Date created on: December 4th, 2016
For: Week 3 project, Developing Data Products
Coursera Data Science Specialization, Johns Hopkins University
Plots Player Average Fantasy Points vs. Salary
Shows Player Efficiency, Visually
mydata = read.csv("FanDuel-NFL-2016-12-04-17105-players-list.csv")
set.seed(2016)
mydata$Position <- factor(mydata$Position, levels = c("QB", "RB", "WR", "TE", "K", "D"))
splt2 <- ggplot(data = mydata, aes(x = Salary, y = FPPG, label = LastName)) +
geom_point(aes(colour = Position)) +
geom_smooth(size = .5, method = loess) +
xlab("Salary") +
ylab("Average Points per Game") +
ggtitle("NFL Data 12/04/2016")
(gg <- ggplotly(splt2))