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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

Changing Series values conditionally

Changing Series values is often more complicated than the previous recipe suggests. We often need to set Series values based on the values of one or more other Series for that row of data. This is complicated further when we need to set Series values based on values from other rows; say, a previous value for an individual, or the mean for a subset. We will deal with these complications in this and the next recipe.

Getting ready

We will work with land temperature data and the NLS data in this recipe.

Data note

The land temperature dataset contains the average temperature readings (in Celsius) in 2023 from over 12,000 stations across the world, though the majority of the stations are in the United States. The raw dataset was retrieved from the Global Historical Climatology Network integrated database. It has been made available for public use by the United States National Oceanic and Atmospheric Administration at https:/...

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