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<link rel="stylesheet" type="text/css" href="https://cdn.jsdelivr.net/hint.css/2.4.1/hint.min.css"><p>pandas常用命令整理。<br><a id="more"></a></p>
<h2 id="重命名列名"><a href="#重命名列名" class="headerlink" title="重命名列名"></a>重命名列名</h2><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></pre></td><td class="code"><pre><span class="line"><span class="comment"># 命名一列</span></span><br><span class="line">df.rename(columns={df.columns[<span class="number">2</span>]: <span class="string">"A"</span>}, inplace=<span class="keyword">True</span>)</span><br><span class="line"><span class="comment"># 命名全部</span></span><br><span class="line">df.columns = [<span class="string">'A'</span>, <span class="string">'B'</span>, <span class="string">'C'</span>]</span><br></pre></td></tr></table></figure>
<h2 id="删除行列"><a href="#删除行列" class="headerlink" title="删除行列"></a>删除行列</h2><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></pre></td><td class="code"><pre><span class="line"><span class="comment"># 删除一行</span></span><br><span class="line">df.drop(<span class="number">0</span>[, inplace=<span class="keyword">False</span>])</span><br><span class="line"><span class="comment"># 删除多行</span></span><br><span class="line">df.drop([a,b])</span><br><span class="line"><span class="comment"># 删除一列</span></span><br><span class="line"><span class="keyword">del</span> df[<span class="string">'A'</span>]</span><br><span class="line">df.drop(<span class="string">'A'</span>)</span><br><span class="line"><span class="comment"># 删除多列</span></span><br><span class="line">df.drop([<span class="string">'A'</span>,<span class="string">'B'</span>])</span><br></pre></td></tr></table></figure>
<h2 id="排序"><a href="#排序" class="headerlink" title="排序"></a>排序</h2><figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line">df.sort_values(<span class="string">'A'</span>[,inplace=<span class="keyword">True</span>])</span><br><span class="line">df.sort_values(by=[<span class="string">'a'</span>,<span class="string">'c'</span>])</span><br></pre></td></tr></table></figure>
<h2 id="去重"><a href="#去重" class="headerlink" title="去重"></a>去重</h2><figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line">df.duplicated() <span class="comment">#返回true or false</span></span><br><span class="line">df.drop_duplicates([<span class="string">'column'</span>])</span><br></pre></td></tr></table></figure>
<h2 id="连接数据库"><a href="#连接数据库" class="headerlink" title="连接数据库"></a>连接数据库</h2><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></pre></td><td class="code"><pre><span class="line"><span class="keyword">import</span> pymysql <span class="comment"># 其他数据库也可以，创建数据库连接就行</span></span><br><span class="line"><span class="keyword">import</span> pandas <span class="keyword">as</span> <span class="keyword">import</span> pd</span><br><span class="line"></span><br><span class="line">db = pymysql.connect(host=<span class="string">''</span>, port=<span class="string">''</span>, user=<span class="string">''</span>, passwd=<span class="string">''</span>, db=<span class="string">''</span>)</span><br><span class="line"><span class="comment"># 读取数据</span></span><br><span class="line">query = <span class="string">""</span> <span class="comment"># 查询语句</span></span><br><span class="line">df = pd.read_sql(sql=query, con=db)</span><br><span class="line"><span class="comment"># 存储数据</span></span><br><span class="line">df.to_sql(<span class="string">'table_name'</span>, con=db, if_exists=<span class="string">'append'</span>, index=<span class="keyword">False</span>) <span class="comment"># if_exists: fail, append, replace</span></span><br></pre></td></tr></table></figure>
<h2 id="写入excel-多sheet"><a href="#写入excel-多sheet" class="headerlink" title="写入excel(多sheet)"></a>写入excel(多sheet)</h2><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></pre></td><td class="code"><pre><span class="line">writer = pd.ExcelWriter(<span class="string">'t.xlsx'</span>)</span><br><span class="line">df1.to_excel(writer,<span class="string">'sheet1'</span>,index=<span class="number">0</span>)</span><br><span class="line">df2.to_excel(writer,<span class="string">'sheet2'</span>,index=<span class="number">0</span>)</span><br><span class="line">writer.save()</span><br></pre></td></tr></table></figure>
<h2 id="透视表"><a href="#透视表" class="headerlink" title="透视表"></a>透视表</h2><figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">pd.pivot_table(dataframe,index=<span class="string">'c1'</span>, values=[<span class="string">'c2'</span>,<span class="string">'c3'</span>,<span class="string">'c4'</span>], aggfunc={<span class="string">'c2'</span>:sum,<span class="string">'c3'</span>:<span class="keyword">lambda</span> x: len(x.unique()),<span class="string">'c4'</span>:len}, margins=<span class="keyword">True</span>,margins_name=<span class="string">'total'</span>)</span><br></pre></td></tr></table></figure>
<h2 id="环比"><a href="#环比" class="headerlink" title="环比"></a>环比</h2><figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><span class="line"><span class="comment"># 计算环比</span></span><br><span class="line">d2 = (dt-dt_last).reindex(dt.index)</span><br></pre></td></tr></table></figure>
<h2 id="切分类别"><a href="#切分类别" class="headerlink" title="切分类别"></a>切分类别</h2><figure class="highlight python"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><span class="line">pd.cut([sequence], bins, labels)</span><br></pre></td></tr></table></figure>
<h2 id="条件替换"><a href="#条件替换" class="headerlink" title="条件替换"></a>条件替换</h2><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></pre></td><td class="code"><pre><span class="line"><span class="comment"># Replace values where the condition is False</span></span><br><span class="line">df.where(cond, other, inplace)</span><br><span class="line"><span class="comment"># Replace values where the condition is True</span></span><br><span class="line">df.mask(cond, other, inplace)</span><br><span class="line"><span class="comment"># 将`nan`替换成0</span></span><br><span class="line">cond = df.isna()</span><br><span class="line">df.where(~cond, <span class="number">0</span>)</span><br><span class="line"><span class="comment"># or</span></span><br><span class="line">df.mask(cond, <span class="number">0</span>)</span><br></pre></td></tr></table></figure>
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