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            <h1 id="seo-header">复旦高性能计算 (七) Python调用R</h1>
            
            
              <div class="markdown-body">
                
                <h2 id="前置要求"><a href="#前置要求" class="headerlink" title="前置要求"></a>前置要求</h2><ul>
<li><a target="_blank" rel="noopener" href="https://limour.top/631.html">复旦高性能计算 (一) Linux无root权限安装软件：以R为示例</a> 这里编译时开启了–enable-R-shlib</li>
<li><a target="_blank" rel="noopener" href="https://limour.top/1098.html">复旦高性能计算 (六) jupyter启用R内核</a> 确保不出奇怪的问题</li>
<li>install.packages(c(‘RJSONIO’, ‘httr’), repos&#x3D;”<a target="_blank" rel="noopener" href="http://mirrors.tuna.tsinghua.edu.cn/CRAN/">http://mirrors.tuna.tsinghua.edu.cn/CRAN/</a>“ )</li>
</ul>
<h2 id="第一步-安装rpy2"><a href="#第一步-安装rpy2" class="headerlink" title="第一步 安装rpy2"></a>第一步 安装rpy2</h2><figure class="highlight awk"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><code class="hljs awk">pip3.<span class="hljs-number">8</span> install rpy2 -i https:<span class="hljs-regexp">//</span>pypi.tuna.tsinghua.edu.cn/simple<br></code></pre></td></tr></table></figure>

<ul>
<li>查看rpy2的安装路径</li>
</ul>
<figure class="highlight elm"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br></pre></td><td class="code"><pre><code class="hljs elm"><span class="hljs-keyword">import</span> sys<br><span class="hljs-title">sys</span>.path<br></code></pre></td></tr></table></figure>

<ul>
<li>配置环境变量 每次启动先运行</li>
</ul>
<figure class="highlight moonscript"><table><tr><td class="gutter"><pre><span class="line">1</span><br><span class="line">2</span><br><span class="line">3</span><br></pre></td><td class="code"><pre><code class="hljs moonscript"><span class="hljs-keyword">import</span> <span class="hljs-built_in">os</span><br><span class="hljs-built_in">os</span>.environ[<span class="hljs-string">&#x27;R_HOME&#x27;</span>] = <span class="hljs-string">&#x27;/home/rqzhang/zlliu/dev/R/R_s/lib64/R&#x27;</span> # R的安装后含SVN-REVISION的目录 非bin目录<br><span class="hljs-built_in">os</span>.environ[<span class="hljs-string">&#x27;R_USER&#x27;</span>] = <span class="hljs-string">&#x27;/home/rqzhang/zlliu/dev/python38/lib/python3.8/site-packages/rpy2&#x27;</span> # rpy2的安装目录<br></code></pre></td></tr></table></figure>

<p><a target="_blank" rel="noopener" href="http://www.lfd.uci.edu/~gohlke/pythonlibs">冷门编译好的python库</a></p>
<h2 id="第二步-调用方法一（不推荐）"><a href="#第二步-调用方法一（不推荐）" class="headerlink" title="第二步 调用方法一（不推荐）"></a>第二步 调用方法一（不推荐）</h2><figure class="highlight coffeescript"><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></pre></td><td class="code"><pre><code class="hljs coffeescript"><span class="hljs-keyword">from</span> rpy2.robjects <span class="hljs-keyword">import</span> r <span class="hljs-keyword">as</span> Rcode<br><span class="hljs-keyword">from</span> rpy2.robjects.packages <span class="hljs-keyword">import</span> importr <span class="hljs-keyword">as</span> Rrequire<br>Rrequire(<span class="hljs-string">&#x27;ggplot2&#x27;</span>) <span class="hljs-comment"># 导入R包</span><br><span class="hljs-built_in">print</span>(Rcode(<span class="hljs-string">&quot;pi&quot;</span>)) <span class="hljs-comment"># 运行R语句</span><br><br><span class="hljs-comment">#rx()相当于”[“操作（注意取出的是R的list对象），而rx2()相当于”[[“操作</span><br></code></pre></td></tr></table></figure>

<p><a target="_blank" rel="noopener" href="https://pandas.pydata.org/pandas-docs/stable/getting_started/comparison/comparison_with_r.html">pandas.py: Comparison with R &#x2F; R libraries</a></p>
<h2 id="第三步-调用方法二（推荐）"><a href="#第三步-调用方法二（推荐）" class="headerlink" title="第三步 调用方法二（推荐）"></a>第三步 调用方法二（推荐）</h2><ul>
<li>开启 %R 支持</li>
</ul>
<figure class="highlight haml"><table><tr><td class="gutter"><pre><span class="line">1</span><br></pre></td><td class="code"><pre><code class="hljs haml"><span class="hljs-tag">%<span class="hljs-selector-tag">load_ext</span></span> rpy2.ipython<br></code></pre></td></tr></table></figure>

<ul>
<li>测试数据集</li>
</ul>
<figure class="highlight apache"><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><code class="hljs apache"><span class="hljs-attribute">import</span> pandas as pd<br><span class="hljs-attribute">data</span> = pd.DataFrame(&#123;&#x27;x&#x27;:[<span class="hljs-number">1</span>,<span class="hljs-number">2</span>,<span class="hljs-number">3</span>,<span class="hljs-number">4</span>,<span class="hljs-number">5</span>,<span class="hljs-number">6</span>],&#x27;y&#x27;:[<span class="hljs-number">1</span>,<span class="hljs-number">2</span>,<span class="hljs-number">3</span>,<span class="hljs-number">4</span>,<span class="hljs-number">5</span>,<span class="hljs-number">6</span>]&#125;)<br><span class="hljs-attribute">px</span> = <span class="hljs-number">1</span><br><span class="hljs-attribute">py</span> = <span class="hljs-number">2</span><br></code></pre></td></tr></table></figure>

<ul>
<li>cell内调用R</li>
</ul>
<figure class="highlight haskell"><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><code class="hljs haskell">%%<span class="hljs-type">R</span> -i <span class="hljs-class"><span class="hljs-keyword">data</span> -o colN</span><br><span class="hljs-title">require</span>(ggplot2)<br><span class="hljs-title">colN</span> = colnames(<span class="hljs-class"><span class="hljs-keyword">data</span>)</span><br><span class="hljs-title">ggplot</span>(<span class="hljs-class"><span class="hljs-keyword">data</span>=<span class="hljs-keyword">data</span>) + geom_point(<span class="hljs-title">aes</span>(<span class="hljs-title">x</span>=<span class="hljs-title">x</span>,<span class="hljs-title">y</span>=<span class="hljs-title">y</span>))</span><br></code></pre></td></tr></table></figure>

<ul>
<li>一行内调用R</li>
</ul>
<figure class="highlight perl"><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><code class="hljs perl">%R <span class="hljs-keyword">require</span>(ggplot2)<br>%R -i px,py<br>z = %R px*py<br><span class="hljs-keyword">print</span>(colN, z[<span class="hljs-number">0</span>]<br></code></pre></td></tr></table></figure>

<p><a target="_blank" rel="noopener" href="https://zhuanlan.zhihu.com/p/139032905">如何优雅地在Jupyter Notebook中同时运行R和IPython</a></p>

                
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