Pitch Location Charts with PITCHf&x and ggplot faq

learnersLearners: 5,910
instructor Instructor: Charles Redmond instructor-icon
duration Duration: instructor-icon

This course is perfect for baseball fans who want to learn how to create pitch location charts with PITCHf/x and ggplot. It will teach you how to break down a game into each at-bat and visualize the location, type, and speed of each pitch, the order in which the pitches were thrown, and the outcome of the at-bat. You will also gain additional R skills, such as how to subset a vector and how to work with factors. With a relaxed pace, you can complete the course in about three weeks. No prior knowledge of R, dplyr, and ggplot is required.

Course Feature Course Overview Course Provider
Go to class

Course Feature

costCost:

Free

providerProvider:

Udemy

certificateCertificate:

No Information

languageLanguage:

English

start dateStart Date:

2015-07-16

Course Overview

❗The content presented here is sourced directly from Udemy platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [August 31st, 2023]

Skills and Knowledge:
By the end of this course, you will have acquired the following skills and knowledge:
- Understanding of PITCHf/x data and how to use it to create pitch location charts
- Knowledge of ggplot and how to use it to create visualizations
- Ability to work with color, aesthetics, and faceting
- Understanding of how to subset a vector and work with factors
- Proficiency in R, dplyr, and ggplot

Professional Growth:
This course provides a great opportunity for professional growth. By learning how to create pitch location charts with PITCHf/x and ggplot, students will gain valuable skills in data visualization, data manipulation, and programming. These skills are highly sought after in the job market and can be applied to a variety of data analysis tasks. Additionally, the course provides a great opportunity to learn more about R, dplyr, and ggplot, which are essential tools for data analysis. By the end of the course, students will have a better understanding of how to work with color, aesthetics, and faceting, as well as how to subset a vector and work with factors.

Further Education:
This course is suitable for preparing further education. It covers topics such as working with data, visualizing data using ggplot, and gaining additional R skills. These skills are valuable for further education in fields such as data analysis, statistics, and research.

Course Provider

Provider Udemy's Stats at OeClass