0 环境与数据准备

#---环境建设---#
rm(list = ls());#清空变量空间
library(datasets)
library(export)

#---数据读入---#
dataname <- "iris"
rawdata <- datasets::iris

1、GGally_ggpairs

#散点图矩阵——Iris(GGally_ggpairs)
library(GGally)
ggpairs(rawdata, columns=1:5, aes(color=Species)) + 
  ggtitle("散点图矩阵——Iris(GGally_ggpairs)")+
  theme_bw() 
graph2png(file = paste("散点图矩阵(GGally_ggpairs) of", dataname))

生成结果：

2、pairs

#散点图矩阵——Iris(pairs)
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(rawdata[1:5], main = "散点图矩阵——Iris(pairs)", pch = 21,
      panel = panel.smooth,
      diag.panel = panel.hist,
      bg = c("#1b9e77", "#d95f02", "#7570b3")[unclass(rawdata$Species)])
graph2png(file = paste("散点图矩阵(pairs) of", dataname))

生成结果： 

3、lattice_splom

#散点图矩阵——Iris(lattice_splom)
library(lattice)
splom(rawdata[1:5], 
      groups=rawdata$Species, 
      main="散点图矩阵——Iris(lattice_splom)")
graph2png(file = paste("散点图矩阵(lattice_splom) of", dataname))

生成结果：

4、WVPlots_PairPlot

#散点图矩阵——Iris(WVPlots_PairPlot)
library(WVPlots) 
PairPlot(rawdata, 
         colnames(rawdata)[1:5], 
         "散点图矩阵——Iris(WVPlots_PairPlot)", 
         group_var = "Species")
graph2png(file = paste("散点图矩阵(WVPlots_PairPlot) of", dataname))

生成结果：

5、YaleToolkit_gpairs

#散点图矩阵——Iris(YaleToolkit_gpairs)
library(YaleToolkit)
library(gpairs)
gpairs(iris, upper.pars = list(scatter = 'stats'),
       scatter.pars = list(pch = 1:3,
                           col = as.numeric(iris$Species)),
       stat.pars = list(verbose = FALSE))
graph2png(file = paste("散点图矩阵(YaleToolkit_gpairs) of", dataname))

致谢：

学习过程中，参考了网络上各位大侠的美文，在此一并表示感谢！