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Pandas Cookbook

You're reading from   Pandas Cookbook Practical recipes for scientific computing, time series, and exploratory data analysis using Python

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Product type Paperback
Published in Oct 2024
Publisher Packt
ISBN-13 9781836205876
Length 404 pages
Edition 3rd Edition
Languages
Tools
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Authors (2):
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William Ayd William Ayd
Author Profile Icon William Ayd
William Ayd
Matthew Harrison Matthew Harrison
Author Profile Icon Matthew Harrison
Matthew Harrison
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Toc

Table of Contents (13) Chapters Close

Preface 1. pandas Foundations FREE CHAPTER 2. Selection and Assignment 3. Data Types 4. The pandas I/O System 5. Algorithms and How to Apply Them 6. Visualization 7. Reshaping DataFrames 8. Group By 9. Temporal Data Types and Algorithms 10. General Usage and Performance Tips 11. The pandas Ecosystem 12. Index

JSON

JavaScript Object Notation (JSON) is a common format used to transfer data over the internet. The JSON specification can be found at https://www.json.org. Despite the name, it does not require JavaScript to read or create.

The Python standard library ships with the json library, which can serialize and deserialize Python objects to/from JSON:

import json
beatles = {
    "first": ["Paul", "John", "Richard", "George",],
    "last": ["McCartney", "Lennon", "Starkey", "Harrison",],
    "birth": [1942, 1940, 1940, 1943],
}
serialized = json.dumps(beatles)
print(f"serialized values are: {serialized}")
deserialized = json.loads(serialized)
print(f"deserialized values are: {deserialized}")
serialized values are: {"first": ["Paul", "John", "Richard", "George"], "last": ["McCartney...
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