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Pitch Location Charts with PITCHf&x and ggplot

Learners: 5,910

Instructor: Charles Redmond

Duration:

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

Cost:

Free

Provider:

Udemy

Certificate:

No Information

Language:

English

Start 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.