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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
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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

Finding the baseball players best at…

The American sport of baseball has long been a subject of intense analytical research, with data collection dating back to the early 1900s. For Major League baseball teams, advanced data analysis helps answer questions like How much should I pay for X player? and What should I do in the game given the current state of things?, For fans, that same data can be used as fodder for endless debates around who is the greatest player ever.

For this recipe, we are going to use data that was collected from retrosheet.org. Per the Retrosheet licensing requirements, you should be aware of the following legal disclaimer:

The information used here was obtained free of charge and is copyrighted by Retrosheet. Interested parties may contact Retrosheet at www.retrosheet.org.

From its raw form, the data was summarized to show the common baseball metrics for at bat (ab), hits (h), runs scored (r), and home runs (hr) for professional...

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