作者：李誉辉

四川大学在读研究生

接上一篇：GGally与pairs相关关系图_史上最全（一）

2.4

 wrap()封装

其它需要指定到geom_xxx()中的参数，可以通过wrap()传递给lower,upper, 或diag。

语法：

1wrap(funcVal, ..., funcArgName = deparse(substitute(funcVal)))2wrapp(funcVal, params = NULL, funcArgName = deparse(substitute(funcVal)))

解释：

• wrap()为参数传递，wrapp()为列表传递。

• funcVal, 表示需要见参数传递给什么类型的对象，
  如ggally_points或"points"则将参数传递给散点图；
  ggally_facetdensity或"facetdensity"则将参数传递给分面密度图。

• ..., params，表示要传递的参数，都是geom_xxx()中的参数，
  如alpha, size, binwidth。

 1library(GGally) 2library(ggplot2) 3diamonds.samp <- diamonds[sample(1:dim(diamonds)[1], 1000), ] 4 5# 下面是plots超过15个，为16个，所以默认产生进度条 6ggpairs( 7  diamonds.samp[, c(1:2,5,7)], 8  mapping = aes(color = cut), 9  diag = list(10    continuous = wrap("densityDiag",alpha = 0.5)), # 给对角线的密度图增加透明度参数11  title = "wrap()传递透明度参数给对角线上的密度图"12)13

 1require(GGally) 2data(tips, package="reshape") 3g1 <-  4  ggpairs(data = tips, mapping = aes(colour = sex), 5    lower = list( 6      continuous = wrap(ggally_points, alpha = 0.5), # 增加透明度参数 7      combo = wrap("facethist", binwidth = 0.5) # 增加柱子宽度参数 8      ),  9    diag = list(10      continuous = wrap(ggally_densityDiag, alpha = 0.5) # 增加透明度参数11    ),12    title="下三角散点图增加透明度，直方图设置宽度，对角线面积图增加透明度"13  )14g115

 1wrap_1 <- wrap(ggally_points, size = 5, color = "magenta", alpha = 0.3) 2wrap_2 <- wrap(ggally_densityDiag, size = 2, color = "lightgreen") 3wrap_3 <- wrap(ggally_cor, size = 8, color = "pink", fontface = "bold") 4 5ggpairs(iris, 1:3,  6        lower = list(continuous = wrap_1), 7        diag = list(continuous = wrap_2), 8        upper = list(continuous = wrap_3), 9        title = "设置点的：透明度，颜色大小；线的：颜色，线宽；字的：字型，颜色，尺寸"10        )11

2.5

自定义主题

 1library(GGally) 2library(ggplot2) 3library(showtext) 4 5# 添加字体 6windowsFonts(YaHei_rontine = windowsFont("微软雅黑")) 7font_add("YaHei_rontine", regular = "msyh.ttc", bold = "msyhbd.ttc")   8 9wrap_1 <- wrap(ggally_points, size = 5, color = "magenta", alpha = 0.3)10wrap_2 <- wrap(ggally_densityDiag, size = 2, color = "lightgreen")11wrap_3 <- wrap(ggally_cor, size = 8, color = "pink", fontface = "bold")1213gg_1 <- ggpairs(iris, 1:3, 14                lower = list(continuous = wrap_1),15                diag = list(continuous = wrap_2),16                upper = list(continuous = wrap_3),17                title = "自定义主题:红色雅黑字体居中"18        ) 1920gg_1 + theme_bw() + 21  theme(plot.title = element_text(size = 20, color = "red", hjust = 0.5,22                                  family = "YaHei_rontine"))23

2.6

scale_xxx()标度调整

只能索引出来子集后调整子集的标度。

 1library(ggplot2) 2library(GGally) 3data(tips, package = "reshape") 4 5mygg <- ggpairs(tips, mapping = aes(color = day), 6                columns = c("total_bill", "time", "tip"), 7                columnLabels = c("Total_Bill(连续变量)", "Time(离散变量)", "Tip(连续变量)"), 8                diag = list(continuous = wrap(ggally_densityDiag, alpha = 0.7)), 9                title = "修改单个plot的标度"10)1112mygg[1,1] <- mygg[1,1] + scale_fill_brewer(palette = "Set2")13mygg[2,2] <- mygg[2,2] + scale_fill_brewer(palette = "Dark2")14mygg[3,3] <- mygg[3,3] + scale_fill_brewer(palette = "Set1")1516mygg + theme_bw() + 17  theme(plot.title = element_text(size = 20, color = "red", hjust = 0.5,18                                  family = "YaHei_rontine"))19

 1gg_2 <- ggpairs(iris, aes(color = Species), 2                title = "循环给每个plot修改标度" 3                )  4 5# 循环给每一个子集plot修改标度 6for(i in 1:gg_2$nrow) { 7  for(j in 1:gg_2$ncol){ 8    gg_2[i,j] <- gg_2[i,j] +  9        scale_fill_manual(values=c("#7fc97f", "#beaed4", "#fdc086")) +10        scale_color_manual(values=c("#7fc97f", "#beaed4", "#fdc086"))  11  }12}13gg_2 + theme_bw() + 14  theme(plot.title = element_text(size = 20, color = "red", hjust = 0.5,15                                  family = "YaHei_rontine"))

2.7

legend图例

 1library(ggplot2) 2library(GGally) 3data(tips, package = "reshape") 4 5gg_3 <- ggpairs(tips, mapping = aes(color = day), 6                columns = c("total_bill", "time", "tip"), 7                columnLabels = c("Total_Bill(连续变量)", "Time(离散变量)", "Tip(连续变量)"), 8                diag = list(continuous = wrap(ggally_densityDiag, alpha = 0.7)), 9                legend = c(2,2), 10                title = "设置图例"11)1213for(i in 1:gg_3$nrow) {14  for(j in 1:gg_3$ncol){15    gg_3[i,j] <- gg_3[i,j] + 16        scale_fill_brewer(palette = "Set2") + 17        scale_color_brewer(palette = "Set2") 18  }19}2021gg_3 + theme_bw() + 22  theme(plot.title = element_text(size = 20, color = "red", hjust = 0.5,23                                  family = "YaHei_rontine"),24        legend.position = "right")

 1library(ggplot2) 2library(GGally) 3data(tips, package = "reshape") 4 5# 提取图例 6mylegend <- grab_legend(ggplot(tips, aes(x = total_bill, fill = day)) +  7                          geom_density() +  8                          scale_fill_brewer(palette = "Set2") 9                       )1011gg_3 <- ggpairs(tips, mapping = aes(color = day),12                columns = c("total_bill", "time", "tip"),13                columnLabels = c("Total_Bill(连续变量)", "Time(离散变量)", "Tip(连续变量)"),14                diag = list(continuous = wrap(ggally_densityDiag, alpha = 0.7)),15                legend = mylegend, 16                title = "grab_legend提取图例"17)1819for(i in 1:gg_3$nrow) {20  for(j in 1:gg_3$ncol){21    gg_3[i,j] <- gg_3[i,j] + 22        scale_fill_brewer(palette = "Set2") + 23        scale_color_brewer(palette = "Set2") 24  }25}2627gg_3 + theme_bw() + 28  theme(plot.title = element_text(size = 20, color = "red", hjust = 0.5,29                                  family = "YaHei_rontine"),30        legend.position = "left")

3.ggscatmat()

语法：

1ggscatmat(data, columns = 1:ncol(data), color = NULL, alpha = 1,2  corMethod = "pearson")

解释：

• ggscatmat()非常简单，功能也非常单一，运算速度比ggpairs更快,
  只能使用连续变量，也就产生下三角为散点图，上三角为相关系数，对角线为密度图。

• color,表示指定颜色变量。

• alpha,指定散点图的透明度，默认为1(不透明)。

• corMethod, 表示指定相关系数的计算方法，默认"pearson",还有"kendall", "spearman"。

1library(ggplot2)2library(GGally)34ggscatmat(tips, columns = c("total_bill", "tip", "size"), # 变量名指定5          color="day", alpha = 0.8)67ggscatmat(tips, columns = c(1,2,7), # 索引值指定8          color="day", alpha = 0.8)

4.pairs()

前面介绍了ggpairs及相关的绘图函数，接下来，我们将介绍graphics包中的pairs()函数。

语法：

 1pairs(formula, data = NULL, ..., subset, 2      na.action = stats::na.pass) 3 4pairs(x, labels, panel = points, ..., 5      horInd = 1:nc, verInd = 1:nc, 6      lower.panel = panel, upper.panel = panel, 7      diag.panel = NULL, text.panel = textPanel, 8      label.pos = 0.5 + has.diag/3, line.main = 3, 9      cex.labels = NULL, font.labels = 1,10      row1attop = TRUE, gap = 1, log = "")

关键参数：

• x, 数据矩阵或数据框，其中逻辑和因子型变量会被强制转换为数值型。

• formula, 形如~x + y + z的公式，x,y,z分别代表多个数值变量。

• data, formula中，变量所在的数据框或列表。

• subset, 指定进行可视化的观测。

• horInd,verInd,表示用索引值指定要绘图的变量。

• na.action, 指定缺失值的处理方式。

• labels, 变量名称(给变量贴标签)。

• panel, 自定义面板函数。

• lower.panel, upper.panel,自定义上三角和下三角面板中的绘图函数。

• diag.panel, 指定主对角线面板上的作图函数。

• text.panel, 指定主对角线面板上文本标签的函数。

• label.pos, 指定文本标签的位置。

• cex.labels, font.labels, 指定文本标签的缩放倍数及字体样式。

• rowlattop, 逻辑值，指定散点图第一行出现在顶部还是底部。

• main, 指定标题。

• gap, 指定子区域之间的间距。

• log, 表示对坐标轴进行对数变换，log = "x"表示x轴对数变换，log="y"表示对y轴对数变换；
  log = "xy"表示x,y同时对数变换。 log = 1:4 表示前4个变量对数变换。

• ...,其它要传递的绘图参数，一般是par()中的参数。

4.1

默认绘图样式

1library(graphics)2head(iris) # 前4列为数字变量34pairs(iris[1:4], main = "默认样式") # 默认绘图样式

4.2

自定义panel

 1library(grDevices) 2 3head(mtcars) 4df <- mtcars[, c(1,3:6)] 5 6# 定义上三角panel 7panel_upper <- function(x, y, digits = 2, col, ...) { 8  usr <- par("usr"); on.exit(par(usr)) 9  par(usr = c(0, 1, 0, 1))10  # 文本颜色11  text_color <- if(cor(x, y) > 0) {"black"} else {"white"} # 大于0为黑色，小于0为白色12  # 文本内容13  txt <- round(cor(x,y), 2) # 保留2位小数14  # 背景颜色15  col_index <- if (cor(x,y) > 0) {(1 - cor(x,y))} else {(1 + cor(x,y))}16  bg_col <- if (cor(x,y) > 0) {17    rgb(red = 1, green = col_index, blue = col_index)18  } else { rgb(red = col_index, green = col_index, blue = 1)}19  # 绘图20  rect(xleft = 0, ybottom = 0, xright = 1, ytop = 1, col = bg_col) # rect画背景21  text(x = 0.5, y = 0.5, labels = txt, cex = 2, col = text_color)22}2324# 定义下三角panel25panel_lower <- function(x, y, bg = NA, pch = par("pch"),26                     cex = 1, col_smooth = "blue",...) {27     points(x, y, pch = pch, bg = bg, cex = cex)28     abline(stats::lm(y ~ x), col = col_smooth,...)29}303132# 绘图33pairs(df, main = "自定义panels",34  pch = 21, 35  upper.panel = panel_upper,36  lower.panel = panel_lower37)

do.call()调用：

 1panel_upper <- function(x, y, digits = 2, bg = NULL, col = NULL, ...) { 2  u <- par("usr") 3  names(u) <- c("xleft", "xright", "ybottom", "ytop") 4  # 背景颜色: 要求，相关系数大于0为红色渐变，小于0为蓝色渐变 5  col_index <- if (cor(x,y) > 0) {(1 - cor(x,y))} else {(1 + cor(x,y))} 6  bg_col <- if (cor(x,y) > 0) { 7    rgb(red = 1, green = col_index, blue = col_index) 8  } else { rgb(red = col_index, green = col_index, blue = 1)} 9  do.call(rect, c(col = bg_col, as.list(u))) 10  par(usr = c(0, 1, 0, 1))11  # 文本颜色:要求相关系数大于0为黑色，小于0为白色12  text_color <- if(cor(x, y) > 0) {"black"} else {"white"} # 大于0为黑色，小于0为白色13  # 文本内容14  txt <- round(cor(x,y), 2) # 保留2位小数15  # 绘图16  text(x = 0.5, y = 0.5, labels = txt, cex = 2, col = text_color)17}1819# 绘图20pairs(df, main = "自定义panels",21  pch = 21, 22  upper.panel = panel_upper,23  lower.panel = panel_lower24)

参

考资料

• R语言相关关系可视化函数梳理

  https://zhuanlan.zhihu.com/p/36925332

• 相关性分析了解一下

  https://mp.weixin.qq.com/s/Nm9NEGG9gy-lEX34kyxFgQ?token=1086251536&lang=zh_CN

• R手册(Visualise)–GGally(ggplot2 extensions)

  https://blog.csdn.net/qq_41518277/article/details/80517791

• Plot Multivariate Continuous Data

  http://www.sthda.com/english/articles/32-r-graphics-essentials/130-plot-multivariate-continuous-data/

• Scatter Plot Matrices - R Base Graphs

  http://www.sthda.com/english/wiki/scatter-plot-matrices-r-base-graphs

• R Exploratory Analysis with ggpairs

  http://timothykylethomas.me/ggpairs.html#1_overview

• ggpairs 参数

  https://www.rdocumentation.org/packages/GGally/versions/1.4.0/topics/ggpairs

• DT包用法

  https://rstudio.github.io/DT/

• R语言相关关系可视化函数梳理

  http://developer.51cto.com/art/201805/573479.htm

• R语言学习系列19-基本统计图形

  https://wenku.baidu.com/view/cfcff51fc4da50e2524de518964bcf84b9d52dc

• R语言中用pairs作图时标出各个分图中的所要显示的点

  https://blog.csdn.net/faith_mo_blog/article/details/39694897

• R 学习笔记: Par 函数

  https://zhuanlan.zhihu.com/p/21394945

• Scatter Plot Matrices - R Base Graphs

  http://www.sthda.com/english/wiki/scatter-plot-matrices-r-base-graphs

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往期精彩：

• 精选| 2019年3月R新包推荐

• R语言自然语言处理：文本分类

• 今天，我改名了！