visualisasi data

korban<-c(10,12,4,16,8)
negara<-c("us","uk","australia","germany","france")
persen<-round((korban/sum(korban))*100)
data.frame(korban,negara,persen)

##   korban    negara persen
## 1     10        us     20
## 2     12        uk     24
## 3      4 australia      8
## 4     16   germany     32
## 5      8    france     16

tabel<-paste(negara,persen,"%")
pie(korban,labels=tabel,col=rainbow(length(tabel)),main="pie chart korban tsunami")

tabel<-paste(negara,persen,"%")
barplot(korban,col=rainbow(length(tabel)),main="bar chart korban tsunami")

tabel<-paste(negara,persen,"%")
dotchart(korban,col=rainbow(length(tabel)),main="dot chart korban tsunami")

data("mtcars")
head(mtcars)

##                    mpg cyl disp  hp drat    wt  qsec vs am gear carb
## Mazda RX4         21.0   6  160 110 3.90 2.620 16.46  0  1    4    4
## Mazda RX4 Wag     21.0   6  160 110 3.90 2.875 17.02  0  1    4    4
## Datsun 710        22.8   4  108  93 3.85 2.320 18.61  1  1    4    1
## Hornet 4 Drive    21.4   6  258 110 3.08 3.215 19.44  1  0    3    1
## Hornet Sportabout 18.7   8  360 175 3.15 3.440 17.02  0  0    3    2
## Valiant           18.1   6  225 105 2.76 3.460 20.22  1  0    3    1

dotchart(mtcars$mpg,cex=0.7,main="jarak tempuh per liter", xlab="jarak tempuh (km) per liter")

hist(mtcars$mpg,breaks=9, main="histogram jarak tempuh kendaraan per liter",col="blue",xlab="jarak tempuh per liter")