nishadiss/python-data-structures-and-algorithms

data-structures-and-algorithms

Data Structures:

Arrays:

Ordered collections of elements of the same type, accessed by index. Efficient for random access but can be slow for insertions and deletions.

Lists:

Built-in mutable sequences in Python, used to store collections of items. They are flexible and easy to modify.

Linked Lists:

Sequences of nodes, where each node contains data and a link to the next node. Efficient for insertions and deletions, but not for random access.

Stacks:

LIFO (Last-In, First-Out) data structures, like a stack of plates. Used for function calls, undo/redo operations, and backtracking.

Queues:

FIFO (First-In, First-Out) data structures, like a line at a store. Used for task scheduling, buffering, and resource management.

Trees:

Hierarchical data structures with a root node and child nodes. Used for representing file systems, decision trees, and organizing data with parent-child relationships.

Graphs:

Networks of nodes (vertices) connected by edges. Used for representing social networks, maps, and relationships between entities.

Dictionaries:

Unordered collections of key-value pairs, used for fast lookups by key.

Sets:

Unordered collections of unique elements, used for membership testing and removing duplicates

Algorithms:

Searching Algorithms:

Finding a specific element within a data structure. Examples: Linear Search, Binary Search.

Sorting Algorithms:

Arranging elements in a specific order. Examples: Bubble Sort, Selection Sort, Insertion Sort, Merge Sort, Quick Sort, Heap Sort.

Recursion:

A technique where a function calls itself to solve smaller subproblems. Used for tree traversals, divide-and-conquer algorithms, and mathematical calculations.

Graph Algorithms:

Algorithms for traversing, searching, and analyzing graphs. Examples: Breadth-First Search (BFS), Depth-First Search (DFS), Dijkstra's Algorithm, Prim's Algorithm.

Dynamic Programming:

Solving problems by breaking them down into smaller overlapping subproblems. Used for optimization problems, sequence alignment, and string parsing.

contents

1. Array

2. Binary Search Tree

Technologies Used

Pragramming language

Python

frameworks