- A histogram can be made by typing:
> x <- rnorm(1000) > hist(x)

- Scatter plot can be made by
> x <- 0:10 > y <- log(x) > plot(x,y)

You can add a straight line of y = a + b x by abline(a, b).

> abline(0.5, 0.2) # y-intercept = 0.5, slope = 0.2

You can add more points by:

> points (x, x * 0.2, pch=4) # pch is points "character", i.e., symbol to use

You can connect the points by lines:

> lines (x, y) > lines (x, x * 0.2, lty = 2) # lty is line type

You can see the pre-set points characters:

> example(points)

- To save this plot to a postscript file called, graph1.ps, type
> dev.print(postscript,file="graph1.ps") > dev.print(pdf,file="graph1.pdf") # to make pdf

The file, graph1.ps, is saved in the directory in which R is invoked. Other graphical devices (i.e. pdf, jpeg, xfig, etc.) can be specified. To see other graphical devices, see

`help(Devices)`

. - A matrix of scatterplots

`pairs(X)`

produces a pairwise scatterplot matrix of the variables defined by the columns of X. Every column of X is plotted against every other column of X.> iris[1:5,] # Anderson's iris data set > pairs(iris[1:4], main = "Anderson's Iris Data -- 3 species", + pch = 21, bg = c("red", "green3", "blue")[unclass(iris$Species)]) > help(iris) > help(pairs) # Try the examples.

- multiple plots per page
> par(mfrow = c(2,2)) > for (i in 1:4) { hist(iris[,i], xlab=names(iris)[i], main=i)} > par(mfrow=c(1,1)) # setting the parameter back to the default

`par(mfcol=c(2,2))`

is similar, but figures are filled by*column*. - Bar plots:
> VADeaths # death rates per 1000 in Virginian in 1940 > tVADeaths <- t(VADeaths)[,5:1] # transpose, and change order of columns > mp <- barplot(tVADeaths, beside=T, legend=colnames(VADeaths), ylim=c(0,130)) > fakeSE <- 2 * sqrt (1000 * tVADeaths/100) # making a fake error bar > mp # contains x-coordinates > segments (mp, tVADeaths, mp, tVADeaths+fakeSE, lwd=1.5)

You can easily make a customized ``wrapper'' function to do all of this if you repeatedly use the same plotting procedure. - Advanced graphics:

See R Graph Gallery for more advanced graphics. The web page contains the example codes to produce the fancy figures, so you can learn through immitation.