Latihan Visualisasi Data

Input Data

korban <- c(10,12,4,16,8) 
negara <- c("US","UK","Australia","Germany","France")
persen <- round((korban/sum(korban))*100)

data_korban <- data.frame(korban, negara, persen)
data_korban

##   korban    negara persen
## 1     10        US     20
## 2     12        UK     24
## 3      4 Australia      8
## 4     16   Germany     32
## 5      8    France     16

Berdasarkan data di atas, Jerman memiliki persentase korban tertinggi sebesar 32%.Sementara, Australia memiliki persentase korban terendah sebesar 8%.

Visualisasi Pie Chart

label <- paste(negara, persen, "%")
pie(korban,
    labels = label,
    col = rainbow(length(label)),
    main = "Pie Chart Korban Tsunami")

Visualisasi Bar Chart

barplot(korban,
        col = "red",
        main = "Barplot Korban Tsunami",
        names.arg = negara,
        ylab = "Jumlah Korban",
        xlab = "Negara")

Diagram Titik (Dot Plot)

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 Kendaraan per Liter",
         xlab = "Jarak Tempuh (mpg)")

Stem and Leaf Plot

stem(mtcars$mpg, scale = 2)

## 
##   The decimal point is at the |
## 
##   10 | 44
##   12 | 3
##   14 | 3702258
##   16 | 438
##   18 | 17227
##   20 | 00445
##   22 | 88
##   24 | 4
##   26 | 03
##   28 | 
##   30 | 44
##   32 | 49

Histogram

hist(mtcars$mpg,
     breaks = 9,
     main = "Histogram Jarak Tempuh Kendaraan per Liter",
     col = "blue",
     xlab = "Jarak Tempuh (mpg)",
     ylab = "Frekuensi")