ICW2

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Last edited Feb 3, 2016

Created on Feb 2, 2016

This gallery example presents visualizations of 2014 college football passing statistics from a CSV file. The scatter matrix uses R's `pairs` function to plot combinations of passing yards, touchdowns, quarterback rating, and rushing stats. A bar chart using `ggplot2` with `geom_bar` displays passing yards per player, while another `ggplot2` bar chart shows average rushing touchdowns per conference, computed with the `aggregate` function. All charts are rendered as SVG.

AI-generated description

John Berlin ICW2 Group Members: John Berlin

Scatter Matrix scattermatrix

setwd(getwd())
playerStats <- read.csv('passing-stats-2014.csv')
pairs(~playerStats$Passing.Yards+playerStats$Passing.TD+playerStats$Rate+playerStats$Rushing.Yards+playerStats$Rushing.TD)

Yards Per Player

pyrdsperplayer

library(ggplot2)
setwd(getwd())
playerStats <- read.csv('passing-stats-2014.csv')
yardsConf = data.frame(yrds=playerStats$Passing.Yards,player=playerStats$Player,conf=playerStats$Conf)
ggplot(yardsConf,aes(x=player,y=yrds,fill=conf)) +  geom_bar(stat="identity") + coord_flip()

Average Rushing TD avrushingtd

library(ggplot2)
setwd(getwd())
playerStats <- read.csv('passing-stats-2014.csv')
two <- playerStats[, c("Conf","Rushing.TD")]
ret <- aggregate(two,by=list(two$Conf),FUN="mean")
present <- data.frame(Conf=ret$Group.1,Av.Russing.TD=ret$Rushing.TD)
ggplot(present,aes(x=Conf,y=Av.Russing.TD,fill=Conf)) +  geom_bar(stat="identity")

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