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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
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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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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

Understanding which position scores the most per team

In baseball, teams are allowed 9 batters in a “lineup,” with 1 representing the first person to bat and 9 representing the last. Over the course of a game, teams cycle through batters in order, starting over with the first batter after the last has batted.

Typically, teams place some of their best hitters toward the “top of the lineup” (i.e., lower number positions) to maximize the opportunity for them to come around and score. However, this does not always mean that the person who bats in position 1 will always be the first to score.

In this recipe, we are going to look at all Major League baseball teams from 2000–2023 and find the position that scored the most runs for a team over each season.

How to do it

Much like we did in the Finding the baseball players best at… recipe, we are going to use data taken from retrosheet.org. For this particular dataset, we are going to...

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