<<echo=FALSE,results='asis',message=FALSE,warning=FALSE,include=FALSE>>=

##################################################
#### Create data set #############################
##################################################

footballdata <- read.csv("http://www.repole.com/sun4cast/stats/cfb20140906.csv")

nums <- sapply(footballdata, is.numeric)

fdata<- footballdata[ , nums]
#data1 <- fdata[fdata$ScoreOff >30, ] 
#data2 <- fdata[fdata$ScoreOff <=30, ]

# Using selected nodes from python mapper

nodeset1 <- unlist(read.table("nodelist1.txt"))
nodeset2 <- unlist(read.table("nodelist2.txt"))
data1 <- fdata[nodeset1+1,]
data2 <- fdata[nodeset2+1,]

##################################################

kslist = list()
for (i in 1:length(fdata[1,])){
  kslist[[i]] <- ks.test(data1[,i], data2[,i])
}

pValue<-unlist(lapply(kslist, "[", "p.value")) 
D<-unlist(lapply(kslist, "[", "statistic"))
KStest<-cbind(D, pValue)
rownames(KStest) <- colnames(fdata)
@

%{r echo=FALSE} opts_chunk$set(echo=FALSE)

\documentclass[12pt]{article}

\begin{document}


 <<echo=FALSE,results='asis',message=FALSE,warning=FALSE>>=
kable(KStest, format = "latex")
@ 

\end{document}