Table of Contents
Data Structures: The Containers of Programming
Data structures are ways to organize and store data so your programs can work with information efficiently. Think of them as different types of containers for different purposes.
Why Do We Need Data Structures?
Just like you organize items in your home differently (clothes in closets, books on shelves, dishes in cabinets), programs need different ways to organize data based on how it will be used.
Common Data Structures
1. Arrays/Lists - The Shopping List
Arrays store multiple items in order, like a shopping list.
Array Examples
// Creating arrays
fruits = ["apple", "banana", "orange", "grape"]
numbers = [1, 2, 3, 4, 5]
temperatures = [72.5, 68.2, 75.1, 69.8]
// Accessing items (usually starts at 0)
firstFruit = fruits[0] // "apple"
secondFruit = fruits[1] // "banana"
// Adding items
fruits.add("strawberry") // Now: ["apple", "banana", "orange", "grape", "strawberry"]
// Getting the size
count = fruits.length // 52. Objects/Dictionaries - The Address Book
Objects store information using key-value pairs, like an address book where you look up information by name.
Object Examples
// Creating an object
person = {
"name": "Alice Johnson",
"age": 28,
"city": "New York",
"email": "alice@email.com"
}
// Accessing values
personName = person["name"] // "Alice Johnson"
personAge = person["age"] // 28
// Adding new information
person["phone"] = "555-1234"
// Updating existing information
person["age"] = 293. Stacks - The Plate Stack
Stacks work like a stack of plates - you can only add or remove from the top (Last In, First Out - LIFO).
Stack Example
stack = []
// Push (add to top)
stack.push("first")
stack.push("second")
stack.push("third")
// Stack now: ["first", "second", "third"]
// Pop (remove from top)
item = stack.pop() // Returns "third"
// Stack now: ["first", "second"]4. Queues - The Line at the Store
Queues work like a line at the store - first person in line is first to be served (First In, First Out - FIFO).
Queue Example
queue = []
// Enqueue (add to back)
queue.enqueue("Alice")
queue.enqueue("Bob")
queue.enqueue("Charlie")
// Queue: ["Alice", "Bob", "Charlie"]
// Dequeue (remove from front)
served = queue.dequeue() // Returns "Alice"
// Queue now: ["Bob", "Charlie"]Choosing the Right Data Structure
| Use Case | Best Data Structure | Why |
|---|---|---|
| Store student grades | Array | Simple list of numbers |
| Store student information | Object | Multiple related properties |
| Undo feature in text editor | Stack | Last action should be undone first |
| Print queue | Queue | First document sent should print first |
Real-World Examples
Student Management System
// Array of student objects
students = [
{
"id": 1,
"name": "Alice",
"grades": [85, 92, 78, 96],
"email": "alice@school.edu"
},
{
"id": 2,
"name": "Bob",
"grades": [79, 85, 88, 82],
"email": "bob@school.edu"
}
]
// Function to calculate average grade
function calculateAverage(grades):
total = 0
for each grade in grades:
total = total + grade
return total / length(grades)
// Process each student
for each student in students:
average = calculateAverage(student["grades"])
print(student["name"] + " average: " + average)Shopping Cart System
// Shopping cart using array of objects
cart = [
{"item": "laptop", "price": 999.99, "quantity": 1},
{"item": "mouse", "price": 25.99, "quantity": 2},
{"item": "keyboard", "price": 79.99, "quantity": 1}
]
// Calculate total
function calculateTotal(cart):
total = 0
for each item in cart:
itemTotal = item["price"] * item["quantity"]
total = total + itemTotal
return total
total = calculateTotal(cart)
print("Cart total: $" + total)Common Operations
Array Operations
- Access: Get item by position
- Search: Find item in the array
- Insert: Add item at specific position
- Delete: Remove item from array
- Sort: Arrange items in order
Object Operations
- Get: Retrieve value by key
- Set: Add or update key-value pair
- Delete: Remove key-value pair
- Keys: Get all keys
- Values: Get all values
🎯 Data Structure Practice
- Create an array of your favorite movies and print each one
- Build an object representing a book with title, author, pages, and year
- Design a simple to-do list using an array
- Create a contact list using an array of person objects
Performance Considerations
Different data structures have different strengths:
- Arrays: Fast access by index, slower for searching
- Objects: Fast lookup by key, good for related data
- Stacks: Very fast add/remove from top
- Queues: Fair processing order, good for task management
Next Steps
As you advance, you'll learn about more complex data structures like:
- Trees (for hierarchical data)
- Graphs (for network-like relationships)
- Hash tables (for very fast lookups)
- Linked lists (for dynamic sizing)