R Graphics

Base Graphics

x <- seq(0, 2*pi, length.out = 20)
y <- sin(x)
plot(x, y, type="l", col="darkblue",
    main="Sine Curve", sub="Copyright (c) 2016 HwB")
points(x, y, col="blue", pch=20)
lines(c(0,2*pi), c(-1,1), lty=2)
grid()
abline(h=0); abline(v=0)

?plot

plot {graphics}

R Documentation

Generic X-Y Plotting

Description

Generic function for plotting of R objects. For more details about the graphical parameter arguments, see par.

For simple scatter plots, plot.default will be used. However, there are plot methods for many R objects, including functions, data.frames, density objects, etc. Use methods(plot) and the documentation for these.

Usage

plot(x, y, ...)

Arguments

x	the coordinates of points in the plot. Alternatively, a single plotting structure, function or any R object with a plot method can be provided.
y	the y coordinates of points in the plot, optional if x is an appropriate structure.
...	Arguments to be passed to methods, such as graphical parameters (see par). Many methods will accept the following arguments: type what type of plot should be drawn. Possible types are "p" for points, "l" for lines, "b" for both, "c" for the lines part alone of "b", "o" for both ‘overplotted’, "h" for ‘histogram’ like (or ‘high-density’) vertical lines, "s" for stair steps, "S" for other steps, see ‘Details’ below, "n" for no plotting. All other types give a warning or an error; using, e.g., type = "punkte" being equivalent to type = "p" for S compatibility. Note that some methods, e.g. plot.factor, do not accept this. main an overall title for the plot: see title. sub a sub title for the plot: see title. xlab a title for the x axis: see title. ylab a title for the y axis: see title. asp the y/x aspect ratio, see plot.window.

Details

The two step types differ in their x-y preference: Going from (x1,y1) to (x2,y2) with x1 < x2, type = "s" moves first horizontal, then vertical, whereas type = "S" moves the other way around.

See Also

plot.default, plot.formula and other methods; points, lines, par. For thousands of points, consider using smoothScatter() instead of plot().

For X-Y-Z plotting see contour, persp and image.

Examples

require(stats) # for lowess, rpois, rnorm
plot(cars)
lines(lowess(cars))

plot(sin, -pi, 2*pi) # see ?plot.function

## Discrete Distribution Plot:
plot(table(rpois(100, 5)), type = "h", col = "red", lwd = 10,
     main = "rpois(100, lambda = 5)")

## Simple quantiles/ECDF, see ecdf() {library(stats)} for a better one:
plot(x <- sort(rnorm(47)), type = "s", main = "plot(x, type = \"s\")")
points(x, cex = .5, col = "dark red")

---

[Package graphics version 3.2.3 ]

Statistical Graphs

worms <- read.table("../data/worms.txt", header=TRUE)  # loads dataframe 'mtcars'
head(worms)

	Field.Name	Area	Slope	Vegetation	Soil.pH	Damp	Worm.density
1	Nashs.Field	3.6	11	Grassland	4.1	FALSE	4
2	Silwood.Bottom	5.1	2	Arable	5.2	FALSE	7
3	Nursery.Field	2.8	3	Grassland	4.3	FALSE	2
4	Rush.Meadow	2.4	5	Meadow	4.9	TRUE	5
5	Gunness.Thicket	3.8	0	Scrub	4.2	FALSE	6
6	Oak.Mead	3.1	2	Grassland	3.9	FALSE	2

plot(worms)  # scatterplot matrix

# attach(worms)
with(worms, plot(Area, Slope))
grid()

hist(worms$Soil.pH, breaks=10)
lines(density(worms$Soil.pH), col="red")

plot(worms$Vegetation, worms$Worm.density)

ggplot2 -- Grammar of Graphics

library(ggplot2)

qplot(worms$Area, worms$Slope)

data(mtcars)  # loads dataframe 'mtcars'
str(mtcars)

'data.frame':	32 obs. of  11 variables:
 $ mpg : num  21 21 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 ...
 $ cyl : num  6 6 4 6 8 6 8 4 4 6 ...
 $ disp: num  160 160 108 258 360 ...
 $ hp  : num  110 110 93 110 175 105 245 62 95 123 ...
 $ drat: num  3.9 3.9 3.85 3.08 3.15 2.76 3.21 3.69 3.92 3.92 ...
 $ wt  : num  2.62 2.88 2.32 3.21 3.44 ...
 $ qsec: num  16.5 17 18.6 19.4 17 ...
 $ vs  : num  0 0 1 1 0 1 0 1 1 1 ...
 $ am  : num  1 1 1 0 0 0 0 0 0 0 ...
 $ gear: num  4 4 4 3 3 3 3 4 4 4 ...
 $ carb: num  4 4 1 1 2 1 4 2 2 4 ...

plt <- ggplot(mtcars)

plt + geom_point(aes(x=disp, y=mpg, shape=factor(gear), color=cyl)) +
      theme_bw()

ozdata = read.table("../data/ozone.csv", header=TRUE, sep=",")
with(ozdata,
     coplot(Ozone ~ Wind|Temp, panel=panel.smooth)
)

 Missing rows: 5, 10, 25, 26, 27, 32, 33, 34, 35, 36, 37, 39, 42, 43, 45, 46, 52, 53, 54, 55, 56, 57, 58, 59, 60, 61, 65, 72, 75, 83, 84, 102, 103, 107, 115, 119, 150 

lattice -- Trellis Graphics

library(lattice)
    xyplot(mpg ~ disp | factor(gear), data=mtcars, layout=c(3,1))

bwplot(Worm.density ~ Soil.pH + Area | Vegetation, data=worms)

Saving Plots

x <- seq(1, 10, by=0.5)
y <- log(x) + 0.5*(runif(length(x))-0.5)
pdf("SplineInterp.pdf")
plot(x, y, col="navy", pch=20,
     main="Spline Interpolation")
lines(spline(x, y), col="red", lwd=2)
grid()
dev.off()

pdf: 2

?pdf