

fruits.append("kiwi")

print(fruits)         # Output: ['apple', 'grape', 'orange', 'kiwi']

1.2 Working with Tuples

Tuples are similar to lists but are immutable, meaning their elements cannot be changed once set.

Example: 

# Working with tuples

coordinates = (3, 4)

# Accessing elements

x, y = coordinates

print("X:", x)        # Output: 3

print("Y:", y)        # Output: 4

Lesson 2: Dictionaries and Sets

2.1 Understanding Dictionaries

Dictionaries are unordered collections of items, where each item consists of a key-value pair.

Example:

# Understanding dictionaries

student = {

    "name": "Alice",

    "age": 22,

    "major": "Computer Science"

}

# Accessing values

print(student["name"])      # Output: Alice

# Modifying values

student["age"] = 23

print(student)              # Output: {'name': 'Alice', 'age': 23, 'major': 'Computer Science'}

# Adding new key-value pairs

student["grade"] = "A"

print(student)              # Output: {'name': 'Alice', 'age': 23, 'major': 'Computer Science', 'grade': 'A'}

2.2 Operations on Sets

Sets are unordered collections of unique elements. They support various operations like union, intersection, and difference.

Example: 

# Operations on sets

set_a = {1, 2, 3, 4}

set_b = {3, 4, 5, 6}

# Union

union_set = set_a.union(set_b)

print(union_set)           # Output: {1, 2, 3, 4, 5, 6}

# Intersection

intersection_set = set_a.intersection(set_b)

print(intersection_set)    # Output: {3, 4}

# Difference

difference_set = set_a - set_b

print(difference_set)      # Output: {1, 2}

In Section 3, we explored essential data structures in Python: lists, tuples, dictionaries, and sets. Lists and tuples provide ways to organize and manipulate collections of items, with lists being mutable and tuples being immutable.

Dictionaries offer a key-value mapping for efficient data retrieval and modification. Sets, with their unique and unordered nature, enable operations like union, intersection, and difference.

Understanding these data structures and their respective use cases is fundamental for effective Python programming. As you incorporate lists, tuples, dictionaries, and sets into your code, you enhance your ability to organize, access, and manipulate data efficiently. These data structures play a central role in building versatile and powerful Python applications.