R语言入门 | 使用 ggplot2 进行数据可视化

R语言入门 | 使用 ggplot2 进行数据可视化

引用

CSDN

1.

https://blog.csdn.net/mooridy/article/details/137018894

本文将介绍如何使用R语言中的ggplot2包进行数据可视化。文章将从数据准备、基本绘图、图形属性映射、分面、几何对象、统计变换、位置调整、坐标系等多个方面进行讲解，并通过具体的代码示例和图形展示帮助读者理解。

准备工作

首先需要安装并加载tidyverse包，其中包含了ggplot2以及其他一些数据处理和可视化的工具包。

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

数据框

数据框是变量（列）和观测（行）的矩形集合。本文将使用mpg数据集，该数据集包含了由美国环境保护协会收集的38种车型的观测数据。

创建ggplot图形

使用ggplot创建一个基本的散点图：

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

• ggplot(data = mpg)：创建一张空白图
• geom_point()：添加一个点层，创建散点图
• aes()：定义数据变量到图形属性的映射

绘图模板

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

图形属性映射

可以将点的颜色映射为变量class：

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

也可以手动设置图形属性：

ggplot(data = mpg) + 
geom_point(mapping = aes(x = displ, y = hwy), color = "blue", shape=21, fill="red")

分面

facet_wrap()

按class分组，排成2行：

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

facet_grid()

按drv和cyl分组：

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

几何对象

常见几何对象

• geom_point()：散点图
• geom_smooth()：平滑曲线图
• geom_bar()：条形图

叠加使用

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

统计变换

位置调整

dodge

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

identity

ggplot(data = diamonds) + 
geom_bar(mapping = aes(x = cut, fill = clarity), position = "identity")

jitter

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

盒图

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

坐标系

图形分层语法

条形图

geom_bar

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

stat_count

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

显示比例

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

stat_summary

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

位置调整

dodge

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

jitter

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

盒图

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

旋转坐标系

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

绘制空间数据

nz <- map_data("nz")
ggplot(nz, aes(long, lat, group = group)) + 
geom_polygon(fill = "white", color = "black") + 
coord_quickmap

鸡冠图

coord_polar(theta="x")

p <- ggplot(data = diamonds) + 
geom_bar(mapping = aes(x = cut, fill = cut)) + 
coord_polar()

coord_polar(theta="y")

p <- ggplot(data = diamonds) + 
geom_bar(mapping = aes(x = cut, fill = cut, width=1)) + 
coord_polar(theta="y")

频率分布图

ggplot(data = diamonds, mapping = aes(x = price)) + 
geom_freqpoly(binwidth = 10)