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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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Toc

Table of Contents (14) Chapters Close

Preface 1. Anticipating Data Cleaning Issues When Importing Tabular Data with pandas 2. Anticipating Data Cleaning Issues When Working with HTML, JSON, and Spark Data FREE CHAPTER 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 simple JSON data

JavaScript Object Notation (JSON) has turned out to be an incredibly useful standard for transferring data from one machine, process, or node to another. Often, a client sends a data request to a server, upon which that server queries the data in local storage and then converts it from something like an SQL Server, MySQL, or PostgreSQL table or tables into JSON, which the client can consume. This is sometimes complicated further by the first server (say, a web server) forwarding the request to a database server. JSON facilitates this, as does XML, by doing the following:

  • Being readable by humans
  • Being consumable by most client devices
  • Not being limited in structure

JSON is quite flexible, which means that it can accommodate just about anything, no matter how unwise. The structure can even change within a JSON file, so different keys might be present at different points. For example, the file might begin with some explanatory...

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Python Data Cleaning Cookbook - Second Edition
Published in: May 2024
Publisher: Packt
ISBN-13: 9781803239873
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