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<span id="text"></span><h1><span class="yiyi-st" id="yiyi-55">Working with Text Data</span></h1>
<blockquote>
<p>原文：<a href="http://pandas.pydata.org/pandas-docs/stable/text.html">http://pandas.pydata.org/pandas-docs/stable/text.html</a></p>
<p>译者：<a href="https://github.com/wizardforcel">飞龙</a> <a href="http://usyiyi.cn/">UsyiyiCN</a></p>
<p>校对：（虚位以待）</p>
</blockquote>
<p id="text-string-methods"><span class="yiyi-st" id="yiyi-56">系列和索引都配备了一组字符串处理方法，使其易于对数组的每个元素进行操作。</span><span class="yiyi-st" id="yiyi-57">也许最重要的是，这些方法自动排除丢失/ NA值。</span><span class="yiyi-st" id="yiyi-58">这些通过<code class="docutils literal"><span class="pre">str</span></code>属性访问，通常具有与等效（标量）内置字符串方法匹配的名称：</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [1]: </span><span class="n">s</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="s1">'A'</span><span class="p">,</span> <span class="s1">'B'</span><span class="p">,</span> <span class="s1">'C'</span><span class="p">,</span> <span class="s1">'Aaba'</span><span class="p">,</span> <span class="s1">'Baca'</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span> <span class="s1">'CABA'</span><span class="p">,</span> <span class="s1">'dog'</span><span class="p">,</span> <span class="s1">'cat'</span><span class="p">])</span>
<span class="gp">In [2]: </span><span class="n">s</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">lower</span><span class="p">()</span>
<span class="gr">Out[2]: </span>
<span class="go">0 a</span>
<span class="go">1 b</span>
<span class="go">2 c</span>
<span class="go">3 aaba</span>
<span class="go">4 baca</span>
<span class="go">5 NaN</span>
<span class="go">6 caba</span>
<span class="go">7 dog</span>
<span class="go">8 cat</span>
<span class="go">dtype: object</span>
<span class="gp">In [3]: </span><span class="n">s</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">upper</span><span class="p">()</span>
<span class="gr">Out[3]: </span>
<span class="go">0 A</span>
<span class="go">1 B</span>
<span class="go">2 C</span>
<span class="go">3 AABA</span>
<span class="go">4 BACA</span>
<span class="go">5 NaN</span>
<span class="go">6 CABA</span>
<span class="go">7 DOG</span>
<span class="go">8 CAT</span>
<span class="go">dtype: object</span>
<span class="gp">In [4]: </span><span class="n">s</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">len</span><span class="p">()</span>
<span class="gr">Out[4]: </span>
<span class="go">0 1.0</span>
<span class="go">1 1.0</span>
<span class="go">2 1.0</span>
<span class="go">3 4.0</span>
<span class="go">4 4.0</span>
<span class="go">5 NaN</span>
<span class="go">6 4.0</span>
<span class="go">7 3.0</span>
<span class="go">8 3.0</span>
<span class="go">dtype: float64</span>
</pre></div>
</div>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [5]: </span><span class="n">idx</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Index</span><span class="p">([</span><span class="s1">' jack'</span><span class="p">,</span> <span class="s1">'jill '</span><span class="p">,</span> <span class="s1">' jesse '</span><span class="p">,</span> <span class="s1">'frank'</span><span class="p">])</span>
<span class="gp">In [6]: </span><span class="n">idx</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">strip</span><span class="p">()</span>
<span class="gr">Out[6]: </span><span class="n">Index</span><span class="p">([</span><span class="s1">u'jack'</span><span class="p">,</span> <span class="s1">u'jill'</span><span class="p">,</span> <span class="s1">u'jesse'</span><span class="p">,</span> <span class="s1">u'frank'</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="s1">'object'</span><span class="p">)</span>
<span class="gp">In [7]: </span><span class="n">idx</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">lstrip</span><span class="p">()</span>
<span class="gr">Out[7]: </span><span class="n">Index</span><span class="p">([</span><span class="s1">u'jack'</span><span class="p">,</span> <span class="s1">u'jill '</span><span class="p">,</span> <span class="s1">u'jesse '</span><span class="p">,</span> <span class="s1">u'frank'</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="s1">'object'</span><span class="p">)</span>
<span class="gp">In [8]: </span><span class="n">idx</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">rstrip</span><span class="p">()</span>
<span class="gr">Out[8]: </span><span class="n">Index</span><span class="p">([</span><span class="s1">u' jack'</span><span class="p">,</span> <span class="s1">u'jill'</span><span class="p">,</span> <span class="s1">u' jesse'</span><span class="p">,</span> <span class="s1">u'frank'</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="s1">'object'</span><span class="p">)</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-59">Index上的字符串方法对清理或转换DataFrame列特别有用。</span><span class="yiyi-st" id="yiyi-60">例如，您可能有具有前导或尾随空格的列：</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [9]: </span><span class="n">df</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">(</span><span class="n">randn</span><span class="p">(</span><span class="mi">3</span><span class="p">,</span> <span class="mi">2</span><span class="p">),</span> <span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s1">' Column A '</span><span class="p">,</span> <span class="s1">' Column B '</span><span class="p">],</span>
<span class="gp"> ...:</span> <span class="n">index</span><span class="o">=</span><span class="nb">range</span><span class="p">(</span><span class="mi">3</span><span class="p">))</span>
<span class="gp"> ...:</span>
<span class="gp">In [10]: </span><span class="n">df</span>
<span class="gr">Out[10]: </span>
<span class="go"> Column A Column B </span>
<span class="go">0 0.017428 0.039049</span>
<span class="go">1 -2.240248 0.847859</span>
<span class="go">2 -1.342107 0.368828</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-61">由于<code class="docutils literal"><span class="pre">df.columns</span></code>是一个Index对象，我们可以使用<code class="docutils literal"><span class="pre">.str</span></code>存取器</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [11]: </span><span class="n">df</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">strip</span><span class="p">()</span>
<span class="gr">Out[11]: </span><span class="n">Index</span><span class="p">([</span><span class="s1">u'Column A'</span><span class="p">,</span> <span class="s1">u'Column B'</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="s1">'object'</span><span class="p">)</span>
<span class="gp">In [12]: </span><span class="n">df</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">lower</span><span class="p">()</span>
<span class="gr">Out[12]: </span><span class="n">Index</span><span class="p">([</span><span class="s1">u' column a '</span><span class="p">,</span> <span class="s1">u' column b '</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="s1">'object'</span><span class="p">)</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-62">然后可以根据需要使用这些字符串方法来清理列。</span><span class="yiyi-st" id="yiyi-63">这里我们删除前导和尾随空格，缩小所有名称，并用下划线替换任何剩余的空白：</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [13]: </span><span class="n">df</span><span class="o">.</span><span class="n">columns</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">columns</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">strip</span><span class="p">()</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">lower</span><span class="p">()</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">' '</span><span class="p">,</span> <span class="s1">'_'</span><span class="p">)</span>
<span class="gp">In [14]: </span><span class="n">df</span>
<span class="gr">Out[14]: </span>
<span class="go"> column_a column_b</span>
<span class="go">0 0.017428 0.039049</span>
<span class="go">1 -2.240248 0.847859</span>
<span class="go">2 -1.342107 0.368828</span>
</pre></div>
</div>
<div class="admonition note">
<p class="first admonition-title"><span class="yiyi-st" id="yiyi-64">注意</span></p>
<p><span class="yiyi-st" id="yiyi-65">假如你有一个许多元素都重复的 <code class="docutils literal"><span class="pre">Series</span></code> (i.e. <code class="docutils literal"><span class="pre">Series</span></code> 中唯一元素的数量远小于<code class="docutils literal"><span class="pre">Series</span></code>的长度),将原始的 <code class="docutils literal"><span class="pre">Series</span></code> 转换成<code class="docutils literal"><span class="pre">category</span></code> 然后使用 <code class="docutils literal"><span class="pre">.str.<method></span></code> or <code class="docutils literal"><span class="pre">.dt.<property></span></code>将会更快.</span><span class="yiyi-st" id="yiyi-66">性能差异来自于对<code class="docutils literal"><span class="pre">category</span></code>类型的<code class="docutils literal"><span class="pre">Series</span></code>，字符串操作在<code class="docutils literal"><span class="pre">.categories</span></code>上完成，而不是在每个元素的<code class="docutils literal"><span class="pre">Series</span></code>。</span></p>
<p class="last"><span class="yiyi-st" id="yiyi-67">请注意，类型字符串<code class="docutils literal"><span class="pre">Series</span></code>的比较类型<code class="docutils literal"><span class="pre">category</span></code>与字符串<code class="docutils literal"><span class="pre">.categories</span></code>的<code class="docutils literal"><span class="pre">Series</span></code> （例如，您不能向对方添加字符串：<code class="docutils literal"><span class="pre">s</span> <span class="pre">+</span> <span class="pre">“</span> <span class="pre">”</span> <span class="pre">如果<code class="docutils literal"><span class="pre">s</span></code>是类型<code class="docutils literal"><span class="pre">category</span></code>的<code class="docutils literal"><span class="pre">Series</span></code>，则 <span class="pre"></span> ）。</span></code></span><span class="yiyi-st" id="yiyi-68">此外，对类型<code class="docutils literal"><span class="pre">list</span></code>的元素进行操作的<code class="docutils literal"><span class="pre">.str</span></code>方法在这种<code class="docutils literal"><span class="pre">Series</span></code>上不可用。</span></p>
</div>
<div class="section" id="splitting-and-replacing-strings">
<h2><span class="yiyi-st" id="yiyi-69">Splitting and Replacing Strings</span></h2>
<p id="text-split"><span class="yiyi-st" id="yiyi-70"><code class="docutils literal"><span class="pre">split</span></code>等方法返回一系列列表：</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [15]: </span><span class="n">s2</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="s1">'a_b_c'</span><span class="p">,</span> <span class="s1">'c_d_e'</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span> <span class="s1">'f_g_h'</span><span class="p">])</span>
<span class="gp">In [16]: </span><span class="n">s2</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">'_'</span><span class="p">)</span>
<span class="gr">Out[16]: </span>
<span class="go">0 [a, b, c]</span>
<span class="go">1 [c, d, e]</span>
<span class="go">2 NaN</span>
<span class="go">3 [f, g, h]</span>
<span class="go">dtype: object</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-71">可以使用<code class="docutils literal"><span class="pre">get</span></code>或<code class="docutils literal"><span class="pre">[]</span></code>符号访问拆分列表中的元素：</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [17]: </span><span class="n">s2</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">'_'</span><span class="p">)</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">get</span><span class="p">(</span><span class="mi">1</span><span class="p">)</span>
<span class="gr">Out[17]: </span>
<span class="go">0 b</span>
<span class="go">1 d</span>
<span class="go">2 NaN</span>
<span class="go">3 g</span>
<span class="go">dtype: object</span>
<span class="gp">In [18]: </span><span class="n">s2</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">'_'</span><span class="p">)</span><span class="o">.</span><span class="n">str</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
<span class="gr">Out[18]: </span>
<span class="go">0 b</span>
<span class="go">1 d</span>
<span class="go">2 NaN</span>
<span class="go">3 g</span>
<span class="go">dtype: object</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-72">使用<code class="docutils literal"><span class="pre">expand</span></code>可以轻松扩展此操作以返回DataFrame。</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [19]: </span><span class="n">s2</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">'_'</span><span class="p">,</span> <span class="n">expand</span><span class="o">=</span><span class="bp">True</span><span class="p">)</span>
<span class="gr">Out[19]: </span>
<span class="go"> 0 1 2</span>
<span class="go">0 a b c</span>
<span class="go">1 c d e</span>
<span class="go">2 NaN None None</span>
<span class="go">3 f g h</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-73">也可以限制分割数：</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [20]: </span><span class="n">s2</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">split</span><span class="p">(</span><span class="s1">'_'</span><span class="p">,</span> <span class="n">expand</span><span class="o">=</span><span class="bp">True</span><span class="p">,</span> <span class="n">n</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="gr">Out[20]: </span>
<span class="go"> 0 1</span>
<span class="go">0 a b_c</span>
<span class="go">1 c d_e</span>
<span class="go">2 NaN None</span>
<span class="go">3 f g_h</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-74"><code class="docutils literal"><span class="pre">rsplit</span></code>类似于<code class="docutils literal"><span class="pre">split</span></code>，除了它在反向工作，即从字符串的末尾到字符串的开头：</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [21]: </span><span class="n">s2</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">rsplit</span><span class="p">(</span><span class="s1">'_'</span><span class="p">,</span> <span class="n">expand</span><span class="o">=</span><span class="bp">True</span><span class="p">,</span> <span class="n">n</span><span class="o">=</span><span class="mi">1</span><span class="p">)</span>
<span class="gr">Out[21]: </span>
<span class="go"> 0 1</span>
<span class="go">0 a_b c</span>
<span class="go">1 c_d e</span>
<span class="go">2 NaN None</span>
<span class="go">3 f_g h</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-75">类似<code class="docutils literal"><span class="pre">replace</span></code>和<code class="docutils literal"><span class="pre">findall</span></code>的方法也可以使用<a class="reference external" href="https://docs.python.org/2/library/re.html">正则表达式</a>：</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [22]: </span><span class="n">s3</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="s1">'A'</span><span class="p">,</span> <span class="s1">'B'</span><span class="p">,</span> <span class="s1">'C'</span><span class="p">,</span> <span class="s1">'Aaba'</span><span class="p">,</span> <span class="s1">'Baca'</span><span class="p">,</span>
<span class="gp"> ....:</span> <span class="s1">''</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span> <span class="s1">'CABA'</span><span class="p">,</span> <span class="s1">'dog'</span><span class="p">,</span> <span class="s1">'cat'</span><span class="p">])</span>
<span class="gp"> ....:</span>
<span class="gp">In [23]: </span><span class="n">s3</span>
<span class="gr">Out[23]: </span>
<span class="go">0 A</span>
<span class="go">1 B</span>
<span class="go">2 C</span>
<span class="go">3 Aaba</span>
<span class="go">4 Baca</span>
<span class="go">5 </span>
<span class="go">6 NaN</span>
<span class="go">7 CABA</span>
<span class="go">8 dog</span>
<span class="go">9 cat</span>
<span class="go">dtype: object</span>
<span class="gp">In [24]: </span><span class="n">s3</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">'^.a|dog'</span><span class="p">,</span> <span class="s1">'XX-XX '</span><span class="p">,</span> <span class="n">case</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
<span class="gr">Out[24]: </span>
<span class="go">0 A</span>
<span class="go">1 B</span>
<span class="go">2 C</span>
<span class="go">3 XX-XX ba</span>
<span class="go">4 XX-XX ca</span>
<span class="go">5 </span>
<span class="go">6 NaN</span>
<span class="go">7 XX-XX BA</span>
<span class="go">8 XX-XX </span>
<span class="go">9 XX-XX t</span>
<span class="go">dtype: object</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-76">必须注意保持正则表达式！</span><span class="yiyi-st" id="yiyi-77">例如，以下代码会因为<cite>$</cite>的正则表达式含义而导致麻烦：</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="c"># Consider the following badly formatted financial data</span>
<span class="gp">In [25]: </span><span class="n">dollars</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="s1">'12'</span><span class="p">,</span> <span class="s1">'-$10'</span><span class="p">,</span> <span class="s1">'$10,000'</span><span class="p">])</span>
<span class="c"># This does what you'd naively expect:</span>
<span class="gp">In [26]: </span><span class="n">dollars</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">'$'</span><span class="p">,</span> <span class="s1">''</span><span class="p">)</span>
<span class="gr">Out[26]: </span>
<span class="go">0 12</span>
<span class="go">1 -10</span>
<span class="go">2 10,000</span>
<span class="go">dtype: object</span>
<span class="c"># But this doesn't:</span>
<span class="gp">In [27]: </span><span class="n">dollars</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">'-$'</span><span class="p">,</span> <span class="s1">'-'</span><span class="p">)</span>
<span class="gr">Out[27]: </span>
<span class="go">0 12</span>
<span class="go">1 -$10</span>
<span class="go">2 $10,000</span>
<span class="go">dtype: object</span>
<span class="c"># We need to escape the special character (for >1 len patterns)</span>
<span class="gp">In [28]: </span><span class="n">dollars</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">replace</span><span class="p">(</span><span class="s1">r'-\$'</span><span class="p">,</span> <span class="s1">'-'</span><span class="p">)</span>
<span class="gr">Out[28]: </span>
<span class="go">0 12</span>
<span class="go">1 -10</span>
<span class="go">2 $10,000</span>
<span class="go">dtype: object</span>
</pre></div>
</div>
</div>
<div class="section" id="indexing-with-str">
<h2><span class="yiyi-st" id="yiyi-78">Indexing with <code class="docutils literal"><span class="pre">.str</span></code></span></h2>
<p id="text-indexing"><span class="yiyi-st" id="yiyi-79">您可以使用<code class="docutils literal"><span class="pre">[]</span></code>表示法直接通过位置位置索引。</span><span class="yiyi-st" id="yiyi-80">如果索引超过字符串的末尾，结果将是<code class="docutils literal"><span class="pre">NaN</span></code>。</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [29]: </span><span class="n">s</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="s1">'A'</span><span class="p">,</span> <span class="s1">'B'</span><span class="p">,</span> <span class="s1">'C'</span><span class="p">,</span> <span class="s1">'Aaba'</span><span class="p">,</span> <span class="s1">'Baca'</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span>
<span class="gp"> ....:</span> <span class="s1">'CABA'</span><span class="p">,</span> <span class="s1">'dog'</span><span class="p">,</span> <span class="s1">'cat'</span><span class="p">])</span>
<span class="gp"> ....:</span>
<span class="gp">In [30]: </span><span class="n">s</span><span class="o">.</span><span class="n">str</span><span class="p">[</span><span class="mi">0</span><span class="p">]</span>
<span class="gr">Out[30]: </span>
<span class="go">0 A</span>
<span class="go">1 B</span>
<span class="go">2 C</span>
<span class="go">3 A</span>
<span class="go">4 B</span>
<span class="go">5 NaN</span>
<span class="go">6 C</span>
<span class="go">7 d</span>
<span class="go">8 c</span>
<span class="go">dtype: object</span>
<span class="gp">In [31]: </span><span class="n">s</span><span class="o">.</span><span class="n">str</span><span class="p">[</span><span class="mi">1</span><span class="p">]</span>
<span class="gr">Out[31]: </span>
<span class="go">0 NaN</span>
<span class="go">1 NaN</span>
<span class="go">2 NaN</span>
<span class="go">3 a</span>
<span class="go">4 a</span>
<span class="go">5 NaN</span>
<span class="go">6 A</span>
<span class="go">7 o</span>
<span class="go">8 a</span>
<span class="go">dtype: object</span>
</pre></div>
</div>
</div>
<div class="section" id="extracting-substrings">
<h2><span class="yiyi-st" id="yiyi-81">Extracting Substrings</span></h2>
<div class="section" id="extract-first-match-in-each-subject-extract">
<span id="text-extract"></span><h3><span class="yiyi-st" id="yiyi-82">Extract first match in each subject (extract)</span></h3>
<div class="versionadded">
<p><span class="yiyi-st" id="yiyi-83"><span class="versionmodified">版本0.13.0中的新功能。</span></span></p>
</div>
<div class="admonition warning">
<p class="first admonition-title"><span class="yiyi-st" id="yiyi-84">警告</span></p>
<p class="last"><span class="yiyi-st" id="yiyi-85">在版本0.18.0中，<code class="docutils literal"><span class="pre">extract</span></code>获得了<code class="docutils literal"><span class="pre">expand</span></code>参数。</span><span class="yiyi-st" id="yiyi-86">当<code class="docutils literal"><span class="pre">expand=False</span></code>时，根据主题和正则表达式模式，它返回<code class="docutils literal"><span class="pre">Series</span></code>，<code class="docutils literal"><span class="pre">Index</span></code>或<code class="docutils literal"><span class="pre">DataFrame</span></code> （与0.18.0之前的行为相同）。</span><span class="yiyi-st" id="yiyi-87">当<code class="docutils literal"><span class="pre">expand=True</span></code>时，它始终返回一个<code class="docutils literal"><span class="pre">DataFrame</span></code>，这从用户的角度来看更一致，更少混淆。</span></p>
</div>
<p><span class="yiyi-st" id="yiyi-88"><code class="docutils literal"><span class="pre">extract</span></code>方法接受具有至少一个捕获组的<a class="reference external" href="https://docs.python.org/2/library/re.html">正则表达式</a>。</span></p>
<p><span class="yiyi-st" id="yiyi-89">使用多个组提取正则表达式会返回每个组一个列的DataFrame。</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [32]: </span><span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="s1">'a1'</span><span class="p">,</span> <span class="s1">'b2'</span><span class="p">,</span> <span class="s1">'c3'</span><span class="p">])</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s1">'([ab])(\d)'</span><span class="p">,</span> <span class="n">expand</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
<span class="gr">Out[32]: </span>
<span class="go"> 0 1</span>
<span class="go">0 a 1</span>
<span class="go">1 b 2</span>
<span class="go">2 NaN NaN</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-90">不匹配的元素返回填充有<code class="docutils literal"><span class="pre">NaN</span></code>的行。</span><span class="yiyi-st" id="yiyi-91">因此，一系列乱码字符串可以被“转换”为清理过的或更有用的字符串的索引相同的系列或数据帧，而不需要<code class="docutils literal"><span class="pre">get()</span></code>来访问元组或<code class="docutils literal"><span class="pre">re.match</span></code>对象。</span><span class="yiyi-st" id="yiyi-92">结果的dtype始终为对象，即使未找到匹配项，结果只包含<code class="docutils literal"><span class="pre">NaN</span></code>。</span></p>
<p><span class="yiyi-st" id="yiyi-93">命名组喜欢</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [33]: </span><span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="s1">'a1'</span><span class="p">,</span> <span class="s1">'b2'</span><span class="p">,</span> <span class="s1">'c3'</span><span class="p">])</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s1">'(?P<letter>[ab])(?P<digit>\d)'</span><span class="p">,</span> <span class="n">expand</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
<span class="gr">Out[33]: </span>
<span class="go"> letter digit</span>
<span class="go">0 a 1</span>
<span class="go">1 b 2</span>
<span class="go">2 NaN NaN</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-94">和可选组</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [34]: </span><span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="s1">'a1'</span><span class="p">,</span> <span class="s1">'b2'</span><span class="p">,</span> <span class="s1">'3'</span><span class="p">])</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s1">'([ab])?(\d)'</span><span class="p">,</span> <span class="n">expand</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
<span class="gr">Out[34]: </span>
<span class="go"> 0 1</span>
<span class="go">0 a 1</span>
<span class="go">1 b 2</span>
<span class="go">2 NaN 3</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-95">也可以使用。</span><span class="yiyi-st" id="yiyi-96">请注意，正则表达式中的任何捕获组名称都将用于列名称；否则将使用捕获组编号。</span></p>
<p><span class="yiyi-st" id="yiyi-97">如果<code class="docutils literal"><span class="pre">expand=True</span></code>，则提取具有一个组的正则表达式将返回一个具有一列的<code class="docutils literal"><span class="pre">DataFrame</span></code>。</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [35]: </span><span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="s1">'a1'</span><span class="p">,</span> <span class="s1">'b2'</span><span class="p">,</span> <span class="s1">'c3'</span><span class="p">])</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s1">'[ab](\d)'</span><span class="p">,</span> <span class="n">expand</span><span class="o">=</span><span class="bp">True</span><span class="p">)</span>
<span class="gr">Out[35]: </span>
<span class="go"> 0</span>
<span class="go">0 1</span>
<span class="go">1 2</span>
<span class="go">2 NaN</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-98">如果<code class="docutils literal"><span class="pre">expand=False</span></code>，则返回一个系列。</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [36]: </span><span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="s1">'a1'</span><span class="p">,</span> <span class="s1">'b2'</span><span class="p">,</span> <span class="s1">'c3'</span><span class="p">])</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s1">'[ab](\d)'</span><span class="p">,</span> <span class="n">expand</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
<span class="gr">Out[36]: </span>
<span class="go">0 1</span>
<span class="go">1 2</span>
<span class="go">2 NaN</span>
<span class="go">dtype: object</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-99">调用具有正好一个捕获组的正则表达式的<code class="docutils literal"><span class="pre">Index</span></code>，如果<code class="docutils literal"><span class="pre">expand=True</span></code>，则返回一个具有一列的<code class="docutils literal"><span class="pre">DataFrame</span></code></span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [37]: </span><span class="n">s</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="s2">"a1"</span><span class="p">,</span> <span class="s2">"b2"</span><span class="p">,</span> <span class="s2">"c3"</span><span class="p">],</span> <span class="p">[</span><span class="s2">"A11"</span><span class="p">,</span> <span class="s2">"B22"</span><span class="p">,</span> <span class="s2">"C33"</span><span class="p">])</span>
<span class="gp">In [38]: </span><span class="n">s</span>
<span class="gr">Out[38]: </span>
<span class="go">A11 a1</span>
<span class="go">B22 b2</span>
<span class="go">C33 c3</span>
<span class="go">dtype: object</span>
<span class="gp">In [39]: </span><span class="n">s</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s2">"(?P<letter>[a-zA-Z])"</span><span class="p">,</span> <span class="n">expand</span><span class="o">=</span><span class="bp">True</span><span class="p">)</span>
<span class="gr">Out[39]: </span>
<span class="go"> letter</span>
<span class="go">0 A</span>
<span class="go">1 B</span>
<span class="go">2 C</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-100">如果<code class="docutils literal"><span class="pre">expand=False</span></code>，则返回<code class="docutils literal"><span class="pre">Index</span></code>。</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [40]: </span><span class="n">s</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s2">"(?P<letter>[a-zA-Z])"</span><span class="p">,</span> <span class="n">expand</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
<span class="gr">Out[40]: </span><span class="n">Index</span><span class="p">([</span><span class="s1">u'A'</span><span class="p">,</span> <span class="s1">u'B'</span><span class="p">,</span> <span class="s1">u'C'</span><span class="p">],</span> <span class="n">dtype</span><span class="o">=</span><span class="s1">'object'</span><span class="p">,</span> <span class="n">name</span><span class="o">=</span><span class="s1">u'letter'</span><span class="p">)</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-101">使用具有多个捕获组的正则表达式调用<code class="docutils literal"><span class="pre">Index</span></code>，如果<code class="docutils literal"><span class="pre">expand=True</span></code>，则会返回<code class="docutils literal"><span class="pre">DataFrame</span></code>。</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [41]: </span><span class="n">s</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s2">"(?P<letter>[a-zA-Z])([0-9]+)"</span><span class="p">,</span> <span class="n">expand</span><span class="o">=</span><span class="bp">True</span><span class="p">)</span>
<span class="gr">Out[41]: </span>
<span class="go"> letter 1</span>
<span class="go">0 A 11</span>
<span class="go">1 B 22</span>
<span class="go">2 C 33</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-102">如果<code class="docutils literal"><span class="pre">expand=False</span></code>，则会引发<code class="docutils literal"><span class="pre">ValueError</span></code>。</span></p>
<div class="highlight-python"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">s</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="s2">"(?P<letter>[a-zA-Z])([0-9]+)"</span><span class="p">,</span> <span class="n">expand</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
<span class="go">ValueError: only one regex group is supported with Index</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-103">下表总结了<code class="docutils literal"><span class="pre">extract(expand=False)</span></code>（第一列中的输入主题，第一行中正则表达式中的组数）</span></p>
<table border="1" class="docutils">
<colgroup>
<col width="28%">
<col width="31%">
<col width="41%">
</colgroup>
<tbody valign="top">
<tr class="row-odd"><td> </td>
<td><span class="yiyi-st" id="yiyi-104">1组</span></td>
<td><span class="yiyi-st" id="yiyi-105">> 1组</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-106">指数</span></td>
<td><span class="yiyi-st" id="yiyi-107">指数</span></td>
<td><span class="yiyi-st" id="yiyi-108">ValueError</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-109">系列</span></td>
<td><span class="yiyi-st" id="yiyi-110">系列</span></td>
<td><span class="yiyi-st" id="yiyi-111">DataFrame</span></td>
</tr>
</tbody>
</table>
</div>
<div class="section" id="extract-all-matches-in-each-subject-extractall">
<h3><span class="yiyi-st" id="yiyi-112">Extract all matches in each subject (extractall)</span></h3>
<div class="versionadded" id="text-extractall">
<p><span class="yiyi-st" id="yiyi-113"><span class="versionmodified">版本0.18.0中的新功能。</span></span></p>
</div>
<p><span class="yiyi-st" id="yiyi-114">与<code class="docutils literal"><span class="pre">extract</span></code>（仅返回第一个匹配项）不同，</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [42]: </span><span class="n">s</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="s2">"a1a2"</span><span class="p">,</span> <span class="s2">"b1"</span><span class="p">,</span> <span class="s2">"c1"</span><span class="p">],</span> <span class="n">index</span><span class="o">=</span><span class="p">[</span><span class="s2">"A"</span><span class="p">,</span> <span class="s2">"B"</span><span class="p">,</span> <span class="s2">"C"</span><span class="p">])</span>
<span class="gp">In [43]: </span><span class="n">s</span>
<span class="gr">Out[43]: </span>
<span class="go">A a1a2</span>
<span class="go">B b1</span>
<span class="go">C c1</span>
<span class="go">dtype: object</span>
<span class="gp">In [44]: </span><span class="n">two_groups</span> <span class="o">=</span> <span class="s1">'(?P<letter>[a-z])(?P<digit>[0-9])'</span>
<span class="gp">In [45]: </span><span class="n">s</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="n">two_groups</span><span class="p">,</span> <span class="n">expand</span><span class="o">=</span><span class="bp">True</span><span class="p">)</span>
<span class="gr">Out[45]: </span>
<span class="go"> letter digit</span>
<span class="go">A a 1</span>
<span class="go">B b 1</span>
<span class="go">C c 1</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-115"><code class="docutils literal"><span class="pre">extractall</span></code>方法返回每个匹配。</span><span class="yiyi-st" id="yiyi-116"><code class="docutils literal"><span class="pre">extractall</span></code>的结果始终是其行上具有<code class="docutils literal"><span class="pre">MultiIndex</span></code>的<code class="docutils literal"><span class="pre">DataFrame</span></code>。</span><span class="yiyi-st" id="yiyi-117"><code class="docutils literal"><span class="pre">MultiIndex</span></code>的最后一个级别命名为<code class="docutils literal"><span class="pre">match</span></code>，并指示主题中的顺序。</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [46]: </span><span class="n">s</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">extractall</span><span class="p">(</span><span class="n">two_groups</span><span class="p">)</span>
<span class="gr">Out[46]: </span>
<span class="go"> letter digit</span>
<span class="go"> match </span>
<span class="go">A 0 a 1</span>
<span class="go"> 1 a 2</span>
<span class="go">B 0 b 1</span>
<span class="go">C 0 c 1</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-118">当系列中的每个主题字符串完全匹配一个时，</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [47]: </span><span class="n">s</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="s1">'a3'</span><span class="p">,</span> <span class="s1">'b3'</span><span class="p">,</span> <span class="s1">'c2'</span><span class="p">])</span>
<span class="gp">In [48]: </span><span class="n">s</span>
<span class="gr">Out[48]: </span>
<span class="go">0 a3</span>
<span class="go">1 b3</span>
<span class="go">2 c2</span>
<span class="go">dtype: object</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-119">then <code class="docutils literal"><span class="pre">extractall(pat).xs(0,</span> <span class="pre">level='match')</span></code> gives the same result as <code class="docutils literal"><span class="pre">extract(pat)</span></code>.</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [49]: </span><span class="n">extract_result</span> <span class="o">=</span> <span class="n">s</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">extract</span><span class="p">(</span><span class="n">two_groups</span><span class="p">,</span> <span class="n">expand</span><span class="o">=</span><span class="bp">True</span><span class="p">)</span>
<span class="gp">In [50]: </span><span class="n">extract_result</span>
<span class="gr">Out[50]: </span>
<span class="go"> letter digit</span>
<span class="go">0 a 3</span>
<span class="go">1 b 3</span>
<span class="go">2 c 2</span>
<span class="gp">In [51]: </span><span class="n">extractall_result</span> <span class="o">=</span> <span class="n">s</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">extractall</span><span class="p">(</span><span class="n">two_groups</span><span class="p">)</span>
<span class="gp">In [52]: </span><span class="n">extractall_result</span>
<span class="gr">Out[52]: </span>
<span class="go"> letter digit</span>
<span class="go"> match </span>
<span class="go">0 0 a 3</span>
<span class="go">1 0 b 3</span>
<span class="go">2 0 c 2</span>
<span class="gp">In [53]: </span><span class="n">extractall_result</span><span class="o">.</span><span class="n">xs</span><span class="p">(</span><span class="mi">0</span><span class="p">,</span> <span class="n">level</span><span class="o">=</span><span class="s2">"match"</span><span class="p">)</span>
<span class="gr">Out[53]: </span>
<span class="go"> letter digit</span>
<span class="go">0 a 3</span>
<span class="go">1 b 3</span>
<span class="go">2 c 2</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-120"><code class="docutils literal"><span class="pre">Index</span></code>也支持<code class="docutils literal"><span class="pre">.str.extractall</span></code>。</span><span class="yiyi-st" id="yiyi-121">它返回一个<code class="docutils literal"><span class="pre">DataFrame</span></code>，其结果与具有默认索引（从0开始）的<code class="docutils literal"><span class="pre">Series.str.extractall</span></code>相同。</span></p>
<div class="versionadded">
<p><span class="yiyi-st" id="yiyi-122"><span class="versionmodified">版本0.19.0中的新功能。</span></span></p>
</div>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [54]: </span><span class="n">pd</span><span class="o">.</span><span class="n">Index</span><span class="p">([</span><span class="s2">"a1a2"</span><span class="p">,</span> <span class="s2">"b1"</span><span class="p">,</span> <span class="s2">"c1"</span><span class="p">])</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">extractall</span><span class="p">(</span><span class="n">two_groups</span><span class="p">)</span>
<span class="gr">Out[54]: </span>
<span class="go"> letter digit</span>
<span class="go"> match </span>
<span class="go">0 0 a 1</span>
<span class="go"> 1 a 2</span>
<span class="go">1 0 b 1</span>
<span class="go">2 0 c 1</span>
<span class="gp">In [55]: </span><span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="s2">"a1a2"</span><span class="p">,</span> <span class="s2">"b1"</span><span class="p">,</span> <span class="s2">"c1"</span><span class="p">])</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">extractall</span><span class="p">(</span><span class="n">two_groups</span><span class="p">)</span>
<span class="gr">Out[55]: </span>
<span class="go"> letter digit</span>
<span class="go"> match </span>
<span class="go">0 0 a 1</span>
<span class="go"> 1 a 2</span>
<span class="go">1 0 b 1</span>
<span class="go">2 0 c 1</span>
</pre></div>
</div>
</div>
</div>
<div class="section" id="testing-for-strings-that-match-or-contain-a-pattern">
<h2><span class="yiyi-st" id="yiyi-123">Testing for Strings that Match or Contain a Pattern</span></h2>
<p><span class="yiyi-st" id="yiyi-124">您可以检查元素是否包含模式：</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [56]: </span><span class="n">pattern</span> <span class="o">=</span> <span class="s1">r'[a-z][0-9]'</span>
<span class="gp">In [57]: </span><span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="s1">'1'</span><span class="p">,</span> <span class="s1">'2'</span><span class="p">,</span> <span class="s1">'3a'</span><span class="p">,</span> <span class="s1">'3b'</span><span class="p">,</span> <span class="s1">'03c'</span><span class="p">])</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">contains</span><span class="p">(</span><span class="n">pattern</span><span class="p">)</span>
<span class="gr">Out[57]: </span>
<span class="go">0 False</span>
<span class="go">1 False</span>
<span class="go">2 False</span>
<span class="go">3 False</span>
<span class="go">4 False</span>
<span class="go">dtype: bool</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-125">或匹配模式：</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [58]: </span><span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="s1">'1'</span><span class="p">,</span> <span class="s1">'2'</span><span class="p">,</span> <span class="s1">'3a'</span><span class="p">,</span> <span class="s1">'3b'</span><span class="p">,</span> <span class="s1">'03c'</span><span class="p">])</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">match</span><span class="p">(</span><span class="n">pattern</span><span class="p">,</span> <span class="n">as_indexer</span><span class="o">=</span><span class="bp">True</span><span class="p">)</span>
<span class="gr">Out[58]: </span>
<span class="go">0 False</span>
<span class="go">1 False</span>
<span class="go">2 False</span>
<span class="go">3 False</span>
<span class="go">4 False</span>
<span class="go">dtype: bool</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-126"><code class="docutils literal"><span class="pre">match</span></code>和<code class="docutils literal"><span class="pre">contains</span></code>是strictness：<code class="docutils literal"><span class="pre">match</span></code>依赖于strict <code class="docutils literal"><span class="pre">re.match</span></code>，而<code class="docutils literal"><span class="pre">contains</span></code>依赖于<code class="docutils literal"><span class="pre">re.search</span></code>。</span></p>
<div class="admonition warning">
<p class="first admonition-title"><span class="yiyi-st" id="yiyi-127">警告</span></p>
<p><span class="yiyi-st" id="yiyi-128">在先前版本中，<code class="docutils literal"><span class="pre">match</span></code>用于<em>提取</em>组，返回不那么方便的系列元组。</span><span class="yiyi-st" id="yiyi-129">现在优选新方法<code class="docutils literal"><span class="pre">extract</span></code>（在上一部分中描述）。</span></p>
<p class="last"><span class="yiyi-st" id="yiyi-130"><code class="docutils literal"><span class="pre">match</span></code>的旧的，已弃用的行为仍是默认行为。</span><span class="yiyi-st" id="yiyi-131">如上所述，通过设置<code class="docutils literal"><span class="pre">as_indexer=True</span></code>来使用新的行为。</span><span class="yiyi-st" id="yiyi-132">在此模式下，<code class="docutils literal"><span class="pre">match</span></code>类似于<code class="docutils literal"><span class="pre">contains</span></code>，返回一个布尔系列。</span><span class="yiyi-st" id="yiyi-133">新行为将成为未来版本中的默认行为。</span></p>
</div>
<dl class="docutils">
<dt><span class="yiyi-st" id="yiyi-134"><code class="docutils literal"><span class="pre">match</span></code>，<code class="docutils literal"><span class="pre">contains</span></code>，<code class="docutils literal"><span class="pre">startswith</span></code>和<code class="docutils literal"><span class="pre">endswith</span></code> take</span></dt>
<dd><span class="yiyi-st" id="yiyi-135">额外的<code class="docutils literal"><span class="pre">na</span></code>参数，因此缺少的值可以被视为True或False：</span></dd>
</dl>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [59]: </span><span class="n">s4</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="s1">'A'</span><span class="p">,</span> <span class="s1">'B'</span><span class="p">,</span> <span class="s1">'C'</span><span class="p">,</span> <span class="s1">'Aaba'</span><span class="p">,</span> <span class="s1">'Baca'</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span> <span class="s1">'CABA'</span><span class="p">,</span> <span class="s1">'dog'</span><span class="p">,</span> <span class="s1">'cat'</span><span class="p">])</span>
<span class="gp">In [60]: </span><span class="n">s4</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">contains</span><span class="p">(</span><span class="s1">'A'</span><span class="p">,</span> <span class="n">na</span><span class="o">=</span><span class="bp">False</span><span class="p">)</span>
<span class="gr">Out[60]: </span>
<span class="go">0 True</span>
<span class="go">1 False</span>
<span class="go">2 False</span>
<span class="go">3 True</span>
<span class="go">4 False</span>
<span class="go">5 False</span>
<span class="go">6 True</span>
<span class="go">7 False</span>
<span class="go">8 False</span>
<span class="go">dtype: bool</span>
</pre></div>
</div>
</div>
<div class="section" id="creating-indicator-variables">
<span id="text-indicator"></span><h2><span class="yiyi-st" id="yiyi-136">Creating Indicator Variables</span></h2>
<p><span class="yiyi-st" id="yiyi-137">您可以从字符串列中提取虚拟变量。</span><span class="yiyi-st" id="yiyi-138">例如，如果它们由<code class="docutils literal"><span class="pre">'|'</span></code>分隔：</span></p>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [61]: </span><span class="n">s</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Series</span><span class="p">([</span><span class="s1">'a'</span><span class="p">,</span> <span class="s1">'a|b'</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span> <span class="s1">'a|c'</span><span class="p">])</span>
<span class="gp">In [62]: </span><span class="n">s</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">get_dummies</span><span class="p">(</span><span class="n">sep</span><span class="o">=</span><span class="s1">'|'</span><span class="p">)</span>
<span class="gr">Out[62]: </span>
<span class="go"> a b c</span>
<span class="go">0 1 0 0</span>
<span class="go">1 1 1 0</span>
<span class="go">2 0 0 0</span>
<span class="go">3 1 0 1</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-139">字符串<code class="docutils literal"><span class="pre">Index</span></code>还支持<code class="docutils literal"><span class="pre">get_dummies</span></code>，它返回<code class="docutils literal"><span class="pre">MultiIndex</span></code>。</span></p>
<div class="versionadded">
<p><span class="yiyi-st" id="yiyi-140"><span class="versionmodified">版本0.18.1中的新功能。</span></span></p>
</div>
<div class="highlight-ipython"><div class="highlight"><pre><span></span><span class="gp">In [63]: </span><span class="n">idx</span> <span class="o">=</span> <span class="n">pd</span><span class="o">.</span><span class="n">Index</span><span class="p">([</span><span class="s1">'a'</span><span class="p">,</span> <span class="s1">'a|b'</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">nan</span><span class="p">,</span> <span class="s1">'a|c'</span><span class="p">])</span>
<span class="gp">In [64]: </span><span class="n">idx</span><span class="o">.</span><span class="n">str</span><span class="o">.</span><span class="n">get_dummies</span><span class="p">(</span><span class="n">sep</span><span class="o">=</span><span class="s1">'|'</span><span class="p">)</span>
<span class="gr">Out[64]: </span>
<span class="go">MultiIndex(levels=[[0, 1], [0, 1], [0, 1]],</span>
<span class="go"> labels=[[1, 1, 0, 1], [0, 1, 0, 0], [0, 0, 0, 1]],</span>
<span class="go"> names=[u'a', u'b', u'c'])</span>
</pre></div>
</div>
<p><span class="yiyi-st" id="yiyi-141">另请参见<a class="reference internal" href="generated/pandas.get_dummies.html#pandas.get_dummies" title="pandas.get_dummies"><code class="xref py py-func docutils literal"><span class="pre">get_dummies()</span></code></a>。</span></p>
</div>
<div class="section" id="method-summary">
<h2><span class="yiyi-st" id="yiyi-142">Method Summary</span></h2>
<table border="1" class="docutils" id="text-summary">
<colgroup>
<col width="20%">
<col width="80%">
</colgroup>
<thead valign="bottom">
<tr class="row-odd"><th class="head"><span class="yiyi-st" id="yiyi-143">方法</span></th>
<th class="head"><span class="yiyi-st" id="yiyi-144">描述</span></th>
</tr>
</thead>
<tbody valign="top">
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-145"><a class="reference internal" href="generated/pandas.Series.str.cat.html#pandas.Series.str.cat" title="pandas.Series.str.cat"><code class="xref py py-meth docutils literal"><span class="pre">cat()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-146">串联字符串</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-147"><a class="reference internal" href="generated/pandas.Series.str.split.html#pandas.Series.str.split" title="pandas.Series.str.split"><code class="xref py py-meth docutils literal"><span class="pre">split()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-148">拆分分隔符上的字符串</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-149"><a class="reference internal" href="generated/pandas.Series.str.rsplit.html#pandas.Series.str.rsplit" title="pandas.Series.str.rsplit"><code class="xref py py-meth docutils literal"><span class="pre">rsplit()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-150">从字符串末尾拆分分隔符上的字符串</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-151"><a class="reference internal" href="generated/pandas.Series.str.get.html#pandas.Series.str.get" title="pandas.Series.str.get"><code class="xref py py-meth docutils literal"><span class="pre">get()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-152">索引到每个元素（检索第i个元素）</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-153"><a class="reference internal" href="generated/pandas.Series.str.join.html#pandas.Series.str.join" title="pandas.Series.str.join"><code class="xref py py-meth docutils literal"><span class="pre">join()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-154">使用传递的分隔符在系列的每个元素中连接字符串</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-155"><a class="reference internal" href="generated/pandas.Series.str.get_dummies.html#pandas.Series.str.get_dummies" title="pandas.Series.str.get_dummies"><code class="xref py py-meth docutils literal"><span class="pre">get_dummies()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-156">在分隔符上分割字符串，返回虚拟变量的DataFrame</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-157"><a class="reference internal" href="generated/pandas.Series.str.contains.html#pandas.Series.str.contains" title="pandas.Series.str.contains"><code class="xref py py-meth docutils literal"><span class="pre">contains()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-158">如果每个字符串包含pattern / regex，则返回布尔数组</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-159"><a class="reference internal" href="generated/pandas.Series.str.replace.html#pandas.Series.str.replace" title="pandas.Series.str.replace"><code class="xref py py-meth docutils literal"><span class="pre">replace()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-160">用一些其他字符串替换模式/正则表达式的出现</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-161"><a class="reference internal" href="generated/pandas.Series.str.repeat.html#pandas.Series.str.repeat" title="pandas.Series.str.repeat"><code class="xref py py-meth docutils literal"><span class="pre">repeat()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-162">重复的值（<code class="docutils literal"><span class="pre">s.str.repeat(3)</span></code>等效于<code class="docutils literal"><span class="pre">x</span> <span class="pre">*</span> <span class="pre">3</span> t2 >）</code></span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-163"><a class="reference internal" href="generated/pandas.Series.str.pad.html#pandas.Series.str.pad" title="pandas.Series.str.pad"><code class="xref py py-meth docutils literal"><span class="pre">pad()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-164">向字符串的左侧，右侧或两侧添加空格</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-165"><a class="reference internal" href="generated/pandas.Series.str.center.html#pandas.Series.str.center" title="pandas.Series.str.center"><code class="xref py py-meth docutils literal"><span class="pre">center()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-166">等效于<code class="docutils literal"><span class="pre">str.center</span></code></span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-167"><a class="reference internal" href="generated/pandas.Series.str.ljust.html#pandas.Series.str.ljust" title="pandas.Series.str.ljust"><code class="xref py py-meth docutils literal"><span class="pre">ljust()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-168">等效于<code class="docutils literal"><span class="pre">str.ljust</span></code></span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-169"><a class="reference internal" href="generated/pandas.Series.str.rjust.html#pandas.Series.str.rjust" title="pandas.Series.str.rjust"><code class="xref py py-meth docutils literal"><span class="pre">rjust()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-170">等效于<code class="docutils literal"><span class="pre">str.rjust</span></code></span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-171"><a class="reference internal" href="generated/pandas.Series.str.zfill.html#pandas.Series.str.zfill" title="pandas.Series.str.zfill"><code class="xref py py-meth docutils literal"><span class="pre">zfill()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-172">等效于<code class="docutils literal"><span class="pre">str.zfill</span></code></span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-173"><a class="reference internal" href="generated/pandas.Series.str.wrap.html#pandas.Series.str.wrap" title="pandas.Series.str.wrap"><code class="xref py py-meth docutils literal"><span class="pre">wrap()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-174">将长字符串拆分成长度小于给定宽度的行</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-175"><a class="reference internal" href="generated/pandas.Series.str.slice.html#pandas.Series.str.slice" title="pandas.Series.str.slice"><code class="xref py py-meth docutils literal"><span class="pre">slice()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-176">切割系列中的每个字符串</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-177"><a class="reference internal" href="generated/pandas.Series.str.slice_replace.html#pandas.Series.str.slice_replace" title="pandas.Series.str.slice_replace"><code class="xref py py-meth docutils literal"><span class="pre">slice_replace()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-178">使用传递的值替换每个字符串中的slice</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-179"><a class="reference internal" href="generated/pandas.Series.str.count.html#pandas.Series.str.count" title="pandas.Series.str.count"><code class="xref py py-meth docutils literal"><span class="pre">count()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-180">计算模式的出现次数</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-181"><a class="reference internal" href="generated/pandas.Series.str.startswith.html#pandas.Series.str.startswith" title="pandas.Series.str.startswith"><code class="xref py py-meth docutils literal"><span class="pre">startswith()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-182">对于每个元素，等于<code class="docutils literal"><span class="pre">str.startswith(pat)</span></code></span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-183"><a class="reference internal" href="generated/pandas.Series.str.endswith.html#pandas.Series.str.endswith" title="pandas.Series.str.endswith"><code class="xref py py-meth docutils literal"><span class="pre">endswith()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-184">对于每个元素，等于<code class="docutils literal"><span class="pre">str.endswith(pat)</span></code></span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-185"><a class="reference internal" href="generated/pandas.Series.str.findall.html#pandas.Series.str.findall" title="pandas.Series.str.findall"><code class="xref py py-meth docutils literal"><span class="pre">findall()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-186">计算每个字符串的所有匹配模式/正则表达式的列表</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-187"><a class="reference internal" href="generated/pandas.Series.str.match.html#pandas.Series.str.match" title="pandas.Series.str.match"><code class="xref py py-meth docutils literal"><span class="pre">match()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-188">在每个元素上调用<code class="docutils literal"><span class="pre">re.match</span></code>，返回匹配的组作为列表</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-189"><a class="reference internal" href="generated/pandas.Series.str.extract.html#pandas.Series.str.extract" title="pandas.Series.str.extract"><code class="xref py py-meth docutils literal"><span class="pre">extract()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-190">在每个元素上调用<code class="docutils literal"><span class="pre">re.search</span></code>，返回DataFrame，每个元素使用一行，每个正则表达式捕获组使用一列</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-191"><a class="reference internal" href="generated/pandas.Series.str.extractall.html#pandas.Series.str.extractall" title="pandas.Series.str.extractall"><code class="xref py py-meth docutils literal"><span class="pre">extractall()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-192">在每个元素上调用<code class="docutils literal"><span class="pre">re.findall</span></code>，返回DataFrame，每个匹配包含一行，每个正则表达式捕获组包含一个列</span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-193"><a class="reference internal" href="generated/pandas.Series.str.len.html#pandas.Series.str.len" title="pandas.Series.str.len"><code class="xref py py-meth docutils literal"><span class="pre">len()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-194">计算字符串长度</span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-195"><a class="reference internal" href="generated/pandas.Series.str.strip.html#pandas.Series.str.strip" title="pandas.Series.str.strip"><code class="xref py py-meth docutils literal"><span class="pre">strip()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-196">等效于<code class="docutils literal"><span class="pre">str.strip</span></code></span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-197"><a class="reference internal" href="generated/pandas.Series.str.rstrip.html#pandas.Series.str.rstrip" title="pandas.Series.str.rstrip"><code class="xref py py-meth docutils literal"><span class="pre">rstrip()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-198">等效于<code class="docutils literal"><span class="pre">str.rstrip</span></code></span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-199"><a class="reference internal" href="generated/pandas.Series.str.lstrip.html#pandas.Series.str.lstrip" title="pandas.Series.str.lstrip"><code class="xref py py-meth docutils literal"><span class="pre">lstrip()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-200">等同于<code class="docutils literal"><span class="pre">str.lstrip</span></code></span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-201"><a class="reference internal" href="generated/pandas.Series.str.partition.html#pandas.Series.str.partition" title="pandas.Series.str.partition"><code class="xref py py-meth docutils literal"><span class="pre">partition()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-202">等效于<code class="docutils literal"><span class="pre">str.partition</span></code></span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-203"><a class="reference internal" href="generated/pandas.Series.str.rpartition.html#pandas.Series.str.rpartition" title="pandas.Series.str.rpartition"><code class="xref py py-meth docutils literal"><span class="pre">rpartition()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-204">等效于<code class="docutils literal"><span class="pre">str.rpartition</span></code></span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-205"><a class="reference internal" href="generated/pandas.Series.str.lower.html#pandas.Series.str.lower" title="pandas.Series.str.lower"><code class="xref py py-meth docutils literal"><span class="pre">lower()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-206">等效于<code class="docutils literal"><span class="pre">str.lower</span></code></span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-207"><a class="reference internal" href="generated/pandas.Series.str.upper.html#pandas.Series.str.upper" title="pandas.Series.str.upper"><code class="xref py py-meth docutils literal"><span class="pre">upper()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-208">等效于<code class="docutils literal"><span class="pre">str.upper</span></code></span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-209"><a class="reference internal" href="generated/pandas.Series.str.find.html#pandas.Series.str.find" title="pandas.Series.str.find"><code class="xref py py-meth docutils literal"><span class="pre">find()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-210">等同于<code class="docutils literal"><span class="pre">str.find</span></code></span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-211"><a class="reference internal" href="generated/pandas.Series.str.rfind.html#pandas.Series.str.rfind" title="pandas.Series.str.rfind"><code class="xref py py-meth docutils literal"><span class="pre">rfind()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-212">等效于<code class="docutils literal"><span class="pre">str.rfind</span></code></span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-213"><a class="reference internal" href="generated/pandas.Series.str.index.html#pandas.Series.str.index" title="pandas.Series.str.index"><code class="xref py py-meth docutils literal"><span class="pre">index()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-214">等效于<code class="docutils literal"><span class="pre">str.index</span></code></span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-215"><a class="reference internal" href="generated/pandas.Series.str.rindex.html#pandas.Series.str.rindex" title="pandas.Series.str.rindex"><code class="xref py py-meth docutils literal"><span class="pre">rindex()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-216">等效于<code class="docutils literal"><span class="pre">str.rindex</span></code></span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-217"><a class="reference internal" href="generated/pandas.Series.str.capitalize.html#pandas.Series.str.capitalize" title="pandas.Series.str.capitalize"><code class="xref py py-meth docutils literal"><span class="pre">capitalize()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-218">等效于<code class="docutils literal"><span class="pre">str.capitalize</span></code></span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-219"><a class="reference internal" href="generated/pandas.Series.str.swapcase.html#pandas.Series.str.swapcase" title="pandas.Series.str.swapcase"><code class="xref py py-meth docutils literal"><span class="pre">swapcase()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-220">等效于<code class="docutils literal"><span class="pre">str.swapcase</span></code></span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-221"><a class="reference internal" href="generated/pandas.Series.str.normalize.html#pandas.Series.str.normalize" title="pandas.Series.str.normalize"><code class="xref py py-meth docutils literal"><span class="pre">normalize()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-222">返回Unicode正常表单。</span><span class="yiyi-st" id="yiyi-223">等同于<code class="docutils literal"><span class="pre">unicodedata.normalize</span></code></span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-224"><a class="reference internal" href="generated/pandas.Series.str.translate.html#pandas.Series.str.translate" title="pandas.Series.str.translate"><code class="xref py py-meth docutils literal"><span class="pre">translate()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-225">等效于<code class="docutils literal"><span class="pre">str.translate</span></code></span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-226"><a class="reference internal" href="generated/pandas.Series.str.isalnum.html#pandas.Series.str.isalnum" title="pandas.Series.str.isalnum"><code class="xref py py-meth docutils literal"><span class="pre">isalnum()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-227">等效于<code class="docutils literal"><span class="pre">str.isalnum</span></code></span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-228"><a class="reference internal" href="generated/pandas.Series.str.isalpha.html#pandas.Series.str.isalpha" title="pandas.Series.str.isalpha"><code class="xref py py-meth docutils literal"><span class="pre">isalpha()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-229">等效于<code class="docutils literal"><span class="pre">str.isalpha</span></code></span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-230"><a class="reference internal" href="generated/pandas.Series.str.isdigit.html#pandas.Series.str.isdigit" title="pandas.Series.str.isdigit"><code class="xref py py-meth docutils literal"><span class="pre">isdigit()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-231">等效于<code class="docutils literal"><span class="pre">str.isdigit</span></code></span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-232"><a class="reference internal" href="generated/pandas.Series.str.isspace.html#pandas.Series.str.isspace" title="pandas.Series.str.isspace"><code class="xref py py-meth docutils literal"><span class="pre">isspace()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-233">等效于<code class="docutils literal"><span class="pre">str.isspace</span></code></span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-234"><a class="reference internal" href="generated/pandas.Series.str.islower.html#pandas.Series.str.islower" title="pandas.Series.str.islower"><code class="xref py py-meth docutils literal"><span class="pre">islower()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-235">等效于<code class="docutils literal"><span class="pre">str.islower</span></code></span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-236"><a class="reference internal" href="generated/pandas.Series.str.isupper.html#pandas.Series.str.isupper" title="pandas.Series.str.isupper"><code class="xref py py-meth docutils literal"><span class="pre">isupper()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-237">等效于<code class="docutils literal"><span class="pre">str.isupper</span></code></span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-238"><a class="reference internal" href="generated/pandas.Series.str.istitle.html#pandas.Series.str.istitle" title="pandas.Series.str.istitle"><code class="xref py py-meth docutils literal"><span class="pre">istitle()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-239">等同于<code class="docutils literal"><span class="pre">str.istitle</span></code></span></td>
</tr>
<tr class="row-odd"><td><span class="yiyi-st" id="yiyi-240"><a class="reference internal" href="generated/pandas.Series.str.isnumeric.html#pandas.Series.str.isnumeric" title="pandas.Series.str.isnumeric"><code class="xref py py-meth docutils literal"><span class="pre">isnumeric()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-241">等效于<code class="docutils literal"><span class="pre">str.isnumeric</span></code></span></td>
</tr>
<tr class="row-even"><td><span class="yiyi-st" id="yiyi-242"><a class="reference internal" href="generated/pandas.Series.str.isdecimal.html#pandas.Series.str.isdecimal" title="pandas.Series.str.isdecimal"><code class="xref py py-meth docutils literal"><span class="pre">isdecimal()</span></code></a></span></td>
<td><span class="yiyi-st" id="yiyi-243">等效于<code class="docutils literal"><span class="pre">str.isdecimal</span></code></span></td>
</tr>
</tbody>
</table>
</div>