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<title>第 14 章 数据规整2 | R编程与作图</title>
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<li><a class="" href="index.html">前言</a></li>
<li class="book-part">R编程基础</li>
<li><a class="" href="baseR-intro-ds.html"><span class="header-section-number">1</span> R语言介绍及资料推荐</a></li>
<li><a class="" href="baseR-install.html"><span class="header-section-number">2</span> 安装与环境配置</a></li>
<li><a class="" href="baseR-objects.html"><span class="header-section-number">3</span> 对象</a></li>
<li><a class="" href="baseR-vectors.html"><span class="header-section-number">4</span> 向量</a></li>
<li><a class="" href="baseR-data-structure.html"><span class="header-section-number">5</span> 数据结构</a></li>
<li><a class="" href="baseR-operators.html"><span class="header-section-number">6</span> 运算符及向量运算</a></li>
<li><a class="" href="baseR-functions.html"><span class="header-section-number">7</span> 函数</a></li>
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<li><a class="" href="tidyverse-dplyr-apply.html"><span class="header-section-number">12</span> dplyr进阶</a></li>
<li><a class="" href="tidyverse-tidyr.html"><span class="header-section-number">13</span> 数据规整1</a></li>
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<li><a class="" href="tidyverse-ggplot2-colors.html"><span class="header-section-number">26</span> ggplot2之数据可视化中的配色</a></li>
<li><a class="" href="tidyverse-ggplot2-override-aes.html"><span class="header-section-number">27</span> ggplot2之控制图例的外观</a></li>
<li><a class="" href="tidyverse-ggplot2-aes-eval.html"><span class="header-section-number">28</span> ggplot2之延迟映射</a></li>
<li><a class="" href="tidyverse-ggplot2-academic.html"><span class="header-section-number">29</span> ggplot2之科研数据可视化</a></li>
<li><a class="" href="tidyverse-ggplot2-gganimate.html"><span class="header-section-number">30</span> ggplot2之让你的数据动起来</a></li>
<li><a class="" href="tidyverse-ggplot2-pass-function-as-parameters.html"><span class="header-section-number">31</span> ggplot2中传递函数作为参数值</a></li>
<li class="book-part">可重复性文档Rmarkdown以及练习</li>
<li><a class="" href="tidyverse-rmarkdown.html"><span class="header-section-number">32</span> 可重复性文档</a></li>
<li><a class="" href="eda-practice.html"><span class="header-section-number">33</span> 一天一练</a></li>
<li class="book-part">GO/KEGG富集分析</li>
<li><a class="" href="GO-KEGG.html"><span class="header-section-number">34</span> GO/KEGG功能富集分析</a></li>
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</header><main class="col-sm-12 col-md-9 col-lg-7" id="content"><div id="tidyverse-tidyr2" class="section level1" number="14">
<h1>
<span class="header-section-number">第 14 章</span> 数据规整2<a class="anchor" aria-label="anchor" href="#tidyverse-tidyr2"><i class="fas fa-link"></i></a>
</h1>
<p>接着上一章，罗列一些<code>tidyr</code>的函数</p>
<div class="sourceCode" id="cb559"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="kw"><a href="https://rdrr.io/r/base/library.html">library</a></span><span class="op">(</span><span class="va"><a href="https://tidyverse.tidyverse.org">tidyverse</a></span><span class="op">)</span></span></code></pre></div>
<div id="fill-缺失值填充" class="section level2" number="14.1">
<h2>
<span class="header-section-number">14.1</span> <code>fill()</code> 缺失值填充<a class="anchor" aria-label="anchor" href="#fill-%E7%BC%BA%E5%A4%B1%E5%80%BC%E5%A1%AB%E5%85%85"><i class="fas fa-link"></i></a>
</h2>
<p>利用<strong>所在列</strong>的上下值进行缺失值填充</p>
<div class="sourceCode" id="cb560"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">sales</span> <span class="op"><-</span> <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/tribble.html">tribble</a></span><span class="op">(</span></span>
<span> <span class="op">~</span><span class="va">quarter</span>, <span class="op">~</span><span class="va">year</span>, <span class="op">~</span><span class="va">sales</span>,</span>
<span> <span class="st">"Q1"</span>, <span class="fl">2000</span>, <span class="fl">66013</span>,</span>
<span> <span class="st">"Q2"</span>, <span class="cn">NA</span>, <span class="fl">69182</span>,</span>
<span> <span class="st">"Q3"</span>, <span class="cn">NA</span>, <span class="fl">53175</span>,</span>
<span> <span class="st">"Q4"</span>, <span class="cn">NA</span>, <span class="fl">21001</span>,</span>
<span> <span class="st">"Q1"</span>, <span class="fl">2001</span>, <span class="fl">46036</span>,</span>
<span> <span class="st">"Q2"</span>, <span class="cn">NA</span>, <span class="fl">58842</span>,</span>
<span> <span class="st">"Q3"</span>, <span class="cn">NA</span>, <span class="fl">44568</span>,</span>
<span> <span class="st">"Q4"</span>, <span class="cn">NA</span>, <span class="fl">50197</span>,</span>
<span> <span class="st">"Q1"</span>, <span class="fl">2002</span>, <span class="fl">39113</span>,</span>
<span> <span class="st">"Q2"</span>, <span class="cn">NA</span>, <span class="fl">41668</span>,</span>
<span> <span class="st">"Q3"</span>, <span class="cn">NA</span>, <span class="fl">30144</span>,</span>
<span> <span class="st">"Q4"</span>, <span class="cn">NA</span>, <span class="fl">52897</span></span>
<span> <span class="op">)</span></span>
<span><span class="va">sales</span></span></code></pre></div>
<pre><code>## # A tibble: 12 × 3
## quarter year sales
## <chr> <dbl> <dbl>
## 1 Q1 2000 66013
## 2 Q2 NA 69182
## 3 Q3 NA 53175
## 4 Q4 NA 21001
## 5 Q1 2001 46036
## 6 Q2 NA 58842
## 7 Q3 NA 44568
## 8 Q4 NA 50197
## 9 Q1 2002 39113
## 10 Q2 NA 41668
## 11 Q3 NA 30144
## 12 Q4 NA 52897</code></pre>
<div class="sourceCode" id="cb562"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">sales</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span> <span class="fu"><a href="https://tidyr.tidyverse.org/reference/fill.html">fill</a></span><span class="op">(</span><span class="va">year</span><span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 12 × 3
## quarter year sales
## <chr> <dbl> <dbl>
## 1 Q1 2000 66013
## 2 Q2 2000 69182
## 3 Q3 2000 53175
## 4 Q4 2000 21001
## 5 Q1 2001 46036
## 6 Q2 2001 58842
## 7 Q3 2001 44568
## 8 Q4 2001 50197
## 9 Q1 2002 39113
## 10 Q2 2002 41668
## 11 Q3 2002 30144
## 12 Q4 2002 52897</code></pre>
<p>也可以控制填充的方向</p>
<div class="sourceCode" id="cb564"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">sales</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span> <span class="fu"><a href="https://tidyr.tidyverse.org/reference/fill.html">fill</a></span><span class="op">(</span><span class="va">year</span>, .direction <span class="op">=</span> <span class="st">"up"</span><span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 12 × 3
## quarter year sales
## <chr> <dbl> <dbl>
## 1 Q1 2000 66013
## 2 Q2 2001 69182
## 3 Q3 2001 53175
## 4 Q4 2001 21001
## 5 Q1 2001 46036
## 6 Q2 2002 58842
## 7 Q3 2002 44568
## 8 Q4 2002 50197
## 9 Q1 2002 39113
## 10 Q2 NA 41668
## 11 Q3 NA 30144
## 12 Q4 NA 52897</code></pre>
</div>
<div id="expand-与-complete" class="section level2" number="14.2">
<h2>
<span class="header-section-number">14.2</span> <code>expand()</code> 与 <code>complete()</code><a class="anchor" aria-label="anchor" href="#expand-%E4%B8%8E-complete"><i class="fas fa-link"></i></a>
</h2>
<p>指定数据框的若干列，根据其向量元素值，产生所有可能的交叉组合</p>
<div class="sourceCode" id="cb566"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><-</span> <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/tribble.html">tribble</a></span><span class="op">(</span></span>
<span> <span class="op">~</span><span class="va">x</span>, <span class="op">~</span><span class="va">y</span>, <span class="op">~</span><span class="va">z</span>,</span>
<span> <span class="fl">1L</span>, <span class="fl">1L</span>, <span class="fl">4L</span>,</span>
<span> <span class="fl">1L</span>, <span class="fl">2L</span>, <span class="fl">5L</span>,</span>
<span> <span class="fl">2L</span>, <span class="fl">1L</span>, <span class="cn">NA</span>,</span>
<span> <span class="fl">3L</span>, <span class="fl">2L</span>, <span class="fl">6L</span></span>
<span><span class="op">)</span></span>
<span></span>
<span></span>
<span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span> <span class="fu"><a href="https://tidyr.tidyverse.org/reference/expand.html">expand</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">y</span><span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 6 × 2
## x y
## <int> <int>
## 1 1 1
## 2 1 2
## 3 2 1
## 4 2 2
## 5 3 1
## 6 3 2</code></pre>
<p><code><a href="https://tidyr.tidyverse.org/reference/expand.html">nesting()</a></code>用于限定只产生数据框已出现的组合。</p>
<div class="sourceCode" id="cb568"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span> <span class="fu"><a href="https://tidyr.tidyverse.org/reference/expand.html">expand</a></span><span class="op">(</span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/expand.html">nesting</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">y</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 4 × 2
## x y
## <int> <int>
## 1 1 1
## 2 1 2
## 3 2 1
## 4 3 2</code></pre>
<div class="sourceCode" id="cb570"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span> <span class="fu"><a href="https://tidyr.tidyverse.org/reference/expand.html">expand</a></span><span class="op">(</span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/expand.html">nesting</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">y</span><span class="op">)</span>, <span class="va">z</span><span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 16 × 3
## x y z
## <int> <int> <int>
## 1 1 1 4
## 2 1 1 5
## 3 1 1 6
## 4 1 1 NA
## 5 1 2 4
## 6 1 2 5
## 7 1 2 6
## 8 1 2 NA
## 9 2 1 4
## 10 2 1 5
## 11 2 1 6
## 12 2 1 NA
## 13 3 2 4
## 14 3 2 5
## 15 3 2 6
## 16 3 2 NA</code></pre>
<p><code><a href="https://tidyr.tidyverse.org/reference/complete.html">complete()</a></code> 补全，可以看做是 <code>expand(nesting()) + fill()</code></p>
<div class="sourceCode" id="cb572"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span> <span class="fu"><a href="https://tidyr.tidyverse.org/reference/complete.html">complete</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">y</span><span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 6 × 3
## x y z
## <int> <int> <int>
## 1 1 1 4
## 2 1 2 5
## 3 2 1 NA
## 4 2 2 NA
## 5 3 1 NA
## 6 3 2 6</code></pre>
<div class="sourceCode" id="cb574"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span> <span class="fu"><a href="https://tidyr.tidyverse.org/reference/complete.html">complete</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">y</span>, fill <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span>z <span class="op">=</span> <span class="fl">0</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 6 × 3
## x y z
## <int> <int> <int>
## 1 1 1 4
## 2 1 2 5
## 3 2 1 0
## 4 2 2 0
## 5 3 1 0
## 6 3 2 6</code></pre>
<p>数据在complete补全的时候，会面临有两种缺失值：</p>
<ol style="list-style-type: decimal">
<li>补位的时候造成的空缺</li>
<li>数据原先就存在缺失值</li>
</ol>
<div class="sourceCode" id="cb576"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span> <span class="fu"><a href="https://tidyr.tidyverse.org/reference/complete.html">complete</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">y</span><span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 6 × 3
## x y z
## <int> <int> <int>
## 1 1 1 4
## 2 1 2 5
## 3 2 1 NA
## 4 2 2 NA
## 5 3 1 NA
## 6 3 2 6</code></pre>
<ul>
<li>补位的时候造成的空缺，可通过<code>fill = list(x = 0)</code> 控制填充</li>
</ul>
<div class="sourceCode" id="cb578"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span> <span class="fu"><a href="https://tidyr.tidyverse.org/reference/complete.html">complete</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">y</span>, fill <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span>z <span class="op">=</span> <span class="fl">0</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 6 × 3
## x y z
## <int> <int> <int>
## 1 1 1 4
## 2 1 2 5
## 3 2 1 0
## 4 2 2 0
## 5 3 1 0
## 6 3 2 6</code></pre>
<ul>
<li>数据原先就存在缺失值，最好通过 <code>explicit = FALSE</code>显式地控制是否填充</li>
</ul>
<div class="sourceCode" id="cb580"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span> <span class="fu"><a href="https://tidyr.tidyverse.org/reference/complete.html">complete</a></span><span class="op">(</span><span class="va">x</span>, <span class="va">y</span>, fill <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/list.html">list</a></span><span class="op">(</span>z <span class="op">=</span> <span class="fl">0</span><span class="op">)</span>, explicit <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 6 × 3
## x y z
## <int> <int> <int>
## 1 1 1 4
## 2 1 2 5
## 3 2 1 NA
## 4 2 2 0
## 5 3 1 0
## 6 3 2 6</code></pre>
</div>
<div id="expand_grid-与-crossing" class="section level2" number="14.3">
<h2>
<span class="header-section-number">14.3</span> <code>expand_grid()</code> 与 <code>crossing()</code><a class="anchor" aria-label="anchor" href="#expand_grid-%E4%B8%8E-crossing"><i class="fas fa-link"></i></a>
</h2>
<p>产生一个新的数据框，每行对应着向量元素的所有交叉组合</p>
<div class="sourceCode" id="cb582"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/expand_grid.html">expand_grid</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fl">1</span><span class="op">:</span><span class="fl">3</span>, y <span class="op">=</span> <span class="fl">1</span><span class="op">:</span><span class="fl">2</span><span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 6 × 2
## x y
## <int> <int>
## 1 1 1
## 2 1 2
## 3 2 1
## 4 2 2
## 5 3 1
## 6 3 2</code></pre>
<div class="sourceCode" id="cb584"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/expand.html">crossing</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fl">1</span><span class="op">:</span><span class="fl">3</span>, y <span class="op">=</span> <span class="fl">1</span><span class="op">:</span><span class="fl">2</span><span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 6 × 2
## x y
## <int> <int>
## 1 1 1
## 2 1 2
## 3 2 1
## 4 2 2
## 5 3 1
## 6 3 2</code></pre>
<p>向量换成数据框也可以，其结果就是数据框行与元素的交叉组合</p>
<div class="sourceCode" id="cb586"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/expand_grid.html">expand_grid</a></span><span class="op">(</span>df <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fl">1</span><span class="op">:</span><span class="fl">2</span>, y <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="fl">2</span>, <span class="fl">1</span><span class="op">)</span><span class="op">)</span>, z <span class="op">=</span> <span class="fl">1</span><span class="op">:</span><span class="fl">3</span><span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 6 × 2
## df$x $y z
## <int> <dbl> <int>
## 1 1 2 1
## 2 1 2 2
## 3 1 2 3
## 4 2 1 1
## 5 2 1 2
## 6 2 1 3</code></pre>
<div class="sourceCode" id="cb588"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/expand.html">crossing</a></span><span class="op">(</span>df <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/data.frame.html">data.frame</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fl">1</span><span class="op">:</span><span class="fl">2</span>, y <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="fl">2</span>, <span class="fl">1</span><span class="op">)</span><span class="op">)</span>, z <span class="op">=</span> <span class="fl">1</span><span class="op">:</span><span class="fl">3</span><span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 6 × 2
## df$x $y z
## <int> <dbl> <int>
## 1 1 2 1
## 2 1 2 2
## 3 1 2 3
## 4 2 1 1
## 5 2 1 2
## 6 2 1 3</code></pre>
<p><code><a href="https://tidyr.tidyverse.org/reference/expand.html">crossing()</a></code>可以看作是<code>expand_grid() + distinct()</code>， 即<code><a href="https://tidyr.tidyverse.org/reference/expand.html">crossing()</a></code>在完成交叉组合之后会自动去重，比如</p>
<div class="sourceCode" id="cb590"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/expand_grid.html">expand_grid</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="fl">1</span>, <span class="fl">1</span><span class="op">)</span>, y <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="fl">1</span><span class="op">:</span><span class="fl">2</span><span class="op">)</span><span class="op">)</span> <span class="co"># 不考虑去重</span></span></code></pre></div>
<pre><code>## # A tibble: 4 × 2
## x y
## <dbl> <int>
## 1 1 1
## 2 1 2
## 3 1 1
## 4 1 2</code></pre>
<div class="sourceCode" id="cb592"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/expand.html">crossing</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="fl">1</span>, <span class="fl">1</span><span class="op">)</span>, y <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="fl">1</span><span class="op">:</span><span class="fl">2</span><span class="op">)</span><span class="op">)</span> <span class="co"># 考虑去重 </span></span></code></pre></div>
<pre><code>## # A tibble: 2 × 2
## x y
## <dbl> <int>
## 1 1 1
## 2 1 2</code></pre>
</div>
<div id="separate-与-unite" class="section level2" number="14.4">
<h2>
<span class="header-section-number">14.4</span> <code>separate()</code> 与 <code>unite()</code><a class="anchor" aria-label="anchor" href="#separate-%E4%B8%8E-unite"><i class="fas fa-link"></i></a>
</h2>
<div class="sourceCode" id="cb594"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">tb</span> <span class="op"><-</span> <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/tribble.html">tribble</a></span><span class="op">(</span></span>
<span> <span class="op">~</span><span class="va">day</span>, <span class="op">~</span><span class="va">price</span>,</span>
<span> <span class="fl">1</span>, <span class="st">"30-45"</span>,</span>
<span> <span class="fl">2</span>, <span class="st">"40-95"</span>,</span>
<span> <span class="fl">3</span>, <span class="st">"89-65"</span>,</span>
<span> <span class="fl">4</span>, <span class="st">"45-63"</span>,</span>
<span> <span class="fl">5</span>, <span class="st">"52-42"</span></span>
<span><span class="op">)</span></span></code></pre></div>
<div class="sourceCode" id="cb595"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">tb1</span> <span class="op"><-</span> <span class="va">tb</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span></span>
<span> <span class="fu"><a href="https://tidyr.tidyverse.org/reference/separate.html">separate</a></span><span class="op">(</span><span class="va">price</span>, into <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"low"</span>, <span class="st">"high"</span><span class="op">)</span>, sep <span class="op">=</span> <span class="st">"-"</span><span class="op">)</span></span>
<span><span class="va">tb1</span></span></code></pre></div>
<pre><code>## # A tibble: 5 × 3
## day low high
## <dbl> <chr> <chr>
## 1 1 30 45
## 2 2 40 95
## 3 3 89 65
## 4 4 45 63
## 5 5 52 42</code></pre>
<div class="sourceCode" id="cb597"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">tb1</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span></span>
<span> <span class="fu"><a href="https://tidyr.tidyverse.org/reference/unite.html">unite</a></span><span class="op">(</span>col <span class="op">=</span> <span class="st">"price"</span>, <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="va">low</span>, <span class="va">high</span><span class="op">)</span>, sep <span class="op">=</span> <span class="st">":"</span>, remove <span class="op">=</span> <span class="cn">FALSE</span><span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 5 × 4
## day price low high
## <dbl> <chr> <chr> <chr>
## 1 1 30:45 30 45
## 2 2 40:95 40 95
## 3 3 89:65 89 65
## 4 4 45:63 45 63
## 5 5 52:42 52 42</code></pre>
<p>有时候分隔符搞不定的，可以用正则表达式，将捕获的每组弄成一列</p>
<div class="sourceCode" id="cb599"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">dfc</span> <span class="op"><-</span> <span class="fu"><a href="https://tibble.tidyverse.org/reference/tibble.html">tibble</a></span><span class="op">(</span>x <span class="op">=</span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"1-12week"</span>, <span class="st">"1-10wk"</span>, <span class="st">"5-12w"</span>, <span class="st">"01-05weeks"</span><span class="op">)</span><span class="op">)</span></span>
<span><span class="va">dfc</span></span></code></pre></div>
<pre><code>## # A tibble: 4 × 1
## x
## <chr>
## 1 1-12week
## 2 1-10wk
## 3 5-12w
## 4 01-05weeks</code></pre>
<div class="sourceCode" id="cb601"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">dfc</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span> <span class="fu">tidyr</span><span class="fu">::</span><span class="fu"><a href="https://tidyr.tidyverse.org/reference/extract.html">extract</a></span><span class="op">(</span></span>
<span> <span class="va">x</span>,</span>
<span> <span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="st">"start"</span>, <span class="st">"end"</span>, <span class="st">"letter"</span><span class="op">)</span>, <span class="st">"(\\d+)-(\\d+)([a-z]+)"</span>,</span>
<span> remove <span class="op">=</span> <span class="cn">FALSE</span></span>
<span><span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 4 × 4
## x start end letter
## <chr> <chr> <chr> <chr>
## 1 1-12week 1 12 week
## 2 1-10wk 1 10 wk
## 3 5-12w 5 12 w
## 4 01-05weeks 01 05 weeks</code></pre>
</div>
<div id="删除缺失值所在行drop_na与replace_na" class="section level2" number="14.5">
<h2>
<span class="header-section-number">14.5</span> 删除缺失值所在行drop_na()与replace_na()<a class="anchor" aria-label="anchor" href="#%E5%88%A0%E9%99%A4%E7%BC%BA%E5%A4%B1%E5%80%BC%E6%89%80%E5%9C%A8%E8%A1%8Cdrop_na%E4%B8%8Ereplace_na"><i class="fas fa-link"></i></a>
</h2>
<div class="sourceCode" id="cb603"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><-</span> <span class="fu">tibble</span><span class="fu">::</span><span class="fu"><a href="https://tibble.tidyverse.org/reference/tribble.html">tribble</a></span><span class="op">(</span></span>
<span> <span class="op">~</span><span class="va">name</span>, <span class="op">~</span><span class="va">type</span>, <span class="op">~</span><span class="va">score</span>, <span class="op">~</span><span class="va">extra</span>,</span>
<span> <span class="st">"Alice"</span>, <span class="st">"english"</span>, <span class="fl">80</span>, <span class="fl">10</span>,</span>
<span> <span class="st">"Alice"</span>, <span class="st">"math"</span>, <span class="cn">NA</span>, <span class="fl">5</span>,</span>
<span> <span class="st">"Bob"</span>, <span class="st">"english"</span>, <span class="cn">NA</span>, <span class="fl">9</span>,</span>
<span> <span class="st">"Bob"</span>, <span class="st">"math"</span>, <span class="fl">69</span>, <span class="cn">NA</span>,</span>
<span> <span class="st">"Carol"</span>, <span class="st">"english"</span>, <span class="fl">80</span>, <span class="fl">10</span>,</span>
<span> <span class="st">"Carol"</span>, <span class="st">"math"</span>, <span class="fl">90</span>, <span class="fl">5</span></span>
<span> <span class="op">)</span></span>
<span></span>
<span><span class="va">df</span></span></code></pre></div>
<pre><code>## # A tibble: 6 × 4
## name type score extra
## <chr> <chr> <dbl> <dbl>
## 1 Alice english 80 10
## 2 Alice math NA 5
## 3 Bob english NA 9
## 4 Bob math 69 NA
## 5 Carol english 80 10
## 6 Carol math 90 5</code></pre>
<p>如果score列中有缺失值<code>NA</code>，就删除所在的row</p>
<div class="sourceCode" id="cb605"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span><span class="op">(</span><span class="op">!</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html">is.na</a></span><span class="op">(</span><span class="va">score</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 4 × 4
## name type score extra
## <chr> <chr> <dbl> <dbl>
## 1 Alice english 80 10
## 2 Bob math 69 NA
## 3 Carol english 80 10
## 4 Carol math 90 5</code></pre>
<p>或者用<code><a href="https://dplyr.tidyverse.org/reference/across.html">across()</a></code></p>
<div class="sourceCode" id="cb607"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span><span class="op">(</span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html">across</a></span><span class="op">(</span><span class="va">score</span>, <span class="op">~</span> <span class="op">!</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html">is.na</a></span><span class="op">(</span><span class="va">.x</span><span class="op">)</span><span class="op">)</span></span>
<span> <span class="op">)</span></span></code></pre></div>
<pre><code>## Warning: Using `across()` in `filter()` was deprecated in dplyr 1.0.8.
## ℹ Please use `if_any()` or `if_all()` instead.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.</code></pre>
<pre><code>## # A tibble: 4 × 4
## name type score extra
## <chr> <chr> <dbl> <dbl>
## 1 Alice english 80 10
## 2 Bob math 69 NA
## 3 Carol english 80 10
## 4 Carol math 90 5</code></pre>
<p>所有列，如果有缺失值<code>NA</code>，就删除所在的row</p>
<div class="sourceCode" id="cb610"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html">filter</a></span><span class="op">(</span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html">across</a></span><span class="op">(</span><span class="fu"><a href="https://tidyselect.r-lib.org/reference/everything.html">everything</a></span><span class="op">(</span><span class="op">)</span>, <span class="op">~</span> <span class="op">!</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html">is.na</a></span><span class="op">(</span><span class="va">.x</span><span class="op">)</span><span class="op">)</span></span>
<span> <span class="op">)</span></span></code></pre></div>
<pre><code>## Warning: Using `across()` in `filter()` was deprecated in dplyr 1.0.8.
## ℹ Please use `if_any()` or `if_all()` instead.
## Call `lifecycle::last_lifecycle_warnings()` to see where this warning was
## generated.</code></pre>
<pre><code>## # A tibble: 3 × 4
## name type score extra
## <chr> <chr> <dbl> <dbl>
## 1 Alice english 80 10
## 2 Carol english 80 10
## 3 Carol math 90 5</code></pre>
<p>现在有更简便的方法</p>
<div class="sourceCode" id="cb613"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span></span>
<span> <span class="fu"><a href="https://tidyr.tidyverse.org/reference/drop_na.html">drop_na</a></span><span class="op">(</span><span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 3 × 4
## name type score extra
## <chr> <chr> <dbl> <dbl>
## 1 Alice english 80 10
## 2 Carol english 80 10
## 3 Carol math 90 5</code></pre>
<p>也可指定某一列</p>
<div class="sourceCode" id="cb615"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span></span>
<span> <span class="fu"><a href="https://tidyr.tidyverse.org/reference/drop_na.html">drop_na</a></span><span class="op">(</span><span class="va">score</span><span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 4 × 4
## name type score extra
## <chr> <chr> <dbl> <dbl>
## 1 Alice english 80 10
## 2 Bob math 69 NA
## 3 Carol english 80 10
## 4 Carol math 90 5</code></pre>
<p>没来参加考试，视为0分，可以用<code><a href="https://tidyr.tidyverse.org/reference/replace_na.html">replace_na()</a></code></p>
<div class="sourceCode" id="cb617"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span><span class="op">(</span>score <span class="op">=</span> <span class="fu"><a href="https://tidyr.tidyverse.org/reference/replace_na.html">replace_na</a></span><span class="op">(</span><span class="va">score</span>, <span class="fl">0</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 6 × 4
## name type score extra
## <chr> <chr> <dbl> <dbl>
## 1 Alice english 80 10
## 2 Alice math 0 5
## 3 Bob english 0 9
## 4 Bob math 69 NA
## 5 Carol english 80 10
## 6 Carol math 90 5</code></pre>
<p>或者使用<code><a href="https://dplyr.tidyverse.org/reference/coalesce.html">coalesce()</a></code></p>
<div class="sourceCode" id="cb619"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span><span class="op">(</span>score <span class="op">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/coalesce.html">coalesce</a></span><span class="op">(</span><span class="va">score</span>, <span class="fl">0</span><span class="op">)</span><span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 6 × 4
## name type score extra
## <chr> <chr> <dbl> <dbl>
## 1 Alice english 80 10
## 2 Alice math 0 5
## 3 Bob english 0 9
## 4 Bob math 69 NA
## 5 Carol english 80 10
## 6 Carol math 90 5</code></pre>
<div class="sourceCode" id="cb621"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span><span class="op">(</span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/across.html">across</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/c.html">c</a></span><span class="op">(</span><span class="va">score</span>, <span class="va">extra</span><span class="op">)</span>, <span class="op">~</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/coalesce.html">coalesce</a></span><span class="op">(</span><span class="va">.x</span>, <span class="fl">0</span><span class="op">)</span><span class="op">)</span></span>
<span> <span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 6 × 4
## name type score extra
## <chr> <chr> <dbl> <dbl>
## 1 Alice english 80 10
## 2 Alice math 0 5
## 3 Bob english 0 9
## 4 Bob math 69 0
## 5 Carol english 80 10
## 6 Carol math 90 5</code></pre>
<p>没来参加考试，用平均分代替</p>
<div class="sourceCode" id="cb623"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span><span class="op">(</span></span>
<span> score <span class="op">=</span> <span class="fu"><a href="https://tidyr.tidyverse.org/reference/replace_na.html">replace_na</a></span><span class="op">(</span><span class="va">score</span>, <span class="fu"><a href="https://rdrr.io/r/base/mean.html">mean</a></span><span class="op">(</span><span class="va">score</span>, na.rm <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span><span class="op">)</span></span>
<span> <span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 6 × 4
## name type score extra
## <chr> <chr> <dbl> <dbl>
## 1 Alice english 80 10
## 2 Alice math 79.8 5
## 3 Bob english 79.8 9
## 4 Bob math 69 NA
## 5 Carol english 80 10
## 6 Carol math 90 5</code></pre>
<p>当然也可以用<code><a href="https://dplyr.tidyverse.org/reference/if_else.html">if_else()</a></code>来做</p>
<div class="sourceCode" id="cb625"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span><span class="va">df</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html">%>%</a></span></span>
<span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/mutate.html">mutate</a></span><span class="op">(</span></span>
<span> score <span class="op">=</span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/if_else.html">if_else</a></span><span class="op">(</span><span class="fu"><a href="https://rdrr.io/r/base/NA.html">is.na</a></span><span class="op">(</span><span class="va">score</span><span class="op">)</span>, <span class="fu"><a href="https://rdrr.io/r/base/mean.html">mean</a></span><span class="op">(</span><span class="va">score</span>, na.rm <span class="op">=</span> <span class="cn">TRUE</span><span class="op">)</span>, <span class="va">score</span><span class="op">)</span></span>
<span> <span class="op">)</span></span></code></pre></div>
<pre><code>## # A tibble: 6 × 4
## name type score extra
## <chr> <chr> <dbl> <dbl>
## 1 Alice english 80 10
## 2 Alice math 79.8 5
## 3 Bob english 79.8 9
## 4 Bob math 69 NA
## 5 Carol english 80 10
## 6 Carol math 90 5</code></pre>
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<li><a class="nav-link" href="#tidyverse-tidyr2"><span class="header-section-number">14</span> 数据规整2</a></li>
<li><a class="nav-link" href="#fill-%E7%BC%BA%E5%A4%B1%E5%80%BC%E5%A1%AB%E5%85%85"><span class="header-section-number">14.1</span> fill() 缺失值填充</a></li>
<li><a class="nav-link" href="#expand-%E4%B8%8E-complete"><span class="header-section-number">14.2</span> expand() 与 complete()</a></li>
<li><a class="nav-link" href="#expand_grid-%E4%B8%8E-crossing"><span class="header-section-number">14.3</span> expand_grid() 与 crossing()</a></li>
<li><a class="nav-link" href="#separate-%E4%B8%8E-unite"><span class="header-section-number">14.4</span> separate() 与 unite()</a></li>
<li><a class="nav-link" href="#%E5%88%A0%E9%99%A4%E7%BC%BA%E5%A4%B1%E5%80%BC%E6%89%80%E5%9C%A8%E8%A1%8Cdrop_na%E4%B8%8Ereplace_na"><span class="header-section-number">14.5</span> 删除缺失值所在行drop_na()与replace_na()</a></li>
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