ggplot

1.

library(reshape2);library(ggplot2);library(HH)
dta <- read.table(file="http://www.ccunix.ccu.edu.tw/~psycfs/dataM/Data/stateAnxiety.txt",h=T)
dtafemale <- dta[,1:5]
dtamale <- dta[,6:10]
dtafemale$Sub <- paste("F",rownames(dtafemale))
dtamale$Sub <- paste("M",rownames(dtamale))
dtafemale$Sex <- "F"
dtamale$Sex <- "M"
dtafemaleong <- melt(dtafemale)
dtamaleong <- melt(dtamale)
dtalong <- rbind(dtamaleong,dtafemaleong)
dtalong$Time <- rep(sort(rep(seq(-5,-1,by =1),50)),2)
ggplot(dtalong,aes(x=Time,y=value,group=Sub,col=Sex))+
        geom_line(aes(col=Sex))+
        xlab("week")+
        ylab("anixety")

ggplot(dtalong,aes(x=Time,y=value,col=Sex))+
        geom_point()+
        stat_smooth(method="lm")+
        xlab("week")+
        ylab("anixety")

2.

dta <- read.table(file="http://www.ccunix.ccu.edu.tw/~psycfs/dataM/Data/langMathDutch.txt",h=T)
dta$ClassSize <-cut(dta$size,3)
levels(dta$ClassSize) <- c("Small","Medium","Large")
dta$IQ <-cut(dta$IQV,3)
levels(dta$IQ) <- c("Low","Middle","High")
dta <- dta[order(dta$IQ,dta$ClassSize),]
dta$CUT <- as.factor(paste(dta$ClassSize,dta$IQ,sep=","))
dta$CUT <-factor(dta$CUT,levels(dta$CUT)[c(8,9,7,5,6,4,2,3,1)])
ggplot(dta,aes(x=lang,y=arith))+
        facet_wrap(~CUT)+
        geom_point(shape=18)+
        stat_smooth(method="lm")+
        xlab("Language score")+
        ylab("Arithmetic score")

3.

dta <- read.table(file="http://www.ccunix.ccu.edu.tw/~psycfs/dataM/Data/mathAttainment.txt",h=T)
dtalong <- melt(dta[,-3])
dtalong$variable <- factor(dtalong$variable,levels(dtalong$variable)[c(2,1)]) 
ggplot(data = dtalong, aes(x = variable, y = value, col = variable)) +
        stat_summary(fun.y = mean, geom = "point", size = 2) +
        stat_summary(fun.data = mean_se, geom = "errorbar",
                  linetype = "solid", width = .2) +
        labs(x = "Math", y = "Mean score") +
        theme_bw()+
        scale_colour_brewer(palette="Set1")

5

data(USPersonalExpenditure)
dta <- log(USPersonalExpenditure,base=10)
dtalong <- melt(dta)
dtalong$Var2 <- as.factor(dtalong$Var2)
ggplot(dtalong,aes(value,Var1))+
        geom_point()+
        geom_segment(aes(xend = 0, yend = Var1)) +
        geom_vline(xintercept = 0, colour = "grey50") +
        facet_wrap(~ Var2, nrow = 1)+
        ylab("categories")+
        xlab("Dollar(log10)")

6

dta <- data.frame(Tall=c(18,20,12),Medium=c(28,51,25),Short=c(14,28,9))
rownames(dta) <- c("Tall","Medium","Short")
likert(dta,as.percent=T,main="",ylab="Husband")

8

dta <- read.table("data/hs0.txt",h=T)
ggplot(dta)+
        geom_tile(aes(x = 1, y=math,fill=math))+
        scale_x_continuous(limits=c(0,2),breaks=1)+
        scale_fill_gradient2(low = "blue2", mid = 'white', high = 'green', midpoint=mean(dta$math))+
        theme_minimal()+
        xlab(" ")+
        ylab("Math score")+
        theme(axis.ticks = element_blank(),
              axis.text.x = element_blank(),
              panel.grid.major.x = element_blank(),
              panel.grid.minor.x = element_blank())