前面介绍了ggplot2的图层（layers），接下来几篇会系统较深入的介绍ggplot2图层图形语法（the Grammar of Graphics），不纠结某一种图的具体绘制方法，不纠结某一个参数的具体设置，这些都交给帮助文档。

本文目录

1、ggplot2图层图形语法（the Grammar of Graphics）的益处

2、图层图形语法（the Grammar of Graphics）中一张图组成?

图层（layer）介绍

ggplot2绘图模板

3、数据集（Data）

4、图像属性（aes）

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1、ggplot2图层图形语法（the Grammar of Graphics）的益处

• The layered grammar is based on Wilkinson’s grammar of graphics , but adds a number of enhancements that help it to be more expressive and fit seamlessly into the R environment.
• It also encourages the use of graphics customised to a particular problem, rather than relying on specific chart types.
• The grammar makes it easier for you to iteratively update a plot, changing a single feature at a time.
• The grammar is also useful because it suggests the high-level aspects of a plot that can be changed, giving you a framework to think about graphics, and hopefully shortening the distance from mind to paper.

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2、图层图形语法（the Grammar of Graphics）中一张图组成

• A default dataset and set of mappings from variables to aesthetics【数据集（data）和图像属性（aes）】.
• One or more layers, each composed of a geometric object, a statistical transformation, a position adjustment, and optionally, a dataset and aesthetic mappings【一或多个图层（layers）：每个图层由数据集（data），图像属性（aes），统计变换（stat），几何对象（geom）和位置调整（position adjustment）组成】.
• One scale for each aesthetic mapping【标度（scale）】.
• A coordinate system【坐标系（coord）】.
• The facetting specification【分面（facet）】.

以上各部分体现在图中如下。 

图层（layer）介绍

图层一般由以下五部分构成

> layer
function (
geom = NULL, #绘制什么图，例如散点图：geom = "point",
stat = NULL, #默认为“identity”， histograms和smoothers图时常用
data = NULL, #指定数据集
mapping = NULL, #aes()函数
position = NULL, #设置多个图之间相对位置，防折叠、设置堆叠等
..........)
{...............
}

了解layer函数会帮助更好理解图层图形语法的底层，不过一般绘图时，不会直接使用layer函数，而是使用阉割版的geom_系列函数添加图层，举个栗子。

library('gridExtra')
library('ggplot2')
options(repr.plot.width = 6, repr.plot.height = 3, repr.plot.res = 300)
#创建一个画布，包含坐标轴和数据信息
p1 <- ggplot(mpg, aes(displ, hwy))#geom_系列函数添加散点图（geom_point()图层
p2 <- p1 + geom_point()+ggtitle('By geom_point()')#geom_point()是捷径，实际上后台调用layer()函数以创建一个散点图图层
p3 <- p1 + layer(mapping = NULL, data = NULL,geom = "point", #指定散点图stat = "identity",position = "identity"
)+ggtitle('By layer()')p4 <- grid.arrange(p2,p3,nrow = 1)
ggsave("scale11.png", p4, width = 6, height = 3)

可以看出效果一模一样。 

ggplot2绘图模板

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3、数据集（Data）

ggplot2中对干净数据定义为： variables in the columns and observations in the rows【每一列为一个变量，每一行为一个观测】，可以通过控制数据集以突出想要突出展示的数据。

library(dplyr) 
options(repr.plot.width = 4.5, repr.plot.height = 3.5, repr.plot.res = 300)
mod <- loess(hwy ~ displ, data = mpg)
grid <- data_frame(displ = seq(min(mpg$displ), max(mpg$displ), length = 50))
grid$hwy <- predict(mod, newdata = grid)#loess变换构建新data gridstd_resid <- resid(mod) / mod$s
outlier <- filter(mpg, abs(std_resid) > 2)#划分离散点ggplot(mpg, aes(displ, hwy)) + geom_point() + #添加散点图图形geom_line(data = grid) + #拟合曲线geom_text(data = outlier, aes(label = model))#离散点添加文本

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4、图像属性（aes）

设置Colour, size, shape等等。

• 在ggplot和在图层中设置aes的区别

library(dplyr)
class <- mpg %>% group_by(class) %>% summarise(n = n(), hwy = mean(hwy))#以下四种方式按class绘制散点图效果一致。
#在ggplot中设置aes
ggplot(mpg, aes(displ, hwy, colour = class)) + geom_point()ggplot(mpg, aes(displ, hwy)) + geom_point(aes(colour = class))#在图层中设置aes
ggplot(mpg, aes(displ)) + geom_point(aes(y = hwy, colour = class))ggplot(mpg) + geom_point(aes(displ, hwy, colour = class))

• aes内和外设置参数的区别 

options(repr.plot.width = 6, repr.plot.height = 3.5, repr.plot.res = 300)p1 <- ggplot(mpg, aes(cty, hwy)) + geom_point(colour = "darkblue")  
#if you want override the default size or colour, put the value outside of aes().p2 <- ggplot(mpg, aes(cty, hwy)) + geom_point(aes(colour = "darkblue"))
#  If you want appearance to be governed by a variable, put the specification inside aes()p3 <- ggplot(mpg, aes(cty, hwy)) + geom_point(aes(colour = "darkblue")) + scale_colour_identity()p4 <- ggplot(mpg, aes(displ, hwy)) + geom_point() +geom_smooth(aes(colour = "loess"), method = "loess", se = FALSE) + geom_smooth(aes(colour = "lm"), method = "lm", se = FALSE) +labs(colour = "Method")p5 <- grid.arrange(p1,p2,p3,p4,nrow = 2)
ggsave("scale11.png", p4, width = 6, height = 3)

 

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