Data Structures Intro

A data structure is a way to store data so you can use it efficiently.

If you choose the right structure:

• your code becomes faster
• your logic becomes simpler
• your programs scale better

If you choose the wrong structure:

• you get slow apps
• messy code
• hard bugs

What you will learn in this playlist

We will go step by step from beginner to advanced:

• Lists, tuples, sets, dictionaries
• Stacks, queues, heaps
• Trees, graphs (intro level)
• How to pick the right structure for the job
• Time complexity (in simple words)

A simple example

Imagine you store student names.

• If you use a list, searching a name can be slow for large data.
• If you use a set, checking if a name exists is fast.

That is the power of picking the right structure.

Core idea: operations you do most

When you choose a data structure, ask:

• Do I add items often?
• Do I search often?
• Do I need ordering?
• Do I need uniqueness?
• Do I need key-value lookup?

Graph: how to choose quickly

flowchart TD
  A[Need to store many items] --> B{Need order?}
  B -->|Yes| C[List / Tuple]
  B -->|No| D{Need uniqueness?}
  D -->|Yes| E[Set]
  D -->|No| F{Need key->value?}
  F -->|Yes| G[Dict]
  F -->|No| H[List]

Key terms (student-friendly)

• Ordered: items keep position (like list)
• Unordered: no fixed position (like set)
• Mutable: you can change it (list, dict)
• Immutable: you cannot change it (tuple)
• Key-Value: look up using keys (dict)

Remember

• Data structure choice decides speed and simplicity
• Python gives powerful built-in containers
• We'll build your concepts so you don’t need to read elsewhere