4/20exercise

exercise1

## 使用 woman 資料，將第一列資料以點畫上
plot(women, type='n')
points(women[1,])
women[1,]

## 使用 lattice 繪製身高與體重的 xyplot ，選取 women 資料裡第一列的子集資料以點繪製
lattice::xyplot(weight ~ height, 
  data=women,
  subset=row.names(women)==1, type='p')

## 使用 ggplot2 繪製 women 的第一列資料，x 軸為身高， y 軸為體重，使用點圖呈現
library(ggplot2)
ggplot(data=women[1,], aes(height, weight))+
  geom_point()

##

exercise2

## 下載資料，讀取資料
dta<-read.table("/Users/fightk/Desktop/langMathDutch.txt", header=T)
str(dta)

## 'data.frame':    2287 obs. of  6 variables:
##  $ school: int  1 1 1 1 1 1 1 1 1 1 ...
##  $ pupil : int  17001 17002 17003 17004 17005 17006 17007 17008 17009 17010 ...
##  $ IQV   : num  15 14.5 9.5 11 8 9.5 9.5 13 9.5 11 ...
##  $ size  : int  29 29 29 29 29 29 29 29 29 29 ...
##  $ lang  : int  46 45 33 46 20 30 30 57 36 36 ...
##  $ arith : int  24 19 24 26 9 13 13 30 23 22 ...

head(dta)

## 將變量分等級
dta$level<-with(dta, factor(findInterval(size, c(-Inf,
                                                    quantile(size, probs=c(1/3, 2/3)), Inf)), 
                            labels=c("Small","Medium","Large")))
dta$IQ<-with(dta, factor(findInterval(IQV, c(-Inf,
                                                 quantile(IQV, probs=c(1/3, 2/3)), Inf)), 
                            labels=c("Low","Meddle","High")))
## 畫圖
library(ggplot2)
p0<-ggplot(data=dta, aes(lang, arith))+
  labs(x="Language score", y="Arithmetic score")+
  geom_point(shape=18, size=2)+ # change shape
  # add regression line +SE, adjust size and color 
  stat_smooth(data=dta, formula=(y~x), method="lm", se=T, fill="#4D4D4D", colour="darkblue",   size=0.5, alpha = 0.2)+ 
  facet_wrap(.~level+IQ, labeller=labeller(.multi_line=F))+ # make two label at the same line
  scale_x_continuous(breaks=seq(10, 50, 10))+ # adjust the tick label
  scale_y_continuous(breaks=seq(5, 30, 5))
p0