多个图形进行组图展示，既可以展示一个“事情”的多个角度，也可以进行异同的比较，同时也是发表paper所必须的。

    可以利用PS或者AI进行处理，但是图形的大小，位置，布局，字体等的调整也不是一个小工程。本文利用R包-ggpubr函数从0开始介绍组图的合并方式，也许。。。比AI或者PS更简单易学呢。

基础函数进行组图合并可参考

R|绘图边距及布局

载入数据，R包

加载函数包及数据集

#install.packages("ggpubr")library(ggpubr)# ToothGrowth数据集data("ToothGrowth")head(ToothGrowth)

   len supp dose

1  4.2   VC  0.5

2 11.5   VC  0.5

3  7.3   VC  0.5

4  5.8   VC  0.5

5  6.4   VC  0.5

6 10.0   VC  0.5

# mtcars 数据集data("mtcars")mtcars$name <- rownames(mtcars)mtcars$cyl <- as.factor(mtcars$cyl)head(mtcars[, c("name", "wt", "mpg", "cyl")])

                               name    wt  mpg cyl

Mazda RX4                 Mazda RX4 2.620 21.0   6

Mazda RX4 Wag         Mazda RX4 Wag 2.875 21.0   6

Datsun 710               Datsun 710 2.320 22.8   4

Hornet 4 Drive       Hornet 4 Drive 3.215 21.4   6

Hornet Sportabout Hornet Sportabout 3.440 18.7   8

Valiant                     Valiant 3.460 18.1   6

创建单图

创建用于图形组合的图：
#箱线图

Box_plot <- ggboxplot(ToothGrowth, x = "dose", y = "len",color = "dose", palette = "jco")Box_plot

#点图

Dot_plot <- ggdotplot(ToothGrowth, x = "dose", y = "len",                 color = "dose", palette = "jco", binwidth = 1)Dot_plot

#有序条形图

Bar_plot <- ggbarplot(mtcars, x = "name", y = "mpg",          fill = "cyl",               # change fill color by cyl          color = "white",            # Set bar border colors to white          palette = "jco",            # jco journal color palett. see ?ggpar          sort.val = "asc",           # Sort the value in ascending order          sort.by.groups = TRUE,      # Sort inside each group          x.text.angle = 90           # Rotate vertically x axis texts          ) + font("x.text", size = 8)Bar_plot

# 散点图

Scatter_plots <- ggscatter(mtcars, x = "wt", y = "mpg",                add = "reg.line",               # Add regression line                conf.int = TRUE,                # Add confidence interval                color = "cyl", palette = "jco", # Color by groups "cyl"                shape = "cyl"                   # Change point shape by groups "cyl"                )+  stat_cor(aes(color = cyl), label.x = 3)       # Add correlation coefficientScatter_plots

图形组合

使用ggpubr包的函数ggarrange（）中在一页上进行组合展示

1）ToothGrowth数据集的箱线图，点图 组合展示

ggarrange(Box_plot, Dot_plot,labels = c("A", "B"),ncol = 2, nrow = 1)

#图的边缘放置共同的唯一图例：common.legend = TRUE参数

ggarrange(bxp, dp, labels = c("A", "B"),         common.legend = TRUE, legend = "bottom")

2）mtcars 数据集的条形图，散点图组合展示

figure <- ggarrange(Scatter_plots, Bar_plot + font("x.text", size = 10),ncol = 1, nrow = 2)

#添加图形的注释信息（标题，副标题，坐标轴，字体，颜色等）

annotate_figure(figure,                top = text_grob("Visualizing mpg", color = "red", face = "bold", size = 14),                bottom = text_grob("Data source:  mtcars data set", color = "blue",                                   hjust = 1, x = 1, face = "italic", size = 10),                left = text_grob("Figure arranged using ggpubr", color = "green", rot = 90),                right = "Here )!",                fig.lab = "Figure 1", fig.lab.face = "bold"                )

3）ggarrange（）函数更改绘图的列/行跨度

#散点图在第一行跨两列，箱形图和点图并于第二行

ggarrange(Scatter_plots,                                                 # First row with scatter plot         ggarrange(Box_plot, Dot_plot, ncol = 2, labels = c("B", "C")), # Second row with box and dot plots         nrow = 2,         labels = "A"                                        # Labels of the scatter plot         )

4）利用NULL构建空白图

示例：绘制具有边际密度图的散点图

#绘制主要散点图

Scatter_plots <- ggscatter(iris, x = "Sepal.Length", y = "Sepal.Width",               color = "Species", palette = "jco",               size = 3, alpha = 0.6)+ border()

#上侧，右侧添加密度图                                  

xplot <- ggdensity(iris, "Sepal.Length", fill = "Species",                  palette = "jco")yplot <- ggdensity(iris, "Sepal.Width", fill = "Species",                  palette = "jco")+ rotate()# 设置主题yplot <- yplot + clean_theme()xplot <- xplot + clean_theme()

# 通过width和height参数调整图的大小

# 利用NULL设置空白图

ggarrange(xplot, NULL, Scatter_plots, yplot,         ncol = 2, nrow = 2,  align = "hv",         widths = c(2, 1), heights = c(1, 2),         common.legend = TRUE)

5）添加统计图表及文本信息

绘制变量“Sepal.Length” 的密度图以及描述性统计（mean，sd，...）的汇总表。

# Sepal.Length密度图

density.p <- ggdensity(iris, x = "Sepal.Length",                      fill = "Species", palette = "jco")

# Sepal.Length描述性统计

stable <- desc_statby(iris, measure.var = "Sepal.Length",                     grps = "Species")stable <- stable[, c("Species", "length", "mean", "sd")]

# 设置table的主题

stable.p <- ggtexttable(stable, rows = NULL,                       theme = ttheme("mOrange"))

#  text 信息

text <- paste("iris data set gives the measurements in cm",             "of the variables sepal length and width",             "and petal length and width, reScatter_plotsectively,",             "for 50 flowers from each of 3 Scatter_plotsecies of iris.",            "The Scatter_plotsecies are Iris setosa, versicolor, and virginica.", sep = " ")text.p <- ggparagraph(text = text, face = "italic", size = 11, color = "black")

# 组图展示，调整高度和宽度

ggarrange(density.p, stable.p, text.p,         ncol = 1, nrow = 3,         heights = c(1, 0.5, 0.3))

#子母图展示

density.p + annotation_custom(ggplotGrob(stable.p),                             xmin = 5.5, ymin = 0.7,                             xmax = 8)

6）嵌套布局展示

p1 <- ggarrange(Scatter_plots, Bar_plot + font("x.text", size = 9),               ncol = 1, nrow = 2)p2 <- ggarrange(density.p, stable.p, text.p,               ncol = 1, nrow = 3,               heights = c(1, 0.5, 0.3))#先组合P1，P2，然后自定义行 列 ，嵌套组合展示ggarrange(p1, p2, ncol = 2, nrow = 1)

参考链接：

http://www.sthda.com/english/articles/24-ggpubr-publication-ready-plots/81-ggplot2-easy-way-to-mix-multiple-graphs-on-the-same-page/

【公众号对话框，回复 R组图 即可获得上述组图R代码】

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