HomeWork 7

Ulziibat Tserenbat

Using Java

cyl.f <- factor(mtcars$cyl)
gear.f <- factor(mtcars$factor) 
attach(mtcars) 

The following objects are masked from mtcars (pos = 3):

    am, carb, cyl, disp, drat, gear,
    hp, mpg, qsec, vs, wt

ihist(mpg)

ID:2 Name: "Histogram (mpg)"

ibar(carb)

ID:3 Name: "Barchart (carb)"

iplot(mpg, wt)

ID:4 Name: "Scatterplot (wt vs mpg)"

ibox(mtcars[c("qsec","disp","hp")])

ID:5 Name: "Boxplot (qsec)"

ipcp(mtcars[c("mpg","wt","hp")])

ID:6 Name: "Parallel coord. plot (default)"

GGobi

g <- ggobi(iris)
clustering <- hclust(dist(iris[,1:4]),method="average")
glyph_colour(g[1]) <- cutree(clustering, 3)
g <- ggobi(mtcars)
d <- display(g[1],
"Parallel Coordinates Display")
variables(d)

$`X`
 mpg  cyl disp   hp drat   wt qsec   vs   am 
   1    2    3    4    5    6    7    8    9 
gear carb 
  10   11 

$Y
named numeric(0)

$Z
named numeric(0)

variables(d) <- list(X=8:6)
variables(d) <- list(X=8:1)
variables(d)

$`X`
  wt qsec   vs drat   hp disp  cyl  mpg 
   6    7    8    5    4    3    2    1 

$Y
named numeric(0)

$Z
named numeric(0)

df <- data.frame(
x=1:2000,
y=sin(1:2000 * pi/20) + runif(2000, max=0.5)
)
g <- ggobi_longitudinal(df[1:100, ])
df_g <- g[1]
for(i in 1:1901) {
df_g[, 2] <- df[i:(i + 99), 2]
}
ggobi_longitudinal(stormtracks, seasday, id)