📚 Data Structures and Algorithms

Welcome to the Data Structures and Algorithms repository! This repository contains practical implementations and examples of various data structures and algorithms.

📂 Contents

• 🔢 Array
  • Basic operations (insertion, deletion, traversal)
  • Sorting algorithms (bubble sort, merge sort, quicksort)
• 🔗 Linked List
  • Singly linked list
  • Doubly linked list
  • Circular linked list
• 📚 Stack
  • Implementation using arrays and linked lists
  • Applications of stacks (expression evaluation, backtracking)
• 📥 Queue
  • Implementation using arrays and linked lists
  • Circular queue
  • Priority queue
• 🌳 Tree
  • Binary tree
  • Binary search tree
  • AVL tree
  • Tree traversals (inorder, preorder, postorder)
• 🌐 Graph
  • Graph representation (adjacency matrix, adjacency list)
  • Graph traversal algorithms (BFS, DFS)
• 🔍 Hashing
  • Hash table implementation
  • Collision resolution techniques (chaining, open addressing)
• ⚡ Sorting and Searching
  • Common sorting algorithms (insertion sort, selection sort, heap sort)
  • Searching algorithms (binary search, linear search)
• 📈 Dynamic Programming
  • Classic problems (knapsack, longest common subsequence, matrix chain multiplication)
• 🛠️ Greedy Algorithms
  • Greedy strategy examples (fractional knapsack, Huffman coding)

🏁 Getting Started

To get started with the code in this repository, simply clone the repository to your local machine:

git clone https://github.com/yourusername/Data-Structures-and-Algorithms.git

🛠️ Prerequisites Make sure you have Python installed on your machine to run the code examples. If you don't have it, you can download and install it from Python.org or use an online compiler.

🚀 Usage Each directory contains source code files related to a specific data structure or algorithm. You can run these files using the following commands:

python filename.py

Replace filename.py with the name of the source code file you want to run.

Happy coding! 🚀