DATA STRUCTURES

WHAT IS DATA STRUCTURES ?

• A data structure is a specialized way of organizing, storing, and managing data in a computer so that it can be accessed and modified efficiently.

In simple terms:

• A data structure is like a container that holds data in a particular layout or pattern, which helps you use the data effectively depending on the task.

Why Data Structures Matter ?

• Improve efficiency of algorithms.
• Allow for faster search, insert, delete, and update operations.

TYPES OF DATA STRUCTURES:
1. Linear Data Structures
2. Non-Linear Data Structures
3. Hash-based Structures

1. Array – Your Playlist

Think of your playlist as a row of seats in a theater. Each seat (position) has a specific number and holds one person (song). If you want to know what song is 5th in the playlist, you just go to seat 5 — fast and direct.

Example: Your playlist has songs in a fixed order:
1. Song A → 2. Song B → 3. Song C
You can easily access the second song without looking through all of them.

1. Linked List – Editable Playlist

Now imagine instead of a fixed row of seats, you have a chain of people holding hands. Each person knows who is next in line. If someone wants to join or leave, it's easy — just change who’s holding whose hand.

Example: You add or remove songs often from your playlist.
The app uses a linked list so it doesn't have to rearrange everything — just reconnect the links.

1. Stack – Recently Played Songs

This works like a stack of plates. You put one plate on top of another. When you want a plate, you take the one on top. Same for songs: you go "back" to the last one played.

Example: You’re listening to:

    Song A

    Song B

    Song C
    Now you press "Back" → it plays Song B (the last one before C).
    Press "Back" again → it plays Song A.

1. Queue – Upcoming Songs

A queue is like people waiting in line. The first person in line gets served first (First In, First Out). Your upcoming songs work the same way.

Example: You line up songs to play next:

    Song D

    Song E

    Song F
    The app plays Song D first, then E, then F — just like a waiting line.

Non-Linear Data Structure

1. Tree

A tree is a structure where each item (called a "node") is connected like a family tree: one parent, many children.
📱 Real-Life Example: Phone Menu System

You call customer care, and it says:

Press 1 for English

Press 2 for Hindi
→ If you press 1:

    Press 1 for Internet

    Press 2 for Calls

    Press 3 for Billing

This is a tree:

Root: Language selection

Branches: Services

Sub-branches: Options inside each service

🟢 Why Tree?

It organizes information hierarchically.

Each choice leads to another set of options.

1. Binary Search Tree (BST)

A BST is a special kind of tree where:

Left child = smaller value

Right child = larger value

📚 Real-Life Example: Dictionary

You want to look up the word “Mouse.” You don’t start at page 1. You go to the middle, then decide whether to move left or right. This “divide and conquer” process is like a binary search tree.

🟢 Why BST?

It makes searching much faster (used in databases and autocomplete features).

1. Graph

A graph is like a network. Items (called “nodes” or “vertices”) are connected by links (called “edges”). You can travel in any direction, sometimes in circles.
🌍 Real-Life Example: Google Maps

Each location is a node. Roads are edges.
If you want to go from your house to a coffee shop, Google Maps checks all possible paths and finds the best one (shortest or fastest).

🟢 Why Graph?

It handles complex connections.

Used in:

    GPS systems

    Social networks (you and your friends are nodes)

    Internet (webpages linking to other webpages)