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
代码语言：javascript复制#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
代码语言：javascript复制# 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
代码语言：javascript复制Box_plot <- ggboxplot(ToothGrowth, x = "dose", y = "len",color = "dose", palette = "jco")
Box_plot
#点图
代码语言：javascript复制Dot_plot <- ggdotplot(ToothGrowth, x = "dose", y = "len",
color = "dose", palette = "jco", binwidth = 1)
Dot_plot
#有序条形图
代码语言：javascript复制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
代码语言：javascript复制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 coefficient
Scatter_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
代码语言：javascript复制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
代码语言：javascript复制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
代码语言：javascript复制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）
代码语言：javascript复制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
代码语言：javascript复制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
代码语言：javascript复制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
代码语言：javascript复制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
代码语言：javascript复制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
代码语言：javascript复制density.p <- ggdensity(iris, x = "Sepal.Length",
fill = "Species", palette = "jco")# Sepal.Length描述性统计
代码语言：javascript复制stable <- desc_statby(iris, measure.var = "Sepal.Length",
grps = "Species")
stable <- stable[, c("Species", "length", "mean", "sd")]# 设置table的主题
代码语言：javascript复制stable.p <- ggtexttable(stable, rows = NULL,
theme = ttheme("mOrange"))# text 信息
代码语言：javascript复制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
代码语言：javascript复制ggarrange(density.p, stable.p, text.p,
ncol = 1, nrow = 3,
heights = c(1, 0.5, 0.3))
#子母图展示
代码语言：javascript复制density.p annotation_custom(ggplotGrob(stable.p),
xmin = 5.5, ymin = 0.7,
xmax = 8)
6）嵌套布局展示
代码语言：javascript复制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/
