pairs                package:graphics                R Documentation

Scatterplot Matrices

Description:

     A matrix of scatterplots is produced.

Usage:

     pairs(x, ...)

     ## S3 method for class 'formula':
     pairs(formula, data = NULL, ..., subset,
           na.action = stats::na.pass)

     ## Default S3 method:
     pairs(x, labels, panel = points, ...,
           lower.panel = panel, upper.panel = panel,
           diag.panel = NULL, text.panel = textPanel,
           label.pos = 0.5 + has.diag/3,
           cex.labels = NULL, font.labels = 1,
           row1attop = TRUE, gap = 1)

Arguments:

       x: the coordinates of points given as numeric columns of a 
          matrix or dataframe.  Logical and factor columns are
          converted to numeric in the same way that 'data.matrix' does. 

 formula: a formula, such as '~ x + y + z'.  Each term will give a
          separate variable in the pairs plot, so terms should be
          numeric vectors.  (A response will be interpreted as another
          variable, but not treated specially, so it is confusing to
          use one.)

    data: a data.frame (or list) from which the variables in 'formula'
          should be taken.

  subset: an optional vector specifying a subset of observations to be
          used for plotting.

na.action: a function which indicates what should happen when the data
          contain 'NA's.  The default is to pass missing values on to
          the panel functions, but 'na.action = na.omit' will cause
          cases with missing values in any of the variables to be
          omitted entirely.

  labels: the names of the variables.

   panel: 'function(x,y,...)' which is used to plot the contents of
          each panel of the display.

     ...: arguments to be passed to or from methods.

          Also, graphical parameters can be given as can arguments to
          'plot' such as 'main'.  'par("oma")' will be set
          appropriately unless specified. 

lower.panel, upper.panel: separate panel functions to be used below and
          above the diagonal respectively.

diag.panel: optional 'function(x, ...)' to be applied on the diagonals.

text.panel: optional 'function(x, y, labels, cex, font, ...)' to be
          applied on the diagonals.

label.pos: 'y' position of labels in the text panel.

cex.labels, font.labels: graphics parameters for the text panel.

row1attop: logical. Should the layout be matrix-like with row 1 at the
          top, or graph-like with row 1 at the bottom?

     gap: Distance between subplots, in margin lines.

Details:

     The ijth scatterplot contains 'x[,i]' plotted against 'x[,j]'. 
     The scatterplot can be customised by setting panel functions to
     appear as something completely different. The off-diagonal panel
     functions are passed the appropriate columns of 'x' as 'x' and
     'y': the diagonal panel function (if any) is passed a single
     column, and the 'text.panel' function is passed a single '(x, y)'
     location and the column name.

     The graphical parameters 'pch' and 'col' can be used to specify a
     vector of plotting symbols and colors to be used in the plots.

     The graphical parameter 'oma' will be set by 'pairs.default'
     unless supplied as an argument.

     A panel function should not attempt to start a new plot, but just
     plot within a given coordinate system: thus 'plot' and 'boxplot'
     are not panel functions.

     By default, missing values are passed to the panel functions and
     will often be ignored within a panel.  However, for the formula
     method and 'na.action = na.omit', all cases which contain a
     missing values for any of the variables are omitted completely
     (including when the scales are selected).

Author(s):

     Enhancements for R 1.0.0 contributed by Dr. Jens
     Oehlschlaegel-Akiyoshi and R-core members.

References:

     Becker, R. A., Chambers, J. M. and Wilks, A. R. (1988) _The New S
     Language_. Wadsworth & Brooks/Cole.

Examples:

     pairs(iris[1:4], main = "Anderson's Iris Data -- 3 species",
           pch = 21, bg = c("red", "green3", "blue")[unclass(iris$Species)])

     ## formula method
     pairs(~ Fertility + Education + Catholic, data = swiss,
           subset = Education < 20, main = "Swiss data, Education < 20")

     pairs(USJudgeRatings)

     ## put histograms on the diagonal
     panel.hist <- function(x, ...)
     {
         usr <- par("usr"); on.exit(par(usr))
         par(usr = c(usr[1:2], 0, 1.5) )
         h <- hist(x, plot = FALSE)
         breaks <- h$breaks; nB <- length(breaks)
         y <- h$counts; y <- y/max(y)
         rect(breaks[-nB], 0, breaks[-1], y, col="cyan", ...)
     }
     pairs(USJudgeRatings[1:5], panel=panel.smooth,
           cex = 1.5, pch = 24, bg="light blue",
           diag.panel=panel.hist, cex.labels = 2, font.labels=2)

     ## put (absolute) correlations on the upper panels,
     ## with size proportional to the correlations.
     panel.cor <- function(x, y, digits=2, prefix="", cex.cor)
     {
         usr <- par("usr"); on.exit(par(usr))
         par(usr = c(0, 1, 0, 1))
         r <- abs(cor(x, y))
         txt <- format(c(r, 0.123456789), digits=digits)[1]
         txt <- paste(prefix, txt, sep="")
         if(missing(cex.cor)) cex.cor <- 0.8/strwidth(txt)
         text(0.5, 0.5, txt, cex = cex.cor * r)
     }
     pairs(USJudgeRatings, lower.panel=panel.smooth, upper.panel=panel.cor)

