Exploratory Data Analysis
Taylor & Francis Ltd (Verlag)
978-1-032-93982-7 (ISBN)
This book is a comprehensive guide to exploratory data analysis (EDA), providing readers with the tools, techniques, and knowledge needed to conduct effective and thorough data exploration. Throughout the seven main chapters, this book details various aspects of EDA, from data description and preprocessing to visualization, storytelling, and dashboard design. We will explore real‑world datasets, uncovering hidden patterns and gaining insights along the way. This book is filled with illustrations using practical examples, Python codes, and different types of exercises designed to reinforce the concepts and processes discussed. Whether you are a student just starting out in the field of data science, a senior professional looking to improve your skills, or a curious individual interested in the power of data, this book is for you.
Leandro Nunes de Castro is an Electrical Engineer by the Federal University of Goiás (1996), holds a Master’s degree in Electrical Engineering (1998) and a Ph.D. in Computer Engineering (2001), both from Unicamp, Brazil. He also has an MBA in Strategic Business Management from the Catholic University of Santos (2008). He was a Research Associate at the Computing Laboratory of the University of Kent in Canterbury from June 2001 to May 2002, a Visiting Professor at the Technological University of Malaysia in September 2005, a Visiting Specialist Professor at Unicamp between March and June 2012, and a Visiting Researcher at the University of Salamanca between January and July 2014. Leandro was a professor and researcher with the Master’s Program in Informatics at Unisantos from 2003 to 2008, and a professor and researcher with the Graduate Program in Electrical Engineering and Computing at Mackenzie Presbyterian University from 2008 to 2022. His main lines of research are Natural Computing and Machine Learning, with applications in Intelligent Data Analysis and Optimization. Leandro N. de Castro is the main author of the book “Artificial Immune Systems: A New Computational Intelligence Approach” (Springer-Verlag, 2002); one of the organizers of “Recent Developments in Biologically Inspired Computing” (Idea Group Publishing, 2004); author of “Fundamentals of Natural Computing: Basic Concepts, Algorithms, and Applications” (CRC Press, 2006), author of the book “Natural Computing: An Illustrated Journey” (Livraria da Física, 2010), organizer of the book “Nature-Inspired Computing Design, Development, and Application” (IGI-Global, 2012) and main author of the book “Introduction to Data Mining: Basic Concepts, Algorithms and Applications” (In Portuguese, Saraiva, 2016). He was the proponent and Editor-in-Chief of the International Journal of Natural Computing Research (IJNCR) between 2010 and 2015, published by IGI-Global. His research work has been recognized globally since 2020 as among the 2% most influential researchers in the world based on scientific impact indices monitored by PLoS Biology. Leandro has published over 250 papers in journals and conferences. His scholarly contributions also include founding two research laboratories and serving as Research Chair and as the Chief Innovation and Entrepreneurship Officer at Mackenzie. In addition to his academic achievements, Leandro is also a successful entrepreneur. He has participated in the founding of three Artificial Intelligence startups and invested, as an angel investor, in other three. Some of the notable startups he has been involved with include Tuilux, a company that offered intelligent recommendation services to e-commerce, and Somma.ai, a low/no code data science platform that allows the building of highly complex analytical applications without having to program. Currently, Leandro is a Full Professor at the Florida Gulf Coast University (FGCU) in the Department of Computing & Software Engineering, US, and the Director of DENDRITIC: A Human-Centered Artificial Intelligence and Data Science Institute at FGCU.
Preface. Acknowledgements. About the Author. Chapter 1. An Introduction to Exploratory Data Analysis. Chapter 2. Data Description and Preparation. Chapter 3. Descriptive Analysis. Chapter 4. Principles of Data Visualization. Chapter 5. Data Visualization Methods. Chapter 6. Special Types of Data. Chapter 7. Data Storytelling and Dashboard Design. Appendices.
| Erscheinungsdatum | 17.10.2025 |
|---|---|
| Reihe/Serie | AK Peters Visualization Series |
| Zusatzinfo | 30 Tables, black and white; 77 Line drawings, color; 9 Line drawings, black and white; 5 Halftones, color; 82 Illustrations, color; 9 Illustrations, black and white |
| Verlagsort | London |
| Sprache | englisch |
| Maße | 178 x 254 mm |
| Gewicht | 650 g |
| Themenwelt | Informatik ► Datenbanken ► Data Warehouse / Data Mining |
| Mathematik / Informatik ► Informatik ► Programmiersprachen / -werkzeuge | |
| Informatik ► Software Entwicklung ► User Interfaces (HCI) | |
| Informatik ► Theorie / Studium ► Künstliche Intelligenz / Robotik | |
| ISBN-10 | 1-032-93982-6 / 1032939826 |
| ISBN-13 | 978-1-032-93982-7 / 9781032939827 |
| Zustand | Neuware |
| Informationen gemäß Produktsicherheitsverordnung (GPSR) | |
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