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<section id="pyspark-pandas-groupby-groupby-apply">
<h1>pyspark.pandas.groupby.GroupBy.apply<a class="headerlink" href="#pyspark-pandas-groupby-groupby-apply" title="Permalink to this headline">#</a></h1>
<dl class="py method">
<dt class="sig sig-object py" id="pyspark.pandas.groupby.GroupBy.apply">
<span class="sig-prename descclassname"><span class="pre">GroupBy.</span></span><span class="sig-name descname"><span class="pre">apply</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">func</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">*</span></span><span class="n"><span class="pre">args</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">**</span></span><span class="n"><span class="pre">kwargs</span></span></em><span class="sig-paren">)</span><a class="reference internal" href="../../../_modules/pyspark/pandas/groupby.html#GroupBy.apply"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#pyspark.pandas.groupby.GroupBy.apply" title="Permalink to this definition">#</a></dt>
<dd><p>Apply function <cite>func</cite> group-wise and combine the results together.</p>
<p>The function passed to <cite>apply</cite> must take a DataFrame as its first
argument and return a DataFrame. <cite>apply</cite> will
then take care of combining the results back together into a single
dataframe. <cite>apply</cite> is therefore a highly flexible
grouping method.</p>
<p>While <cite>apply</cite> is a very flexible method, its downside is that
using it can be quite a bit slower than using more specific methods
like <cite>agg</cite> or <cite>transform</cite>. pandas-on-Spark offers a wide range of method that will
be much faster than using <cite>apply</cite> for their specific purposes, so try to
use them before reaching for <cite>apply</cite>.</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>this API executes the function once to infer the type which is
potentially expensive, for instance, when the dataset is created after
aggregations or sorting.</p>
<p>To avoid this, specify return type in <code class="docutils literal notranslate"><span class="pre">func</span></code>, for instance, as below:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="k">def</span> <span class="nf">pandas_div</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ps</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">]]:</span>
<span class="gp">... </span> <span class="k">return</span> <span class="n">x</span><span class="p">[[</span><span class="s1">&#39;B&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">]]</span> <span class="o">/</span> <span class="n">x</span><span class="p">[[</span><span class="s1">&#39;B&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">]]</span>
</pre></div>
</div>
<p>If the return type is specified, the output column names become
<cite>c0, c1, c2 … cn</cite>. These names are positionally mapped to the returned
DataFrame in <code class="docutils literal notranslate"><span class="pre">func</span></code>.</p>
<p>To specify the column names, you can assign them in a NumPy compound type style
as below:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="k">def</span> <span class="nf">pandas_div</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ps</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">[(</span><span class="s2">&quot;index&quot;</span><span class="p">,</span> <span class="nb">int</span><span class="p">),</span> <span class="p">[(</span><span class="s2">&quot;a&quot;</span><span class="p">,</span> <span class="nb">float</span><span class="p">),</span> <span class="p">(</span><span class="s2">&quot;b&quot;</span><span class="p">,</span> <span class="nb">float</span><span class="p">)]]:</span>
<span class="gp">... </span> <span class="k">return</span> <span class="n">x</span><span class="p">[[</span><span class="s1">&#39;B&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">]]</span> <span class="o">/</span> <span class="n">x</span><span class="p">[[</span><span class="s1">&#39;B&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">]]</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">pdf</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="s1">&#39;B&#39;</span><span class="p">:</span> <span class="p">[</span><span class="mf">1.</span><span class="p">],</span> <span class="s1">&#39;C&#39;</span><span class="p">:</span> <span class="p">[</span><span class="mf">3.</span><span class="p">]})</span>
<span class="gp">&gt;&gt;&gt; </span><span class="k">def</span> <span class="nf">plus_one</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ps</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">[</span>
<span class="gp">... </span> <span class="p">(</span><span class="n">pdf</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">name</span><span class="p">,</span> <span class="n">pdf</span><span class="o">.</span><span class="n">index</span><span class="o">.</span><span class="n">dtype</span><span class="p">),</span> <span class="nb">zip</span><span class="p">(</span><span class="n">pdf</span><span class="o">.</span><span class="n">columns</span><span class="p">,</span> <span class="n">pdf</span><span class="o">.</span><span class="n">dtypes</span><span class="p">)]:</span>
<span class="gp">... </span> <span class="k">return</span> <span class="n">x</span><span class="p">[[</span><span class="s1">&#39;B&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">]]</span> <span class="o">/</span> <span class="n">x</span><span class="p">[[</span><span class="s1">&#39;B&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">]]</span>
</pre></div>
</div>
</div>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>the dataframe within <code class="docutils literal notranslate"><span class="pre">func</span></code> is actually a pandas dataframe. Therefore,
any pandas API within this function is allowed.</p>
</div>
<dl class="field-list simple">
<dt class="field-odd">Parameters</dt>
<dd class="field-odd"><dl class="simple">
<dt><strong>func</strong><span class="classifier">callable</span></dt><dd><p>A callable that takes a DataFrame as its first argument, and
returns a dataframe.</p>
</dd>
<dt><strong>*args</strong></dt><dd><p>Positional arguments to pass to func.</p>
</dd>
<dt><strong>**kwargs</strong></dt><dd><p>Keyword arguments to pass to func.</p>
</dd>
</dl>
</dd>
<dt class="field-even">Returns</dt>
<dd class="field-even"><dl class="simple">
<dt><strong>applied</strong><span class="classifier">DataFrame or Series</span></dt><dd></dd>
</dl>
</dd>
</dl>
<div class="admonition seealso">
<p class="admonition-title">See also</p>
<dl class="simple">
<dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">aggregate</span></code></dt><dd><p>Apply aggregate function to the GroupBy object.</p>
</dd>
<dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">DataFrame.apply</span></code></dt><dd><p>Apply a function to a DataFrame.</p>
</dd>
<dt><code class="xref py py-obj docutils literal notranslate"><span class="pre">Series.apply</span></code></dt><dd><p>Apply a function to a Series.</p>
</dd>
</dl>
</div>
<p class="rubric">Examples</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">df</span> <span class="o">=</span> <span class="n">ps</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">({</span><span class="s1">&#39;A&#39;</span><span class="p">:</span> <span class="s1">&#39;a a b&#39;</span><span class="o">.</span><span class="n">split</span><span class="p">(),</span>
<span class="gp">... </span> <span class="s1">&#39;B&#39;</span><span class="p">:</span> <span class="p">[</span><span class="mi">1</span><span class="p">,</span> <span class="mi">2</span><span class="p">,</span> <span class="mi">3</span><span class="p">],</span>
<span class="gp">... </span> <span class="s1">&#39;C&#39;</span><span class="p">:</span> <span class="p">[</span><span class="mi">4</span><span class="p">,</span> <span class="mi">6</span><span class="p">,</span> <span class="mi">5</span><span class="p">]},</span> <span class="n">columns</span><span class="o">=</span><span class="p">[</span><span class="s1">&#39;A&#39;</span><span class="p">,</span> <span class="s1">&#39;B&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">])</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">g</span> <span class="o">=</span> <span class="n">df</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="s1">&#39;A&#39;</span><span class="p">)</span>
</pre></div>
</div>
<p>Notice that <code class="docutils literal notranslate"><span class="pre">g</span></code> has two groups, <code class="docutils literal notranslate"><span class="pre">a</span></code> and <code class="docutils literal notranslate"><span class="pre">b</span></code>.
Calling <cite>apply</cite> in various ways, we can get different grouping results:</p>
<p>Below the functions passed to <cite>apply</cite> takes a DataFrame as
its argument and returns a DataFrame. <cite>apply</cite> combines the result for
each group together into a new DataFrame:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="k">def</span> <span class="nf">plus_min</span><span class="p">(</span><span class="n">x</span><span class="p">):</span>
<span class="gp">... </span> <span class="k">return</span> <span class="n">x</span> <span class="o">+</span> <span class="n">x</span><span class="o">.</span><span class="n">min</span><span class="p">()</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">g</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">plus_min</span><span class="p">)</span><span class="o">.</span><span class="n">sort_index</span><span class="p">()</span>
<span class="go"> A B C</span>
<span class="go">0 aa 2 8</span>
<span class="go">1 aa 3 10</span>
<span class="go">2 bb 6 10</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">g</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="nb">sum</span><span class="p">)</span><span class="o">.</span><span class="n">sort_index</span><span class="p">()</span>
<span class="go"> A B C</span>
<span class="go">A</span>
<span class="go">a aa 3 10</span>
<span class="go">b b 3 5</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="n">g</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="nb">len</span><span class="p">)</span><span class="o">.</span><span class="n">sort_index</span><span class="p">()</span>
<span class="go">A</span>
<span class="go">a 2</span>
<span class="go">b 1</span>
<span class="go">dtype: int64</span>
</pre></div>
</div>
<p>You can specify the type hint and prevent schema inference for better performance.</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="k">def</span> <span class="nf">pandas_div</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ps</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">[</span><span class="nb">int</span><span class="p">,</span> <span class="p">[</span><span class="nb">float</span><span class="p">,</span> <span class="nb">float</span><span class="p">]]:</span>
<span class="gp">... </span> <span class="k">return</span> <span class="n">x</span><span class="p">[[</span><span class="s1">&#39;B&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">]]</span> <span class="o">/</span> <span class="n">x</span><span class="p">[[</span><span class="s1">&#39;B&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">]]</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">g</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">pandas_div</span><span class="p">)</span><span class="o">.</span><span class="n">sort_index</span><span class="p">()</span>
<span class="go"> c0 c1</span>
<span class="go">0 1.0 1.0</span>
<span class="go">1 1.0 1.0</span>
<span class="go">2 1.0 1.0</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="k">def</span> <span class="nf">pandas_div</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ps</span><span class="o">.</span><span class="n">DataFrame</span><span class="p">[(</span><span class="s2">&quot;index&quot;</span><span class="p">,</span> <span class="nb">int</span><span class="p">),</span> <span class="p">[(</span><span class="s2">&quot;f1&quot;</span><span class="p">,</span> <span class="nb">float</span><span class="p">),</span> <span class="p">(</span><span class="s2">&quot;f2&quot;</span><span class="p">,</span> <span class="nb">float</span><span class="p">)]]:</span>
<span class="gp">... </span> <span class="k">return</span> <span class="n">x</span><span class="p">[[</span><span class="s1">&#39;B&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">]]</span> <span class="o">/</span> <span class="n">x</span><span class="p">[[</span><span class="s1">&#39;B&#39;</span><span class="p">,</span> <span class="s1">&#39;C&#39;</span><span class="p">]]</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">g</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">pandas_div</span><span class="p">)</span><span class="o">.</span><span class="n">sort_index</span><span class="p">()</span>
<span class="go"> f1 f2</span>
<span class="go">index</span>
<span class="go">0 1.0 1.0</span>
<span class="go">1 1.0 1.0</span>
<span class="go">2 1.0 1.0</span>
</pre></div>
</div>
<p>In case of Series, it works as below.</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="k">def</span> <span class="nf">plus_max</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="n">ps</span><span class="o">.</span><span class="n">Series</span><span class="p">[</span><span class="nb">int</span><span class="p">]:</span>
<span class="gp">... </span> <span class="k">return</span> <span class="n">x</span> <span class="o">+</span> <span class="n">x</span><span class="o">.</span><span class="n">max</span><span class="p">()</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">df</span><span class="o">.</span><span class="n">B</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">A</span><span class="p">)</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">plus_max</span><span class="p">)</span><span class="o">.</span><span class="n">sort_index</span><span class="p">()</span>
<span class="go">0 6</span>
<span class="go">1 3</span>
<span class="go">2 4</span>
<span class="go">Name: B, dtype: int64</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="k">def</span> <span class="nf">plus_min</span><span class="p">(</span><span class="n">x</span><span class="p">):</span>
<span class="gp">... </span> <span class="k">return</span> <span class="n">x</span> <span class="o">+</span> <span class="n">x</span><span class="o">.</span><span class="n">min</span><span class="p">()</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">df</span><span class="o">.</span><span class="n">B</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">A</span><span class="p">)</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">plus_min</span><span class="p">)</span><span class="o">.</span><span class="n">sort_index</span><span class="p">()</span>
<span class="go">0 2</span>
<span class="go">1 3</span>
<span class="go">2 6</span>
<span class="go">Name: B, dtype: int64</span>
</pre></div>
</div>
<p>You can also return a scalar value as an aggregated value of the group:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="k">def</span> <span class="nf">plus_length</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">int</span><span class="p">:</span>
<span class="gp">... </span> <span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="n">x</span><span class="p">)</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">df</span><span class="o">.</span><span class="n">B</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">A</span><span class="p">)</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">plus_length</span><span class="p">)</span><span class="o">.</span><span class="n">sort_index</span><span class="p">()</span>
<span class="go">0 1</span>
<span class="go">1 2</span>
<span class="go">Name: B, dtype: int64</span>
</pre></div>
</div>
<p>The extra arguments to the function can be passed as below.</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">&gt;&gt;&gt; </span><span class="k">def</span> <span class="nf">calculation</span><span class="p">(</span><span class="n">x</span><span class="p">,</span> <span class="n">y</span><span class="p">,</span> <span class="n">z</span><span class="p">)</span> <span class="o">-&gt;</span> <span class="nb">int</span><span class="p">:</span>
<span class="gp">... </span> <span class="k">return</span> <span class="nb">len</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="o">+</span> <span class="n">y</span> <span class="o">*</span> <span class="n">z</span>
<span class="gp">&gt;&gt;&gt; </span><span class="n">df</span><span class="o">.</span><span class="n">B</span><span class="o">.</span><span class="n">groupby</span><span class="p">(</span><span class="n">df</span><span class="o">.</span><span class="n">A</span><span class="p">)</span><span class="o">.</span><span class="n">apply</span><span class="p">(</span><span class="n">calculation</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="n">z</span><span class="o">=</span><span class="mi">10</span><span class="p">)</span><span class="o">.</span><span class="n">sort_index</span><span class="p">()</span>
<span class="go">0 51</span>
<span class="go">1 52</span>
<span class="go">Name: B, dtype: int64</span>
</pre></div>
</div>
</dd></dl>
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