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.
Author(s): Galety Mohammad
Series: premier reference source
Publisher: Engineering Science Reference
Year: 2023
Language: English
Pages: 320
Cover
Title Page
Copyright Page
Book Series
Mission
Coverage
Preface
Acknowledgment
Introduction
Chapter 1: Fundamentals of Data Structures
ABSTRACT
INTRODUCTION
STACK
QUEUE
LINKED LIST
SINGLY LINKED LIST
DOUBLY LINKED LIST
CIRCULAR LINKED LIST
GRAPH
SEARCHING
SORTING
CONCLUSION
REFERENCES
Chapter 2: Organizing Data Using Lists
ABSTRACT
THE BASICS OF LIST
STACK
QUEUE
RESEARCH DIRECTIONS AND CHALLENGES
CONCLUSION
REFERENCES
Chapter 3: Linear Data Structures and Their Applications
ABSTRACT
INTRODUCTION
CHARACTERISTICS OF LINEAR DATA STRUCTURES
APPLICATIONS OF LINEAR DATA STRUCTURES
ADVANTAGES OF LINEAR DATA STRUCTURES
DRAWBACKS OF LINEAR DATA STRUCTURES
ARRAYS
SINGLY-LINKED LIST
DOUBLY LINKED LIST
CIRCULAR LINKED LIST
STACK
QUEUE
PRIORITY QUEUE
CONCLUSION
REFERENCES
Chapter 4: A Comprehensive Analysis of Stack and Queue Data Structures and Their Uses
ABSTRACT
INTRODUCTION TO STACK
FEATURES OF STACK
STACK OPERATIONS
STACK IMPLEMENTATION
APPLICATIONS OF STACK
QUEUE: INTRODUCTION
FEATURES OF QUEUE
QUEUE OPERATIONS
QUEUE IMPLEMENTATION
TYPES OF QUEUES
APPLICATIONS OF QUEUE
DIFFERENCES BETWEEN STACK AND QUEUE DATA STRUCTURES
CONCLUSION
REFERENCES
Chapter 5: Dynamic Programming With Python
ABSTRACT
INTRODUCTION
DYNAMIC PROGRAMMING
FIBONACCI SERIES
TOWERS OF HANOI PUZZLE
DIJKSTRA'S ALGORITHM
CHECKERED BOARD PROBLEM
CONCLUSION
REFERENCES
Chapter 6: Exploratory Data Analysis in Python
ABSTRACT
INTRODUCTION
PYTHON LIBRARIES TO PERFORM EDA
PYTHON FUNCTIONS FOR EDA
UNIVARIATE GRAPHICAL METHOD
UNIVARIATE NON-GRAPHICAL METHOD
MULTIVARIATE NON-GRAPHICAL METHOD
MULTIVARIATE GRAPHICAL METHOD
DATA VISUALISATION IN EDA
BIVARIATE ANALYSIS
NUMERICAL AND NUMERICAL
NUMERICAL AND CATEGORICAL
CATEGORICAL AND CATEGORICAL
CONCLUSION
REFERENCES
Chapter 7: Empowering Scientific Computing and Data Manipulation With Numerical Python (NumPy)
ABSTRACT
INTRODUCTION
NUMPY DATATYPES
NUMPY ARRAYS
THE DIFFERENCE BETWEEN A NUMPY ARRAY AND A LIST
ARRAY OPERATIONS
SPECIAL FUNCTION OF NUMPY PYTHON
CONCLUSION
REFERENCES
Chapter 8: Exploring Python's Powerful Data Collections
ABSTRACT
INTRODUCTION TO LIST
NESTED LIST
LIST METHODS
LIST AND FUNCTIONS
INTRODUCTION TO TUPLE
TUPLE SLICING
TUPLE PACKING AND UNPACKING
NESTED TUPLES
COUNT AND INDEX METHODS OF A TUPLE
INTRODUCTION TO SET
INITIALIZING AND PRINTING A SET
SET METHODS
INTRODUCTION TO DICTIONARY
CREATING A DICTIONARY
ACCESS DICTIONARY ITEMS
ADDING AND REMOVING ITEMS
DICTIONARY METHODS
CONCLUSION
REFERENCES
Chapter 9: Interactive Visualization With Plotly Express
ABSTRACT
IMPORTANCE OF DATA VISUALIZATION
PLOTLY EXPRESS FOR DATA VISUALIZATION
INTERACTIVE VISUALIZATION WITH PLOTLY EXPRESS
CONCLUSION
REFERENCES
Chapter 10: Enhancing Big Data Analytics and Recommendation Systems With Python
ABSTRACT
INTRODUCTION
CLUSTERING
RELATED WORK
PROPOSED WORK
MULTI-DIMENSIONAL CONTENT DIFFICULTY RATING
EXPERIMENTAL RESULT
CONCLUSION
REFERENCES
Chapter 11: Optimizing Energy Consumption in Wireless Sensor Networks Using Python Libraries
ABSTRACT
INTRODUCTION
WIRELESS SENSOR NETWORKS
LITERATURE REVIEW
RESEARCH GAP IDENTIFIED
OBJECTIVES OF THE STUDY
METHODOLOGY
LIMITATIONS OF LEACH PROTOCOL
IMPORTANCE OF RELAY NODES
ENERGY CONSUMPTION OPTIMISATION IN WSN USING PYTHON
ADAPTIVE DUTY CYCLING WITH RELAY NODES
CONCLUSION
REFERENCES
Chapter 12: An Exploratory Study of Python's Role in the Advancement of Cryptocurrency and Blockchain Ecosystems
ABSTRACT
INTRODUCTION
LITERATURE REVIEW
THE FACTORS AND PARAMETERS
PROBLEM STATEMENT
OBJECTIVES OF THE STUDY
SCOPE OF THE STUDY
METHODOLOGY
TOOLS
ANALYZING CRYPTO MARKET DATA WITH PYTHON
CREATING OUR OWN CRYPTOCURRENCY USING PYTHON
CONCLUSION
REFERENCES
Chapter 13: Exploring the Role of Python in Self-Supervised Contrastive Learning for Generating Medical Imaging Reports
ABSTRACT
INTRODUCTION
LITERATURE REVIEW
RESEARCH GAP
RESEARCH QUESTIONS
THE FACTORS AND PARAMETERS
PROBLEM STATEMENT
OBJECTIVES OF THE STUDY
SCOPE OF THE STUDY
METHODOLOGY
A STUDY ON EXITING VGG16 MODEL TO PREDICT LABELS
ROLE OF PYTHON TO PREDICT LABELS
CONCLUSION
REFERENCES
Chapter 14: Python's Role in Predicting Type 2 Diabetes Using Insulin DNA Sequence
ABSTRACT
INTRODUCTION
PREDICTING TYPE 2 DIABETES
THE MAIN OBJECTIVES OF THE RESEARCH
THE ROLE OF PYTHON
VISUALIZATION TOOLS
ALGORITHMS IN PYTHON
BIOINFORMATICS TOOLS
CONCLUSION
REFERENCES
Compilation of References
About the Contributors
