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Python Data Cleaning Cookbook

You're reading from   Python Data Cleaning Cookbook Prepare your data for analysis with pandas, NumPy, Matplotlib, scikit-learn, and OpenAI

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Product type Paperback
Published in May 2024
Publisher Packt
ISBN-13 9781803239873
Length 486 pages
Edition 2nd Edition
Languages
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Author (1):
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Michael Walker Michael Walker
Author Profile Icon Michael Walker
Michael Walker
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Table of Contents (14) Chapters Close

Preface 1. Anticipating Data Cleaning Issues When Importing Tabular Data with pandas FREE CHAPTER 2. Anticipating Data Cleaning Issues When Working with HTML, JSON, and Spark Data 3. Taking the Measure of Your Data 4. Identifying Outliers in Subsets of Data 5. Using Visualizations for the Identification of Unexpected Values 6. Cleaning and Exploring Data with Series Operations 7. Identifying and Fixing Missing Values 8. Encoding, Transforming, and Scaling Features 9. Fixing Messy Data When Aggregating 10. Addressing Data Issues When Combining DataFrames 11. Tidying and Reshaping Data 12. Automate Data Cleaning with User-Defined Functions, Classes, and Pipelines 13. Index

Identifying outliers and unexpected values in bivariate relationships

A value might be unexpected, even if it is not an extreme value, when it does not deviate significantly from the distribution mean. Some values for a variable are unexpected when a second variable has certain values. This is easy to illustrate when one variable is categorical and the other is continuous.

The following diagram illustrates the number of bird sightings per day over a period of several years, but shows different distributions for each of the two sites. One site has a mean sightings per day of 33, and the other 52. (This is fictional data.) The overall mean (not shown) is 42. What should we make of a value of 58 for daily sightings? Is that an outlier? That clearly depends on which of the two sites was being observed.

If there were 58 sightings on a day at site A, 58 would be an unusually high number. Not so for site B, where 58 sightings would not be very different from the mean for that site...

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