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<link rel="stylesheet" type="text/css" href="https://cdn.jsdelivr.net/hint.css/2.4.1/hint.min.css"><p>昨天遇到一个问题，怎么把时间按条件分类。<br><a id="more"></a><br>这个问题让我忙活了很久。数据是从<code>csv</code>中导入的，主要想根据不同时间范围划分几类。</p>
<p>一开始我将时间字段和<code>'2018-03-15'</code>相比大小，结果出了问题。<code>csv</code>中导入的时间字段也是字符串，这是字符串之间的比较，得不到想要的结果。写函数进行处理的时候，也搞混了很多问题。最后成功了，总结一下。</p>
<p>利用<code>pandas</code>导入<code>csv</code>，然后对时间列进行处理。首先要对字符串的时间转为<code>datetime</code>，然后对每个时间进行处理。利用循环，返回<code>list</code>；利用<code>apply</code>，针对每个元素处理。<br><figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br><span class="line">4</span><br><span class="line">5</span><br><span class="line">6</span><br><span class="line">7</span><br><span class="line">8</span><br><span class="line">9</span><br><span class="line">10</span><br><span class="line">11</span><br><span class="line">12</span><br><span class="line">13</span><br><span class="line">14</span><br><span class="line">15</span><br><span class="line">16</span><br><span class="line">17</span><br><span class="line">18</span><br><span class="line">19</span><br><span class="line">20</span><br><span class="line">21</span><br><span class="line">22</span><br><span class="line">23</span><br><span class="line">24</span><br><span class="line">25</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment">#!/usr/bin/env python3</span></span><br><span class="line"><span class="comment"># -*- coding: utf-8 -*-</span></span><br><span class="line"></span><br><span class="line"><span class="keyword">import</span> pandas</span><br><span class="line"><span class="keyword">from</span> datetime <span class="keyword">import</span> datetime</span><br><span class="line"></span><br><span class="line">df=pandas.read_csv(open(file=<span class="string">'test.csv'</span>))</span><br><span class="line"><span class="comment"># 把字符串时间变为datetime</span></span><br><span class="line">df[<span class="string">'time'</span>]=pandas.to_datetime(df[<span class="string">'时间'</span>])</span><br><span class="line"><span class="comment"># 设定标准</span></span><br><span class="line">a=datetime(<span class="number">2018</span>,<span class="number">3</span>,<span class="number">15</span>)</span><br><span class="line"><span class="comment"># 循环函数</span></span><br><span class="line"><span class="function"><span class="keyword">def</span> <span class="title">test</span><span class="params">(times)</span>:</span></span><br><span class="line"> results=[]</span><br><span class="line"> <span class="keyword">for</span> x <span class="keyword">in</span> times:</span><br><span class="line"> <span class="keyword">if</span> x<a:</span><br><span class="line"> results.append(<span class="number">1</span>)</span><br><span class="line"> <span class="keyword">else</span>:</span><br><span class="line"> results.append(<span class="number">0</span>)</span><br><span class="line"> <span class="keyword">return</span> results</span><br><span class="line"><span class="comment"># 利用循环函数，分类时间</span></span><br><span class="line">df[<span class="string">'categories1'</span>]=test(df[<span class="string">'time'</span>])</span><br><span class="line"><span class="comment"># 利用apply处理</span></span><br><span class="line">df[<span class="string">'categories2'</span>]=df[<span class="string">'time'</span>].apply(<span class="keyword">lambda</span> x:test(x))</span><br><span class="line">print(df)</span><br></pre></td></tr></table></figure></p>
<p><code>pandas</code>的每一列是<code>Series</code>，本质上就是一个<code>list</code>，<code>apply</code>针对每个元素处理，直接利用函数就要返回<code>list</code>。</p>
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<div style="text-align:center;color: #ccc;font-size:14px;">-------------本文结束<i class="fa fa-paw"></i>感谢您的阅读-------------</div>
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