Data Capstone Project.R

# Capstone Data Project (Moneyball Project)

# Setting the Working Directory
setwd("./R Bootcamp/R-Course-HTML-Notes/R-for-Data-Science-and-Machine-Learning/Training Exercises/Capstone and Data Viz Projects/Capstone Project")

# Loading the Data
batting <- read.csv('Batting.csv')
head(batting)

# Gathering the Batting Averages
str(batting)
head(batting$AB)
head(batting$X2B)

batting$BA <- batting$H / batting$AB
tail(batting$BA,5)

# On-Base Percentage
batting$OBP <- (batting$H + batting$BB + batting$HBP)/(batting$AB + batting$BB + batting$HBP + batting$SF)

# Batting Singles
batting$X1B <- batting$H - batting$X2B - batting$X3B - batting$HR

# Slugging Averages
batting$SLG <- ((1 * batting$X1B) + (2 * batting$X2B) + (3 * batting$X3B) + (4 * batting$HR) ) / batting$AB

# Check the Data Frame 
str(batting)

## Merging Salary Data

# Gathering Data
sal <- read.csv('Salaries.csv')
summary(batting)

# >1985 Data
batting <- subset(batting,yearID >= 1985)

summary(batting)


# Merging the Data Together with Salary and Batting
combo <- merge(batting,sal,by=c('playerID','yearID'))
summary(combo)

# Getting the Lost Players Season
lost_players <- subset(combo,playerID %in% c('giambija01','damonjo01','saenzol01'))
lost_players


# Grabbing the information for 2001
lost_players <- subset(lost_players,yearID == 2001)
lost_players <- lost_players[,c('playerID','H','X2B','X3B','HR','OBP','SLG','BA','AB')]
head(lost_players)


# Replacement Players to Look For
#1469AB, AVG 0.364 OBP, # 15 Million
combo <- subset(combo,yearID == 2001)
str(combo)

# Plotting the Data
library(ggplot2)
library(dplyr)
ggplot(combo,aes(x=OBP,y=salary)) + geom_point(size=2, color = 'limegreen',alpha=1)

# Cutting Off the Salary Mark at $8M

combo <- subset(combo,salary < 8000000, OBP > 0)
str(combo)

1469/3
combo <- subset(combo,AB>=450)
str(combo)

# Sorting the OBP
options <- head(arrange(combo,desc(OBP)),10)

options[,c('playerID', 'AB', 'salary', 'OBP')]

4950000+4833333+305000