Building Baseball Data Visualizations with Python
What you'll learn
In this project you’ll follow along with our instructions to build data visualizations that present data on Major League Baseball All-star games.
Table of contents
- Set up your local environment for projects. We'll walk you through everything you need to know, including how to install and configure your environment to be able to complete all of the tasks.
Game Files - Clean and Import Data
- 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.
Attendance - Select and Plot Data
- In this module, we will answer the question: "How has All-star game attendance changed over time?"
Pitching - Group Data
- In this module, we will answer the question: "How have the number of strike outs changed over time?"
Offense - Reshape with Pivot
- In this module, we will use the `pivot()` function to show the distribution of hit types across innings.
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.