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You're reading from  Hands-On Data Preprocessing in Python

Product typeBook
Published inJan 2022
PublisherPackt
ISBN-139781801072137
Edition1st Edition
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Author (1)
Roy Jafari
Roy Jafari
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Roy Jafari

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.
Read more about Roy Jafari

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Conventions used

There are a number of text conventions used throughout this book.

Code in text: Indicates code words in text, database table names, folder names, filenames, file extensions, pathnames, dummy URLs, user input, and Twitter handles. Here is an example: "To create this interactive visual, we have used the interact and widgets programming objects from the ipywidgets module."

A block of code is set as follows:

from ipywidgets import interact, widgets
interact(plotyear,year=widgets.IntSlider(min=2010,max=2019,step=1,value=2010))

When we wish to draw your attention to a particular part of a code block, the relevant lines or items are set in bold:

Xs_t.plot.scatter(x='PC1',y='PC2',c='PC3',sharex=False, 
                  vmin=-1/0.101, vmax=1/0.101,
                  figsize=(12,9))
x_ticks_vs = [-2.9*4 + 2.9*i for i in range(9)]

Bold: Indicates a new term, an important word, or words that you see on screen. For instance, words in menus or dialog boxes appear in bold. Here is an example: "The missing values for the attributes from SupportQ1 to AttitudeQ3 are from the same data objects."

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Hands-On Data Preprocessing in Python
Published in: Jan 2022Publisher: PacktISBN-13: 9781801072137

Author (1)

author image
Roy Jafari

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.
Read more about Roy Jafari