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Python Data Cleaning Cookbook

You're reading from Python Data Cleaning Cookbook Modern techniques and Python tools to detect and remove dirty data and extract key insights

Product type Paperback

Published in Dec 2020

Publisher Packt

ISBN-13 9781800565661

Length 436 pages

Edition 1st Edition

Languages

Python

Tools

Pandas

Concepts

Data Analysis

Authors (2):

Michael B Walker

Michael Walker

View More author details

Table of Contents (12) Chapters

Preface

1. Chapter 1: Anticipating Data Cleaning Issues when Importing Tabular Data into pandas

2. Chapter 2: Anticipating Data Cleaning Issues when Importing HTML and JSON into pandas FREE CHAPTER

3. Chapter 3: Taking the Measure of Your Data

4. Chapter 4: Identifying Missing Values and Outliers in Subsets of Data

5. Chapter 5: Using Visualizations for the Identification of Unexpected Values

6. Chapter 6: Cleaning and Exploring Data with Series Operations

7. Chapter 7: Fixing Messy Data when Aggregating

8. Chapter 8: Addressing Data Issues When Combining DataFrames

9. Chapter 9: Tidying and Reshaping Data

10. Chapter 10: User-Defined Functions and Classes to Automate Data Cleaning

11. Other Books You May Enjoy

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Who this book is for

This 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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Authors (2)

Michael B Walker

Michael B Walker

See other products by Michael B Walker

Michael Walker

Michael Walker

Michael Walker has worked as a data analyst for over 30 years at a variety of educational institutions. He is currently the CIO at College Unbound in Providence, Rhode Island, in the United States. He has also taught data science, research methods, statistics, and computer programming to undergraduates since 2006.

See other products by Michael Walker

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