Pitch Location Charts with PITCHf/x and ggplot

Pitch Location Charts with PITCHf/x and ggplot, available at Free, has an average rating of 4.7, with 37 lectures, based on 104 reviews, and has 6011 subscribers.

You will learn about scrape PITCHf/x data into an R session plot pitch locations with ggplot visualize pitch type and speed with ggplot subset vectors in R work with color in ggplot facet in ggplot label with geom_text work with seq, lapply, unlist, and unique in R save plots as png's write for loops in R work with factors in R This course is ideal for individuals who are This course is for students interested in learning how to create pitch location charts and how to wrangle data from PITCHf/x. or It would be best for each student to have a bit of a background in R, dplyr, and ggplot, but it is not completely necessary. It is particularly useful for This course is for students interested in learning how to create pitch location charts and how to wrangle data from PITCHf/x. or It would be best for each student to have a bit of a background in R, dplyr, and ggplot, but it is not completely necessary.

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Summary

Title: Pitch Location Charts with PITCHf/x and ggplot

Price: Free

Average Rating: 4.7

Number of Lectures: 37

Number of Published Lectures: 37

Number of Curriculum Items: 37

Number of Published Curriculum Objects: 37

Original Price: Free

Quality Status: approved

Status: Live

What You Will Learn

scrape PITCHf/x data into an R session
plot pitch locations with ggplot
visualize pitch type and speed with ggplot
subset vectors in R
work with color in ggplot
facet in ggplot
label with geom_text
work with seq, lapply, unlist, and unique in R
save plots as png's
write for loops in R
work with factors in R

Who Should Attend

This course is for students interested in learning how to create pitch location charts and how to wrangle data from PITCHf/x.
It would be best for each student to have a bit of a background in R, dplyr, and ggplot, but it is not completely necessary.

Target Audiences

This course is for students interested in learning how to create pitch location charts and how to wrangle data from PITCHf/x.
It would be best for each student to have a bit of a background in R, dplyr, and ggplot, but it is not completely necessary.

In this course, we make use of PITCHf/x data to create pitch location charts for a given baseball game. We break the game out 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.

In order to accomplish this, we will be taking a deep dive into ggplot. We will learn much about how to work with color, how to use aesthetics, and how to facet. We will also gain additional R skills, such as how to subset a vector and how to work with factors.

One should be able to complete the course, at a relaxed pace, in about three weeks. It is best if students already have a little bit of a background in R, dplyr, and ggplot, but it is not completely necessary.

Course Curriculum

Chapter 1: Extracting PITCHf/x Data

Lecture 1: Introduction

Lecture 2: PITCHf/x Data

Lecture 3: Scraping the Data

Lecture 4: Joining the atbat and pitch Data Frames

Lecture 5: Choosing Columns from the atbat Data Frame

Lecture 6: Choosing Columns from the pitch Data Frame

Chapter 2: Multi-Batter Visualizations

Lecture 1: The Strike-Zone

Lecture 2: Drawing the Strike-Zone

Lecture 3: Vizualizing the Pitch Locations

Lecture 4: Visualizing Pitch Speed

Lecture 5: Visualizing Pitch Type

Lecture 6: Subsetting R vectors and "which"

Lecture 7: Better Pitch Descriptions

Chapter 3: Working with Color

Lecture 1: Hue

Lecture 2: Chromaticity (saturation)

Lecture 3: Luminance (brightness)

Lecture 4: Palettes

Lecture 5: Manual Color Specification

Lecture 6: Colors and Factors

Chapter 4: Faceting

Lecture 1: Faceting with One Variable

Lecture 2: Stand on the Correct Side

Lecture 3: Facet Order through Factors

Lecture 4: Faceting by At-Bat

Chapter 5: At-Bat by At-Bat

Lecture 1: Specifying Batter and Inning

Lecture 2: Labeling Pitches

Lecture 3: Replacing "In Play"

Lecture 4: Counting the Number of Pitches in an At-Bat

Lecture 5: lapply and seq

Lecture 6: unlist

Lecture 7: Visualizing Pitch Enumeration

Chapter 6: Slide-Show

Lecture 1: Saving a Single Plot

Lecture 2: For Loop Part I

Lecture 3: For Loop Part II

Lecture 4: Difficulties and Problems!

Lecture 5: Solving the Color Problem

Lecture 6: Solving the Speed Problem Part I

Lecture 7: Solving the Speed Problem Part II and Wrap-Up

Instructors

Charles Redmond
Professor at Mercyhurst University

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4 stars: 16 votes
5 stars: 85 votes

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