本文系统介绍ggplot2的统计变换（stat）、位置设置（Position adjustments）和标度（scale）。

本文目录

6、统计变换（stat）stats can be created with a geom_ functionstats can’t be created with a geom_ function7、 位置设置（Position adjustments）条形图中stack|fill|dodge散点图中nudge|jitter|jitterdodge8、标度（scale）marker的形状和大小图例和坐标轴

6、统计变换（stat）

将data经过一种统计方法整理，然后再绘图，ggplot2的统计方法如下，都是以stat_开头的函数。

可以分为两类：

stats can be created with a geom_ function

• stat_bin(): geom_bar(), geom_freqpoly(), geom_histogram()
• stat_bin2d(): geom_bin2d()
• stat_bindot(): geom_dotplot()
• stat_binhex(): geom_hex()
• stat_boxplot(): geom_boxplot()
• stat_contour(): geom_contour()
• stat_quantile(): geom_quantile()
• stat_smooth(): geom_smooth()
• stat_sum(): geom_count()

options(repr.plot.width = 4.5, repr.plot.height = 3, repr.plot.res = 300)
f <- ggplot(mpg, aes(class, hwy))
f + geom_boxplot() 

stats can’t be created with a geom_ function

• stat_ecdf(): compute a empirical cumulative distribution plot.
• stat_function(): compute y values from a function of x values.
• stat_summary(): summarise y values at distinct x values.
• stat_summary2d(), stat_summary_hex(): summarise binned values.
• stat_qq(): perform calculations for a quantile-quantile plot.
• stat_spoke(): convert angle and radius to position.
• stat_unique(): remove duplicated rows.

ggplot(mpg, aes(trans, cty)) + geom_point() + stat_summary(geom = "point", fun = "mean", colour = "red", size = 4)

7、 位置设置（Position adjustments）

• 条形图中stack|fill|dodge
• position_stack(): stack overlapping bars (or areas) on top of each other.
• position_fill(): stack overlapping bars, scaling so the top is always at 1.
• position_dodge(): place overlapping bars (or boxplots) side-by-side.

options(repr.plot.width = 4.5, repr.plot.height = 5, repr.plot.res = 300)
dplot <- ggplot(diamonds, aes(color, fill = cut)) + xlab(NULL) + ylab(NULL) + theme(legend.position = "none")p1 <- dplot + geom_bar()#默认堆叠
p2 <- dplot + geom_bar(position = "fill")#堆叠且按比例
p3 <- dplot + geom_bar(position = "dodge")#并列p4 <- grid.arrange(p1,p2,p3,nrow = 3)
ggsave("scale23.png", p4, width = 4.5, height = 5) 

• 散点图中nudge|jitter|jitterdodge
• position_nudge(): move points by a fixed offset.
• position_jitter(): add a little random noise to every position.
• position_jitterdodge(): dodge points within groups, then add a little random noise.

p1 <- ggplot(mpg, aes(displ, hwy)) + geom_point(position = "jitter")
p2 <- ggplot(mpg, aes(displ, hwy)) + geom_point(position = position_jitter(width = 0.05, height = 0.5))
p3 <- ggplot(mpg, aes(displ, hwy)) + geom_jitter(width = 0.05, height = 0.5)p4 <- grid.arrange(p1,p2,p3,nrow = 3)
ggsave("scale24.png", p4, width = 4.5, height = 5) 

8、标度（scale）

这部分内容，这里介绍一些没提到的，前面写已过三篇文章详细介绍：

R可视化06|ggplot2图层-标度图层（scale layer）-坐标轴篇
R可视化07|ggplot2图层-标度图层（scale layer）-颜色盘篇
R可视化08|ggplot2图层-标度图层（scale layer）-图例篇

• marker的形状和大小

使用第一行的数字即可使用第二行的形状。

options(repr.plot.width = 6.5, repr.plot.height = 5, repr.plot.res = 300)#marker形状
p <- e + geom_point(aes(shape = fl, size = cyl))p1 <- p + scale_shape() + scale_size()
p2 <- p + scale_shape_manual(values = c(1:26))#values = c(1:26)指定marker#marker大小
p3 <- p + scale_radius(range = c(1,6))
p4 <- p + scale_size_area(max_size = 6)
p5 <- grid.arrange(p2,p3,p4,nrow = 2)
ggsave("scale25.png", p5, width = 4.5, height = 5)

• 图例和坐标轴

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