library(ggplot2)
ggplot(data = iris) + 
  geom_point(mapping = aes(x = Sepal.Length, 
                           y = Petal.Length), 
             size = 1,     # 点的大小5mm
             alpha = 0.5,  # 透明度 50%
             shape = 8,  # 点的形状
             color = "blue")#这里color是geom_point的参数，即：把图形设置为一个或n个颜色，与数据内容无关

ggplot(data = iris)+
  geom_point(mapping = aes(x = Sepal.Length,
                           y = Petal.Length,
                           color = Species))+#这里的color为aes的参数，紧跟x，y出现，是数据框列名
  scale_color_manual(values =c("blue","grey","red")) #自行指定映射的颜色

#分一面
ggplot(data = iris) + 
  geom_point(mapping = aes(x = Sepal.Length, y = Petal.Length)) + 
  facet_wrap(~ Species) 

#双分面
dat = iris 
#sample()取值,replace表示是否放回
dat$Group = sample(letters[1:5],150,replace = T)#结果是新增一列group内容为随机取的1：5中一个
head(dat)
ggplot(data = dat) + 
  geom_point(mapping = aes(x = Sepal.Length, y = Petal.Length)) + 
  facet_grid(Group ~ Species) 

#局部设置
#全局设置
ggplot(data = iris,mapping = aes(x = Sepal.Width,
                                 y = Species)) + 
  geom_violin(aes(fill = Species))+
  geom_boxplot()+
  geom_jitter(aes(shape=Species))

#统计变换-直方图
head(diamonds)
table(diamonds$cut)
## 
##      Fair      Good Very Good   Premium     Ideal 
##      1610      4906     12082     13791     21551
ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut))

ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut,fill=clarity))

ggplot(data = diamonds) + 
  geom_bar(mapping = aes(x = cut, fill = clarity), position = "dodge")

library(ggpubr)
my_comparisons <- list(c("setosa","versicolor"),
                        c("setosa","virginica"),
                        c("versicolor","virginica"))
ggboxplot(iris,
               x = "Species",
               y= "Sepal.Length",
               add = "jitter")+
  stat_compare_means(comparisons = my_comparisons)+
  stat_compare_means(label.y = 9)