lattice (version 0.17-25)

xyplot: Common Bivariate Trellis Plots

Description

These are the most commonly used high level Trellis functions to plot pairs of variables. By far the most common is xyplot, designed mainly for two continuous variates (though factors can be supplied as well, in which case they will simply be coerced to numeric), which produces Conditional Scatter plots. The others are useful when one of the variates is a factor or a shingle. Most of these arguments are also applicable to other high level functions in the lattice package, but are only documented here.

Usage

xyplot(x, data, ...)
dotplot(x, data, ...)
barchart(x, data, ...)
stripplot(x, data, ...)
bwplot(x, data, ...)
## S3 method for class 'formula':
xyplot(x,
       data,
       allow.multiple = is.null(groups) || outer,
       outer = !is.null(groups),
       auto.key = FALSE,
       aspect = "fill",
       panel = lattice.getOption("panel.xyplot"),
       prepanel = NULL,
       scales = list(),
       strip = TRUE,
       groups = NULL,
       xlab,
       xlim,
       ylab,
       ylim,
       drop.unused.levels = lattice.getOption("drop.unused.levels"),
       ...,
       lattice.options = NULL,
       default.scales,
       subscripts = !is.null(groups),
       subset = TRUE)

## S3 method for class 'formula':
dotplot(x,
        data,
        panel = lattice.getOption("panel.dotplot"),
        ...)
## S3 method for class 'formula':
barchart(x,
         data,
         panel = lattice.getOption("panel.barchart"),
         box.ratio = 2,
         ...)
## S3 method for class 'formula':
stripplot(x,
          data,
          panel = lattice.getOption("panel.stripplot"),
          ...)
## S3 method for class 'formula':
bwplot(x,
       data,
       allow.multiple = is.null(groups) || outer,
       outer = FALSE,
       auto.key = FALSE,
       aspect = "fill",
       panel = lattice.getOption("panel.bwplot"),
       prepanel = NULL,
       scales = list(),
       strip = TRUE,
       groups = NULL,
       xlab,
       xlim,
       ylab,
       ylim,
       box.ratio = 1,
       horizontal = NULL,
       drop.unused.levels = lattice.getOption("drop.unused.levels"),
       ...,
       lattice.options = NULL,
       default.scales,
       subscripts = !is.null(groups),
       subset = TRUE)

Arguments

x

The object on which method dispatch is carried out.

For the "formula" methods, a formula describing the form of conditioning plot. The formula is generally of the form y ~ x | g1 * g2 * ..., indicating that plots o

data

For the formula method, a data frame containing values (or more precisely, anything that is a valid envir argument in eval, e.g. a list or an environment) for any variables in

allow.multiple, outer

logical flags to control what happens with formulas like y1 + y2 ~ x. See the entry for x for details. allow.multiple defaults to TRUE whenever it makes sense, and outer defaul

box.ratio

applicable to bwplot, barchart and stripplot, specifies the ratio of the width of the rectangles to the inter rectangle space.

horizontal

logical, applicable to bwplot, dotplot, barchart and stripplot. Determines which of x and y is to be a factor or shingle (y if TRUE, x otherwise). Defaults to

panel

Once the subset of rows defined by each unique combination of the levels of the grouping variables are obtained (see details), the corresponding x and y variables (or other variables, as appropriate, in the case of ot

aspect

controls physical aspect ratio of the panels (same for all the panels). It can be specified as a ratio (vertical size/horizontal size) or as a character string. Legitimate values are "fill" (the default) which tries to make the

groups

a variable or expression to be evaluated in the data frame specified by data, expected to act as a grouping variable within each panel, typically used to distinguish different groups by varying graphical parameters like color and

auto.key

A logical (indicating whether a key is to be drawn automatically when a grouping variable is present in the plot), or a list of parameters that would be valid arguments to simpleKey (in effect,

prepanel

function that takes the same arguments as the panel function and returns a list, possibly containing components named xlim, ylim, dx and dy (and less frequently, xat

strip

logical flag or function. If FALSE, strips are not drawn. Otherwise, strips are drawn using the strip function, which defaults to strip.default. See documentation of strip.default to see th

xlab

character string or expression (or a "grob") giving label for the x-axis. Defaults to the expression for x in formula. Can be specified as NULL to omit the label altogether. Finer control

ylab

character string or expression (or "grob") giving label for the y-axis. Defaults to the expression for y in formula. Fine control is possible, see entries for main and xlab.

scales

list determining how the x- and y-axes (tick marks and labels) are drawn. The list contains parameters in name=value form, and may also contain two other lists called x and y of the same form (described

subscripts

logical specifying whether or not a vector named subscripts should be passed to the panel function. Defaults to FALSE, unless groups is specified, or if the panel function accepts an argument named

subset

logical or integer indexing vector (can be specified in terms of variables in data). Only these rows of data will be used for the plot. If subscripts is TRUE, the subscripts will provide in

xlim

Normally a numeric vector of length 2 (possibly a DateTime object) giving minimum and maximum for the x-axis, or, a character vector, expected to denote the levels of x. The latter form is interpreted as a range containing c(1, l

ylim

similar to xlim, applied to the y-axis.

drop.unused.levels

logical indicating whether the unused levels of factors will be dropped, usually relevant with a subsetting operation is performed or an interaction is created. Unused levels are usually dr

default.scales

list giving the default values of scales for a particular high level function. This should not be of any interest to the normal user, but may be helpful when defining other functions that act as a wrapper to one of the high level

lattice.options

a list that could be supplied to lattice.options. These options are temporarily in effect for the duration of the call, after which the settings revert back to whatever they were before.

...

further arguments, usually not directly processed by the high level functions documented here, but rather passed on to other functions. Such arguments can be broadly categorized into two types: those that affect all high level Trellis function

Value

• An object of class "trellis". The update method can be used to update components of the object and the print method (usually called by default) will plot it on an appropriate plotting device.

Details

All the functions documented here are generic, with the formula method usually doing the actual work. The structure of the plot that is produced is mostly controlled by the formula. For each unique combination of the levels of the conditioning variables g1, g2, ..., a separate panel is produced using the points (x,y) for the subset of the data (also called packet) defined by that combination. The display can be though of as a 3-dimensional array of panels, consisting of one 2-dimensional matrix per page. The dimensions of this array are determined by the layout argument. If there are no conditioning variables, the plot produced consists of a single panel.

The coordinate system used by lattice by default is like a graph, with the origin at the bottom left, with axes increasing to left and up. In particular, panels are by default drawn starting from the bottom left corner, going right and then up; unless as.table = TRUE, in which case panels are drawn from the top left corner, going right and then down. One might wish to set a global preference for a table-like arrangement by changing the default to as.table=TRUE; this can be done by setting lattice.options(default.args = list(as.table = TRUE)). In fact, default values can be set in this manner for the following arguments: as.table, aspect, between, page, main, sub, par.strip.text, layout, skip and strip. Note that these global defaults are sometimes overridden by individual functions.

The order of the panels depends on the order in which the conditioning variables are specified, with g1 varying fastest. Within a conditioning variable, the order depends on the order of the levels (which for factors is usually in alphabetical order). Both of these orders can be modified using the index.cond and perm.cond arguments, possibly using the update (and other related) method(s).

References

Sarkar, Deepayan (2008) "Lattice: Multivariate Data Visualization with R", Springer. http://lmdvr.r-forge.r-project.org/

See Also

Lattice for an overview of the package, as well as barchart.table, Lattice, print.trellis, shingle, banking, reshape, panel.xyplot, panel.bwplot, panel.barchart, panel.dotplot, panel.stripplot, panel.superpose, panel.loess, panel.linejoin, strip.default, simpleKey trellis.par.set

Examples

## wait for user input before each new page (like 'par(ask = TRUE)')
old.prompt <- grid::grid.prompt(TRUE)

require(stats)

## Tonga Trench Earthquakes

Depth <- equal.count(quakes$depth, number=8, overlap=.1)
xyplot(lat ~ long | Depth, data = quakes)
update(trellis.last.object(),
       strip = strip.custom(strip.names = TRUE, strip.levels = TRUE),
       par.strip.text = list(cex = 0.75),
       aspect = "iso")

## Examples with data from `Visualizing Data' (Cleveland)
## (obtained from Bill Cleveland's Homepage :
## http://cm.bell-labs.com/cm/ms/departments/sia/wsc/, also
## available at statlib)

EE <- equal.count(ethanol$E, number=9, overlap=1/4)
## Constructing panel functions on the fly; prepanel
xyplot(NOx ~ C | EE, data = ethanol,
       prepanel = function(x, y) prepanel.loess(x, y, span = 1),
       xlab = "Compression Ratio", ylab = "NOx (micrograms/J)",
       panel = function(x, y) {
           panel.grid(h=-1, v= 2)
           panel.xyplot(x, y)
           panel.loess(x,y, span=1)
       },
       aspect = "xy")



## with and without banking

plot <- xyplot(sunspot.year ~ 1700:1988, xlab = "", type = "l",
               scales = list(x = list(alternating = 2)),
               main = "Yearly Sunspots")
print(plot, position = c(0, .3, 1, .9), more = TRUE)
print(update(plot, aspect = "xy", main = "", xlab = "Year"),
      position = c(0, 0, 1, .3))




## Multiple variables in formula for grouped displays

xyplot(Sepal.Length + Sepal.Width ~ Petal.Length + Petal.Width | Species, 
       data = iris, scales = "free", layout = c(2, 2),
       auto.key = list(x = .6, y = .7, corner = c(0, 0)))


## user defined panel functions

states <- data.frame(state.x77,
                     state.name = dimnames(state.x77)[[1]], 
                     state.region = state.region) 
xyplot(Murder ~ Population | state.region, data = states, 
       groups = state.name, 
       panel = function(x, y, subscripts, groups)  
       ltext(x = x, y = y, labels = groups[subscripts], cex=1,
             fontfamily = "HersheySans"))

barchart(yield ~ variety | site, data = barley,
         groups = year, layout = c(1,6),
         ylab = "Barley Yield (bushels/acre)",
         scales = list(x = list(abbreviate = TRUE,
                       minlength = 5)))
barchart(yield ~ variety | site, data = barley,
         groups = year, layout = c(1,6), stack = TRUE, 
         auto.key = list(points = FALSE, rectangles = TRUE, space = "right"),
         ylab = "Barley Yield (bushels/acre)",
         scales = list(x = list(rot = 45)))

bwplot(voice.part ~ height, data=singer, xlab="Height (inches)")
dotplot(variety ~ yield | year * site, data=barley)

dotplot(variety ~ yield | site, data = barley, groups = year,
        key = simpleKey(levels(barley$year), space = "right"),
        xlab = "Barley Yield (bushels/acre) ",
        aspect=0.5, layout = c(1,6), ylab=NULL)

stripplot(voice.part ~ jitter(height), data = singer, aspect = 1,
          jitter.data = TRUE, xlab = "Height (inches)")
## Interaction Plot

xyplot(decrease ~ treatment, OrchardSprays, groups = rowpos,
       type = "a",
       auto.key =
       list(space = "right", points = FALSE, lines = TRUE))

## longer version with no x-ticks

bwplot(decrease ~ treatment, OrchardSprays, groups = rowpos,
       panel = "panel.superpose",
       panel.groups = "panel.linejoin",
       xlab = "treatment",
       key = list(lines = Rows(trellis.par.get("superpose.line"),
                  c(1:7, 1)), 
                  text = list(lab = as.character(unique(OrchardSprays$rowpos))),
                  columns = 4, title = "Row position"))

grid::grid.prompt(old.prompt)