Python Fundamentals for Data Analytics

Python is a simple, easy-to-learn, and one of the top programming languages across the globe. As a result of advancements in AI, data mining, and numerical computing fields, Python has become a popular programming language catering to various stakeholders. It is a powerful tool for working with a variety of data. This book provides the basics of Python and an introduction to data analytics.

This book offers a complete introduction to Python programming, covering everything from the basics to the advanced topics. It starts by explaining core concepts like syntax and the Python interpreter, then dives into data structures, control flow, functions, and modules. You will also learn about data analysis and visualization with popular libraries like NumPy, Pandas, Matplotlib, and Seaborn. It wraps up with practical case studies, showing how to apply Python in real-world scenarios effectively.

The book serves as a step-by-step guide to performing data analysis. Its content is designed so that even a novice can learn and perform data analysis and visualization simply by following the instructions in the book.  

KEY FEATURES  

• The book covers a wide range of topics, from Python fundamentals to advanced data analysis techniques.
• It includes practical exercises and real-world case studies to illustrate the applications of Python for data analysis.
• The book explains complex concepts in a clear and understandable manner.

WHAT YOU WILL LEARN

• Understand the basics of programming languages and the role of the Python interpreter.
• Read about different data structures like lists, sets, tuples, and dictionaries, and understand their applications.
• Learn how to work with files in Python, including reading, writing, and appending data.
• Discover how to use NumPy and Pandas for efficient data manipulation and analysis.
• Learn how to create informative visualizations using Matplotlib and Seaborn.

WHO THIS BOOK IS FOR

This book is designed for students studying UG or PG courses in the computer science and applications domain. Learning Python is a simple way to begin the journey of data analytics. One of the in-demand domains in the job market, and research is data analytics. This book will be helpful for students interested in this domain.

1. Programming Languages and Python Interpreter
2. Python Fundamentals
3. Project Jupyter and JupyterLab Environment
4. Collection Types
5. Conditional Branching
6. Iterating Constructs
7. Functions and Methods
8. Modules
9. File Operations
10. Working with Data
11. Data Visualization
12. Case Studies
Appendix I: Abbreviations

The authors Dr Chandrika M and Dr Pavithra B Shetty are distinguished academicians with more than a decade of academic experience in higher education and are constantly involved in academic activities. They like to work on the projects where they get to share their valuable knowledge along with interpersonal, technical, communication, and teaching skills. They are keen on the opportunities where they can learn and experience, mentor, and share. Their research interests include advanced computing topics such as data science, machine learning, and computer programming.

They have a shared interest in working on projects that allow them to mentor students while continuing their own learning journey. Their roles as assistant professors at Dayananda Sagar College of Engineering, an institution affiliated with Visvesvaraya Technological University (VTU), Belagavi, place them at the forefront of academic activities where they constantly engage with new trends in technology and education. Their contributions to academia are not only in teaching but also in collaborative projects that bridge the gap between industry and academia.