ggplot2学习（3）

1、Aesthetic mappings

library(ggplot2)
p <- ggplot(mtcars, aes(x = mpg, y = wt))
p + geom_point()

p + geom_point(aes(colour = factor(cyl)))   #cyl为整型​
#Add aes(colour = factor(cyl))  =====>  aes(x = mpg, y = wt, colour = factor(cyl))

p + geom_point(aes(y = disp))    #将y轴的数据更改为disp，但要注意y轴标签名不会更改
#Override  aes(y = disp)  ======>  aes(x = mpg, y = disp)  覆盖
#Remove  aes(y = NULL)  ======>  aes(x = mpg)  删除

关于颜色设置有两种方式： Setting vs Mapping
Mapping: aes(colour = cut)
Setting: colour = "blue"

# Setting
p + geom_point(colour = "green") 

# Mapping
p + geom_point(aes(colour = "green")) 

# Mapping
#倘若希望为指定的颜色
p + geom_point(aes(colour = I("green"))) 
# 因为Mapping默认的是一组向量，颜色为内部默认的颜色

分组 grouping
分组和分面都用于对数据分组，便于观察各自的规律、趋势和模式，不同的是，分组是把图形绘制到一个大的图形中，通过美学特征来区分，而分面是把图形绘制到不同的网格中。

library(nlme)   #nlme包中有许多数据集
dat <- Oxboys

Oxboys是牛津大学学生年龄和身高的一个数据集，其中Subject共有26个组，age是标准化后的年龄，Occasion每个Subject有9个样本

p <- ggplot(dat, aes(age, height, group = Subject)) + geom_line()
p
#按照Subject来分组，那些下面应该有26条线，注意分组的依据应当是因子类型

p <- ggplot(dat, aes(age, height, group = 1)) + geom_line()
p
# group = 1则不论1改为多大的值，下图中都只会有一条线，相当于分为一组，不加group和group = 1等同

#Different groups on different layers 即将在不同的图层中设置分组
p <- ggplot(dat, aes(age, height, group = Subject)) + geom_line()
p + geom_smooth(aes(group = Subject), method = "lm", se = F)

p <- ggplot(dat, aes(age, height, group = Subject)) + geom_line()
p + geom_smooth(aes(group = 1), method = "lm", se = F, size = 2)
#不加group和group = 1等同 ,相当于把所有组当作一个整体来构建smooth​

p <- ggplot(dat, aes(age, height, group = 1)) + geom_line()
p + geom_smooth(aes(group = Subject), method = "lm", se = F)

p <- ggplot(dat, aes(age, height, group = 1)) + geom_line()
p + geom_smooth(aes(group = 1), method = "lm", se = F)

boysbox <- ggplot(Oxboys, aes(Occasion, height)) + geom_boxplot()   #Occasion为因子类型
boysbox

boysbox + geom_line(aes(group = Subject),colour = "green")

2、Position adjustments

ggplot(diamonds,
       aes(clarity, fill = cut)) + geom_bar(position = "stack")

ggplot(diamonds,
       aes(clarity, fill = cut)) + geom_bar(position = "fill")

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

ggplot(diamonds,
         aes(clarity, price, colour = cut)) + geom_point(position = "jitter")

ggplot(diamonds,
       aes(clarity, price, colour = cut)) + geom_point(position = "identity")

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