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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

Importing data from web pages

We use Beautiful Soup in this recipe to scrape data from a web page and load that data into pandas. Web scraping is very useful when there is data on a website that is updated regularly but there is no API. We can rerun our code to generate new data whenever the page is updated.

Unfortunately, the web scrapers we build can be broken when the structure of the targeted page changes. That is less likely to happen with APIs because they are designed for data exchange and carefully curated with that end in mind. The priority for most web designers is the quality of the display of information, not the reliability and ease of data exchange. This causes data cleaning challenges that are unique to web scraping, including HTML elements that house the data in surprising and changing locations, formatting tags that obfuscate the underlying data, and explanatory text that aid data interpretation being difficult to retrieve. In addition to these challenges, scraping...

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