Data structures are essential for organizing and managing data efficiently. Here's a quick overview of core concepts:

Arrays

  • 📌 Fixed Size: Arrays have a predetermined size, making them ideal for scenarios with known data volume.
  • 🚀 Fast Access: Elements are accessed via indexes (e.g., array[0]), enabling O(1) time complexity for retrieval.
Array

Linked Lists

  • 🧠 Dynamic Growth: Nodes are linked, allowing flexible resizing during runtime.
  • 🔁 Efficient Insertions: Adding/removing elements in the middle is efficient (O(1) with pointers).
Linked_List

Stacks & Queues

  • 📦 LIFO Principle: Stacks follow Last-In-First-Out (e.g., browser history).
  • 🚫 FIFO Principle: Queues follow First-In-First-Out (e.g., print job scheduling).
Stack_Queue

Trees & Graphs

  • 🌳 Hierarchical Structure: Trees store data in parent-child relationships (e.g., file systems).
  • 🌐 Networked Relationships: Graphs represent connections between nodes (e.g., social networks).
Tree_Graph

For interactive visualizations and code examples, explore our Data Structures Tutorials section. 🚀