Hands-On Data Preprocessing in Python: Learn how to effectively prepare data for successful data analytics

by Roy Jafari

Overview

Hands-On Data Preprocessing is a primer on the best data cleaning and preprocessing techniques, written by an expert who’s developed college-level courses on data preprocessing and related subjects.
With this book, you’ll be equipped with the optimum data preprocessing techniques from multiple perspectives, ensuring that you get the best possible insights from your data.
You'll learn about different technical and analytical aspects of data preprocessing – data collection, data cleaning, data integration, data reduction, and data transformation – and get to grips with implementing them using the open source Python programming environment.
The hands-on examples and easy-to-follow chapters will help you gain a comprehensive articulation of data preprocessing, its whys and hows, and identify opportunities where data analytics could lead to more effective decision making. As you progress through the chapters, you’ll also understand the role of data management systems and technologies for effective analytics and how to use APIs to pull data.
By the end of this Python data preprocessing book, you'll be able to use Python to read, manipulate, and analyze data; perform data cleaning, integration, reduction, and transformation techniques, and handle outliers or missing values to effectively prepare data for analytic tools.

Product Details

ISBN-13:	9781801079952
Publisher:	Packt Publishing
Publication date:	01/21/2022
Sold by:	Barnes & Noble
Format:	eBook
Pages:	602
File size:	40 MB
Note:	This product may take a few minutes to download.

About the Author

Roy Jafari, Ph.D. is an assistant professor of business analytics at the University of Redlands.
Roy has taught and developed college-level courses that cover data cleaning, decision making, data science, machine learning, and optimization.
Roy's style of teaching is hands-on and he believes the best way to learn is to learn by doing. He uses active learning teaching philosophy and readers will get to experience active learning in this book.
Roy believes that successful data preprocessing only happens when you are equipped with the most efficient tools, have an appropriate understanding of data analytic goals, are aware of data preprocessing steps, and can compare a variety of methods. This belief has shaped the structure of this book.