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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

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Product type Paperback
Published in Dec 2020
Publisher Packt
ISBN-13 9781800565661
Length 436 pages
Edition 1st Edition
Languages
Tools
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Authors (2):
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Michael B Walker Michael B Walker
Author Profile Icon Michael B Walker
Michael B Walker
Michael Walker Michael Walker
Author Profile Icon Michael Walker
Michael Walker
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Table of Contents (12) Chapters Close

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

Getting a first look at your data

We will work with two datasets in this chapter: The National Longitudinal Survey of Youth for 1997, a survey conducted by the United States government that surveyed the same group of individuals from 1997 through 2017; and the counts of COVID cases and deaths by country from Our World in Data.

Getting ready…

We will mainly be using the pandas library for this recipe. We will use pandas tools to take a closer look at the National Longitudinal Survey (NLS) and COVID-19 case data.

Note

The NLS of Youth was conducted by the United States Bureau of Labor Statistics. This survey started with a cohort of individuals in 1997 who were born between 1980 and 1985, with annual follow-ups each year through 2017. For this recipe, I pulled 89 variables on grades, employment, income, and attitudes toward government from the hundreds of data items on the survey. Separate files for SPSS, Stata, and SAS can be downloaded from the repository. NLS data...

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