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 `function`s, `data.frame`s, `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 `type`s 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 3.4.3 Index]