install.packages("ggpubr")

# Install
if(!require(devtools)) install.packages("devtools")
devtools::install_github("kassambara/ggpubr")

library(ggplot2)
library(ggpubr)

# 构建数据集
set.seed(1234)
#set.seed()设定生成随机数的种子，种子是为了让结果具有重复性，重现结果。如果不设定种子，生成的随机数无法重现。
wdata = data.frame(
   sex = factor(rep(c("F", "M"), each=200)),
   weight = c(rnorm(200, 55), rnorm(200, 58)))
head(wdata, 4)
set.seed(1234)
#set.seed()设定生成随机数的种子，种子是为了让结果具有重复性，重现结果。如果不设定种子，生成的随机数无法重现。
wdata = data.frame(
   sex = factor(rep(c("F", "M"), each=200)),
   weight = c(rnorm(200, 55), rnorm(200, 58)))
head(wdata, 4)

> head(wdata, 4)
  sex   weight
1   F 53.79293
2   F 55.27743
3   F 56.08444
4   F 52.65430

ggdensityggdensity(wdata, x = "weight",
   add = "mean", rug = TRUE,
   color = "sex", fill = "sex",
   palette = c("#00AFBB", "#E7B800"))

#参数详解
Usage
ggdensity(
  data,
  y = "..density..",
  combine = FALSE,#对于多类型数据是否分面
  merge = FALSE,#对于多类型数据是否合并
  color = "black",#线条颜色
  fill = NA,#线条填充色
  palette = NULL,#自定义颜色画板
  size = NULL,#点、线大小
  linetype = "solid",#线条类型
  alpha = 0.5,#透明度
  title = NULL,#设置标题
  xlab = NULL,#设置x轴标题
  ylab = NULL,#设置y轴标题
  facet.by = NULL,#设置分组分面
  panel.labs = NULL,#设置分面各组的标题
  short.panel.labs = TRUE,
  add = c("none", "mean", "median"),#添加均值或中位数线
  add.params = list(linetype = "dashed"),#添加其他参数
  rug = FALSE,#是否添加边际线
  label = NULL,#设置列标签
  font.label = list(size = 11, color = "black"), #设置标签字体
  label.select = NULL,
  repel = FALSE,#是否避字体免重叠 
  label.rectangle = FALSE,#是否给标签添加方框
  ggtheme = theme_pubr(),#设置画图主题 
)

gghistogram(wdata, x = "weight",
   add = "mean", rug = TRUE,
   color = "sex", fill = "sex",
   palette = c("#00AFBB", "#E7B800"))

#导入内置数据
data("ToothGrowth")
df <- ToothGrowth
head(df, 4)

> head(df, 4)
   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

p <- ggboxplot(df,
               x = "dose", 
               y = "len",
               color = "dose", 
               palette =c("#00AFBB", "#E7B800", "#FC4E07"),
               add = "jitter",#添加散点 
               shape = "dose"#点的形状)
p

# 添加P值
 # 建立需要比较的分组
my_comparisons <- list( c("0.5", "1"), c("1", "2"), c("0.5", "2") )
p + stat_compare_means(comparisons = my_comparisons)+ # 添加两两比较的p-value
  stat_compare_means(label.y = 50)                   # 添加多组间比较p-value

# 参数详解
stat_compare_means(
  mapping = NULL,
  data = NULL,
  method = NULL,#检验方法见下表
  paired = FALSE,#是否配对
  method.args = list(),#用于检验的附加参数,如method.args = list(alternative = "greater")
  ref.group = NULL,#指定对照组
  comparisons = NULL,#包含比较分组的列表
  hide.ns = FALSE,#是否隐藏无差异的标志ns
  label.sep = ", ",#分隔术语的字符串。默认为“，”，以分离相关系数和p值
  label = NULL,#标签
  label.x.npc = "left",#标签的x轴位置
  label.y.npc = "top",#标签的y轴位置
  #数字0~1，或者字符('right'， 'left'， 'center'， 'centre'， 'middle')
  label.x = NULL,
  label.y = NULL,#指定一个数值，表示显示标签的绝对坐标位置
  vjust = 0,#向上或向下移动文本
  tip.length = 0.03,
  bracket.size = 0.3,
  step.increase = 0,
  symnum.args = list(),#默认symnum.args <- list(cutpoints = c(0, 0.0001, 0.001, 0.01, 0.05, 1), symbols = c("****", "***", "**", "*", "ns")).可以自己修改
  geom = "text",
  position = "identity",
  na.rm = FALSE,#如果为FALSE(默认值)，则通过警告删除缺失的值。如果为真，则静默删除缺失的值。
  show.legend = NA,#是否包含图例
  inherit.aes = TRUE,
)