Python Programming Using Problem Solving / / Harsh Bhasin.

• VerfasserIn: Bhasin, Harsh,
• Place / Publishing House: Dulles, VA : : Mercury Learning and Information, , [2023]; ©2023
• Year of Publication: 2023
• Language: English
• Physical Description: 1 online resource (574 p.)
• Other title: Frontmatter --; Contents --; Preface --; Section I: Algorithmic Problem-Solving and Python Fundamentals --; Chapter 1: Algorithmic Problem-Solving --; Chapter 2: Introduction to Python --; Chapter 3: Fundamentals --; Section II: Procedural Programming --; Chapter 4: Conditional Statements --; Chapter 5: Looping --; Chapter 6: Functions --; Chapter 7: File Handling --; Chapter 8: Lists, Tuple, and Dictionary --; Chapter 9: Iterations, Generators, and Comprehensions --; Chapter 10: Strings --; Section III: Object-Oriented Programming --; Chapter 11: Introduction to Object-Oriented Paradigm --; Chapter 12: Classes and Objects --; Chapter 13: Inheritance --; Chapter 14: Operator Overloading --; Chapter 15: Exception Handling --; Section IV: Numpy, Pandas, and Matplotlib --; Chapter 16: Numpy–I --; Chapter 17: Numpy–II --; Chapter 18: Data Visualization-I --; Chapter 19: Data Visualization–II --; Chapter 20: Pandas–I --; Chapter 21: Pandas–II --; Appendix A: Problems for Practice: Programming Questions --; Appendix B: Answers to MCQS --; References --; Web Resources --; Index
• Format: Mode of access: Internet via World Wide Web.
• ISBN: 9781683928614
• DOI: 10.1515/9781683928614
• Access: restricted access
• Hierarchical level: Monograph
• Statement of Responsibility: Harsh Bhasin.

Python is a robust, procedural, object-oriented, and functional language. The features of the language make it valuable for web development, game development, business, and scientific programming. This book deals with problem-solving and programming in Python. It concentrates on the development of efficient algorithms, the syntax of the language, and the ability to design programs in order to solve problems. In addition to standard Python topics, the book has extensive coverage of NumPy, data visualization, and Matplotlib. Numerous types of exercises, including theoretical, programming, and multiple-choice, reinforce the concepts covered in each chapter.