Building Baseball Data Visualizations with Python

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Building Baseball Data Visualizations with Python

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Lab Info

Level

Intermediate

Last updated

Aug 14, 2025

Duration

2h 50m

Challenge

Game Files - Clean and Import Data

In this lab you’ll follow along with our instructions to build data visualizations that present data on Major League Baseball All-star games.

The data we will work with in this project is stored in several CSV files. In this module we will clean and import the data using the Pandas library. The event files for this project are provided by Retrosheet.

As per the Retrosheet license. The information used here was obtained free of charge from and is copyrighted by Retrosheet. Interested parties may contact Retrosheet at "www.retrosheet.org". ### Solution The solution can be found in the solution directory.
Challenge

Attendance - Select and Plot Data

In this module, we will answer the question: "How has All-star game attendance changed over time?"
Challenge

Pitching - Group Data

In this module, we will answer the question: "How have the number of strike outs changed over time?"
Challenge

Offense - Reshape with Pivot

In this module, we will use the pivot() function to show the distribution of hit types across innings.
Challenge

Defensive Efficiency Ratio - Merge Data

Defensive Efficiency Ratio is used as a metric to gauge team defense. In this module we will calculate this for each league over time.

About the author

Tom Bell

Tom is a staff author at Pluralsight helping to develop Hands-On content. Tom's background in software development, UI/UX, and instructional design was developed over the years while working as a faculty member at the School of Computing at Weber State University in Utah, and continues to grow as he develops Projects and Labs for Pluralsight. When he's not creating content to allow learners to gain real-life experience, he enjoys spending time with his family.

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