, Data Mining with Python
Data is everywhere and it’s growing at an unprecedented rate. But making sense of all that data
is a challenge. Data Mining is the process of discovering patterns and knowledge from large data
sets, and Data Mining with Python focuses on the hands-on approach to learning Data Mining.
It showcases how to use Python Packages to fulfil the Data Mining pipeline, which is to collect,
integrate, manipulate, clean, process, organize, and analyze data for knowledge.
The contents are organized based on the Data Mining pipeline, so readers can naturally prog-
ress step by step through the process. Topics, methods, and tools are explained in three aspects:
“What it is” as a theoretical background, “why we need it” as an application orientation, and
“how we do it” as a case study.
This book is designed to give students, data scientists, and business analysts an understanding of
Data Mining concepts in an applicable way. Through interactive tutorials that can be run, modi-
fied, and used for a more comprehensive learning experience, this book will help its readers gain
practical skills to implement Data Mining techniques in their work.
Dr. Di Wu is an Assistant Professor of Finance, Information Systems, and Economics department
of Business School, Lehman College. He obtained a Ph.D. in Computer Science from the Graduate
Center, CUNY. Dr. Wu's research interests includeTemporal extensions to RDF and semantic
web, Applied Data Science, and Experiential Learning and Pedagogy in Business Education.
Dr. Wu developed and taught courses including Strategic Management, Databases, Business
Statistics, Management Decision Making, Programming Languages (C++, Java, and Python),
Data Structures and Algorithms, Data Mining, Big Data, and Machine Learning.
,Chapman & Hall/CRC
The Python Series
About the Series
Python has been ranked as the most popular programming language, and it is widely used in
education and industry. This book series will offer a wide range of books on Python for students
and professionals. Titles in the series will help users learn the language at an introductory and
advanced level, and explore its many applications in data science, AI, and machine learning.
Series titles can also be supplemented with Jupyter notebooks.
Image Processing and Acquisition using Python, Second Edition
Ravishankar Chityala, Sridevi Pudipeddi
Python Packages
Tomas Beuzen and Tiffany-Anne Timbers
Statistics and Data Visualisation with Python
Jesús Rogel-Salazar
Introduction to Python for Humanists
William J.B. Mattingly
Python for Scientific Computation and Artificial Intelligence
Stephen Lynch
Learning Professional Python Volume 1: The Basics
Usharani Bhimavarapu and Jude D. Hemanth
Learning Professional Python Volume 2: Advanced
Usharani Bhimavarapu and Jude D. Hemanth
Learning Advanced Python from Open Source Projects
Rongpeng Li
Foundations of Data Science with Python
John Mark Shea
Data Mining with Python: Theory, Application, and Case Studies
Di Wu
For more information about this series please visit: https://www.crcpress.com/Chapman--Hall-
CRC/book-series/PYTH
, Data Mining with Python
Theory, Application, and Case Studies
Di Wu
Data is everywhere and it’s growing at an unprecedented rate. But making sense of all that data
is a challenge. Data Mining is the process of discovering patterns and knowledge from large data
sets, and Data Mining with Python focuses on the hands-on approach to learning Data Mining.
It showcases how to use Python Packages to fulfil the Data Mining pipeline, which is to collect,
integrate, manipulate, clean, process, organize, and analyze data for knowledge.
The contents are organized based on the Data Mining pipeline, so readers can naturally prog-
ress step by step through the process. Topics, methods, and tools are explained in three aspects:
“What it is” as a theoretical background, “why we need it” as an application orientation, and
“how we do it” as a case study.
This book is designed to give students, data scientists, and business analysts an understanding of
Data Mining concepts in an applicable way. Through interactive tutorials that can be run, modi-
fied, and used for a more comprehensive learning experience, this book will help its readers gain
practical skills to implement Data Mining techniques in their work.
Dr. Di Wu is an Assistant Professor of Finance, Information Systems, and Economics department
of Business School, Lehman College. He obtained a Ph.D. in Computer Science from the Graduate
Center, CUNY. Dr. Wu's research interests includeTemporal extensions to RDF and semantic
web, Applied Data Science, and Experiential Learning and Pedagogy in Business Education.
Dr. Wu developed and taught courses including Strategic Management, Databases, Business
Statistics, Management Decision Making, Programming Languages (C++, Java, and Python),
Data Structures and Algorithms, Data Mining, Big Data, and Machine Learning.
,Chapman & Hall/CRC
The Python Series
About the Series
Python has been ranked as the most popular programming language, and it is widely used in
education and industry. This book series will offer a wide range of books on Python for students
and professionals. Titles in the series will help users learn the language at an introductory and
advanced level, and explore its many applications in data science, AI, and machine learning.
Series titles can also be supplemented with Jupyter notebooks.
Image Processing and Acquisition using Python, Second Edition
Ravishankar Chityala, Sridevi Pudipeddi
Python Packages
Tomas Beuzen and Tiffany-Anne Timbers
Statistics and Data Visualisation with Python
Jesús Rogel-Salazar
Introduction to Python for Humanists
William J.B. Mattingly
Python for Scientific Computation and Artificial Intelligence
Stephen Lynch
Learning Professional Python Volume 1: The Basics
Usharani Bhimavarapu and Jude D. Hemanth
Learning Professional Python Volume 2: Advanced
Usharani Bhimavarapu and Jude D. Hemanth
Learning Advanced Python from Open Source Projects
Rongpeng Li
Foundations of Data Science with Python
John Mark Shea
Data Mining with Python: Theory, Application, and Case Studies
Di Wu
For more information about this series please visit: https://www.crcpress.com/Chapman--Hall-
CRC/book-series/PYTH
, Data Mining with Python
Theory, Application, and Case Studies
Di Wu
