ggplot2 Version of Figures in “Lattice: Multivariate Data Visualization with R” (Part 2)

This is the second post in a series attempting to recreate the figures in Lattice: Multivariate Data Visualization with R (R code) with ggplot2.

Chapter 2 – A Technical Overview of lattice

Topics covered:

• The formula interface
• object dimensions and physical layout
• Annotation
• Scales and Axes
• Panel functions

Figure 2.1

> library(lattice) > library(ggplot2) > data(Oats, package = "MEMSS")

lattice

> tp1.oats <- xyplot(yield ~ nitro | Variety + Block, data = Oats, + type = "o") > print(tp1.oats)

ggplot2

> pg.oats <- ggplot(Oats, aes(nitro, yield)) + geom_line() + + geom_point() + facet_wrap(~Block + Variety, ncol = 3) > print(pg.oats)

Figure 2.2

lattice

> print(tp1.oats[, 1])

ggplot2

> pg <- pg.oats %+% subset(Oats, Block == "I") > print(pg)

Figure 2.3

lattice

> pl <- update(tp1.oats, aspect = "xy") > print(pl)

ggplot2

> pg <- pg.oats + opts(panel.margin = unit(0, "lines")) > print(pg)

Note	Currently it is not possible to manipulate the facet aspect ratio. A workaround is to tweak the output image dimensions when saving the output graph to a file.

Note	ggplot2 orders facets in the opposite direction compared to lattice.

Figure 2.4

lattice

> pl <- update(tp1.oats, aspect = "xy", layout = c(0, 18)) > print(pl)

ggplot2

> pg <- pg.oats + facet_wrap(~Block + Variety, ncol = 6) > print(pg)

Figure 2.5

lattice

> pl <- update(tp1.oats, aspect = "xy", layout = c(0, 18), + between = list(x = c(0, 0, 0.5), y = 0.5)) > print(pl)

ggplot2

Grouping of individual facets not possible in ggplot2.

Figure 2.6

lattice

> pl <- dotplot(variety ~ yield | site, barley, layout = c(1, + 6), aspect = c(0.7), groups = year, auto.key = list(space = "right")) > print(pl)

ggplot2

> pg <- ggplot(barley, aes(yield, variety, colour = year)) + + geom_point() + facet_wrap(~site, ncol = 1) > print(pg)

Note	Currently it is not possible to manipulate the facet aspect ratio. A workaround is to tweak the output image dimensions when saving the output graph to a file.

Figure 2.7

lattice

> key.variety <- list(space = "right", text = list(levels(Oats$Variety)), + points = list(pch = 1:3, col = "black")) > pl <- xyplot(yield ~ nitro | Block, Oats, aspect = "xy", + type = "o", groups = Variety, key = key.variety, + lty = 1, pch = 1:3, col.line = "darkgrey", col.symbol = "black", + xlab = "Nitrogen concentration (cwt/acre)", ylab = "Yield (bushels/acre)", + main = "Yield of three varieties of oats", sub = "A 3 x 4 split plot experiment with 6 blocks") > print(pl)

ggplot2

> p <- ggplot(Oats, aes(nitro, yield, group = Variety, + shape = Variety)) > pg <- p + geom_line(colour = "darkgrey") + geom_point() + + facet_grid(~Block) + scale_x_continuous(breaks = seq(0, + 0.6, by = 0.2), labels = seq(0, 0.6, by = 0.2)) + + opts(title = "Yield of three varieties of oats") + + labs(x = "Nitrogen concentration (cwt/acre) \n A 3 x 4 split plot experiment with 6 blocks", + y = "Yield (bushels/acre)") > print(pg)

Note	ggplot2 does not have the subtitle functionality. Nevertheless, very similar result can be achieved by splitting the x-axis label into two rows.

Note	scale_x_continuous() is used to manually set the axis breaks and labels. Otherwise these would be illegible like on Figures 2.3 & 2.4 above.

Figure 2.8

lattice

> pl <- barchart(Class ~ Freq | Sex + Age, data = as.data.frame(Titanic), + groups = Survived, stack = TRUE, layout = c(4, 1), + auto.key = list(title = "Survived", columns = 2)) > print(pl)

ggplot2

> p <- ggplot(as.data.frame(Titanic), aes(Class, Freq, + fill = Survived)) > pg.titanic <- p + geom_bar(stat = "identity") + facet_wrap(~Age + + Sex, nrow = 1) + coord_flip() > print(pg.titanic)

Note	Currently it is not possible to manipulate the facet aspect ratio. A workaround is to tweak the output image dimensions when saving the output graph to a file.

Figure 2.9

lattice

> pl <- barchart(Class ~ Freq | Sex + Age, data = as.data.frame(Titanic), + groups = Survived, stack = TRUE, layout = c(4, 1), + auto.key = list(title = "Survived", columns = 2), + scales = list(x = "free")) > print(pl)

ggplot2

> pg <- pg.titanic + facet_wrap(~Age + Sex, nrow = 1, scales = "free") > print(pg)

Note	Currently it is not possible to manipulate the facet aspect ratio. A workaround is to tweak the output image dimensions when saving the output graph to a file.