This project demonstrates the implementation of various Python data structures including lists, dictionaries, sets, tuples, stacks, and queues. Each data structure is implemented in its own class with ...

Below is an overview of some Abstract Data Types (ADTs) and my implementations of them using Python, including a summary of their worst case Time Complexities. Queues are a collection (or sequence) ...

Lists and tuples are both ordered and iterable data structures that can store heterogeneous data types. However, lists are mutable, meaning they can be modified after creation, while tuples are ...

Python lists significantly impact code optimization. It offer versatility and efficiency for storing and manipulating data, allowing for quick access, insertion, and removal of elements.

2. Versatility: Python's versatility makes it an excellent choice for handling a wide range of data structures. Whether you're working with lists, sets, dictionaries, or more advanced structures, ...

Each of these Python data structures serves a specific purpose, and the choice often depends on the nature of the statistical task at hand. For instance, NumPy arrays excel in numerical computations, ...