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| <div class="section" id="pyspark-pandas-series-transform"> |
| <h1>pyspark.pandas.Series.transform<a class="headerlink" href="#pyspark-pandas-series-transform" title="Permalink to this headline">¶</a></h1> |
| <dl class="py method"> |
| <dt id="pyspark.pandas.Series.transform"> |
| <code class="sig-prename descclassname">Series.</code><code class="sig-name descname">transform</code><span class="sig-paren">(</span><em class="sig-param"><span class="n">func</span><span class="p">:</span> <span class="n">Union<span class="p">[</span>Callable<span class="p">, </span>List<span class="p">[</span>Callable<span class="p">]</span><span class="p">]</span></span></em>, <em class="sig-param"><span class="n">axis</span><span class="p">:</span> <span class="n">Union<span class="p">[</span>int<span class="p">, </span>str<span class="p">]</span></span> <span class="o">=</span> <span class="default_value">0</span></em>, <em class="sig-param"><span class="o">*</span><span class="n">args</span><span class="p">:</span> <span class="n">Any</span></em>, <em class="sig-param"><span class="o">**</span><span class="n">kwargs</span><span class="p">:</span> <span class="n">Any</span></em><span class="sig-paren">)</span> → Union<span class="p">[</span>pyspark.pandas.series.Series<span class="p">, </span>pyspark.pandas.frame.DataFrame<span class="p">]</span><a class="reference internal" href="../../../_modules/pyspark/pandas/series.html#Series.transform"><span class="viewcode-link">[source]</span></a><a class="headerlink" href="#pyspark.pandas.Series.transform" title="Permalink to this definition">¶</a></dt> |
| <dd><p>Call <code class="docutils literal notranslate"><span class="pre">func</span></code> producing the same type as <cite>self</cite> with transformed values |
| and that has the same axis length as input.</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">>>> </span><span class="k">def</span> <span class="nf">square</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="o">-></span> <span class="n">np</span><span class="o">.</span><span class="n">int32</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="mi">2</span> |
| </pre></div> |
| </div> |
| <p>pandas-on-Spark uses return type hint and does not try to infer the type.</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">function or list</span></dt><dd><p>A function or a list of functions to use for transforming the data.</p> |
| </dd> |
| <dt><strong>axis</strong><span class="classifier">int, default 0 or ‘index’</span></dt><dd><p>Can only be set to 0 at the moment.</p> |
| </dd> |
| <dt><strong>*args</strong></dt><dd><p>Positional arguments to pass to <cite>func</cite>.</p> |
| </dd> |
| <dt><strong>**kwargs</strong></dt><dd><p>Keyword arguments to pass to <cite>func</cite>.</p> |
| </dd> |
| </dl> |
| </dd> |
| <dt class="field-even">Returns</dt> |
| <dd class="field-even"><dl class="simple"> |
| <dt>An instance of the same type with <cite>self</cite> that must have the same length as input.</dt><dd></dd> |
| </dl> |
| </dd> |
| </dl> |
| <div class="admonition seealso"> |
| <p class="admonition-title">See also</p> |
| <dl class="simple"> |
| <dt><a class="reference internal" href="pyspark.pandas.Series.aggregate.html#pyspark.pandas.Series.aggregate" title="pyspark.pandas.Series.aggregate"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Series.aggregate</span></code></a></dt><dd><p>Only perform aggregating type operations.</p> |
| </dd> |
| <dt><a class="reference internal" href="pyspark.pandas.Series.apply.html#pyspark.pandas.Series.apply" title="pyspark.pandas.Series.apply"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Series.apply</span></code></a></dt><dd><p>Invoke function on Series.</p> |
| </dd> |
| <dt><a class="reference internal" href="pyspark.pandas.DataFrame.transform.html#pyspark.pandas.DataFrame.transform" title="pyspark.pandas.DataFrame.transform"><code class="xref py py-obj docutils literal notranslate"><span class="pre">DataFrame.transform</span></code></a></dt><dd><p>The equivalent function for DataFrame.</p> |
| </dd> |
| </dl> |
| </div> |
| <p class="rubric">Examples</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">s</span> <span class="o">=</span> <span class="n">ps</span><span class="o">.</span><span class="n">Series</span><span class="p">(</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="n">s</span> |
| <span class="go">0 0</span> |
| <span class="go">1 1</span> |
| <span class="go">2 2</span> |
| <span class="go">dtype: int64</span> |
| </pre></div> |
| </div> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="k">def</span> <span class="nf">sqrt</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="o">-></span> <span class="nb">float</span><span class="p">:</span> |
| <span class="gp">... </span> <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">s</span><span class="o">.</span><span class="n">transform</span><span class="p">(</span><span class="n">sqrt</span><span class="p">)</span> |
| <span class="go">0 0.000000</span> |
| <span class="go">1 1.000000</span> |
| <span class="go">2 1.414214</span> |
| <span class="go">dtype: float64</span> |
| </pre></div> |
| </div> |
| <p>Even though the resulting instance must have the same length as the |
| input, it is possible to provide several input functions:</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="k">def</span> <span class="nf">exp</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> <span class="o">-></span> <span class="nb">float</span><span class="p">:</span> |
| <span class="gp">... </span> <span class="k">return</span> <span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">(</span><span class="n">x</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">s</span><span class="o">.</span><span class="n">transform</span><span class="p">([</span><span class="n">sqrt</span><span class="p">,</span> <span class="n">exp</span><span class="p">])</span> |
| <span class="go"> sqrt exp</span> |
| <span class="go">0 0.000000 1.000000</span> |
| <span class="go">1 1.000000 2.718282</span> |
| <span class="go">2 1.414214 7.389056</span> |
| </pre></div> |
| </div> |
| <p>You can omit the type hint and let pandas-on-Spark infer its type.</p> |
| <div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">s</span><span class="o">.</span><span class="n">transform</span><span class="p">([</span><span class="n">np</span><span class="o">.</span><span class="n">sqrt</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">exp</span><span class="p">])</span> |
| <span class="go"> sqrt exp</span> |
| <span class="go">0 0.000000 1.000000</span> |
| <span class="go">1 1.000000 2.718282</span> |
| <span class="go">2 1.414214 7.389056</span> |
| </pre></div> |
| </div> |
| </dd></dl> |
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