R语言学习6.1---ggplot绘图

ggplot绘图是生信技能树生信爆款入门课程R语言部分Day6的讲到的一个重要知识点。为加深理解,现在做下练习巩固。

加载数据

> library(ggplot2)
> test = iris

1.入门级绘图模板

> ggplot(data = test)+
+   geom_point(mapping = aes(x = Sepal.Length,
+                            y = Petal.Length))
image.png

2.映射

> ggplot(data = test)+
+   geom_point(mapping = aes(x = Sepal.Length,
+                            y = Petal.Length,
+                            color = Species))
image.png

3.分面

> ggplot(data = test) + 
+   geom_point(mapping = aes(x = Sepal.Length, y = Petal.Length)) + 
+   facet_wrap(~ Species) 
image.png

双分面

> test$Group = sample(letters[1:5],150,replace = T)
> ggplot(data = test) + 
+   geom_point(mapping = aes(x = Sepal.Length, y = Petal.Length)) + 
+   facet_grid(Group ~ Species) 
image.png

练习

示例数据:ggplot2中数据集mpg

1.分别以mpg的displ和hwy两列作为横纵坐标,画点图。

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy))
image.png

2.尝试修改颜色或大小,从mpg数据框中任选可以用来分类的列。

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy, col = drv))
image.png

3.根据class列来分面

ggplot(data = mpg) + 
  geom_point(mapping = aes(x = displ, y = hwy, col = drv))+
  facet_wrap(~ class) 
image.png

4.根据drv和cyl两个变量来分面

ggplot(data = mpg) + 
geom_point(mapping = aes(x = displ, y = hwy, col = drv))+
facet_wrap(drv~ cyl) 
image.png

4.几何对象

4.1分组

不分组

> ggplot(data = test) + 
+   geom_smooth(mapping = aes(x = Sepal.Length, 
+                           y = Petal.Length))
image.png

geom_smooth() using method = 'loess' and formula 'y ~ x'

根据Species分组

> ggplot(data = test) + 
+   geom_smooth(mapping = aes(x = Sepal.Length, 
+                             y = Petal.Length,
+                             group = Species))
`geom_smooth()` using method = 'loess' and formula 'y ~ x'
image.png

根据Species着色

> ggplot(data = test) + 
+   geom_smooth(mapping = aes(x = Sepal.Length, 
+                           y = Petal.Length,
+                           color = Species)) 
`geom_smooth()` using method = 'loess' and formula 'y ~ x'
image.png

4.2图层

局部映射和全局映射

> ggplot(data = test) + 
+   geom_smooth(mapping = aes(x = Sepal.Length, 
+                           y = Petal.Length))+
+   geom_point(mapping = aes(x = Sepal.Length, 
+                            y = Petal.Length))
`geom_smooth()` using method = 'loess' and formula 'y ~ x'
image.png
> ggplot(data = test,mapping = aes(x = Sepal.Length, y = Petal.Length))+
+   geom_smooth()+
+   geom_point()
`geom_smooth()` using method = 'loess' and formula 'y ~ x'
image.png

练习

>  1.尝试写出下图的代码
> 数据是iris
>  X轴是Species
> y轴是Sepal.Width
>  图是箱线图
image.png
>2. 尝试在此图上叠加点图,能发现什么问题?

点数量不够

>3.用下列代码作图,观察结果
> ggplot(test,aes(x = Sepal.Length,y = Petal.Length,color = Species)) +
+   geom_point()+
+   geom_smooth(color = "black")
`geom_smooth()` using method = 'loess' and formula 'y ~ x'

> 请问,当局部映射和全局映射冲突,以谁为准?
局部

5.统计变换-直方图

> View(diamonds)
> table(diamonds$cut)

     Fair      Good Very Good   Premium     Ideal 
     1610      4906     12082     13791     21551 
> 
> ggplot(data = diamonds) + 
+   geom_bar(mapping = aes(x = cut))
image.png
> ggplot(data = diamonds) + 
+   stat_count(mapping = aes(x = cut))
image.png

5.1.不统计,数据直接做图

> fre = as.data.frame(table(diamonds$cut))
> fre
       Var1  Freq
1      Fair  1610
2      Good  4906
3 Very Good 12082
4   Premium 13791
5     Ideal 21551
> 
> ggplot(data = fre) +
+   geom_bar(mapping = aes(x = Var1, y = Freq), stat = "identity")

image.png

5.2count改为prop

> ggplot(data = diamonds) + 
+   geom_bar(mapping = aes(x = cut, y = ..prop.., group = 1))
image.png

6.位置关系

6.1抖动的点图

> ggplot(data = mpg,mapping = aes(x = class, 
+                                 y = hwy,
+                                 group = class)) + 
+   geom_boxplot()+
+   geom_point()
image.png
> ggplot(data = mpg,mapping = aes(x = class, 
+                                 y = hwy,
+                                 group = class)) + 
+   geom_boxplot()+
+   geom_jitter()
image.png

6.2堆叠直方图

> ggplot(data = diamonds) + 
+   geom_bar(mapping = aes(x = cut,fill=clarity))
image.png

6.3 并列直方图

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

7.坐标系

翻转coord_flip()

> ggplot(data = mpg, mapping = aes(x = class, y = hwy)) + 
+   geom_boxplot() +
+   coord_flip()
image.png

极坐标系coord_polar()

 bar <- ggplot(data = diamonds) + 
+   geom_bar(
+     mapping = aes(x = cut, fill = cut), 
+     show.legend = FALSE,
+     width = 1
+   ) + 
+   theme(aspect.ratio = 1) +
+   labs(x = NULL, y = NULL)
> bar + coord_flip()
image.png
> bar + coord_polar()
image.png

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