b1 <- ggplot(btw9s, aes(Bundesland, Voters/1000000)) +
             geom_bar(stat="identity") +
             ylab("Voters (millions)")
b2 <- ggplot(btw9s, aes(reorder(Bundesland, -Voters),
             Voters/1000000)) + geom_bar(stat="identity")  +
             xlab("Bundesland") + ylab("Voters (millions)")
b3 <- ggplot(btw9s, aes(State1, Voters/1000000)) +
             geom_bar(stat="identity")  + xlab("Bundesland") +
             ylab("Voters (millions)")
grid.arrange(b1, b2, b3)

data(Fleiss93, package="meta")
Fleiss93 <- within(Fleiss93, {
                   total <- n.e + n.c
                   st <- reorder(study, -(total)) })
ggplot(Fleiss93, aes(st, total)) + geom_bar(stat="identity") +
       xlab("") + ylab("") + ylim(0,20000)

data(anorexia, package="MASS")
ggplot(anorexia, aes(Treat)) + geom_bar() +  xlab("Treatment")

Titanic1 <- data.frame(Titanic)
p <- ggplot(Titanic1, aes(weight=Freq)) +
            ylab("") + ylim(0,2250)
cs <- p + aes(Class) + geom_bar(fill="blue")
sx <- p + aes(Sex) + geom_bar(fill="green")
ag <- p + aes(Age) + geom_bar(fill="tan2")
su <- p + aes(Survived) + geom_bar(fill="red")
grid.arrange(cs, sx, ag, su, nrow=1, widths=c(3, 2, 2, 2))

Party <- c("Fine Gael", "Labour", "Fianna Fail",
           "Sinn Fein", "Indeps", "Green", "Don't know")
nos <- c(181, 51, 171, 119, 91, 4, 368)
IrOP <- data.frame(Party, nos)
IrOP <- within(IrOP, {
               percwith <- nos/sum(nos)
               percnot <- nos/sum(nos[-7])})
par(mfrow=c(2,1), mar = c(2.1, 2.1, 2.1, 2.1))
with(IrOP, pie(percwith, labels=Party, clockwise=TRUE,
               col=c("blue", "red", "darkgreen", "black",
               "grey", "lightgreen", "white"), radius=1))
with(IrOP, pie(percnot[-7], labels=Party, clockwise=TRUE,
               col=c("blue", "red", "darkgreen", "black",
               "grey", "lightgreen"), radius=1))

data("BEPS", package="effects")
a1 <- ggplot(BEPS, aes(factor(Hague))) +
             geom_bar(fill="blue") + ylab("") + 
             xlab("Hague (Conservative)") + ylim(0, 900)
a2 <- ggplot(BEPS, aes(factor(Blair))) +
             geom_bar(fill="red") + ylab("") + 
             xlab("Blair (Labour)") + ylim(0, 900)
a3 <- ggplot(BEPS, aes(factor(Kennedy))) +
             geom_bar(fill="yellow") + ylab("") + 
             xlab("Kennedy (Liberal)") + ylim(0, 900)
grid.arrange(a1, a2, a3, nrow=1)

b1 <- ggplot(BEPS, aes(factor(political.knowledge))) +
             geom_bar(fill="tan2")  + coord_flip() + ylab("") +
             xlab("Knowledge of policies on Europe")
b2 <- ggplot(BEPS, aes(factor(Europe))) +
             geom_bar(fill="lightgreen") + ylab("") + 
             xlab("Attitudes to European integration")
grid.arrange(b1, b2, nrow=1, widths=c(4, 8))

data(survey, package="MASS")
s1 <- ggplot(survey, aes(Sex)) + geom_bar() + ylab("")
s2 <- ggplot(survey, aes(W.Hnd)) + geom_bar() +
            xlab("Writing hand") + ylab("")
s3 <- ggplot(survey, aes(Fold)) + geom_bar() + 
            xlab("Folding arms: arm on top") + ylab("")
s4 <- ggplot(survey, aes(Clap))  + geom_bar() + 
            xlab("Clapping: hand on top") + ylab("")
survey <- within(survey,
                ExerN <- factor(Exer,
                levels=c("None", "Some", "Freq")))
s5 <- ggplot(survey, aes(ExerN))  + geom_bar() +
            xlab("Exercise") +  ylab("")
s6 <- ggplot(survey, aes(M.I))  + geom_bar() +
            xlab("Height units") + ylab("")
survey <- within(survey,
                SmokeN <- factor(Smoke,
                levels=c("Never", "Occas", "Regul", "Heavy")))
s7 <- ggplot(survey, aes(SmokeN))  + geom_bar() + 
            xlab("Smoking") + ylab("")
grid.arrange(s1, s2, s3, s4, s5, s6, s7, ncol=3)

data(VonBort, package="vcd")
ggplot(VonBort, aes(x=factor(deaths))) + geom_bar() +
       xlab("Deaths by horse kick")

data(VonBort, package="vcd")
h1 <- ggplot(VonBort[VonBort$year=="1891", ],
             aes(x=factor(deaths))) + geom_bar()
h2 <- ggplot(VonBort[VonBort$year=="1891", ],
             aes(x=factor(deaths, levels=seq(0, 4)))) +
             geom_bar() + scale_x_discrete(drop=FALSE)
grid.arrange(h1, h2, nrow=1)

data(UKSoccer, package="vcd")
PL <- data.frame(UKSoccer)
lx <- c("0","1","2","3","4 or more")
b1 <- ggplot(PL, aes(x=factor(Home), weight=Freq)) +
             geom_bar(fill="firebrick1") +
             ylab("") + xlab("Home Goals")  +
             scale_x_discrete(labels=lx) +  ylim(0,150)
b2 <- ggplot(PL, aes(x=factor(Away), weight=Freq)) +
             geom_bar(fill="cyan1") +
             ylab("") + xlab("Away Goals")  +
             scale_x_discrete(labels=lx) + ylim(0,150)
grid.arrange(b1, b2, nrow=1)

xx <- 1:9
Ben <- data.frame(xx, pdf=log10(1+1/xx))
ggplot(Ben, aes(factor(xx), weight=pdf)) + geom_bar() +
       xlab("") + ylab("") + ylim(0,0.35)