Python for Data Science: Concepts, Techniques, and Applications has been released as a comprehensive guide designed to bridge the gap between theory and practice in the field of data science. Authored by Dr. Krishna Kumar P R, Dr. Manjunath K V, Mrs. Sowmya Rani, and Ms. Hithaishi KV, the book takes readers on a structured journey from the foundations of Python programming to advanced applications of data science, making it suitable for students, educators, researchers, and industry professionals alike.
The book begins with an introduction to the fundamentals of Python and core concepts of data science, covering essential techniques such as predictive modeling, customer segmentation, fraud detection, and recommendation systems. A unique aspect of the text is its broad coverage of data types, including text, numeric, categorical, image, audio, video, geospatial, and time-series data, ensuring that learners understand the diversity of datasets they may encounter.
Moving beyond theoretical concepts, the authors provide detailed explanations of data collection methods—ranging from surveys and experiments to web scraping and sensor-based data gathering—along with practical demonstrations of how Python can be leveraged to acquire and simulate datasets. The book also dedicates a significant portion to data visualization techniques, presenting a wide array of charts, scatter plots, histograms, heatmaps, treemaps, 3D visualizations, and word clouds. Each visualization concept is accompanied by code examples and outputs, enabling readers to learn by doing.
A crucial highlight of the book is its thorough exploration of data preprocessing and manipulation using Python libraries like pandas. Readers are guided step-by-step through handling missing values, outliers, categorical encodings, and consistency checks, while Exploratory Data Analysis (EDA) is explained in depth using statistical measures and Python code. The later sections of the book delve into statistical modeling, integrating programming with theory to build a strong conceptual foundation before concluding with real-world case studies that demonstrate how data science transforms industries such as healthcare, finance, and cybersecurity.
Behind this book stands a team of accomplished authors with diverse expertise. Dr. Krishna Kumar P R, Professor and Head of the Department of Computer Science and Engineering at SEA College of Engineering & Technology, Bangalore, brings more than 24 years of experience in teaching, research, and academic leadership. His contributions in IoT, AI, Big Data, and Cybersecurity, along with his extensive publications and patents, have established him as a pioneer in the field.
Dr. Manjunath K V, Associate Professor at Presidency University, Bangalore, and former guest faculty at BITS Pilani, adds his deep expertise in Data Science, Artificial Intelligence, and Machine Learning. With over 17 years of academic experience, multiple patents, and a wide portfolio of research, he has enriched the book with insights from both academia and industry-driven research.
Mrs. Sowmya Rani, Assistant Professor at SEA College of Engineering and Technology, contributes her strong interest and experience in Data Science, Machine Learning, and AI, reflecting her commitment to teaching and mentoring students in emerging technologies.