Python Data Cleaning Cookbook

Python Data Cleaning Cookbook

eBook Details:

  • Paperback: 439 pages
  • Publisher: WOW! eBook (December 11, 2020)
  • Language: English
  • ISBN-10: 1800565666
  • ISBN-13: 978-1800565661

eBook Description:

Python Data Cleaning Cookbook: 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

Getting 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.

  • 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

By the end of this Python Data Cleaning Cookbook book, you’ll be equipped with all the key skills that you need to clean data and diagnose problems within it.

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