Data Structures Introduction

A data structure is a way to organize and store data in a computer so that it can be efficiently accessed, modified, and manipulated.
Data structures provide a way to manage large amounts of data efficiently in terms of time and space complexity.

Arrays: A collection of elements of the same data type stored in contiguous memory locations.
- Operations: indexing, slicing, concatenation
Linked Lists: A dynamic collection of elements, where each element points to the next element.
- Operations: insertion, deletion, traversal
Stacks: A Last-In-First-Out (LIFO) data structure, where elements are added and removed from the top.
- Operations: push, pop, peek
Queues: A First-In-First-Out (FIFO) data structure, where elements are added to the end and removed from the front.
- Operations: enqueue, dequeue, peek
Trees: A hierarchical data structure, where each node has a value and zero or more child nodes.
- Operations: insertion, deletion, traversal
Graphs: A non-linear data structure, where nodes are connected by edges.
- Operations: traversal, shortest path, minimum spanning tree
Hash Tables: A data structure that maps keys to values using a hash function.
- Operations: insertion, deletion, search

Time Complexity: The amount of time an algorithm takes to complete, usually measured in Big O notation.
Space Complexity: The amount of memory an algorithm uses, usually measured in Big O notation.

Database Systems: Data structures are used to store and retrieve data efficiently.
Compilers: Data structures are used to parse and analyze source code.
Web Search Engines: Data structures are used to index and retrieve web pages efficiently.
Social Networks: Data structures are used to store and analyze relationships between users.

A data structure is a way to organize and store data in a computer to efficiently access, modify, and manipulate it.
Data structures provide a way to manage large amounts of data efficiently in terms of time and space complexity.

Arrays: A collection of elements of the same data type stored in contiguous memory locations, with operations including indexing, slicing, and concatenation.
Linked Lists: A dynamic collection of elements, where each element points to the next element, with operations including insertion, deletion, and traversal.
Stacks: A Last-In-First-Out (LIFO) data structure, where elements are added and removed from the top, with operations including push, pop, and peek.
Queues: A First-In-First-Out (FIFO) data structure, where elements are added to the end and removed from the front, with operations including enqueue, dequeue, and peek.
Trees: A hierarchical data structure, where each node has a value and zero or more child nodes, with operations including insertion, deletion, and traversal.
Graphs: A non-linear data structure, where nodes are connected by edges, with operations including traversal, shortest path, and minimum spanning tree.
Hash Tables: A data structure that maps keys to values using a hash function, with operations including insertion, deletion, and search.

Time Complexity: The amount of time an algorithm takes to complete, usually measured in Big O notation.
Space Complexity: The amount of memory an algorithm uses, usually measured in Big O notation.

Database Systems: Data structures are used to store and retrieve data efficiently.
Compilers: Data structures are used to parse and analyze source code.
Web Search Engines: Data structures are used to index and retrieve web pages efficiently.
Social Networks: Data structures are used to store and analyze relationships between users.