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<!DOCTYPE html>
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<title>4 使用 ggplot2 包绘图 | 庄闪闪的可视化手册</title>
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<meta name="twitter:title" content="4 使用 ggplot2 包绘图 | 庄闪闪的可视化手册" />
<meta name="twitter:description" content="这是用R的bookdown功能制作中文图书的模板，输出格式为bookdown::gitbook和bookdown::pdf_book." />
<meta name="author" content="庄闪闪" />
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<ul class="summary">
<li class="chapter" data-level="" data-path="index.html"><a href="index.html"><i class="fa fa-check"></i>简介</a></li>
<li class="part"><span><b>I R 语言基础</b></span></li>
<li class="chapter" data-level="1" data-path="base-tutorial.html"><a href="base-tutorial.html"><i class="fa fa-check"></i><b>1</b> Base 系列</a></li>
<li class="chapter" data-level="2" data-path="tidyverse-tutorial.html"><a href="tidyverse-tutorial.html"><i class="fa fa-check"></i><b>2</b> Tidyverse 系列</a></li>
<li class="part"><span><b>II R 语言可视化</b></span></li>
<li class="chapter" data-level="3" data-path="causal.html"><a href="causal.html"><i class="fa fa-check"></i><b>3</b> 使用基础包绘图</a>
<ul>
<li class="chapter" data-level="3.1" data-path="causal.html"><a href="causal.html#绘制基本图形"><i class="fa fa-check"></i><b>3.1</b> 绘制基本图形</a>
<ul>
<li class="chapter" data-level="3.1.1" data-path="causal.html"><a href="causal.html#绘制分布关系"><i class="fa fa-check"></i><b>3.1.1</b> 绘制分布关系</a></li>
<li class="chapter" data-level="3.1.2" data-path="causal.html"><a href="causal.html#绘制数据间关系"><i class="fa fa-check"></i><b>3.1.2</b> 绘制数据间关系</a></li>
<li class="chapter" data-level="3.1.3" data-path="causal.html"><a href="causal.html#绘制其他图形"><i class="fa fa-check"></i><b>3.1.3</b> 绘制其他图形</a></li>
</ul></li>
<li class="chapter" data-level="3.2" data-path="causal.html"><a href="causal.html#修改图形参数"><i class="fa fa-check"></i><b>3.2</b> 修改图形参数</a>
<ul>
<li class="chapter" data-level="3.2.1" data-path="causal.html"><a href="causal.html#修改颜色"><i class="fa fa-check"></i><b>3.2.1</b> 修改颜色</a></li>
<li class="chapter" data-level="3.2.2" data-path="causal.html"><a href="causal.html#修改点符号与线条"><i class="fa fa-check"></i><b>3.2.2</b> 修改点符号与线条</a></li>
</ul></li>
<li class="chapter" data-level="3.3" data-path="causal.html"><a href="causal.html#绘制组合图形"><i class="fa fa-check"></i><b>3.3</b> 绘制组合图形</a>
<ul>
<li class="chapter" data-level="3.3.1" data-path="causal.html"><a href="causal.html#par"><i class="fa fa-check"></i><b>3.3.1</b> par()</a></li>
<li class="chapter" data-level="3.3.2" data-path="causal.html"><a href="causal.html#layout"><i class="fa fa-check"></i><b>3.3.2</b> layout</a></li>
</ul></li>
<li class="chapter" data-level="3.4" data-path="causal.html"><a href="causal.html#保存图形"><i class="fa fa-check"></i><b>3.4</b> 保存图形</a>
<ul>
<li class="chapter" data-level="3.4.1" data-path="causal.html"><a href="causal.html#使用代码"><i class="fa fa-check"></i><b>3.4.1</b> 使用代码</a></li>
<li class="chapter" data-level="3.4.2" data-path="causal.html"><a href="causal.html#在-rstudio-窗口点击按钮保存"><i class="fa fa-check"></i><b>3.4.2</b> 在 Rstudio 窗口点击按钮保存</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="4" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html"><i class="fa fa-check"></i><b>4</b> 使用 ggplot2 包绘图</a>
<ul>
<li class="chapter" data-level="4.1" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#简介-1"><i class="fa fa-check"></i><b>4.1</b> 简介</a></li>
<li class="chapter" data-level="4.2" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#qplot"><i class="fa fa-check"></i><b>4.2</b> qplot</a></li>
<li class="chapter" data-level="4.3" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#ggplot2包图形语法"><i class="fa fa-check"></i><b>4.3</b> ggplot2包图形语法</a>
<ul>
<li class="chapter" data-level="4.3.1" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#对比不同画图语法"><i class="fa fa-check"></i><b>4.3.1</b> 对比不同画图语法</a></li>
<li class="chapter" data-level="4.3.2" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#思想介绍"><i class="fa fa-check"></i><b>4.3.2</b> 思想介绍</a></li>
<li class="chapter" data-level="4.3.3" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#全局变量-vs.-局部变量"><i class="fa fa-check"></i><b>4.3.3</b> 全局变量 vs. 局部变量</a></li>
</ul></li>
<li class="chapter" data-level="4.4" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#几何对象"><i class="fa fa-check"></i><b>4.4</b> 几何对象</a>
<ul>
<li class="chapter" data-level="4.4.1" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#参考书籍"><i class="fa fa-check"></i><b>4.4.1</b> 参考书籍</a></li>
</ul></li>
<li class="chapter" data-level="4.5" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#统计变换"><i class="fa fa-check"></i><b>4.5</b> 统计变换</a></li>
<li class="chapter" data-level="4.6" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#刻度scale"><i class="fa fa-check"></i><b>4.6</b> 刻度scale</a>
<ul>
<li class="chapter" data-level="4.6.1" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#丰富的刻度体系"><i class="fa fa-check"></i><b>4.6.1</b> 丰富的刻度体系</a></li>
</ul></li>
<li class="chapter" data-level="4.7" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#坐标系"><i class="fa fa-check"></i><b>4.7</b> 坐标系</a></li>
<li class="chapter" data-level="4.8" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#分面"><i class="fa fa-check"></i><b>4.8</b> 分面</a></li>
<li class="chapter" data-level="4.9" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#标题标注指南拼接"><i class="fa fa-check"></i><b>4.9</b> 标题、标注、指南、拼接</a>
<ul>
<li class="chapter" data-level="4.9.1" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#标题"><i class="fa fa-check"></i><b>4.9.1</b> 标题</a></li>
<li class="chapter" data-level="4.9.2" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#标注功能"><i class="fa fa-check"></i><b>4.9.2</b> 标注功能</a></li>
<li class="chapter" data-level="4.9.3" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#指南"><i class="fa fa-check"></i><b>4.9.3</b> 指南</a></li>
<li class="chapter" data-level="4.9.4" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#主题"><i class="fa fa-check"></i><b>4.9.4</b> 主题</a></li>
</ul></li>
<li class="chapter" data-level="4.10" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#保存图片"><i class="fa fa-check"></i><b>4.10</b> 保存图片</a></li>
<li class="chapter" data-level="4.11" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#例子"><i class="fa fa-check"></i><b>4.11</b> 例子</a>
<ul>
<li class="chapter" data-level="4.11.1" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#柱状图误差项"><i class="fa fa-check"></i><b>4.11.1</b> 柱状图+误差项</a></li>
<li class="chapter" data-level="4.11.2" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#有正值和负值的柱形图"><i class="fa fa-check"></i><b>4.11.2</b> 有正值和负值的柱形图</a></li>
<li class="chapter" data-level="4.11.3" data-path="ggplot2-plot.html"><a href="ggplot2-plot.html#合并两图"><i class="fa fa-check"></i><b>4.11.3</b> 合并两图</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="5" data-path="main-diagram-types.html"><a href="main-diagram-types.html"><i class="fa fa-check"></i><b>5</b> 常用图形</a>
<ul>
<li class="chapter" data-level="5.1" data-path="main-diagram-types.html"><a href="main-diagram-types.html#散点图-1"><i class="fa fa-check"></i><b>5.1</b> 散点图</a></li>
<li class="chapter" data-level="5.2" data-path="main-diagram-types.html"><a href="main-diagram-types.html#气泡图"><i class="fa fa-check"></i><b>5.2</b> 气泡图</a></li>
<li class="chapter" data-level="5.3" data-path="main-diagram-types.html"><a href="main-diagram-types.html#线性图"><i class="fa fa-check"></i><b>5.3</b> 线性图</a></li>
<li class="chapter" data-level="5.4" data-path="main-diagram-types.html"><a href="main-diagram-types.html#相关系数图热力图"><i class="fa fa-check"></i><b>5.4</b> 相关系数图/热力图</a></li>
<li class="chapter" data-level="5.5" data-path="main-diagram-types.html"><a href="main-diagram-types.html#条形图-1"><i class="fa fa-check"></i><b>5.5</b> 条形图</a></li>
<li class="chapter" data-level="5.6" data-path="main-diagram-types.html"><a href="main-diagram-types.html#箱线图-1"><i class="fa fa-check"></i><b>5.6</b> 箱线图</a></li>
<li class="chapter" data-level="5.7" data-path="main-diagram-types.html"><a href="main-diagram-types.html#小提琴图-1"><i class="fa fa-check"></i><b>5.7</b> 小提琴图</a></li>
<li class="chapter" data-level="5.8" data-path="main-diagram-types.html"><a href="main-diagram-types.html#饼图-1"><i class="fa fa-check"></i><b>5.8</b> 饼图</a></li>
<li class="chapter" data-level="5.9" data-path="main-diagram-types.html"><a href="main-diagram-types.html#冲积图"><i class="fa fa-check"></i><b>5.9</b> 冲积图</a></li>
<li class="chapter" data-level="5.10" data-path="main-diagram-types.html"><a href="main-diagram-types.html#系谱图"><i class="fa fa-check"></i><b>5.10</b> 系谱图</a></li>
<li class="chapter" data-level="5.11" data-path="main-diagram-types.html"><a href="main-diagram-types.html#哑铃图"><i class="fa fa-check"></i><b>5.11</b> 哑铃图</a></li>
<li class="chapter" data-level="5.12" data-path="main-diagram-types.html"><a href="main-diagram-types.html#斜率图"><i class="fa fa-check"></i><b>5.12</b> 斜率图</a></li>
<li class="chapter" data-level="5.13" data-path="main-diagram-types.html"><a href="main-diagram-types.html#堆叠面积图"><i class="fa fa-check"></i><b>5.13</b> 堆叠面积图</a></li>
<li class="chapter" data-level="5.14" data-path="main-diagram-types.html"><a href="main-diagram-types.html#棒棒糖图"><i class="fa fa-check"></i><b>5.14</b> 棒棒糖图</a></li>
<li class="chapter" data-level="5.15" data-path="main-diagram-types.html"><a href="main-diagram-types.html#树状图"><i class="fa fa-check"></i><b>5.15</b> 树状图</a></li>
<li class="chapter" data-level="5.16" data-path="main-diagram-types.html"><a href="main-diagram-types.html#瀑布图"><i class="fa fa-check"></i><b>5.16</b> 瀑布图</a></li>
<li class="chapter" data-level="5.17" data-path="main-diagram-types.html"><a href="main-diagram-types.html#双标图"><i class="fa fa-check"></i><b>5.17</b> 双标图</a></li>
<li class="chapter" data-level="5.18" data-path="main-diagram-types.html"><a href="main-diagram-types.html#雷达图星图蜘蛛图"><i class="fa fa-check"></i><b>5.18</b> 雷达图/星图/蜘蛛图</a></li>
</ul></li>
<li class="chapter" data-level="6" data-path="other-packages.html"><a href="other-packages.html"><i class="fa fa-check"></i><b>6</b> 其他相关拓展包</a>
<ul>
<li class="chapter" data-level="6.1" data-path="other-packages.html"><a href="other-packages.html#ggplot2-官网-109-种拓展包"><i class="fa fa-check"></i><b>6.1</b> ggplot2 官网 109 种拓展包</a></li>
<li class="chapter" data-level="6.2" data-path="other-packages.html"><a href="other-packages.html#整理的相关扩展包"><i class="fa fa-check"></i><b>6.2</b> 整理的相关扩展包</a></li>
</ul></li>
<li class="chapter" data-level="7" data-path="interactive-ploting.html"><a href="interactive-ploting.html"><i class="fa fa-check"></i><b>7</b> 认识交互式绘图工具</a>
<ul>
<li class="chapter" data-level="7.1" data-path="interactive-ploting.html"><a href="interactive-ploting.html#leaflet包"><i class="fa fa-check"></i><b>7.1</b> leaflet包</a></li>
<li class="chapter" data-level="7.2" data-path="interactive-ploting.html"><a href="interactive-ploting.html#dygraphs包"><i class="fa fa-check"></i><b>7.2</b> dygraphs包</a></li>
<li class="chapter" data-level="7.3" data-path="interactive-ploting.html"><a href="interactive-ploting.html#plotly包"><i class="fa fa-check"></i><b>7.3</b> plotly包</a></li>
<li class="chapter" data-level="7.4" data-path="interactive-ploting.html"><a href="interactive-ploting.html#dt包"><i class="fa fa-check"></i><b>7.4</b> DT包</a></li>
<li class="chapter" data-level="7.5" data-path="interactive-ploting.html"><a href="interactive-ploting.html#networkd3包"><i class="fa fa-check"></i><b>7.5</b> networkD3包</a></li>
<li class="chapter" data-level="7.6" data-path="interactive-ploting.html"><a href="interactive-ploting.html#利用shiny包实现可交互的web应用"><i class="fa fa-check"></i><b>7.6</b> 利用Shiny包实现可交互的Web应用</a></li>
</ul></li>
<li class="chapter" data-level="8" data-path="some-tips-alls.html"><a href="some-tips-alls.html"><i class="fa fa-check"></i><b>8</b> 常用案例</a>
<ul>
<li class="chapter" data-level="8.1" data-path="some-tips-alls.html"><a href="some-tips-alls.html#绘制不同分布的-qq-图"><i class="fa fa-check"></i><b>8.1</b> 绘制不同分布的 QQ 图</a>
<ul>
<li class="chapter" data-level="8.1.1" data-path="some-tips-alls.html"><a href="some-tips-alls.html#简单版本"><i class="fa fa-check"></i><b>8.1.1</b> 简单版本</a></li>
<li class="chapter" data-level="8.1.2" data-path="some-tips-alls.html"><a href="some-tips-alls.html#进阶版本"><i class="fa fa-check"></i><b>8.1.2</b> 进阶版本</a></li>
</ul></li>
<li class="chapter" data-level="8.2" data-path="some-tips-alls.html"><a href="some-tips-alls.html#绘制混合密度函数图以及添加分位数线"><i class="fa fa-check"></i><b>8.2</b> 绘制混合密度函数图以及添加分位数线</a>
<ul>
<li class="chapter" data-level="8.2.1" data-path="some-tips-alls.html"><a href="some-tips-alls.html#加载包"><i class="fa fa-check"></i><b>8.2.1</b> 加载包</a></li>
<li class="chapter" data-level="8.2.2" data-path="some-tips-alls.html"><a href="some-tips-alls.html#产生数据集"><i class="fa fa-check"></i><b>8.2.2</b> 产生数据集</a></li>
<li class="chapter" data-level="8.2.3" data-path="some-tips-alls.html"><a href="some-tips-alls.html#绘制密度函数图并添加分位数线"><i class="fa fa-check"></i><b>8.2.3</b> 绘制密度函数图并添加分位数线</a></li>
<li class="chapter" data-level="8.2.4" data-path="some-tips-alls.html"><a href="some-tips-alls.html#合并两图使用cowplot包"><i class="fa fa-check"></i><b>8.2.4</b> 合并两图（使用cowplot包）</a></li>
</ul></li>
<li class="chapter" data-level="8.3" data-path="some-tips-alls.html"><a href="some-tips-alls.html#绘制不同参数的密度函数"><i class="fa fa-check"></i><b>8.3</b> 绘制不同参数的密度函数</a>
<ul>
<li class="chapter" data-level="8.3.1" data-path="some-tips-alls.html"><a href="some-tips-alls.html#beta-密度函数"><i class="fa fa-check"></i><b>8.3.1</b> Beta 密度函数</a></li>
</ul></li>
<li class="chapter" data-level="8.4" data-path="some-tips-alls.html"><a href="some-tips-alls.html#散点图中加入第三变量的密度函数"><i class="fa fa-check"></i><b>8.4</b> 散点图中加入第三变量的密度函数</a></li>
<li class="chapter" data-level="8.5" data-path="some-tips-alls.html"><a href="some-tips-alls.html#绘制-gamma-分布相关图形"><i class="fa fa-check"></i><b>8.5</b> 绘制 Gamma 分布相关图形</a></li>
<li class="chapter" data-level="8.6" data-path="some-tips-alls.html"><a href="some-tips-alls.html#纯手动复现密度图"><i class="fa fa-check"></i><b>8.6</b> 纯手动复现密度图</a></li>
<li class="chapter" data-level="8.7" data-path="some-tips-alls.html"><a href="some-tips-alls.html#绘制贝叶斯分析相关图形"><i class="fa fa-check"></i><b>8.7</b> 绘制贝叶斯分析相关图形</a>
<ul>
<li class="chapter" data-level="8.7.1" data-path="some-tips-alls.html"><a href="some-tips-alls.html#模型建模"><i class="fa fa-check"></i><b>8.7.1</b> 模型建模</a></li>
<li class="chapter" data-level="8.7.2" data-path="some-tips-alls.html"><a href="some-tips-alls.html#后验预测检查"><i class="fa fa-check"></i><b>8.7.2</b> 后验预测检查</a></li>
<li class="chapter" data-level="8.7.3" data-path="some-tips-alls.html"><a href="some-tips-alls.html#诊断"><i class="fa fa-check"></i><b>8.7.3</b> 诊断</a></li>
</ul></li>
</ul></li>
<li class="part"><span><b>III R 语言文档沟通</b></span></li>
<li class="chapter" data-level="9" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html"><i class="fa fa-check"></i><b>9</b> R Markdown 入门教程</a>
<ul>
<li class="chapter" data-level="9.1" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#rmarkdown-简介"><i class="fa fa-check"></i><b>9.1</b> Rmarkdown 简介</a>
<ul>
<li class="chapter" data-level="9.1.1" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#官网视频介绍"><i class="fa fa-check"></i><b>9.1.1</b> 官网视频介绍</a></li>
</ul></li>
<li class="chapter" data-level="9.2" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#rmarkdown-流程演示"><i class="fa fa-check"></i><b>9.2</b> Rmarkdown 流程演示</a>
<ul>
<li class="chapter" data-level="9.2.1" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#安装"><i class="fa fa-check"></i><b>9.2.1</b> 安装</a></li>
<li class="chapter" data-level="9.2.2" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#rstudio界面介绍"><i class="fa fa-check"></i><b>9.2.2</b> Rstudio界面介绍</a></li>
<li class="chapter" data-level="9.2.3" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#代码输出"><i class="fa fa-check"></i><b>9.2.3</b> 代码输出</a></li>
<li class="chapter" data-level="9.2.4" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#图片输出"><i class="fa fa-check"></i><b>9.2.4</b> 图片输出</a></li>
<li class="chapter" data-level="9.2.5" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#表格输出"><i class="fa fa-check"></i><b>9.2.5</b> 表格输出</a></li>
<li class="chapter" data-level="9.2.6" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#表格渲染"><i class="fa fa-check"></i><b>9.2.6</b> 表格渲染</a></li>
</ul></li>
<li class="chapter" data-level="9.3" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#rmarkdown-的主题格式"><i class="fa fa-check"></i><b>9.3</b> Rmarkdown 的主题格式</a>
<ul>
<li class="chapter" data-level="9.3.1" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#rmdformats-包"><i class="fa fa-check"></i><b>9.3.1</b> rmdformats 包</a></li>
<li class="chapter" data-level="9.3.2" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#tufte-包"><i class="fa fa-check"></i><b>9.3.2</b> tufte 包</a></li>
<li class="chapter" data-level="9.3.3" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#cerulean-包"><i class="fa fa-check"></i><b>9.3.3</b> cerulean 包</a></li>
</ul></li>
<li class="chapter" data-level="9.4" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#总结一些常用技巧"><i class="fa fa-check"></i><b>9.4</b> 总结一些常用技巧</a>
<ul>
<li class="chapter" data-level="9.4.1" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#修改某些字体颜色"><i class="fa fa-check"></i><b>9.4.1</b> 修改某些字体颜色</a></li>
<li class="chapter" data-level="9.4.2" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#更改全文页边距等"><i class="fa fa-check"></i><b>9.4.2</b> 更改全文页边距等</a></li>
<li class="chapter" data-level="9.4.3" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#缩进文本"><i class="fa fa-check"></i><b>9.4.3</b> 缩进文本</a></li>
<li class="chapter" data-level="9.4.4" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#分页"><i class="fa fa-check"></i><b>9.4.4</b> 分页</a></li>
<li class="chapter" data-level="9.4.5" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#控制文本输出的宽度"><i class="fa fa-check"></i><b>9.4.5</b> 控制文本输出的宽度</a></li>
<li class="chapter" data-level="9.4.6" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#控制图片输出大小"><i class="fa fa-check"></i><b>9.4.6</b> 控制图片输出大小</a></li>
<li class="chapter" data-level="9.4.7" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#图片对齐"><i class="fa fa-check"></i><b>9.4.7</b> 图片对齐</a></li>
<li class="chapter" data-level="9.4.8" data-path="rmarkdown-base.html"><a href="rmarkdown-base.html#多列输出"><i class="fa fa-check"></i><b>9.4.8</b> 多列输出</a></li>
</ul></li>
</ul></li>
<li class="chapter" data-level="10" data-path="rmarkdown-extended.html"><a href="rmarkdown-extended.html"><i class="fa fa-check"></i><b>10</b> 其他方式的文档沟通</a>
<ul>
<li class="chapter" data-level="10.1" data-path="rmarkdown-extended.html"><a href="rmarkdown-extended.html#typora"><i class="fa fa-check"></i><b>10.1</b> Typora</a></li>
<li class="chapter" data-level="10.2" data-path="rmarkdown-extended.html"><a href="rmarkdown-extended.html#xaringan-幻灯片"><i class="fa fa-check"></i><b>10.2</b> xaringan 幻灯片</a></li>
<li class="chapter" data-level="10.3" data-path="rmarkdown-extended.html"><a href="rmarkdown-extended.html#制作幻灯片"><i class="fa fa-check"></i><b>10.3</b> 制作幻灯片</a></li>
<li class="chapter" data-level="10.4" data-path="rmarkdown-extended.html"><a href="rmarkdown-extended.html#rbeamer"><i class="fa fa-check"></i><b>10.4</b> Rbeamer</a></li>
<li class="chapter" data-level="10.5" data-path="rmarkdown-extended.html"><a href="rmarkdown-extended.html#dashboards"><i class="fa fa-check"></i><b>10.5</b> Dashboards</a></li>
<li class="chapter" data-level="10.6" data-path="rmarkdown-extended.html"><a href="rmarkdown-extended.html#shiny"><i class="fa fa-check"></i><b>10.6</b> shiny</a></li>
<li class="chapter" data-level="10.7" data-path="rmarkdown-extended.html"><a href="rmarkdown-extended.html#blogdown"><i class="fa fa-check"></i><b>10.7</b> blogdown</a></li>
<li class="chapter" data-level="10.8" data-path="rmarkdown-extended.html"><a href="rmarkdown-extended.html#制作简历"><i class="fa fa-check"></i><b>10.8</b> 制作简历</a></li>
<li class="chapter" data-level="10.9" data-path="rmarkdown-extended.html"><a href="rmarkdown-extended.html#bookdown"><i class="fa fa-check"></i><b>10.9</b> bookdown</a></li>
<li class="chapter" data-level="10.10" data-path="rmarkdown-extended.html"><a href="rmarkdown-extended.html#小编有话说"><i class="fa fa-check"></i><b>10.10</b> 小编有话说</a></li>
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<li class="chapter" data-level="11" data-path="appendix.html"><a href="appendix.html"><i class="fa fa-check"></i><b>11</b> 附录</a>
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<li class="chapter" data-level="" data-path="appendix.html"><a href="appendix.html#安装r和rstudio"><i class="fa fa-check"></i>安装R和Rstudio</a>
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<li class="chapter" data-level="" data-path="appendix.html"><a href="appendix.html#安装-r"><i class="fa fa-check"></i>安装 R</a></li>
<li class="chapter" data-level="" data-path="appendix.html"><a href="appendix.html#安装rstudio"><i class="fa fa-check"></i>安装RStudio</a></li>
</ul></li>
<li class="chapter" data-level="" data-path="appendix.html"><a href="appendix.html#可能的问题"><i class="fa fa-check"></i>可能的问题</a></li>
<li class="chapter" data-level="" data-path="appendix.html"><a href="appendix.html#如何获取帮助"><i class="fa fa-check"></i>如何获取帮助</a></li>
<li class="chapter" data-level="" data-path="appendix.html"><a href="appendix.html#r-语言社区"><i class="fa fa-check"></i>R 语言社区</a></li>
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<li class="chapter" data-level="12" data-path="reference.html"><a href="reference.html"><i class="fa fa-check"></i><b>12</b> 参考书籍</a></li>
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<i class="fa fa-circle-o-notch fa-spin"></i><a href="./">庄闪闪的可视化手册</a>
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<div id="ggplot2-plot" class="section level1 hasAnchor" number="4">
<h1><span class="header-section-number">4</span> 使用 ggplot2 包绘图<a href="ggplot2-plot.html#ggplot2-plot" class="anchor-section" aria-label="Anchor link to header"></a></h1>
<div id="简介-1" class="section level2 hasAnchor" number="4.1">
<h2><span class="header-section-number">4.1</span> 简介<a href="ggplot2-plot.html#简介-1" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p>ggplot2 包是 Harley Wickham 在 2005
年创建的，是包含了一套全面而连贯的语法的绘图系统。</p>
<div class="figure">
<img src="figure/15.png" alt="" />
<p class="caption">Harley Wickham</p>
</div>
<p>弥补了R中创建图形缺乏一致性的缺点，且不会局限于一些已经定义好的统计图形，可以根据需要创造出任何有助于解决所遇到问题的图形。</p>
<p><strong>核心理念</strong>：将绘图与数据分离，数据相关的绘图与数据无关的绘图分离，<strong>按图层作图</strong>。</p>
</div>
<div id="qplot" class="section level2 hasAnchor" number="4.2">
<h2><span class="header-section-number">4.2</span> qplot<a href="ggplot2-plot.html#qplot" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p><code>ggplot2</code>包的绘图语言与常用的绘图函数的使用方法不同，为了让读者快速使用<code>ggplot2</code>包，包的作者Harley
Wickham提供了<code>qplot</code>函数（quick
plot），让人在了解<code>ggplot2</code>的语言逻辑之前，就能迅速实现数据的可视化。</p>
<p>鸢尾花数据集<code>iris</code></p>
<div class="sourceCode" id="cb51"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb51-1"><a href="ggplot2-plot.html#cb51-1" aria-hidden="true" tabindex="-1"></a><span class="fu">head</span>(iris,<span class="dv">10</span>)</span></code></pre></div>
<pre><code>## Sepal.Length Sepal.Width Petal.Length Petal.Width Species
## 1 5.1 3.5 1.4 0.2 setosa
## 2 4.9 3.0 1.4 0.2 setosa
## 3 4.7 3.2 1.3 0.2 setosa
## 4 4.6 3.1 1.5 0.2 setosa
## 5 5.0 3.6 1.4 0.2 setosa
## 6 5.4 3.9 1.7 0.4 setosa
## 7 4.6 3.4 1.4 0.3 setosa
## 8 5.0 3.4 1.5 0.2 setosa
## 9 4.4 2.9 1.4 0.2 setosa
## 10 4.9 3.1 1.5 0.1 setosa</code></pre>
<div class="sourceCode" id="cb53"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb53-1"><a href="ggplot2-plot.html#cb53-1" aria-hidden="true" tabindex="-1"></a><span class="fu">str</span>(iris)</span></code></pre></div>
<pre><code>## 'data.frame': 150 obs. of 5 variables:
## $ Sepal.Length: num 5.1 4.9 4.7 4.6 5 5.4 4.6 5 4.4 4.9 ...
## $ Sepal.Width : num 3.5 3 3.2 3.1 3.6 3.9 3.4 3.4 2.9 3.1 ...
## $ Petal.Length: num 1.4 1.4 1.3 1.5 1.4 1.7 1.4 1.5 1.4 1.5 ...
## $ Petal.Width : num 0.2 0.2 0.2 0.2 0.2 0.4 0.3 0.2 0.2 0.1 ...
## $ Species : Factor w/ 3 levels "setosa","versicolor",..: 1 1 1 1 1 1 1 1 1 1 ...</code></pre>
<ul>
<li><strong>例子一：</strong></li>
</ul>
<p>创建一个以物种种类为分组的花萼长度的箱线图，箱线图的颜色依据不同的物种种类而变化。</p>
<div class="sourceCode" id="cb55"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb55-1"><a href="ggplot2-plot.html#cb55-1" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(ggplot2)</span>
<span id="cb55-2"><a href="ggplot2-plot.html#cb55-2" aria-hidden="true" tabindex="-1"></a><span class="fu">qplot</span>(Species, Sepal.Length, <span class="at">data =</span> iris, <span class="at">geom =</span> <span class="st">"boxplot"</span>,</span>
<span id="cb55-3"><a href="ggplot2-plot.html#cb55-3" aria-hidden="true" tabindex="-1"></a> <span class="at">fill =</span> Species,<span class="at">main =</span> <span class="st">"依据种类分组的花萼长度箱线图"</span>)</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-3-1.png" width="672" style="display: block; margin: auto;" /></p>
<div class="sourceCode" id="cb56"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb56-1"><a href="ggplot2-plot.html#cb56-1" aria-hidden="true" tabindex="-1"></a><span class="fu">boxplot</span>(Sepal.Length<span class="sc">~</span>Species,<span class="at">data =</span>iris,<span class="at">main =</span> <span class="st">"依据种类分组的花萼长度箱线图"</span>)</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-3-2.png" width="672" style="display: block; margin: auto;" /></p>
<ul>
<li><strong>例子二：</strong></li>
</ul>
<p>利用<code>qplot</code>函数画出小提琴图，只需要将<code>geom</code>设置为<code>“violon”</code>即可，并添加扰动以减少数据重叠。</p>
<div class="sourceCode" id="cb57"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb57-1"><a href="ggplot2-plot.html#cb57-1" aria-hidden="true" tabindex="-1"></a><span class="fu">qplot</span>(Species, Sepal.Length, <span class="at">data =</span> iris, <span class="at">geom =</span> <span class="fu">c</span>(<span class="st">"violin"</span>, <span class="st">"jitter"</span>), </span>
<span id="cb57-2"><a href="ggplot2-plot.html#cb57-2" aria-hidden="true" tabindex="-1"></a> <span class="at">fill =</span> Species,<span class="at">main =</span> <span class="st">"依据种类分组的花萼长度小提琴图"</span>)</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-4-1.png" width="672" style="display: block; margin: auto;" /></p>
<ul>
<li><strong>例子三：</strong></li>
</ul>
<p>建一个以花萼长度和花萼宽度的散点图，并利用颜色和符号形状区分物种种类。</p>
<div class="sourceCode" id="cb58"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb58-1"><a href="ggplot2-plot.html#cb58-1" aria-hidden="true" tabindex="-1"></a><span class="fu">qplot</span>(Sepal.Length, Sepal.Width, <span class="at">geom =</span> <span class="st">"point"</span>,<span class="at">data =</span> iris, <span class="at">colour =</span> Species, </span>
<span id="cb58-2"><a href="ggplot2-plot.html#cb58-2" aria-hidden="true" tabindex="-1"></a> <span class="at">shape =</span> Species,<span class="at">main =</span> <span class="st">"绘制花萼长度和花萼宽度的散点图"</span>)</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-5-1.png" width="672" style="display: block; margin: auto;" /></p>
<ul>
<li><strong>例子四：</strong></li>
</ul>
<p>利用facets参数绘制分面板散点图,并增加光滑曲线。</p>
<div class="sourceCode" id="cb59"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb59-1"><a href="ggplot2-plot.html#cb59-1" aria-hidden="true" tabindex="-1"></a><span class="fu">qplot</span>(Sepal.Length, Sepal.Width, <span class="at">data =</span> iris, <span class="at">geom =</span> <span class="fu">c</span>(<span class="st">"point"</span>, <span class="st">"smooth"</span>),</span>
<span id="cb59-2"><a href="ggplot2-plot.html#cb59-2" aria-hidden="true" tabindex="-1"></a> <span class="at">facets =</span> <span class="sc">~</span>Species,<span class="at">main =</span> <span class="st">"绘制分面板的散点图"</span>)</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-6-1.png" width="672" style="display: block; margin: auto;" /></p>
</div>
<div id="ggplot2包图形语法" class="section level2 hasAnchor" number="4.3">
<h2><span class="header-section-number">4.3</span> ggplot2包图形语法<a href="ggplot2-plot.html#ggplot2包图形语法" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p><strong>推荐书籍</strong>：</p>
<p>ggplot2: Elegant Graphics for Data Analysis <a href="https://ggplot2-book.org/" class="uri">https://ggplot2-book.org/</a></p>
<p>Fundamentals of Data Visualization <a href="https://clauswilke.com/dataviz/" class="uri">https://clauswilke.com/dataviz/</a></p>
<div id="对比不同画图语法" class="section level3 hasAnchor" number="4.3.1">
<h3><span class="header-section-number">4.3.1</span> 对比不同画图语法<a href="ggplot2-plot.html#对比不同画图语法" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<p>以绘制iris数据集中Sepal.Length与Sepal.Width的散点图为例，分别采用内置的plot函数与ggplot2包的ggplot函数绘制散点图，对比理解ggplot2包的语言逻辑。</p>
<p>代码（三种类型）：</p>
<div class="sourceCode" id="cb60"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb60-1"><a href="ggplot2-plot.html#cb60-1" aria-hidden="true" tabindex="-1"></a><span class="co"># 基础包</span></span>
<span id="cb60-2"><a href="ggplot2-plot.html#cb60-2" aria-hidden="true" tabindex="-1"></a><span class="fu">plot</span>(iris<span class="sc">$</span>Sepal.Length, iris<span class="sc">$</span>Sepal.Width)</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-8-1.png" width="672" style="display: block; margin: auto;" /></p>
<div class="sourceCode" id="cb61"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb61-1"><a href="ggplot2-plot.html#cb61-1" aria-hidden="true" tabindex="-1"></a><span class="co"># qplot()</span></span>
<span id="cb61-2"><a href="ggplot2-plot.html#cb61-2" aria-hidden="true" tabindex="-1"></a><span class="fu">qplot</span>(<span class="at">x =</span> Sepal.Length, <span class="at">y =</span> Sepal.Width,<span class="at">data =</span> iris,<span class="at">geom =</span> <span class="st">"point"</span>)</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-8-2.png" width="672" style="display: block; margin: auto;" /></p>
<div class="sourceCode" id="cb62"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb62-1"><a href="ggplot2-plot.html#cb62-1" aria-hidden="true" tabindex="-1"></a><span class="co"># ggplot()</span></span>
<span id="cb62-2"><a href="ggplot2-plot.html#cb62-2" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data=</span> iris, <span class="fu">aes</span>(<span class="at">x =</span> Sepal.Length, <span class="at">y =</span> Sepal.Width)) <span class="sc">+</span> <span class="co">#绘制底层画布</span></span>
<span id="cb62-3"><a href="ggplot2-plot.html#cb62-3" aria-hidden="true" tabindex="-1"></a><span class="fu">geom_point</span>() <span class="co">#在画布上添加点</span></span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-8-3.png" width="672" style="display: block; margin: auto;" /></p>
</div>
<div id="思想介绍" class="section level3 hasAnchor" number="4.3.2">
<h3><span class="header-section-number">4.3.2</span> 思想介绍<a href="ggplot2-plot.html#思想介绍" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<p><strong>注：</strong>该部分主要参考<a href="https://bookdown.org/wangminjie/R4DS/intro-R.html#%E5%AE%89%E8%A3%85-rstudio">数据科学中的R语言——王敏杰</a>。</p>
<p>ggplot的绘图有以下几个特点。</p>
<ol style="list-style-type: decimal">
<li><p>有明确的起始（以ggplot函数开始）与终止（一句语句一幅图）。</p></li>
<li><p>ggplot2语句可以理解为一句语句绘制一幅图，然后进行图层叠加，而叠加是通过”+“号把绘图语句拼接实现的。</p></li>
</ol>
<p>ggplot函数包括9个部件：</p>
<ul>
<li>数据 (data) （ 数据框）</li>
<li>映射 (mapping)</li>
<li>几何对象 (geom_point() , geom_boxplot())</li>
<li>统计变换 (stats)</li>
<li>标度 (scale)</li>
<li>坐标系 (coord)</li>
<li>分面 (facet)</li>
<li>主题 (theme)</li>
<li>存储和输出 (output)</li>
</ul>
<p>其中前三个是必需的。</p>
<p>Hadley
Wickham将这套可视化语法诠释为：一张统计图形就是从<strong>数据</strong>到<strong>几何对象</strong>(geometric
object，缩写geom)的<strong>图形属性</strong>(aesthetic
attribute，缩写aes)的一个映射。</p>
<p><img src="figure/10.png" /></p>
<p>此外，图形中还可能包含数据的<strong>统计变换</strong>(statistical
transformation，缩写stats)，最后绘制在某个特定的<strong>坐标系</strong>(coordinate
system，缩写coord)中，而<strong>分面</strong>(facet)则可以用来生成数据不同子集的图形。</p>
<div class="figure">
<img src="figure/11.png" alt="" />
<p class="caption">语法模板</p>
</div>
<div class="figure">
<img src="figure/22.png" alt="" />
<p class="caption">把这看懂其实差不多了</p>
</div>
<p><strong>例子（带你入门）</strong></p>
<div class="sourceCode" id="cb63"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb63-1"><a href="ggplot2-plot.html#cb63-1" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> iris, <span class="at">mapping =</span> <span class="fu">aes</span>(Petal.Length,Petal.Width)) <span class="sc">+</span></span>
<span id="cb63-2"><a href="ggplot2-plot.html#cb63-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>(<span class="at">size =</span> <span class="dv">2</span>,<span class="at">alpha =</span> <span class="fl">0.5</span>,<span class="at">col =</span><span class="st">"red"</span>) <span class="sc">+</span></span>
<span id="cb63-3"><a href="ggplot2-plot.html#cb63-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_smooth</span>(<span class="at">method =</span> <span class="st">"lm"</span>,<span class="at">se =</span> F)</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-9-1.png" width="672" style="display: block; margin: auto;" /></p>
</div>
<div id="全局变量-vs.-局部变量" class="section level3 hasAnchor" number="4.3.3">
<h3><span class="header-section-number">4.3.3</span> 全局变量 vs. 局部变量<a href="ggplot2-plot.html#全局变量-vs.-局部变量" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<div class="sourceCode" id="cb64"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb64-1"><a href="ggplot2-plot.html#cb64-1" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> iris, <span class="at">mapping =</span> <span class="fu">aes</span>(<span class="at">x =</span> Petal.Length,<span class="at">y =</span> Petal.Width, <span class="at">col =</span> Species)) <span class="sc">+</span></span>
<span id="cb64-2"><a href="ggplot2-plot.html#cb64-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>() </span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-10-1.png" width="672" style="display: block; margin: auto;" /></p>
<div class="sourceCode" id="cb65"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb65-1"><a href="ggplot2-plot.html#cb65-1" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> iris) <span class="sc">+</span></span>
<span id="cb65-2"><a href="ggplot2-plot.html#cb65-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>(<span class="at">mapping =</span> <span class="fu">aes</span>(<span class="at">x =</span> Petal.Length,<span class="at">y =</span> Petal.Width, <span class="at">col =</span> Species))</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-10-2.png" width="672" style="display: block; margin: auto;" /></p>
<p>大家可以看到，以上两段代码出来的图是一样。但背后的含义却不同。</p>
<p><strong>例子(观察两者之间的区别)</strong></p>
<div class="sourceCode" id="cb66"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb66-1"><a href="ggplot2-plot.html#cb66-1" aria-hidden="true" tabindex="-1"></a><span class="co">#版本一</span></span>
<span id="cb66-2"><a href="ggplot2-plot.html#cb66-2" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> iris, <span class="at">mapping =</span> <span class="fu">aes</span>(<span class="at">x =</span> Petal.Length,<span class="at">y =</span> Petal.Width, <span class="at">col =</span> Species)) <span class="sc">+</span></span>
<span id="cb66-3"><a href="ggplot2-plot.html#cb66-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>() <span class="sc">+</span> </span>
<span id="cb66-4"><a href="ggplot2-plot.html#cb66-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_smooth</span>() </span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-11-1.png" width="672" style="display: block; margin: auto;" /></p>
<div class="sourceCode" id="cb67"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb67-1"><a href="ggplot2-plot.html#cb67-1" aria-hidden="true" tabindex="-1"></a><span class="co"># 版本二</span></span>
<span id="cb67-2"><a href="ggplot2-plot.html#cb67-2" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> iris, <span class="at">mapping =</span> <span class="fu">aes</span>(<span class="at">x =</span> Petal.Length,<span class="at">y =</span> Petal.Width)) <span class="sc">+</span></span>
<span id="cb67-3"><a href="ggplot2-plot.html#cb67-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>(<span class="at">mapping =</span> <span class="fu">aes</span>(<span class="at">col =</span> Species)) <span class="sc">+</span> </span>
<span id="cb67-4"><a href="ggplot2-plot.html#cb67-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_smooth</span>()</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-11-2.png" width="672" style="display: block; margin: auto;" /></p>
</div>
</div>
<div id="几何对象" class="section level2 hasAnchor" number="4.4">
<h2><span class="header-section-number">4.4</span> 几何对象<a href="ggplot2-plot.html#几何对象" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p><code>geom_xxx()</code>提供了各种基本图形。 列表如下：</p>
<ul>
<li><p>基础图形：</p>
<ul>
<li><code>geom_blank()</code>不画图，可以按映射的变量设定坐标范围；</li>
<li><code>geom_point()</code>每个观测为一个散点；</li>
<li><code>geom_hline()</code>, <code>geom_vline()</code>, <code>geom_abline()</code>画线；</li>
<li><code>geom_path()</code>每个观测提供坐标，在相邻观测之间连线；</li>
<li><code>geom_ribbon()</code>需要x和ymin,
ymax维，在从小到大排序后的相邻观测之间连接阴影区域；</li>
<li><code>geom_segment()</code>需要x, y和xend, yend，为每个观测画一条线段；</li>
<li><code>geom_rect()</code>需要xmin, xmax, ymin,
ymax，为每个观测画一个长方形，可有填充色；</li>
<li><code>geom_polygon()</code>需要x,
y，将相邻观测连续并连接成一个闭合的多边形，中间填充颜色；</li>
<li><code>geom_text()</code>需要x, y和lable，每个观测画一条文字标签。</li>
</ul></li>
<li><p>单变量图层：</p>
<ul>
<li><code>geom_bar()</code>, <code>geom_col()</code>作条形图；</li>
<li><code>geom_histogram()</code>对连续变量x作直方图；</li>
<li><code>geom_density()</code>对连续变量x作一元密度估计曲线；</li>
<li><code>geom_dotplot()</code>用原点作直方图；</li>
<li><code>geom_freqpoly()</code>用折线作直方图。</li>
</ul></li>
<li><p>两变量图形：</p>
<ul>
<li><p>两个连续变量x, y：</p>
<ul>
<li><code>geom_point()</code>散点图；</li>
<li><code>geom_quantile()</code>拟合分位数回归曲线；</li>
<li><code>geom_rug()</code>在坐标轴处画数值对应的短须线；</li>
<li><code>geom_smooth()</code>画各种拟合曲线；</li>
<li><code>geom_text()</code>在指定的x, y位置画label给出的文字标签；</li>
</ul></li>
<li><p>显示二元分布:</p>
<ul>
<li><code>geom_bin2d()</code>作长方形分块的二维直方图；</li>
<li><code>geom_density2d()</code>作二元密度估计等值线图；</li>
<li><code>geom_hex()</code>作正六边形分块的二维直方图。</li>
</ul></li>
<li><p>两个变量中有分类变量时：</p>
<ul>
<li><code>geom_count()</code>：重叠点越多画点越大；</li>
<li><code>geom_jitter()</code>:
随机扰动散点位置避免重叠，数值变量有重叠时也可以用；</li>
</ul></li>
<li><p>一个连续变量和一个分类变量：</p>
<ul>
<li><code>geom_col()</code>作条形图，对分类变量的每个值画一个条形，长度与连续变量值成比例；</li>
<li><code>geom_boxplot()</code>对每个类做一个盒形图；</li>
<li><code>geom_violin()</code>对每个类做一个小提琴图。</li>
</ul></li>
<li><p>一个时间变量和一个连续变量：</p>
<ul>
<li><code>geom_area()</code>作阴影曲线图，曲线下方填充阴影色；</li>
<li><code>geom_line()</code>作折线图，在相邻两个时间之间连接线段；</li>
<li><code>geom_step()</code>作阶梯函数图，在相邻两个时间之间连接阶梯函数线。</li>
</ul></li>
<li><p>不确定性：</p>
<ul>
<li><code>geom_crossbar()</code>对每个观测输入的x, y, ymin,
ymax画中间有线的纵向条形；</li>
<li><code>geom_errbar()</code>对每个观测输入的x, ymin, ymax画纵向误差条；</li>
<li><code>geom_linerange()</code>对每个观测输入的x, ymin, ymax画一条竖线；</li>
<li><code>geom_pointrnage()</code>对每个观测输入的x, y, ymin,
ymax画一条中间有点的竖线。</li>
</ul></li>
</ul></li>
<li><p>地图：</p>
<ul>
<li><code>geom_map()</code>: 用区域边界坐标数据画边界线地图。</li>
</ul></li>
<li><p>三个变量：</p>
<ul>
<li><p><code>geom_contour()</code>: 用输入的x, y, z数据画等值线图。</p></li>
<li><p><code>geom_tile()</code>用输入的x, y位置, width,
height大小和指定的fill维画长方形色块填充图。</p></li>
<li><p><code>geom_raster()</code>是<code>geom_tile()</code>的长方形大小相同时的快速版本。</p></li>
</ul></li>
</ul>
<div id="参考书籍" class="section level3 hasAnchor" number="4.4.1">
<h3><span class="header-section-number">4.4.1</span> 参考书籍<a href="ggplot2-plot.html#参考书籍" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<p>由于这部分内容非常的多，短短两小时不可能讲完，这里给了一些参考资料，各个都是满满的干货。</p>
<ul>
<li><p><a href="https://bookdown.org/wangminjie/R4DS/ggplot2-geom.html#%E5%9F%BA%E6%9C%AC%E7%BB%98%E5%9B%BE">数据科学中的R-第14章ggplot之集合对象</a></p></li>
<li><p><a href="https://www.math.pku.edu.cn/teachers/lidf/docs/Rbook/html/_Rbook/ggplotvis.html">R语言教程第30节-ggplot各种图形</a></p></li>
<li><p><a href="http://r-statistics.co/Top50-Ggplot2-Visualizations-MasterList-R-Code.html">Top 50 ggplot2
Visualizations</a></p></li>
<li><p><a href="http://r4ds.had.co.nz/data-visualisation.html">Chapter 3: Data
Visualisation</a> of <em>R
for Data Science</em></p></li>
<li><p><a href="http://r4ds.had.co.nz/graphics-for-communication.html">Chapter 28: Graphics for
communication</a>
of <em>R for Data Science</em></p></li>
<li><p><a href="https://r-graphics.org/">Graphs</a> in <em>R Graphics Cookbook</em></p></li>
</ul>
</div>
</div>
<div id="统计变换" class="section level2 hasAnchor" number="4.5">
<h2><span class="header-section-number">4.5</span> 统计变换<a href="ggplot2-plot.html#统计变换" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p><strong>概念</strong>：对数据所应用的统计类型/方法。</p>
<p>ggplot2为每一种几何类型指定了一种默认的统计类型，如果仅指定geom或stat中的一个，另外一个会自动获取。其中，stat_identity则表示不做任何的统计变换。</p>
<p><strong>示例</strong>：只需指定geom或stat中的一个，具体细小细节可以参考这
<a href="https://bookdown.org/wangminjie/R4DS/ggplot2-stat-layer.html" class="uri">https://bookdown.org/wangminjie/R4DS/ggplot2-stat-layer.html</a></p>
<div class="sourceCode" id="cb68"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb68-1"><a href="ggplot2-plot.html#cb68-1" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(iris) <span class="sc">+</span> </span>
<span id="cb68-2"><a href="ggplot2-plot.html#cb68-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_bar</span>(<span class="fu">aes</span>(<span class="at">x=</span>Sepal.Length), <span class="at">stat=</span><span class="st">"bin"</span>, <span class="at">binwidth =</span> <span class="fl">0.5</span>)</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-12-1.png" width="672" style="display: block; margin: auto;" /></p>
<div class="sourceCode" id="cb69"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb69-1"><a href="ggplot2-plot.html#cb69-1" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(iris) <span class="sc">+</span> </span>
<span id="cb69-2"><a href="ggplot2-plot.html#cb69-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">stat_bin</span>(<span class="fu">aes</span>(<span class="at">x=</span>Sepal.Length), <span class="at">geom=</span><span class="st">"bar"</span>, <span class="at">binwidth =</span> <span class="fl">0.5</span>)</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-12-2.png" width="672" style="display: block; margin: auto;" /></p>
</div>
<div id="刻度scale" class="section level2 hasAnchor" number="4.6">
<h2><span class="header-section-number">4.6</span> 刻度scale<a href="ggplot2-plot.html#刻度scale" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p>这一节我们一起学习ggplot2中的scales语法，推荐大家阅读Hadley
Wickham最新版的<a href="https://ggplot2-book.org/">《ggplot2: Elegant Graphics for Data
Analysis》</a>，但如果需要详细了解<strong>标度</strong>参数体系，还是要看<a href="https://cran.r-project.org/web/packages/ggplot2/index.html">ggplot2官方文档</a></p>
<p>在<code>ggplot()</code>的mapping参数中指定x维、y维、color维等，实际上每一维度都有一个<strong>对应的默认刻度</strong>(scale)，即，将<strong>数据值映射到图形中的映射方法</strong>。</p>
<p>如果需要修改刻度对应的变换或者标度方法，可以调用相应的scale_xxx()函数。</p>
<p><strong>画图都没用到scale啊！</strong></p>
<p>能画个很漂亮的图，那是因为ggplot2默认缺省条件下，已经很美观了。（据说Hadley
Wickham很后悔使用了这么漂亮的缺省值，因为很漂亮了大家都不认真学画图了。马云好像也说后悔创立了阿里巴巴？）</p>
<div class="sourceCode" id="cb70"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb70-1"><a href="ggplot2-plot.html#cb70-1" aria-hidden="true" tabindex="-1"></a><span class="co">#解释</span></span>
<span id="cb70-2"><a href="ggplot2-plot.html#cb70-2" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> iris, <span class="at">mapping =</span> <span class="fu">aes</span>(<span class="at">x =</span> Petal.Length,<span class="at">y =</span> Petal.Width, <span class="at">col =</span> Species)) <span class="sc">+</span></span>
<span id="cb70-3"><a href="ggplot2-plot.html#cb70-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>() <span class="sc">+</span> </span>
<span id="cb70-4"><a href="ggplot2-plot.html#cb70-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_smooth</span>() </span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-13-1.png" width="672" style="display: block; margin: auto;" /></p>
<div id="丰富的刻度体系" class="section level3 hasAnchor" number="4.6.1">
<h3><span class="header-section-number">4.6.1</span> 丰富的刻度体系<a href="ggplot2-plot.html#丰富的刻度体系" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<p><strong>注意：</strong>标度函数是由”_“分割的三个部分构成的 - scale - 视觉属性名
(e.g., colour, shape or x) - 标度名 (e.g., continuous, discrete,
brewer).</p>
<ul>
<li>将数据变量映射到具体的位置、颜色、填充色、大小、符号等。</li>
</ul>
<p><img src="figure/23.jpg" /></p>
<p>每个标度函数内部都有丰富的参数系统</p>
<pre><code>scale_colour_manual(
palette = function(),
limits = NULL,
name = waiver(),
labels = waiver(),
breaks = waiver(),
minor_breaks = waiver(),
values = waiver(),
...
)</code></pre>
<ul>
<li><p>参数<code>name</code>，坐标和图例的名字，如果不想要图例的名字，就可以
<code>name = NULL</code></p></li>
<li><p>参数<code>limits</code>,
坐标或图例的范围区间。连续性<code>c(n, m)</code>，离散型<code>c("a", "b", "c")</code></p></li>
<li><p>参数<code>breaks</code>, 控制显示在坐标轴或者图例上的值（元素）</p></li>
<li><p>参数<code>labels</code>, 坐标和图例的间隔标签</p>
<ul>
<li>一般情况下，内置函数会自动完成</li>
<li>也可人工指定一个字符型向量，与<code>breaks</code>提供的字符型向量一一对应</li>
<li>也可以是函数，把<code>breaks</code>提供的字符型向量当做函数的输入</li>
<li><code>NULL</code>，就是去掉标签</li>
</ul></li>
<li><p>参数<code>values</code> 指的是（颜色、形状等）视觉属性值,</p>
<ul>
<li>要么，与数值的顺序一致；</li>
<li>要么，与<code>breaks</code>提供的字符型向量长度一致</li>
<li>要么，用命名向量<code>c("数据标签" = "视觉属性")</code>提供</li>
</ul></li>
<li><p>参数<code>expand</code>, 控制参数溢出量</p></li>
<li><p>参数<code>range</code>, 设置尺寸大小范围，比如针对点的相对大小</p></li>
</ul>
<p>下面，我们通过具体的案例讲解如何使用参数，把图形变成我们想要的模样。</p>
<p><strong>例子</strong>：随机从iris数据集的150个样本中抽取100个样本，并绘制条形图反映100个样本中各个鸢尾花种类的数量情况。然后通过修改标尺参数做前后对比图，进而理解标尺在ggplot2包中的作用。</p>
<div class="sourceCode" id="cb72"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb72-1"><a href="ggplot2-plot.html#cb72-1" aria-hidden="true" tabindex="-1"></a><span class="fu">set.seed</span>(<span class="dv">1</span>) <span class="co"># 设置随机种子</span></span>
<span id="cb72-2"><a href="ggplot2-plot.html#cb72-2" aria-hidden="true" tabindex="-1"></a>my_iris <span class="ot"><-</span> iris[<span class="fu">sample</span>(<span class="dv">1</span><span class="sc">:</span><span class="dv">150</span>, <span class="dv">100</span>, <span class="at">replace =</span> <span class="cn">FALSE</span>),] <span class="co"># 随机抽样</span></span>
<span id="cb72-3"><a href="ggplot2-plot.html#cb72-3" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb72-4"><a href="ggplot2-plot.html#cb72-4" aria-hidden="true" tabindex="-1"></a>p <span class="ot"><-</span> <span class="fu">ggplot</span>(my_iris) <span class="sc">+</span> </span>
<span id="cb72-5"><a href="ggplot2-plot.html#cb72-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_bar</span>(<span class="fu">aes</span>(<span class="at">x =</span> Species, <span class="at">fill =</span> Species))</span>
<span id="cb72-6"><a href="ggplot2-plot.html#cb72-6" aria-hidden="true" tabindex="-1"></a>p</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-14-1.png" width="672" style="display: block; margin: auto;" /></p>
<div class="sourceCode" id="cb73"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb73-1"><a href="ggplot2-plot.html#cb73-1" aria-hidden="true" tabindex="-1"></a>p <span class="sc">+</span> <span class="fu">scale_fill_manual</span>(</span>
<span id="cb73-2"><a href="ggplot2-plot.html#cb73-2" aria-hidden="true" tabindex="-1"></a> <span class="at">values =</span> <span class="fu">c</span>(<span class="st">"orange"</span>, <span class="st">"red"</span>, <span class="st">"lightyellow3"</span>), <span class="co"># 颜色设置</span></span>
<span id="cb73-3"><a href="ggplot2-plot.html#cb73-3" aria-hidden="true" tabindex="-1"></a> <span class="at">name =</span> <span class="cn">NULL</span>, <span class="co"># 图例和轴使用的名称</span></span>
<span id="cb73-4"><a href="ggplot2-plot.html#cb73-4" aria-hidden="true" tabindex="-1"></a> <span class="at">labels =</span> <span class="fu">c</span>(<span class="st">"set"</span>, <span class="st">"ver"</span>, <span class="st">"vir"</span>) <span class="co"># 图例使用的标签</span></span>
<span id="cb73-5"><a href="ggplot2-plot.html#cb73-5" aria-hidden="true" tabindex="-1"></a>) <span class="sc">+</span> </span>
<span id="cb73-6"><a href="ggplot2-plot.html#cb73-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_x_discrete</span>(<span class="at">labels =</span> <span class="fu">c</span>(<span class="st">"set"</span>, <span class="st">"ver"</span>, <span class="st">"vir"</span>),<span class="at">name =</span> <span class="st">"A"</span>) <span class="sc">+</span></span>
<span id="cb73-7"><a href="ggplot2-plot.html#cb73-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_y_continuous</span>(<span class="at">name =</span> <span class="st">"B"</span>,<span class="at">breaks =</span> <span class="fu">c</span>(<span class="dv">20</span>,<span class="dv">40</span>)) <span class="sc">+</span></span>
<span id="cb73-8"><a href="ggplot2-plot.html#cb73-8" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_bw</span>()</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-14-2.png" width="672" style="display: block; margin: auto;" /></p>
<p>使用<code>scale_color_manual</code>或<code>scale_color_brewer</code>函数修改图形的颜色。在对iris数据集中的Sepal.Length与Sepal.Width的散点图分别使用以上两种方法修改散点颜色</p>
<div class="sourceCode" id="cb74"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb74-1"><a href="ggplot2-plot.html#cb74-1" aria-hidden="true" tabindex="-1"></a><span class="co">#图一：使用scale_color_manual函数</span></span>
<span id="cb74-2"><a href="ggplot2-plot.html#cb74-2" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(iris, <span class="fu">aes</span>(<span class="at">x =</span> Sepal.Length, <span class="at">y =</span> Sepal.Width, <span class="at">colour =</span> Species))<span class="sc">+</span></span>
<span id="cb74-3"><a href="ggplot2-plot.html#cb74-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>(<span class="at">size =</span> <span class="dv">2</span>) <span class="sc">+</span></span>
<span id="cb74-4"><a href="ggplot2-plot.html#cb74-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_color_manual</span>(<span class="at">values =</span> <span class="fu">c</span>(<span class="st">"orange"</span>, <span class="st">"olivedrab"</span>, <span class="st">"navy"</span>),</span>
<span id="cb74-5"><a href="ggplot2-plot.html#cb74-5" aria-hidden="true" tabindex="-1"></a> <span class="at">name =</span> <span class="cn">NULL</span>) </span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-16-1.png" width="672" style="display: block; margin: auto;" /></p>
<div class="sourceCode" id="cb75"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb75-1"><a href="ggplot2-plot.html#cb75-1" aria-hidden="true" tabindex="-1"></a><span class="co">#图二:使用scale_color_brewer函数</span></span>
<span id="cb75-2"><a href="ggplot2-plot.html#cb75-2" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(iris,<span class="fu">aes</span>(<span class="at">x =</span> Sepal.Length, <span class="at">y =</span> Sepal.Width, <span class="at">colour =</span> Species))<span class="sc">+</span></span>
<span id="cb75-3"><a href="ggplot2-plot.html#cb75-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_color_grey</span>()<span class="sc">+</span></span>
<span id="cb75-4"><a href="ggplot2-plot.html#cb75-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>(<span class="at">size=</span><span class="dv">2</span>) </span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-16-2.png" width="672" style="display: block; margin: auto;" /></p>
<div class="sourceCode" id="cb76"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb76-1"><a href="ggplot2-plot.html#cb76-1" aria-hidden="true" tabindex="-1"></a><span class="co"># library(RColorBrewer)</span></span>
<span id="cb76-2"><a href="ggplot2-plot.html#cb76-2" aria-hidden="true" tabindex="-1"></a><span class="co"># brewer.pal(3, "Set1")</span></span>
<span id="cb76-3"><a href="ggplot2-plot.html#cb76-3" aria-hidden="true" tabindex="-1"></a><span class="co"># display.brewer.all()</span></span></code></pre></div>
</div>
</div>
<div id="坐标系" class="section level2 hasAnchor" number="4.7">
<h2><span class="header-section-number">4.7</span> 坐标系<a href="ggplot2-plot.html#坐标系" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p>ggplot2默认的坐标系是笛卡尔坐标系，可以用如下方法指定取值范围：<code>coord_cartesian(xlim = c(0,5), ylim = c(0, 3))</code>。</p>
<p><code>coord_flip</code>：x轴和y轴换位置。</p>
<p><code>coord_polar(theta = "x",direction=1)</code>是角度坐标系,theta指定角度对应的变量，start指定起点离12点钟方向的偏离值，direction若为1表示顺时针方向，若为-1表示逆时针方向。</p>
<div class="sourceCode" id="cb77"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb77-1"><a href="ggplot2-plot.html#cb77-1" aria-hidden="true" tabindex="-1"></a><span class="co"># 饼图 = 堆叠长条图 + polar_coordinates</span></span>
<span id="cb77-2"><a href="ggplot2-plot.html#cb77-2" aria-hidden="true" tabindex="-1"></a>pie <span class="ot"><-</span> <span class="fu">ggplot</span>(my_iris, <span class="fu">aes</span>(<span class="at">x =</span> <span class="fu">factor</span>(<span class="dv">1</span>), <span class="at">fill =</span> Species)) <span class="sc">+</span></span>
<span id="cb77-3"><a href="ggplot2-plot.html#cb77-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_bar</span>(<span class="at">width =</span> <span class="dv">1</span>)</span>
<span id="cb77-4"><a href="ggplot2-plot.html#cb77-4" aria-hidden="true" tabindex="-1"></a>pie <span class="sc">+</span> <span class="fu">coord_polar</span>(<span class="at">theta =</span> <span class="st">"y"</span>,<span class="at">direction =</span> <span class="sc">-</span><span class="dv">1</span>,<span class="at">start =</span> <span class="dv">30</span>)</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-17-1.png" width="672" style="display: block; margin: auto;" /></p>
<div class="sourceCode" id="cb78"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb78-1"><a href="ggplot2-plot.html#cb78-1" aria-hidden="true" tabindex="-1"></a><span class="co"># 靶心图 = 饼图 + polar_coordinates</span></span>
<span id="cb78-2"><a href="ggplot2-plot.html#cb78-2" aria-hidden="true" tabindex="-1"></a>pie <span class="sc">+</span> <span class="fu">coord_polar</span>()</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-17-2.png" width="672" style="display: block; margin: auto;" /></p>
<div class="sourceCode" id="cb79"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb79-1"><a href="ggplot2-plot.html#cb79-1" aria-hidden="true" tabindex="-1"></a><span class="co">#锯齿图 = 柱状图 + polar_coordinates</span></span>
<span id="cb79-2"><a href="ggplot2-plot.html#cb79-2" aria-hidden="true" tabindex="-1"></a>cxc <span class="ot"><-</span> <span class="fu">ggplot</span>(my_iris, <span class="fu">aes</span>(<span class="at">x =</span> Species)) <span class="sc">+</span></span>
<span id="cb79-3"><a href="ggplot2-plot.html#cb79-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_bar</span>(<span class="at">width =</span> <span class="dv">1</span>, <span class="at">colour =</span> <span class="st">"black"</span>)</span>
<span id="cb79-4"><a href="ggplot2-plot.html#cb79-4" aria-hidden="true" tabindex="-1"></a>cxc <span class="sc">+</span> <span class="fu">coord_polar</span>()</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-17-3.png" width="672" style="display: block; margin: auto;" /></p>
</div>
<div id="分面" class="section level2 hasAnchor" number="4.8">
<h2><span class="header-section-number">4.8</span> 分面<a href="ggplot2-plot.html#分面" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p>分面，就是分组绘图，根据定义的规则，将数据分为多个子集，每个子集按照统一的规则单独制图，排布在一个页面上。</p>
<p>ggplot2提供两种分面方法：<code>facet_grid</code>函数和<code>facet_wrap</code>函数。</p>
<p><strong>1. facet_grid函数</strong></p>
<p>注意<code>facet_grid</code>函数是一个二维的矩形布局，每个子集的位置由行位置变量~列位置变量的决定</p>
<div class="sourceCode" id="cb80"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb80-1"><a href="ggplot2-plot.html#cb80-1" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(ggplot2)</span>
<span id="cb80-2"><a href="ggplot2-plot.html#cb80-2" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(tidyr)</span>
<span id="cb80-3"><a href="ggplot2-plot.html#cb80-3" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(dplyr)</span>
<span id="cb80-4"><a href="ggplot2-plot.html#cb80-4" aria-hidden="true" tabindex="-1"></a>my_iris1 <span class="ot"><-</span> iris <span class="sc">%>%</span> <span class="fu">gather</span>(feature_name, feature_value, <span class="fu">one_of</span>(<span class="fu">c</span>(<span class="st">"Sepal.Length"</span>, <span class="st">"Sepal.Width"</span>, <span class="st">"Petal.Length"</span>, <span class="st">"Petal.Width"</span>))) <span class="co"># 数据变换</span></span>
<span id="cb80-5"><a href="ggplot2-plot.html#cb80-5" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(my_iris1) <span class="sc">+</span> </span>
<span id="cb80-6"><a href="ggplot2-plot.html#cb80-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_violin</span>(<span class="fu">aes</span>(<span class="at">x =</span> Species, <span class="at">y =</span> feature_value)) <span class="sc">+</span> <span class="co"># 绘制小提琴图</span></span>
<span id="cb80-7"><a href="ggplot2-plot.html#cb80-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">facet_grid</span>(feature_name <span class="sc">~</span> Species, <span class="at">scales =</span> <span class="st">"free"</span>) <span class="co"># 分面</span></span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-18-1.png" width="672" style="display: block; margin: auto;" /></p>
<div class="sourceCode" id="cb81"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb81-1"><a href="ggplot2-plot.html#cb81-1" aria-hidden="true" tabindex="-1"></a><span class="co"># iris例子</span></span>
<span id="cb81-2"><a href="ggplot2-plot.html#cb81-2" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> iris, <span class="at">mapping =</span> <span class="fu">aes</span>(<span class="at">x =</span> Sepal.Length, <span class="at">y =</span> Sepal.Width)) <span class="sc">+</span> <span class="co"># 底层画布</span></span>
<span id="cb81-3"><a href="ggplot2-plot.html#cb81-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>() <span class="sc">+</span></span>
<span id="cb81-4"><a href="ggplot2-plot.html#cb81-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_smooth</span>() <span class="sc">+</span></span>
<span id="cb81-5"><a href="ggplot2-plot.html#cb81-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">facet_grid</span>(<span class="sc">~</span>Species)</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-19-1.png" width="672" style="display: block; margin: auto;" /></p>
<p><strong>2. facet_wrap函数</strong></p>
<p>facet_wrap函数生成一个动态调整的一维布局，根据”~位置变量1+位置变量2+…“来确定每个子集的位置，先逐行排列，放不下了移动到下一行。</p>
<div class="sourceCode" id="cb82"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb82-1"><a href="ggplot2-plot.html#cb82-1" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(my_iris1) <span class="sc">+</span></span>
<span id="cb82-2"><a href="ggplot2-plot.html#cb82-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_violin</span>(<span class="fu">aes</span>(<span class="at">x =</span> Species, <span class="at">y =</span> feature_value)) <span class="sc">+</span></span>
<span id="cb82-3"><a href="ggplot2-plot.html#cb82-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">facet_wrap</span>(<span class="sc">~</span> feature_name <span class="sc">+</span> Species, <span class="at">scales =</span> <span class="st">"free_y"</span>,<span class="at">nrow =</span> <span class="dv">3</span>,</span>
<span id="cb82-4"><a href="ggplot2-plot.html#cb82-4" aria-hidden="true" tabindex="-1"></a> <span class="at">strip.position =</span> <span class="st">"bottom"</span>)</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-20-1.png" width="672" style="display: block; margin: auto;" /></p>
<div class="sourceCode" id="cb83"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb83-1"><a href="ggplot2-plot.html#cb83-1" aria-hidden="true" tabindex="-1"></a><span class="co"># iris例子</span></span>
<span id="cb83-2"><a href="ggplot2-plot.html#cb83-2" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> iris, <span class="at">mapping =</span> <span class="fu">aes</span>(<span class="at">x =</span> Sepal.Length, <span class="at">y =</span> Sepal.Width)) <span class="sc">+</span> <span class="co"># 底层画布</span></span>
<span id="cb83-3"><a href="ggplot2-plot.html#cb83-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>() <span class="sc">+</span></span>
<span id="cb83-4"><a href="ggplot2-plot.html#cb83-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_smooth</span>()<span class="sc">+</span></span>
<span id="cb83-5"><a href="ggplot2-plot.html#cb83-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">facet_wrap</span>(<span class="sc">~</span>Species)</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-21-1.png" width="672" style="display: block; margin: auto;" /></p>
</div>
<div id="标题标注指南拼接" class="section level2 hasAnchor" number="4.9">
<h2><span class="header-section-number">4.9</span> 标题、标注、指南、拼接<a href="ggplot2-plot.html#标题标注指南拼接" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p>除了<code>ggplot()</code>指定数据与映射，<code>geom_xxx()</code>作图，还可以用许多辅助函数增强图形。</p>
<ul>
<li><code>labs()</code>可以设置适当的标题和标签。</li>
<li><code>annotate()</code>函数可以直接在坐标系内进行<em>文字、符号、线段、箭头、长方形</em>的绘制。</li>
<li><code>guides()</code>函数可以控制图例的取舍以及做法。</li>
<li><code>theme()</code>函数可以控制一些整体的选项如背景色、字体类型、图例的摆放位置等。</li>
</ul>
<div id="标题" class="section level3 hasAnchor" number="4.9.1">
<h3><span class="header-section-number">4.9.1</span> 标题<a href="ggplot2-plot.html#标题" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<p>函数<code>labs()</code>可以用来指定图形上方的<code>标题(title)</code>、<code>副标题(subtitle)</code>、右下方的<code>标注(caption)</code>、<code>左上方的标签</code>以及<code>坐标轴标题</code>和其它维的名称。
例如：</p>
<div class="sourceCode" id="cb84"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb84-1"><a href="ggplot2-plot.html#cb84-1" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(gapminder)</span>
<span id="cb84-2"><a href="ggplot2-plot.html#cb84-2" aria-hidden="true" tabindex="-1"></a>p <span class="ot"><-</span> <span class="fu">ggplot</span>(<span class="at">data =</span> gapminder,</span>
<span id="cb84-3"><a href="ggplot2-plot.html#cb84-3" aria-hidden="true" tabindex="-1"></a> <span class="at">mapping =</span> <span class="fu">aes</span>(</span>
<span id="cb84-4"><a href="ggplot2-plot.html#cb84-4" aria-hidden="true" tabindex="-1"></a> <span class="at">x =</span> gdpPercap,</span>
<span id="cb84-5"><a href="ggplot2-plot.html#cb84-5" aria-hidden="true" tabindex="-1"></a> <span class="at">y =</span> lifeExp))</span>
<span id="cb84-6"><a href="ggplot2-plot.html#cb84-6" aria-hidden="true" tabindex="-1"></a>p <span class="sc">+</span> <span class="fu">geom_point</span>(<span class="at">alpha =</span> <span class="fl">0.4</span>) <span class="sc">+</span> </span>
<span id="cb84-7"><a href="ggplot2-plot.html#cb84-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(</span>
<span id="cb84-8"><a href="ggplot2-plot.html#cb84-8" aria-hidden="true" tabindex="-1"></a> <span class="at">title =</span> <span class="st">"各国各年度人均GDP与期望寿命的关系"</span>,</span>
<span id="cb84-9"><a href="ggplot2-plot.html#cb84-9" aria-hidden="true" tabindex="-1"></a> <span class="at">subtitle =</span> <span class="st">"1952-2007"</span>,</span>
<span id="cb84-10"><a href="ggplot2-plot.html#cb84-10" aria-hidden="true" tabindex="-1"></a> <span class="at">tag =</span> <span class="st">"散点图"</span>,</span>
<span id="cb84-11"><a href="ggplot2-plot.html#cb84-11" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"数据来源：gapminder"</span>,</span>
<span id="cb84-12"><a href="ggplot2-plot.html#cb84-12" aria-hidden="true" tabindex="-1"></a> <span class="at">x =</span> <span class="st">"人均GDP(单位：美元)"</span>,</span>
<span id="cb84-13"><a href="ggplot2-plot.html#cb84-13" aria-hidden="true" tabindex="-1"></a> <span class="at">y =</span> <span class="st">"期望寿命"</span></span>
<span id="cb84-14"><a href="ggplot2-plot.html#cb84-14" aria-hidden="true" tabindex="-1"></a> )</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-22-1.png" width="672" style="display: block; margin: auto;" /></p>
<div class="sourceCode" id="cb85"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb85-1"><a href="ggplot2-plot.html#cb85-1" aria-hidden="true" tabindex="-1"></a><span class="co">#iris案例</span></span>
<span id="cb85-2"><a href="ggplot2-plot.html#cb85-2" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> iris, <span class="at">mapping =</span> <span class="fu">aes</span>(<span class="at">x =</span> Sepal.Length, <span class="at">y =</span> Sepal.Width)) <span class="sc">+</span> <span class="co"># 底层画布</span></span>
<span id="cb85-3"><a href="ggplot2-plot.html#cb85-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>() <span class="sc">+</span></span>
<span id="cb85-4"><a href="ggplot2-plot.html#cb85-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_smooth</span>() <span class="sc">+</span></span>
<span id="cb85-5"><a href="ggplot2-plot.html#cb85-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(</span>
<span id="cb85-6"><a href="ggplot2-plot.html#cb85-6" aria-hidden="true" tabindex="-1"></a> <span class="at">title =</span> <span class="st">"22"</span>,</span>
<span id="cb85-7"><a href="ggplot2-plot.html#cb85-7" aria-hidden="true" tabindex="-1"></a> <span class="at">subtitle =</span> <span class="st">"22"</span>,</span>
<span id="cb85-8"><a href="ggplot2-plot.html#cb85-8" aria-hidden="true" tabindex="-1"></a> <span class="at">caption =</span> <span class="st">"22"</span></span>
<span id="cb85-9"><a href="ggplot2-plot.html#cb85-9" aria-hidden="true" tabindex="-1"></a> )</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-23-1.png" width="672" style="display: block; margin: auto;" /></p>
<p><code>labs()</code>只是提供了这些标题功能，一般并不会同时使用这些功能。
在出版图书内，图形下方一般伴随有图形说明，这时一般就不再使用标题、副标题、标签、标注，而只需写在图的伴随说明文字中，当然，坐标轴标签一般还是需要的。</p>
</div>
<div id="标注功能" class="section level3 hasAnchor" number="4.9.2">
<h3><span class="header-section-number">4.9.2</span> 标注功能<a href="ggplot2-plot.html#标注功能" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<p>通过<code>annotate(geom = "text")</code>调用<code>geom_text()</code>的功能，
可以在一个散点图中标注多行文字，多行之间用<code>"\n"</code>分开：</p>
<p>在<code>annotate()</code>中选<code>geom="rect"</code>，给出长方形的左右和上限界限，
可以将上面图形中最右侧偏低的点用长方形填充标出。
可以在<code>annotate()</code>中选<code>geom="line"</code>画线，需要给出线的起点和终点坐标，可以<code>arrow</code>选项要求画箭头，用<code>arrow()</code>函数给出箭头的大小、角度等设置，
如：</p>
<div class="sourceCode" id="cb86"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb86-1"><a href="ggplot2-plot.html#cb86-1" aria-hidden="true" tabindex="-1"></a>p <span class="sc">+</span> <span class="fu">geom_point</span>() <span class="sc">+</span></span>
<span id="cb86-2"><a href="ggplot2-plot.html#cb86-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_smooth</span>(<span class="at">method=</span><span class="st">"gam"</span>) <span class="sc">+</span></span>
<span id="cb86-3"><a href="ggplot2-plot.html#cb86-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_x_log10</span>() <span class="sc">+</span></span>
<span id="cb86-4"><a href="ggplot2-plot.html#cb86-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">annotate</span>(<span class="at">geom =</span> <span class="st">"rect"</span>, </span>
<span id="cb86-5"><a href="ggplot2-plot.html#cb86-5" aria-hidden="true" tabindex="-1"></a> <span class="at">xmin =</span> <span class="fl">5.5E4</span>, <span class="at">xmax =</span> <span class="fl">1.2E5</span>,</span>
<span id="cb86-6"><a href="ggplot2-plot.html#cb86-6" aria-hidden="true" tabindex="-1"></a> <span class="at">ymin =</span> <span class="dv">54</span>, <span class="at">ymax =</span> <span class="dv">71</span>,<span class="at">col =</span> <span class="st">'red'</span>,<span class="at">fill =</span> <span class="st">'red'</span>,<span class="at">alpha =</span> <span class="fl">0.5</span>) <span class="sc">+</span> </span>
<span id="cb86-7"><a href="ggplot2-plot.html#cb86-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">annotate</span>(<span class="at">geom =</span> <span class="st">"line"</span>,</span>
<span id="cb86-8"><a href="ggplot2-plot.html#cb86-8" aria-hidden="true" tabindex="-1"></a> <span class="at">x =</span> <span class="fu">c</span>(<span class="fl">5.9E4</span>, <span class="fl">3.16E4</span>),</span>
<span id="cb86-9"><a href="ggplot2-plot.html#cb86-9" aria-hidden="true" tabindex="-1"></a> <span class="at">y =</span> <span class="fu">c</span>(<span class="dv">53</span>, <span class="dv">40</span>),</span>
<span id="cb86-10"><a href="ggplot2-plot.html#cb86-10" aria-hidden="true" tabindex="-1"></a> <span class="at">arrow =</span> <span class="fu">arrow</span>(<span class="at">angle =</span> <span class="dv">20</span>, <span class="at">length =</span> <span class="fu">unit</span>(<span class="dv">4</span>, <span class="st">"mm"</span>))) <span class="sc">+</span></span>
<span id="cb86-11"><a href="ggplot2-plot.html#cb86-11" aria-hidden="true" tabindex="-1"></a> <span class="fu">annotate</span>(<span class="at">geom =</span> <span class="st">"text"</span>,</span>
<span id="cb86-12"><a href="ggplot2-plot.html#cb86-12" aria-hidden="true" tabindex="-1"></a> <span class="at">x =</span> <span class="fl">3.16E4</span>, <span class="at">y =</span> <span class="dv">38</span>,</span>
<span id="cb86-13"><a href="ggplot2-plot.html#cb86-13" aria-hidden="true" tabindex="-1"></a> <span class="at">label =</span> <span class="st">"这些国家的期望寿命低于预期"</span>)</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-24-1.png" width="672" style="display: block; margin: auto;" /></p>
<div class="sourceCode" id="cb87"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb87-1"><a href="ggplot2-plot.html#cb87-1" aria-hidden="true" tabindex="-1"></a><span class="co">#iris例子 + annotate，hline，abline</span></span>
<span id="cb87-2"><a href="ggplot2-plot.html#cb87-2" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> iris, <span class="at">mapping =</span> <span class="fu">aes</span>(<span class="at">x =</span> Sepal.Length, <span class="at">y =</span> Sepal.Width)) <span class="sc">+</span> <span class="co"># 底层画布</span></span>
<span id="cb87-3"><a href="ggplot2-plot.html#cb87-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>() <span class="sc">+</span></span>
<span id="cb87-4"><a href="ggplot2-plot.html#cb87-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_smooth</span>() </span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-25-1.png" width="672" style="display: block; margin: auto;" /></p>
<p>可以用<code>geom_hline()</code>、<code>geom_vline()</code>和<code>geom_abline()</code>画横线、竖线、斜线。
ggplot2的默认主题会自动画参考线，可以用<code>theme()</code>函数指定参考线画法。</p>
</div>
<div id="指南" class="section level3 hasAnchor" number="4.9.3">
<h3><span class="header-section-number">4.9.3</span> 指南<a href="ggplot2-plot.html#指南" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<p>对于颜色、填充色等维度，
会自动生成图例。用<code>guides(color = FALSE)</code>这样的方法可以取消指定维度的图例。</p>
<p><code>theme()</code>可以调整一些整体的设置，如背景色、字体、图例的摆放位置。</p>
<p><strong>例如：</strong>用<code>theme()</code>的<code>legend.position</code>改变图例的位置，
如<code>theme(legend.position = "top")</code>可以将图例放置在上方，
默认是放置在右侧的。可取值有<code>"none"、"left"、"right"、"bottom"、"top"</code>，如：</p>
<div class="sourceCode" id="cb88"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb88-1"><a href="ggplot2-plot.html#cb88-1" aria-hidden="true" tabindex="-1"></a><span class="co">#iris 例子</span></span>
<span id="cb88-2"><a href="ggplot2-plot.html#cb88-2" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(<span class="at">data =</span> iris, <span class="at">mapping =</span> <span class="fu">aes</span>(<span class="at">x =</span> Sepal.Length, <span class="at">y =</span> Sepal.Width,<span class="at">col =</span> Species)) <span class="sc">+</span> <span class="co"># 底层画布</span></span>
<span id="cb88-3"><a href="ggplot2-plot.html#cb88-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>() <span class="sc">+</span></span>
<span id="cb88-4"><a href="ggplot2-plot.html#cb88-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_smooth</span>() <span class="sc">+</span></span>
<span id="cb88-5"><a href="ggplot2-plot.html#cb88-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">legend.position =</span> <span class="st">'left'</span>,<span class="at">panel.background =</span> <span class="fu">element_blank</span>()) <span class="sc">+</span><span class="fu">theme_bw</span>()</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-26-1.png" width="672" style="display: block; margin: auto;" /></p>
</div>
<div id="主题" class="section level3 hasAnchor" number="4.9.4">
<h3><span class="header-section-number">4.9.4</span> 主题<a href="ggplot2-plot.html#主题" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<p>ggplot2包作图可以实现内容与设计的分离，这里内容就是指数据、映射、统计、图形类型等方面，而设计就是指背景色、颜色表、字体、坐标轴做法、图例位置等的安排。将作图任务分解为内容与设计两个方面，可以让数据科学家不必关心设计有关的元素，而设计可以让专门的艺术设计人才来处理。这种工作分配已经在图书出版、网站、游戏开发等行业发挥了重要作用。</p>
<p>theme()函数用来指定设计元素，称为主题(theme)，而且可以单独开发R扩展包来提供适当的主题。<strong>ggthemes扩展包</strong>是一个这样的包。</p>
<p><code>theme_set()</code>可以改变后续ggplot2作图的主题（配色、字体等）。如<code>theme_set(theme_bw()),theme_set(theme_dark())</code>等。
对单次绘图，可以直接用加号连接<code>theme_gray()</code>等这些主题函数。
主题包括<code>theme_gray()（默认主题）、theme_minimal()、theme_classic()</code>等。</p>
<p><code>theme()</code>函数还可以直接指定颜色、字体、大小等设置。</p>
<div class="sourceCode" id="cb89"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb89-1"><a href="ggplot2-plot.html#cb89-1" aria-hidden="true" tabindex="-1"></a><span class="co">#iris 例子</span></span></code></pre></div>
</div>
</div>
<div id="保存图片" class="section level2 hasAnchor" number="4.10">
<h2><span class="header-section-number">4.10</span> 保存图片<a href="ggplot2-plot.html#保存图片" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p>ggplot2包中提供ggsave函数进行图形保存。ggsave函数的使用格式如下所示。</p>
<p><code>ggsave(filename,width,height,...)</code></p>
<p>其中，filename为保存的文件名与路径，width指图像宽度，height指图像高度。</p>
<p><strong>示例：</strong>运行下列代码将会在当前工作目录下生成一个名为mygraph的pdf图形。</p>
<div class="sourceCode" id="cb90"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb90-1"><a href="ggplot2-plot.html#cb90-1" aria-hidden="true" tabindex="-1"></a><span class="fu">ggplot</span>(iris, <span class="fu">aes</span>(<span class="at">x =</span> Sepal.Length, <span class="at">y =</span> Sepal.Width, <span class="at">colour =</span> Species))<span class="sc">+</span></span>
<span id="cb90-2"><a href="ggplot2-plot.html#cb90-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_point</span>(<span class="at">size =</span> <span class="dv">2</span>)</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-28-1.png" width="672" style="display: block; margin: auto;" /></p>
<div class="sourceCode" id="cb91"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb91-1"><a href="ggplot2-plot.html#cb91-1" aria-hidden="true" tabindex="-1"></a><span class="fu">ggsave</span>(<span class="at">file =</span> <span class="st">"mygraph1.png"</span>, <span class="at">width =</span> <span class="dv">6</span>, <span class="at">height =</span> <span class="dv">8</span>)</span></code></pre></div>
<p>或者可以使用Rstudio界面进行保存图片，具体教程课件（R语言可视化基础教程）</p>
</div>
<div id="例子" class="section level2 hasAnchor" number="4.11">
<h2><span class="header-section-number">4.11</span> 例子<a href="ggplot2-plot.html#例子" class="anchor-section" aria-label="Anchor link to header"></a></h2>
<p>该部分来源于：公众号[小明的数据分析笔记本]。大家可以通过以下例子对今天所学的知识进行回顾。其他例子可以在第 <span class="math inline">\(\ref{#some-tips-alls}\)</span> 找到。</p>
<div id="柱状图误差项" class="section level3 hasAnchor" number="4.11.1">
<h3><span class="header-section-number">4.11.1</span> 柱状图+误差项<a href="ggplot2-plot.html#柱状图误差项" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<div class="sourceCode" id="cb92"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb92-1"><a href="ggplot2-plot.html#cb92-1" aria-hidden="true" tabindex="-1"></a><span class="do">## 小明推送笔记《小明的数据分析笔记本》</span></span>
<span id="cb92-2"><a href="ggplot2-plot.html#cb92-2" aria-hidden="true" tabindex="-1"></a><span class="co"># 跟着Nature microbiology学画图~R语言ggplot2画柱形图 </span></span>
<span id="cb92-3"><a href="ggplot2-plot.html#cb92-3" aria-hidden="true" tabindex="-1"></a><span class="co"># https://mp.weixin.qq.com/s/E-1X_VSq03AhvC_0cNEgyQ</span></span>
<span id="cb92-4"><a href="ggplot2-plot.html#cb92-4" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb92-5"><a href="ggplot2-plot.html#cb92-5" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(ggplot2)</span>
<span id="cb92-6"><a href="ggplot2-plot.html#cb92-6" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb92-7"><a href="ggplot2-plot.html#cb92-7" aria-hidden="true" tabindex="-1"></a><span class="do">### 柱状图+误差项</span></span>
<span id="cb92-8"><a href="ggplot2-plot.html#cb92-8" aria-hidden="true" tabindex="-1"></a>data <span class="ot">=</span> <span class="fu">data.frame</span>(<span class="st">"group"</span> <span class="ot">=</span> <span class="fu">c</span>(<span class="st">"A"</span>,<span class="st">"B"</span>),<span class="st">"value"</span><span class="ot">=</span><span class="fu">c</span>(<span class="fl">0.8</span>,<span class="fl">0.4</span>),<span class="st">"errorbar"</span><span class="ot">=</span><span class="fu">c</span>(.<span class="dv">2</span>,.<span class="dv">1</span>))</span>
<span id="cb92-9"><a href="ggplot2-plot.html#cb92-9" aria-hidden="true" tabindex="-1"></a>data</span></code></pre></div>
<pre><code>## group value errorbar
## 1 A 0.8 0.2
## 2 B 0.4 0.1</code></pre>
<div class="sourceCode" id="cb94"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb94-1"><a href="ggplot2-plot.html#cb94-1" aria-hidden="true" tabindex="-1"></a>p1 <span class="ot">=</span> <span class="fu">ggplot</span>(data,<span class="fu">aes</span>(<span class="at">x =</span> group, <span class="at">y =</span> value)) <span class="sc">+</span></span>
<span id="cb94-2"><a href="ggplot2-plot.html#cb94-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_col</span>(<span class="fu">aes</span>(<span class="at">fill=</span>group),<span class="at">color=</span><span class="st">"black"</span>) <span class="sc">+</span> <span class="co">#柱状图</span></span>
<span id="cb94-3"><a href="ggplot2-plot.html#cb94-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="dv">1</span>,<span class="at">lty =</span> <span class="dv">2</span>) <span class="sc">+</span> <span class="co">#加横线</span></span>
<span id="cb94-4"><a href="ggplot2-plot.html#cb94-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="fl">0.5</span>,<span class="at">lty =</span> <span class="st">"dashed"</span>) <span class="sc">+</span></span>
<span id="cb94-5"><a href="ggplot2-plot.html#cb94-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_bw</span>() <span class="sc">+</span> <span class="co">#主题设置</span></span>
<span id="cb94-6"><a href="ggplot2-plot.html#cb94-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">panel.grid =</span> <span class="fu">element_blank</span>(), <span class="co">#网格为空</span></span>
<span id="cb94-7"><a href="ggplot2-plot.html#cb94-7" aria-hidden="true" tabindex="-1"></a> <span class="at">legend.position =</span> <span class="st">"none"</span>) <span class="sc">+</span> <span class="co">#legend位置为无，就是不加</span></span>
<span id="cb94-8"><a href="ggplot2-plot.html#cb94-8" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_y_continuous</span>(<span class="at">expand =</span> <span class="fu">c</span>(<span class="dv">0</span>,<span class="dv">0</span>),<span class="at">limits =</span> <span class="fu">c</span>(<span class="dv">0</span>,<span class="fl">1.5</span>)) <span class="sc">+</span> <span class="co">#y为连续，设置ylim</span></span>
<span id="cb94-9"><a href="ggplot2-plot.html#cb94-9" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_x_discrete</span>(<span class="at">label =</span> <span class="fu">c</span>(<span class="st">"Ositive </span><span class="sc">\n</span><span class="st"> interactions"</span>,<span class="st">"Negative</span><span class="sc">\n</span><span class="st">interactions"</span>)) <span class="sc">+</span> <span class="co">#x为离散</span></span>
<span id="cb94-10"><a href="ggplot2-plot.html#cb94-10" aria-hidden="true" tabindex="-1"></a> <span class="fu">annotate</span>(<span class="st">"segment"</span>,<span class="at">x=</span><span class="dv">1</span>,<span class="at">y=</span><span class="fl">0.8</span>,<span class="at">xend=</span><span class="dv">1</span>,<span class="at">yend=</span><span class="dv">1</span>) <span class="sc">+</span> <span class="co">#加线段segment，当然这个函数可以加很多其他的包括字</span></span>
<span id="cb94-11"><a href="ggplot2-plot.html#cb94-11" aria-hidden="true" tabindex="-1"></a> <span class="fu">annotate</span>(<span class="st">"segment"</span>,<span class="at">x=</span><span class="dv">2</span>,<span class="at">y=</span><span class="fl">0.4</span>,<span class="at">xend=</span><span class="dv">2</span>,<span class="at">yend=</span><span class="fl">0.5</span>) <span class="sc">+</span></span>
<span id="cb94-12"><a href="ggplot2-plot.html#cb94-12" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">x =</span> <span class="cn">NULL</span>, <span class="co">#标签，注意\n可以空行</span></span>
<span id="cb94-13"><a href="ggplot2-plot.html#cb94-13" aria-hidden="true" tabindex="-1"></a> <span class="at">y =</span> <span class="st">'Absolute fold change</span><span class="sc">\n</span><span class="st">in growth from co-cultures</span><span class="sc">\n</span><span class="st">compared to monocultures'</span>,</span>
<span id="cb94-14"><a href="ggplot2-plot.html#cb94-14" aria-hidden="true" tabindex="-1"></a> <span class="at">title =</span> <span class="st">"Average growth fold change in</span><span class="sc">\n</span><span class="st">co-cultures"</span>) <span class="sc">+</span></span>
<span id="cb94-15"><a href="ggplot2-plot.html#cb94-15" aria-hidden="true" tabindex="-1"></a> <span class="fu">annotate</span>(<span class="st">"segment"</span>,<span class="at">x=</span><span class="dv">1</span>,<span class="at">y=</span><span class="dv">1</span>,<span class="at">xend=</span><span class="fl">1.2</span>,<span class="at">yend=</span><span class="fl">1.05</span>) <span class="sc">+</span></span>
<span id="cb94-16"><a href="ggplot2-plot.html#cb94-16" aria-hidden="true" tabindex="-1"></a> <span class="fu">annotate</span>(<span class="st">"segment"</span>,<span class="at">x=</span><span class="dv">2</span>,<span class="at">y=</span><span class="dv">1</span>,<span class="at">xend=</span><span class="fl">1.8</span>,<span class="at">yend=</span><span class="fl">1.05</span>) <span class="sc">+</span> </span>
<span id="cb94-17"><a href="ggplot2-plot.html#cb94-17" aria-hidden="true" tabindex="-1"></a> <span class="fu">annotate</span>(<span class="st">"segment"</span>,<span class="at">x=</span><span class="fl">1.2</span>,<span class="at">y=</span><span class="fl">1.05</span>,<span class="at">xend=</span><span class="fl">1.8</span>,<span class="at">yend=</span><span class="fl">1.05</span>) <span class="sc">+</span> </span>
<span id="cb94-18"><a href="ggplot2-plot.html#cb94-18" aria-hidden="true" tabindex="-1"></a> <span class="fu">annotate</span>(<span class="st">"text"</span>, <span class="at">x =</span> <span class="fl">1.5</span>, <span class="at">y =</span> <span class="fl">1.1</span>, <span class="at">label =</span> <span class="st">"p=0.005"</span> ) <span class="sc">+</span> </span>
<span id="cb94-19"><a href="ggplot2-plot.html#cb94-19" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_manual</span>(<span class="at">values =</span> <span class="fu">c</span>(<span class="st">"#ff8080"</span>,<span class="st">"#90bff9"</span>)) <span class="co">#填充色使用离散颜色manual，两种颜色这里。</span></span>
<span id="cb94-20"><a href="ggplot2-plot.html#cb94-20" aria-hidden="true" tabindex="-1"></a>p1</span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-29-1.png" width="672" style="display: block; margin: auto;" /></p>
</div>
<div id="有正值和负值的柱形图" class="section level3 hasAnchor" number="4.11.2">
<h3><span class="header-section-number">4.11.2</span> 有正值和负值的柱形图<a href="ggplot2-plot.html#有正值和负值的柱形图" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<div class="sourceCode" id="cb95"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb95-1"><a href="ggplot2-plot.html#cb95-1" aria-hidden="true" tabindex="-1"></a><span class="do">## 有正值和负值的柱形图</span></span>
<span id="cb95-2"><a href="ggplot2-plot.html#cb95-2" aria-hidden="true" tabindex="-1"></a></span>
<span id="cb95-3"><a href="ggplot2-plot.html#cb95-3" aria-hidden="true" tabindex="-1"></a>x <span class="ot"><-</span> <span class="dv">1</span><span class="sc">:</span><span class="dv">28</span></span>
<span id="cb95-4"><a href="ggplot2-plot.html#cb95-4" aria-hidden="true" tabindex="-1"></a>y <span class="ot"><-</span> <span class="fu">sample</span>(<span class="sc">-</span><span class="dv">100</span><span class="sc">:</span><span class="dv">150</span>,<span class="dv">28</span>,<span class="at">replace =</span> F)</span>
<span id="cb95-5"><a href="ggplot2-plot.html#cb95-5" aria-hidden="true" tabindex="-1"></a>df2 <span class="ot"><-</span> <span class="fu">data.frame</span>(x,y)</span>
<span id="cb95-6"><a href="ggplot2-plot.html#cb95-6" aria-hidden="true" tabindex="-1"></a>df2<span class="sc">$</span>x <span class="ot">=</span> <span class="fu">as.factor</span>(df2<span class="sc">$</span>x)</span>
<span id="cb95-7"><a href="ggplot2-plot.html#cb95-7" aria-hidden="true" tabindex="-1"></a>df2<span class="sc">$</span>group <span class="ot"><-</span> <span class="fu">ifelse</span>(df2<span class="sc">$</span>y<span class="sc">></span><span class="dv">0</span>,<span class="st">"A"</span>,<span class="st">"B"</span>)</span>
<span id="cb95-8"><a href="ggplot2-plot.html#cb95-8" aria-hidden="true" tabindex="-1"></a>df2<span class="sc">$</span>group<span class="ot"><-</span><span class="fu">factor</span>(df2<span class="sc">$</span>group,</span>
<span id="cb95-9"><a href="ggplot2-plot.html#cb95-9" aria-hidden="true" tabindex="-1"></a> <span class="at">labels =</span> <span class="fu">c</span>(<span class="st">"Synergistic interactions"</span>,</span>
<span id="cb95-10"><a href="ggplot2-plot.html#cb95-10" aria-hidden="true" tabindex="-1"></a> <span class="st">"Non-synergistic interactions"</span>))</span>
<span id="cb95-11"><a href="ggplot2-plot.html#cb95-11" aria-hidden="true" tabindex="-1"></a><span class="fu">head</span>(df2)</span></code></pre></div>
<pre><code>## x y group
## 1 1 62 Synergistic interactions
## 2 2 -58 Non-synergistic interactions
## 3 3 -100 Non-synergistic interactions
## 4 4 -72 Non-synergistic interactions
## 5 5 -23 Non-synergistic interactions
## 6 6 49 Synergistic interactions</code></pre>
<div class="sourceCode" id="cb97"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb97-1"><a href="ggplot2-plot.html#cb97-1" aria-hidden="true" tabindex="-1"></a>p2 <span class="ot">=</span> <span class="fu">ggplot</span>(df2,<span class="fu">aes</span>(x,y)) <span class="sc">+</span> </span>
<span id="cb97-2"><a href="ggplot2-plot.html#cb97-2" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_col</span>(<span class="fu">aes</span>(<span class="at">fill =</span> group),<span class="at">col =</span> <span class="st">"black"</span>) <span class="sc">+</span> </span>
<span id="cb97-3"><a href="ggplot2-plot.html#cb97-3" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="dv">100</span>,<span class="at">lty =</span> <span class="st">"dashed"</span>) <span class="sc">+</span></span>
<span id="cb97-4"><a href="ggplot2-plot.html#cb97-4" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="dv">50</span>,<span class="at">lty =</span> <span class="st">"dashed"</span>) <span class="sc">+</span></span>
<span id="cb97-5"><a href="ggplot2-plot.html#cb97-5" aria-hidden="true" tabindex="-1"></a> <span class="fu">geom_hline</span>(<span class="at">yintercept =</span> <span class="sc">-</span><span class="dv">50</span>,<span class="at">lty =</span> <span class="st">"dashed"</span>) <span class="sc">+</span></span>
<span id="cb97-6"><a href="ggplot2-plot.html#cb97-6" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme_bw</span>() <span class="sc">+</span></span>
<span id="cb97-7"><a href="ggplot2-plot.html#cb97-7" aria-hidden="true" tabindex="-1"></a> <span class="fu">theme</span>(<span class="at">panel.grid =</span> <span class="fu">element_blank</span>(),</span>
<span id="cb97-8"><a href="ggplot2-plot.html#cb97-8" aria-hidden="true" tabindex="-1"></a> <span class="at">axis.text.x =</span> <span class="fu">element_text</span>(<span class="at">angle =</span> <span class="dv">90</span>,<span class="at">hjust =</span> <span class="fl">0.5</span>,</span>
<span id="cb97-9"><a href="ggplot2-plot.html#cb97-9" aria-hidden="true" tabindex="-1"></a> <span class="at">vjust =</span> <span class="fl">0.5</span>),</span>
<span id="cb97-10"><a href="ggplot2-plot.html#cb97-10" aria-hidden="true" tabindex="-1"></a> <span class="at">plot.title =</span> <span class="fu">element_text</span>(<span class="at">hjust =</span> <span class="fl">0.5</span>),</span>
<span id="cb97-11"><a href="ggplot2-plot.html#cb97-11" aria-hidden="true" tabindex="-1"></a> <span class="at">legend.position =</span> <span class="st">"bottom"</span>,</span>
<span id="cb97-12"><a href="ggplot2-plot.html#cb97-12" aria-hidden="true" tabindex="-1"></a> <span class="at">legend.title =</span> <span class="fu">element_blank</span>()) <span class="sc">+</span> <span class="co">#取消标签的名称</span></span>
<span id="cb97-13"><a href="ggplot2-plot.html#cb97-13" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_y_continuous</span>(<span class="at">expand =</span> <span class="fu">c</span>(<span class="dv">0</span>,<span class="dv">0</span>),</span>
<span id="cb97-14"><a href="ggplot2-plot.html#cb97-14" aria-hidden="true" tabindex="-1"></a> <span class="at">limits =</span> <span class="fu">c</span>(<span class="sc">-</span><span class="dv">100</span>,<span class="dv">150</span>),</span>
<span id="cb97-15"><a href="ggplot2-plot.html#cb97-15" aria-hidden="true" tabindex="-1"></a> <span class="at">breaks =</span> <span class="fu">c</span>(<span class="sc">-</span><span class="dv">100</span>,<span class="sc">-</span><span class="dv">50</span>,<span class="dv">0</span>,<span class="dv">50</span>,<span class="dv">100</span>,<span class="dv">150</span>)) <span class="sc">+</span></span>
<span id="cb97-16"><a href="ggplot2-plot.html#cb97-16" aria-hidden="true" tabindex="-1"></a> <span class="fu">labs</span>(<span class="at">x=</span><span class="st">"Pairwise interactions"</span>,</span>
<span id="cb97-17"><a href="ggplot2-plot.html#cb97-17" aria-hidden="true" tabindex="-1"></a> <span class="at">y=</span><span class="st">"Percentage change from</span><span class="sc">\n</span><span class="st">monoculture"</span>,</span>
<span id="cb97-18"><a href="ggplot2-plot.html#cb97-18" aria-hidden="true" tabindex="-1"></a> <span class="at">title =</span> <span class="st">"Synergistic versus non-synergistic</span><span class="sc">\n</span><span class="st">interactions"</span>) <span class="sc">+</span> <span class="co">#标签说明</span></span>
<span id="cb97-19"><a href="ggplot2-plot.html#cb97-19" aria-hidden="true" tabindex="-1"></a> <span class="fu">scale_fill_manual</span>(<span class="at">values =</span> <span class="fu">c</span>(<span class="st">"#ff8080"</span>,<span class="st">"#90bff9"</span>))</span>
<span id="cb97-20"><a href="ggplot2-plot.html#cb97-20" aria-hidden="true" tabindex="-1"></a>p2 </span></code></pre></div>
<p><img src="2001-ggplot-ploting_files/figure-html/unnamed-chunk-30-1.png" width="672" style="display: block; margin: auto;" /></p>
</div>
<div id="合并两图" class="section level3 hasAnchor" number="4.11.3">
<h3><span class="header-section-number">4.11.3</span> 合并两图<a href="ggplot2-plot.html#合并两图" class="anchor-section" aria-label="Anchor link to header"></a></h3>
<p>合并两图或者多图可以使用以下包：</p>
<ul>
<li><code>cowplot</code>包的<code>plot_grid()</code></li>
<li><code>pathwork</code>包</li>
<li><code>gridEctra</code>包的<code>grid.arrange()</code></li>
</ul>
<p>具体可以参考我公众号的这篇推文<a href="https://mp.weixin.qq.com/s/goFqnPtH85oXAwlxcacRDw">R可视乎｜合并多幅图形</a></p>
<p>这里使用了cowplot包</p>
<div class="sourceCode" id="cb98"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb98-1"><a href="ggplot2-plot.html#cb98-1" aria-hidden="true" tabindex="-1"></a><span class="do">## 合并两图（使用cowplot包）</span></span>
<span id="cb98-2"><a href="ggplot2-plot.html#cb98-2" aria-hidden="true" tabindex="-1"></a><span class="fu">library</span>(cowplot)</span>
<span id="cb98-3"><a href="ggplot2-plot.html#cb98-3" aria-hidden="true" tabindex="-1"></a><span class="fu">pdf</span>(<span class="st">"test/plot_cow.pdf"</span>,<span class="at">width =</span> <span class="dv">8</span>,<span class="at">height =</span> <span class="dv">4</span>)</span>
<span id="cb98-4"><a href="ggplot2-plot.html#cb98-4" aria-hidden="true" tabindex="-1"></a><span class="fu">plot_grid</span>(p1,p2,<span class="at">ncol =</span> <span class="dv">2</span>,<span class="at">nrow =</span> <span class="dv">1</span>,<span class="at">labels =</span> <span class="fu">c</span>(<span class="st">"d"</span>,<span class="st">"e"</span>))</span>
<span id="cb98-5"><a href="ggplot2-plot.html#cb98-5" aria-hidden="true" tabindex="-1"></a><span class="fu">dev.off</span>()</span></code></pre></div>
<pre><code>## quartz_off_screen
## 2</code></pre>
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