图的顺序:

> x <- 1:12
> y <- 100:111
> z <- 300:311
> x[1]  1  2  3  4  5  6  7  8  9 10 11 12
> y[1] 100 101 102 103 104 105 106 107 108 109 110 111
> z[1] 300 301 302 303 304 305 306 307 308 309 310 311
> coplot(y ~ x | z)

> mtcars$wt[1] 2.620 2.875 2.320 3.215 3.440 3.460 3.570 3.190 3.150 3.440 3.440 4.070
[13] 3.730 3.780 5.250 5.424 5.345 2.200 1.615 1.835 2.465 3.520 3.435 3.840
[25] 3.845 1.935 2.140 1.513 3.170 2.770 3.570 2.780
> mtcars$mpg[1] 21.0 21.0 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 17.8 16.4 17.3 15.2 10.4
[16] 10.4 14.7 32.4 30.4 33.9 21.5 15.5 15.2 13.3 19.2 27.3 26.0 30.4 15.8 19.7
[31] 15.0 21.4
> as.factor(mtcars$cyl)[1] 6 6 4 6 8 6 8 4 4 6 6 8 8 8 8 8 8 4 4 4 4 8 8 8 8 4 4 4 8 6 8 4
Levels: 4 6 8coplot(mtcars$wt ~ mtcars$mpg | as.factor(mtcars$cyl), main="", xlab="", ylab="", pch=19)

> as.factor(mtcars$vs)[1] 0 0 1 1 0 1 0 1 1 1 1 0 0 0 0 0 0 1 1 1 1 0 0 0 0 1 0 1 0 0 0 1
Levels: 0 1coplot(mtcars$wt ~ mtcars$mpg | as.factor(mtcars$cyl) * as.factor(mtcars$vs), main="", xlab="", ylab="", pch=19)

coplot                package:graphics                 R DocumentationConditioning PlotsDescription:This function produces two variants of the *co*nditioning plotsdiscussed in the reference below.Usage:coplot(formula, data, given.values, panel = points, rows, columns,show.given = TRUE, col = par("fg"), pch = par("pch"),bar.bg = c(num = gray(0.8), fac = gray(0.95)),xlab = c(x.name, paste("Given :", a.name)),ylab = c(y.name, paste("Given :", b.name)),subscripts = FALSE,axlabels = function(f) abbreviate(levels(f)),number = 6, overlap = 0.5, xlim, ylim, ...)co.intervals(x, number = 6, overlap = 0.5)Arguments:formula: a formula describing the form of conditioning plot.  Aformula of the form ‘y ~ x | a’ indicates that plots of ‘y’versus ‘x’ should be produced conditional on the variable‘a’.  A formula of the form ‘y ~ x| a * b’ indicates thatplots of ‘y’ versus ‘x’ should be produced conditional on thetwo variables ‘a’ and ‘b’.All three or four variables may be either numeric or factors.When ‘x’ or ‘y’ are factors, the result is almost as if‘as.numeric()’ was applied, whereas for factor ‘a’ or ‘b’,the conditioning (and its graphics if ‘show.given’ is true)are adapted.data: a data frame containing values for any variables in theformula.  By default the environment where ‘coplot’ wascalled from is used.given.values: a value or list of two values which determine how theconditioning on ‘a’ and ‘b’ is to take place.When there is no ‘b’ (i.e., conditioning only on ‘a’),usually this is a matrix with two columns each row of whichgives an interval, to be conditioned on, but is can also be asingle vector of numbers or a set of factor levels (if thevariable being conditioned on is a factor). In this case (no‘b’), the result of ‘co.intervals’ can be used directly as‘given.values’ argument.panel: a ‘function(x, y, col, pch, ...)’ which gives the action tobe carried out in each panel of the display.  The default is‘points’.rows: the panels of the plot are laid out in a ‘rows’ by ‘columns’array.  ‘rows’ gives the number of rows in the array.columns: the number of columns in the panel layout array.show.given: logical (possibly of length 2 for 2 conditioningvariables): should conditioning plots be shown for thecorresponding conditioning variables (default ‘TRUE’).col: a vector of colors to be used to plot the points.  If tooshort, the values are recycled.pch: a vector of plotting symbols or characters.  If too short,the values are recycled.bar.bg: a named vector with components ‘"num"’ and ‘"fac"’ giving thebackground colors for the (shingle) bars, for *num*eric and*fac*tor conditioning variables respectively.xlab: character; labels to use for the x axis and the firstconditioning variable.  If only one label is given, it isused for the x axis and the default label is used for theconditioning variable.ylab: character; labels to use for the y axis and any secondconditioning variable.subscripts: logical: if true the panel function is given an additional(third) argument ‘subscripts’ giving the subscripts of thedata passed to that panel.axlabels: function for creating axis (tick) labels when x or y arefactors.number: integer; the number of conditioning intervals, for a and b,possibly of length 2.  It is only used if the correspondingconditioning variable is not a ‘factor’.overlap: numeric < 1; the fraction of overlap of the conditioningvariables, possibly of length 2 for x and y direction.  Whenoverlap < 0, there will be _gaps_ between the data slices.xlim: the range for the x axis.ylim: the range for the y axis....: additional arguments to the panel function.x: a numeric vector.Details:In the case of a single conditioning variable ‘a’, when both‘rows’ and ‘columns’ are unspecified, a ‘close to square’ layoutis chosen with ‘columns >= rows’.In the case of multiple ‘rows’, the _order_ of the panel plots isfrom the bottom and from the left (corresponding to increasing‘a’, typically).A panel function should not attempt to start a new plot, but justplot within a given coordinate system: thus ‘plot’ and ‘boxplot’are not panel functions.The rendering of arguments ‘xlab’ and ‘ylab’ is not controlled by‘par’ arguments ‘cex.lab’ and ‘font.lab’ even though they areplotted by ‘mtext’ rather than ‘title’.Value:‘co.intervals(., number, .)’ returns a (‘number’ x 2) ‘matrix’,say ‘ci’, where ‘ci[k,]’ is the ‘range’ of ‘x’ values for the‘k’-th interval.References:Chambers, J. M. (1992) _Data for models._ Chapter 3 of_Statistical Models in S_ eds J. M. Chambers and T. J. Hastie,Wadsworth & Brooks/Cole.Cleveland, W. S. (1993) _Visualizing Data._ New Jersey: SummitPress.See Also:‘pairs’, ‘panel.smooth’, ‘points’.Examples:## Tonga Trench Earthquakescoplot(lat ~ long | depth, data = quakes)given.depth <- co.intervals(quakes$depth, number = 4, overlap = .1)coplot(lat ~ long | depth, data = quakes, given.v = given.depth, rows = 1)## Conditioning on 2 variables:ll.dm <- lat ~ long | depth * magcoplot(ll.dm, data = quakes)coplot(ll.dm, data = quakes, number = c(4, 7), show.given = c(TRUE, FALSE))coplot(ll.dm, data = quakes, number = c(3, 7),overlap = c(-.5, .1)) # negative overlap DROPS values## given two factorsIndex <- seq(length = nrow(warpbreaks)) # to get nicer default labelscoplot(breaks ~ Index | wool * tension, data = warpbreaks,show.given = 0:1)coplot(breaks ~ Index | wool * tension, data = warpbreaks,col = "red", bg = "pink", pch = 21,bar.bg = c(fac = "light blue"))## Example with empty panels:with(data.frame(state.x77), {coplot(Life.Exp ~ Income | Illiteracy * state.region, number = 3,panel = function(x, y, ...) panel.smooth(x, y, span = .8, ...))## y ~ factor -- not really sensible, but 'show off':coplot(Life.Exp ~ state.region | Income * state.division,panel = panel.smooth)})