Script for tableplot vignette

tableplot.R

# https://cran.r-project.org/web/packages/tabplot/vignettes/tabplot-vignette.html

require(ggplot2)
data(diamonds)
is.na(diamonds$price) <- diamonds$cut == "Ideal"
is.na(diamonds$cut) <- (runif(nrow(diamonds)) > 0.8)
tableplot(diamonds)
tableplot(diamonds, select = c(carat, price, cut, color, clarity), sortCol = price)
tableplot(diamonds, select = c(carat, price, cut, color, clarity), sortCol = price,
    from = 0, to = 5)
tableplot(diamonds, subset = price < 5000 & cut == "Premium")
tablePalettes()
tableplot(diamonds, pals = list(cut = "Set1(6)", color = "Set5", clarity = rainbow(8)))
diamonds$carat_class <- num2fac(diamonds$carat, n = 20)
diamonds$price_class <- num2fac(diamonds$price, n = 100)
tableplot(diamonds, select = c(carat, price, carat_class, price_class))
# create large dataset
large_diamonds <- diamonds[rep(seq.int(nrow(diamonds)), 10), ]

system.time({
    p <- tablePrepare(large_diamonds)
})
system.time({
    tableplot(p, plot = FALSE)
})

system.time({
    tableplot(p, sortCol = price, nBins = 200, plot = FALSE)
})
Although the first step takes a couple of seconds on a moderate desktop computer, the processing time to create a tableplot from the intermediate result, object p, is very short in comparison to the direct approach:

system.time({
    tableplot(large_diamonds, plot = FALSE)
})

system.time({
    tableplot(large_diamonds, sortCol = price, nBins = 200, plot = FALSE)
})

system.time({
    tableplot(p, sample = TRUE)
})


# calculate normalized carats to be used as sample probabilities
carat.norm <- with(diamonds, carat/max(diamonds$carat))

# draw samples
exp.diamonds <- diamonds[sample(1:nrow(diamonds), size = 10000, prob = carat.norm,
    replace = TRUE), ]
chp.diamonds <- diamonds[sample(1:nrow(diamonds), size = 10000, prob = 1 - carat.norm,
    replace = TRUE), ]

tp1 <- tableplot(exp.diamonds, plot = FALSE)
tp2 <- tableplot(chp.diamonds, plot = FALSE)

plot(tp2 - tp1)


tab <- tableplot(diamonds, plot = FALSE)

summary(tab)
plot(tab)

tableplot(diamonds, select = 1:7, fontsize = 14, legend.lines = 8, title = "Shine on you crazy Diamond",
    fontsize.title = 18)

tab2 <- tableChange(tab, select_string = c("carat", "price", "cut", "color",
        "clarity"), pals = list(cut = "Set1(2)"))
plot(tab2)


tableSave(tab, filename = "diamonds.png", width = 5, height = 3, fontsize = 6,
        legend.lines = 6)