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| <section id="column-selections"> |
| <h1>Column Selections<a class="headerlink" href="#column-selections" title="Link to this heading">¶</a></h1> |
| <p>Use <a class="reference internal" href="../../autoapi/datafusion/dataframe/index.html#datafusion.dataframe.DataFrame.select" title="datafusion.dataframe.DataFrame.select"><code class="xref py py-func docutils literal notranslate"><span class="pre">select()</span></code></a> for basic column selection.</p> |
| <p>DataFusion can work with several file types, to start simple we can use a subset of the |
| <a class="reference external" href="https://www.nyc.gov/site/tlc/about/tlc-trip-record-data.page">TLC Trip Record Data</a>, |
| which you can download <a class="reference external" href="https://d37ci6vzurychx.cloudfront.net/trip-data/yellow_tripdata_2021-01.parquet">here</a>.</p> |
| <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="n">In</span> <span class="p">[</span><span class="mi">1</span><span class="p">]:</span> <span class="kn">from</span><span class="w"> </span><span class="nn">datafusion</span><span class="w"> </span><span class="kn">import</span> <span class="n">SessionContext</span> |
| |
| <span class="n">In</span> <span class="p">[</span><span class="mi">2</span><span class="p">]:</span> <span class="n">ctx</span> <span class="o">=</span> <span class="n">SessionContext</span><span class="p">()</span> |
| |
| <span class="n">In</span> <span class="p">[</span><span class="mi">3</span><span class="p">]:</span> <span class="n">df</span> <span class="o">=</span> <span class="n">ctx</span><span class="o">.</span><span class="n">read_parquet</span><span class="p">(</span><span class="s2">"yellow_tripdata_2021-01.parquet"</span><span class="p">)</span> |
| |
| <span class="n">In</span> <span class="p">[</span><span class="mi">4</span><span class="p">]:</span> <span class="n">df</span><span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="s2">"trip_distance"</span><span class="p">,</span> <span class="s2">"passenger_count"</span><span class="p">)</span> |
| <span class="n">Out</span><span class="p">[</span><span class="mi">4</span><span class="p">]:</span> |
| <span class="n">DataFrame</span><span class="p">()</span> |
| <span class="o">+---------------+-----------------+</span> |
| <span class="o">|</span> <span class="n">trip_distance</span> <span class="o">|</span> <span class="n">passenger_count</span> <span class="o">|</span> |
| <span class="o">+---------------+-----------------+</span> |
| <span class="o">|</span> <span class="mf">2.1</span> <span class="o">|</span> <span class="mf">1.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">0.2</span> <span class="o">|</span> <span class="mf">1.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">14.7</span> <span class="o">|</span> <span class="mf">1.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">10.6</span> <span class="o">|</span> <span class="mf">0.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">4.94</span> <span class="o">|</span> <span class="mf">1.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">1.6</span> <span class="o">|</span> <span class="mf">1.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">4.1</span> <span class="o">|</span> <span class="mf">1.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">5.7</span> <span class="o">|</span> <span class="mf">1.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">9.1</span> <span class="o">|</span> <span class="mf">1.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">2.7</span> <span class="o">|</span> <span class="mf">2.0</span> <span class="o">|</span> |
| <span class="o">+---------------+-----------------+</span> |
| <span class="n">Data</span> <span class="n">truncated</span><span class="o">.</span> |
| </pre></div> |
| </div> |
| <p>For mathematical or logical operations use <a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.col" title="datafusion.col"><code class="xref py py-func docutils literal notranslate"><span class="pre">col()</span></code></a> to select columns, and give meaningful names to the resulting |
| operations using <a class="reference internal" href="../../autoapi/datafusion/expr/index.html#datafusion.expr.Expr.alias" title="datafusion.expr.Expr.alias"><code class="xref py py-func docutils literal notranslate"><span class="pre">alias()</span></code></a></p> |
| <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="n">In</span> <span class="p">[</span><span class="mi">5</span><span class="p">]:</span> <span class="kn">from</span><span class="w"> </span><span class="nn">datafusion</span><span class="w"> </span><span class="kn">import</span> <span class="n">col</span><span class="p">,</span> <span class="n">lit</span> |
| |
| <span class="n">In</span> <span class="p">[</span><span class="mi">6</span><span class="p">]:</span> <span class="n">df</span><span class="o">.</span><span class="n">select</span><span class="p">((</span><span class="n">col</span><span class="p">(</span><span class="s2">"tip_amount"</span><span class="p">)</span> <span class="o">+</span> <span class="n">col</span><span class="p">(</span><span class="s2">"tolls_amount"</span><span class="p">))</span><span class="o">.</span><span class="n">alias</span><span class="p">(</span><span class="s2">"tips_plus_tolls"</span><span class="p">))</span> |
| <span class="n">Out</span><span class="p">[</span><span class="mi">6</span><span class="p">]:</span> |
| <span class="n">DataFrame</span><span class="p">()</span> |
| <span class="o">+-----------------+</span> |
| <span class="o">|</span> <span class="n">tips_plus_tolls</span> <span class="o">|</span> |
| <span class="o">+-----------------+</span> |
| <span class="o">|</span> <span class="mf">0.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">0.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">8.65</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">6.05</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">4.06</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">2.35</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">0.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">0.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">0.0</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mf">3.15</span> <span class="o">|</span> |
| <span class="o">+-----------------+</span> |
| <span class="n">Data</span> <span class="n">truncated</span><span class="o">.</span> |
| </pre></div> |
| </div> |
| <div class="admonition warning"> |
| <p class="admonition-title">Warning</p> |
| <p>Please be aware that all identifiers are effectively made lower-case in SQL, so if your file has capital letters |
| (ex: Name) you must put your column name in double quotes or the selection won’t work. As an alternative for simple |
| column selection use <a class="reference internal" href="../../autoapi/datafusion/dataframe/index.html#datafusion.dataframe.DataFrame.select" title="datafusion.dataframe.DataFrame.select"><code class="xref py py-func docutils literal notranslate"><span class="pre">select()</span></code></a> without double quotes</p> |
| </div> |
| <p>For selecting columns with capital letters use <code class="docutils literal notranslate"><span class="pre">'"VendorID"'</span></code></p> |
| <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="n">In</span> <span class="p">[</span><span class="mi">7</span><span class="p">]:</span> <span class="n">df</span><span class="o">.</span><span class="n">select</span><span class="p">(</span><span class="n">col</span><span class="p">(</span><span class="s1">'"VendorID"'</span><span class="p">))</span> |
| <span class="n">Out</span><span class="p">[</span><span class="mi">7</span><span class="p">]:</span> |
| <span class="n">DataFrame</span><span class="p">()</span> |
| <span class="o">+----------+</span> |
| <span class="o">|</span> <span class="n">VendorID</span> <span class="o">|</span> |
| <span class="o">+----------+</span> |
| <span class="o">|</span> <span class="mi">1</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mi">1</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mi">1</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mi">1</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mi">2</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mi">1</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mi">1</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mi">1</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mi">1</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="mi">1</span> <span class="o">|</span> |
| <span class="o">+----------+</span> |
| <span class="n">Data</span> <span class="n">truncated</span><span class="o">.</span> |
| </pre></div> |
| </div> |
| <p>To combine it with literal values use the <a class="reference internal" href="../../autoapi/datafusion/index.html#datafusion.lit" title="datafusion.lit"><code class="xref py py-func docutils literal notranslate"><span class="pre">lit()</span></code></a></p> |
| <div class="highlight-ipython notranslate"><div class="highlight"><pre><span></span><span class="n">In</span> <span class="p">[</span><span class="mi">8</span><span class="p">]:</span> <span class="n">large_trip_distance</span> <span class="o">=</span> <span class="n">col</span><span class="p">(</span><span class="s2">"trip_distance"</span><span class="p">)</span> <span class="o">></span> <span class="n">lit</span><span class="p">(</span><span class="mf">5.0</span><span class="p">)</span> |
| |
| <span class="n">In</span> <span class="p">[</span><span class="mi">9</span><span class="p">]:</span> <span class="n">low_passenger_count</span> <span class="o">=</span> <span class="n">col</span><span class="p">(</span><span class="s2">"passenger_count"</span><span class="p">)</span> <span class="o"><</span> <span class="n">lit</span><span class="p">(</span><span class="mi">4</span><span class="p">)</span> |
| |
| <span class="n">In</span> <span class="p">[</span><span class="mi">10</span><span class="p">]:</span> <span class="n">df</span><span class="o">.</span><span class="n">select</span><span class="p">((</span><span class="n">large_trip_distance</span> <span class="o">&</span> <span class="n">low_passenger_count</span><span class="p">)</span><span class="o">.</span><span class="n">alias</span><span class="p">(</span><span class="s2">"lonely_trips"</span><span class="p">))</span> |
| <span class="n">Out</span><span class="p">[</span><span class="mi">10</span><span class="p">]:</span> |
| <span class="n">DataFrame</span><span class="p">()</span> |
| <span class="o">+--------------+</span> |
| <span class="o">|</span> <span class="n">lonely_trips</span> <span class="o">|</span> |
| <span class="o">+--------------+</span> |
| <span class="o">|</span> <span class="n">false</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="n">false</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="n">true</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="n">true</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="n">false</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="n">false</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="n">false</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="n">true</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="n">true</span> <span class="o">|</span> |
| <span class="o">|</span> <span class="n">false</span> <span class="o">|</span> |
| <span class="o">+--------------+</span> |
| <span class="n">Data</span> <span class="n">truncated</span><span class="o">.</span> |
| </pre></div> |
| </div> |
| </section> |
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