data(Teams)
# subset on a few variables
teams <- subset(Teams, lgID %in% c("AL", "NL"))
teams <- subset(teams, yearID>1900)
# drop some variables
teams <- subset(teams, select=-c(Ghome,divID,DivWin:WSWin,name,park,teamIDBR:teamIDretro))
teams <- subset(teams, select=-c(HBP,CS,BPF,PPF))
# subset to remove infrequent teams
tcount <- table(teams$teamID)
teams <- subset(teams, teams$teamID %in% names(tcount)[tcount>10], drop=TRUE)
teams$teamID <- factor(teams$teamID, levels=names(tcount)[tcount>10])
# relevel lgID
teams$lgID <- factor(teams$lgID, levels= c("AL", "NL"))
# create new variables
teams <- within(teams, {
WinPct = W / G ## Winning percentage
})
library(lattice)
xyplot(attendance/1000 ~ WinPct|yearID, groups=lgID, data=subset(teams, yearID>1980),
type=c("p", "r"), col=c("red","blue"))
if(require(googleVis)) {
motion1 <- gvisMotionChart(teams, idvar='teamID', timevar='yearID',
chartid="gvisTeams", options=list(width=700, height=600))
plot(motion1)
#print(motion1, file="gvisTeams.html")
}Run the code above in your browser using DataLab