plot                  package:base                  R Documentation

Generic X-Y Plotting

Description:

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

Usage:

     plot(x, y, xlim=range(x), ylim=range(y), type="p",
          main, xlab, ylab, ...)

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.

xlim, ylim: the ranges to be encompassed by the x and y axes.

    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 `type's give a warning or an error; using, e.g.,
          `type = "punkte"' being equivalent to `type = "p"' for S
          compatibility. 

    main: an overall title for the plot.

    xlab: a title for the x axis.

    ylab: a title for the y axis.

     ...: graphical parameters can be given as arguments to `plot'.

Details:

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

     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'.

Examples:

     data(cars)
     plot(cars)
     lines(lowess(cars))

     plot(sin, -pi, 2*pi)

     ## 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(stepfun)} for a better one:
     plot(x <- sort(rnorm(47)), type = "s", main = "plot(x, type = \"s\")")
     points(x, cex = .5, col = "dark red")

