R: Generic X-Y Plotting

plot {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")

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