Galety M.G., Natarajan A.K., Sriharsha A.V. Advanced Applications of Python Data Structures and Algorithms

IGI Global, 2023. — 318 p. — (Advances in Systems Analysis, Software Engineering, and High Performance Computing). — ISBN 9781668471005.Продвинутые приложения структур данных и алгоритмов Python
Data structures are essential principles applicable to any programming language in computer science. Data structures may be studied more easily with Python than with any other programming language because of their interpretability, interactivity, and object-oriented nature. Computers may store and process data at an extraordinary rate and with outstanding accuracy. Therefore, it is of the utmost importance that the data is efficiently stored and is able to be accessed promptly. In addition, data processing should take as little time as feasible while maintaining the highest possible level of precision.Advanced Applications of Python Data Structures and Algorithms assists in understanding and applying the fundamentals of data structures and their many implementations and discusses the advantages and disadvantages of various data structures. Covering key topics such as Python, linked lists, datatypes, and operators, this reference work is ideal for industry professionals, computer scientists, researchers, academicians, scholars, practitioners, instructors, and students.Preface
Introduction
Chapter 1 Fundamentals of Data Structures: Stacks, Queues, Linked Lists, and Graphs
Chapter 2 Organizing Data Using Lists: A Sequential Data Structure
Chapter 3 Linear Data Structures and Their Applications
Chapter 4 A Comprehensive Analysis of Stack and Queue Data Structures and Their Uses
Chapter 5 Dynamic Programming With Python
Chapter 6 Exploratory Data Analysis in Python
Chapter 7 Empowering Scientific Computing and Data Manipulation With Numerical Python (NumPy)
Chapter 8 Exploring Python’s Powerful Data Collections
Chapter 9 Interactive Visualization With Plotly Express
Chapter 10 Enhancing Big Data Analytics and Recommendation Systems With Python: Hierarchical Clustering and Filtering Using Slicing Technique
Chapter 11 Optimizing Energy Consumption in Wireless Sensor Networks Using PythonLibraries
Chapter 12 An Exploratory Study of Python’s Role in the Advancement of Cryptocurrency and Blockchain Ecosystems
Chapter 13 Exploring the Role of Python in Self-Supervised Contrastive Learning for Generating Medical Imaging Reports
Chapter 14 Python’s Role in Predicting Type 2 Diabetes Using Insulin DNA Sequence