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Books > Computing & IT > Social & legal aspects of computing > Human-computer interaction
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Python Data Cleaning Cookbook - Modern techniques and Python tools to detect and remove dirty data and extract key insights (Paperback)
Loot Price: R1,321
Discovery Miles 13 210
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Python Data Cleaning Cookbook - Modern techniques and Python tools to detect and remove dirty data and extract key insights (Paperback)
Expected to ship within 10 - 15 working days
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Discover how to describe your data in detail, identify data issues,
and find out how to solve them using commonly used techniques and
tips and tricks Key Features Get well-versed with various data
cleaning techniques to reveal key insights Manipulate data of
different complexities to shape them into the right form as per
your business needs Clean, monitor, and validate large data volumes
to diagnose problems before moving on to data analysis Book
DescriptionGetting clean data to reveal insights is essential, as
directly jumping into data analysis without proper data cleaning
may lead to incorrect results. This book shows you tools and
techniques that you can apply to clean and handle data with Python.
You'll begin by getting familiar with the shape of data by using
practices that can be deployed routinely with most data sources.
Then, the book teaches you how to manipulate data to get it into a
useful form. You'll also learn how to filter and summarize data to
gain insights and better understand what makes sense and what does
not, along with discovering how to operate on data to address the
issues you've identified. Moving on, you'll perform key tasks, such
as handling missing values, validating errors, removing duplicate
data, monitoring high volumes of data, and handling outliers and
invalid dates. Next, you'll cover recipes on using supervised
learning and Naive Bayes analysis to identify unexpected values and
classification errors, and generate visualizations for exploratory
data analysis (EDA) to visualize unexpected values. Finally, you'll
build functions and classes that you can reuse without modification
when you have new data. By the end of this Python book, you'll be
equipped with all the key skills that you need to clean data and
diagnose problems within it. What you will learn Find out how to
read and analyze data from a variety of sources Produce summaries
of the attributes of data frames, columns, and rows Filter data and
select columns of interest that satisfy given criteria Address
messy data issues, including working with dates and missing values
Improve your productivity in Python pandas by using method chaining
Use visualizations to gain additional insights and identify
potential data issues Enhance your ability to learn what is going
on in your data Build user-defined functions and classes to
automate data cleaning Who this book is forThis book is for anyone
looking for ways to handle messy, duplicate, and poor data using
different Python tools and techniques. The book takes a
recipe-based approach to help you to learn how to clean and manage
data. Working knowledge of Python programming is all you need to
get the most out of the book.
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