dta <- read.table("C:/Users/PARENTCARECHILDREN/Desktop/2020-04-13-Homework-2-Trellis/girlsGrowth.txt", header = T)
colnames(dta) <- c("Weight","Height","Head-butt","Head.circ","Chest.circ","Arm.len","Calf.len","Pelvis.circ","Age","ID")
head(dta)
##   Weight Height Head-butt Head.circ Chest.circ Arm.len Calf.len Pelvis.circ Age
## 1   1456   1025       602       486        520     157      205         170   4
## 2   1426    998       572       501        520     150      215         169   4
## 3   1335    961       560       494        495     145      214         158   4
## 4   1607   1006       595       497        560     178      218         172   4
## 5   1684   1012       584       490        553     165      220         158   4
## 6   1374   1012       580       492        525     158      202         167   4
##   ID
## 1 S1
## 2 S2
## 3 S3
## 4 S4
## 5 S5
## 6 S6

年齡越大，體重、身高越大

library(lattice)
dta$Age <- as.factor(dta$Age)
dta$Weight <- round((dta$Weight/1000),0)

stripplot(Weight ~ Height | Age, groups=ID, data=dta, type=c('g','p'),  xlab="Height", ylab="Weight/1000", auto.key=list(space="top", columns=6),alpha=.8,layout=c(4, 3))

年齡越大，頭圍、身高越大

dta$Head.circ <- round((dta$Head.circ/50),0)
dotplot(Head.circ ~ Height | Age, groups=ID, data=dta, layout=c(3, 4), xlab="Height", ylab="Head.circ/50", auto.key=list(space="top", columns=6))

年齡越大，胸圍越大

bwplot( ~ Chest.circ | Age, data=dta, layout=c(3, 4), xlab="Chest.circ")

年齡越大，身高越高、手臂越長

xyplot(Arm.len ~ Height | Age, data=dta, layout=c(3, 4), xlab="Height", type=c('p', 'g', 'r'))

不同年齡的身高密度長條圖

histogram(~ Height | Age, data=dta, type='density', layout=c(4, 3))

體重&身高的平行座標圖

parallelplot(~ dta[, c("Height", "Weight")] | Age, data=dta,horizontal.axis=T, layout=c(4, 3), par.settings=standard.theme(color=FALSE))

綜合以上，隨著年齡越大．各項素質跟著變大