R语言ggplot2

之前下载过Rstudio，这次直接开始学

准备工作

• 安装并打开包

install.packages("tidyverse")
library(tidyverse)

用到了一个mpg数据框，不了解时可以?mpg

ggplot2作图基本

• 模板

ggplot(data = <DATA>) +
<GEOM_FUNCTION>(mapping = aes(<MAPPINGS>))

注意+的位置，geom指图的类型，mapping是加图层，aesthetic是各种显示的属性

• 颜色、大小、透明度、形状

ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy, color = class))

ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy, size = class))

ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy, alpha = class))

ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy, shape = class))

可以手动设置属性，要放在aes外面：

ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy), color = "blue")

• 分面

ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy)) +
facet_grid(drv ~ cyl)

ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy)) +
facet_wrap(~ class, nrow = 2)

ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy)) +
facet_grid(. ~ cyl)

• 分组

ggplot(data = mpg) +
geom_smooth(mapping = aes(x = displ, y = hwy, group = drv))

ggplot(data = mpg) +
geom_smooth(
mapping = aes(x = displ, y = hwy, linetype = drv),
)

ggplot(data = mpg) +
geom_smooth(
mapping = aes(x = displ, y = hwy, color = drv),
show.legend = FALSE #不显示图例
)

• 全局映射

ggplot(data = mpg, mapping = aes(x = displ, y = hwy)) +
geom_point(mapping = aes(color = class)) +
geom_smooth(data = filter(mpg, class == "subcompact"), se = FALSE)

局部映射与全局映射冲突时，服从局部映射; se默认显示标准差

统计变换

这里用到新的diamond数据

• 统计变换函数和几何对象函数

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

ggplot(data = diamonds) +
stat_count(mapping = aes(x = cut))

每个几何对象函数都有一个默认的统计变换，每个统计变换函数都又一个默认的几何对象(绘图时用来计算新数据的算法叫做统计变换stat)

• 修改stat

demo <- tribble(
~cut, ~freq,
"Fair", 1610,
"Good", 4906,
"Very Good", 12082,
"Premium", 13791,
"Ideal", 21551
)

ggplot(data = demo) +
geom_bar(mapping = aes(x = cut, y = freq), stat = "identity")

• 显示比例

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

group把所有钻石当成一组

• 从统计变换角度作图

ggplot(data = diamonds) +
stat_summary(
mapping = aes(x = cut, y = depth),
fun.ymin = min,
fun.ymax = max,
fun.y = median
)

R for Data Science原文：stat_summary summarises the y values for each unique x value, to draw attention to the summary that you’re computing

位置调整

• color和fill

ggplot(data = diamonds) +
geom_bar(mapping = aes(x = cut, colour = cut)) #边框

ggplot(data = diamonds) +
geom_bar(mapping = aes(x = cut, fill = cut)) #给柱子上色

ggplot(data = diamonds) +
geom_bar(mapping = aes(x = cut, fill = clarity)) #根据clarity用fill上色

position会调整数据在图上的位置：

ggplot(data = diamonds, mapping = aes(x = cut, colour = clarity)) +
geom_bar(fill = NA, position = "identity") #加上identity会“place each object exactly where it falls in the context of the graph”

ggplot(data = diamonds) +
geom_bar(mapping = aes(x = cut, fill = clarity), position = "dodge") #将数据横着分开

jitter让重合的点抖动开：

ggplot(data = mpg) +
geom_point(mapping = aes(x = displ, y = hwy), position = "jitter")

坐标系

• 翻转坐标系

ggplot(data = mpg, mapping = aes(x = class, y = hwy)) +
geom_boxplot()

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

• 极坐标

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()

bar + coord_polar()

总结公式

ggplot(data = <DATA>) +
<GEOM_FUNCTION>(
mapping = aes(<MAPPINGS>),
stat = <STAT>,
position = <POSITION>
) +
<COORDINATE_FUNCTION> +
<FACET_FUNCTION>

思维导图

ggplot2