R语言实战：中级绘图

plot(
  mtcars$wt, mtcars$mpg,
  main="Basic Scatter plot of MPG vs. Weight",
  xlab="Car Weight (lbs/1000)",
  ylab="Miles Per Gallon", 
  pch=19
)

abline(
  lm(mpg~wt, data=mtcars),
  col="red",
  lwd=2,
  lty=1
)

lines(
  lowess(mtcars$wt, mtcars$mpg),
  col="blue",
  lwd=2,
  lty=2
)

library(car)

scatterplot(
  mpg ~ wt | cyl,
  data=mtcars,
  lwd=2,
  smooth=list(span=0.75),
  main="Scatter Plot of MPG vs. Weight by # Cylinders",
  xlab="Weight of Car (lbs/1000)",
  ylab="Miles Per Gallon",
  legend=TRUE,
  boxplots="xy"
)

pairs(
  ~ mpg + disp + drat + wt,
  data=mtcars,
  main="Basic Scatter Plot Matrix"
)

scatterplotMatrix(
  ~ mpg + disp + drat + wt,
  data=mtcars,
  smooth=list(
    smoother=loessLine, 
    lty.smooth=2, 
    spread=FALSE
  ),
  main="Scatter Plot Matrix via car Package"
)

library(HH)

xysplom(
  mpg ~ disp + drat + wt,
  data=mtcars,
  corr=TRUE
)

set.seed(1234)
n <- 10000
c1 <- matrix(
  rnorm(n, mean=0, sd=.5),
  ncol=2
)
c2 <- matrix(
  rnorm(n, mean=3, sd=2),
  ncol=2
)
my_data <- rbind(c1, c2)
my_data <- as.data.frame(my_data)
names(my_data) <- c("x", "y")
head(my_data)

with(
  my_data,
  plot(
    x, y,
    pch=19,
    main="Scatter Plot with 10,000 Observations"
  )
)

with(
  my_data,
  smoothScatter(
    x, y,
    main="Scatter Plot Colored by Smoothed Densities"
  )
)

library(hexbin)

with(
  my_data,
  {
    bin <- hexbin(
      x, y,
      xbins=50
    )
    plot(
      bin,
      main="Hexagonal Binning with 10,000 Observations",
    )
  }
)

library(IDPmisc)

ipairs(my_data, pixs=1)

library(scatterplot3d)

attach(mtcars)
scatterplot3d(
  wt, disp, mpg,
  main="Basic 3D Scatter Plot"
)
detach(mtcars)

with(
  mtcars,
  scatterplot3d(
    wt, disp, mpg,
    pch=16,
    highlight.3d=TRUE,
    type="h",
    main="3D Scatter Plot with Verical Lines"
  )
)

with(
  mtcars,
  {
    s3d <- scatterplot3d(
      wt, disp, mpg,
      pch=16,
      highlight.3d=TRUE,
      type="h",
      main="3D Scatter Plot with Vertical LInes and Regression Plane"
    )
    fit <- lm(mpg ~ wt + disp)
    s3d$plane3d(fit)
  }
)

library(rgl)

with(
  mtcars,
  plot3d(
    wt, disp, mpg,
    col="red",
    size=5
  )
)

with(
  mtcars,
  scatter3d(
    wt, disp, mpg
  )
)

with(
  mtcars,
  {
    r <- sqrt(disp/pi)
    symbols(
      wt, mpg, 
      circle=r,
      inches=0.30,
      fg="white",
      bg="lightblue",
      main="Bubble Plot with point size proportional to displacement",
      ylab="Miles Per Gallon",
      xlab="Weight of Car (lbs/1000)"
    )
    text(
      wt, mpg,
      rownames(mtcars),
      cex=0.6
    )
  }
)

tail(Orange)

t1 <- subset(
  Orange,
  Tree==1
)
tail(t1)

opar <- par(no.readonly=TRUE)
par(mfrow=c(1, 2))

plot(
  t1$age, t1$circumference,
  xlab="Age (days)",
  ylab="Circumference (mm)",
  main="Orange Tree 1 Growth"
)

plot(
  t1$age, t1$circumference,
  xlab="Age (days)",
  ylab="Circumference (mm)",
  main="Orange Tree 1 Growth",
  type="b"
)

par(opar)

x <- y <- 1:5
opar <- par(no.readonly=TRUE)
par(mfrow=c(2, 4))

type_list <- c(
  "p",
  "l",
  "o",
  "b",
  "c",
  "s",
  "S",
  "h"
)

for (t in type_list) {
  plot(
    x, y,
    type=t,
    xlab="x",
    ylab="y",
    main=paste("type=\"", t, "\"", sep="")
  )
}

par(opar)

Orange$Tree <- as.numeric(Orange$Tree)
ntrees <- max(Orange$Tree)
xrange <- range(Orange$age)
yrange <- range(Orange$circumference)

colors <- rainbow(ntrees)
line_type <- c(1:ntrees)
plot_char <- seq(18, 18+ntrees, 1)

plot(
  xrange, yrange,
  type="n",
  xlab="Age (days)",
  ylab="Circumference (mm)"
)

for (i in 1:ntrees) {
  tree <- subset(Orange, Tree==i)
  lines(
    tree$age, tree$circumference,
    type="b",
    lwd=2,
    lty=line_type[i],
    col=colors[i],
    pch=plot_char[i]
  )
}

title(
  "Tree Growth",
  "example of line plot"
)

legend(
  xrange[1], yrange[2],
  1:ntrees,
  cex=0.8,
  col=colors,
  pch=plot_char,
  lty=line_type,
  title="Tree"
)

options(digits=2)
cor(mtcars)

library(corrgram)

corrgram(
  mtcars,
  order=TRUE,
  lower.panel=panel.shade,
  upper.panel=panel.pie,
  text.panel=panel.txt,
  main="Corrgram of mtcars intercorrlations"
)

corrgram(
  mtcars,
  order=TRUE,
  lower.panel=panel.ellipse,
  upper.panel=panel.pts,
  text.panel=panel.txt,
  main="Corrgram of mtcars intercorrlations"
)

corrgram(
  mtcars,
  order=TRUE,
  lower.panel=panel.shade,
  upper.panel=NULL,
  text.panel=panel.txt,
  main="Corrgram of mtcars intercorrlations"
)

cols <- colorRampPalette(
  c(
    "darkgoldenrod4",
    "burlywood1",
    "darkkhaki",
    "darkgreen"
  )
)
corrgram(
  mtcars,
  order=TRUE,
  col.regions=cols,
  lower.panel=panel.shade,
  upper.panel=panel.conf,
  text.panel=panel.txt,
  main="A Corrgram (or Horse) of a Different Color"
)

ftable(Titanic)

library(vcd)

mosaic(
  Titanic,
  shade=TRUE,
  legend=TRUE
)

mosaic(
  ~ Class + Survived,
  data=Titanic,
  shade=TRUE,
  legend=TRUE
)