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| <div class="section" id="numpy-integration"> |
| <span id="numpy-interop"></span><h1>NumPy Integration<a class="headerlink" href="#numpy-integration" title="Permalink to this headline">¶</a></h1> |
| <p>PyArrow allows converting back and forth from |
| <a class="reference external" href="https://www.numpy.org/">NumPy</a> arrays to Arrow <a class="reference internal" href="data.html#data-array"><span class="std std-ref">Arrays</span></a>.</p> |
| <div class="section" id="numpy-to-arrow"> |
| <h2>NumPy to Arrow<a class="headerlink" href="#numpy-to-arrow" title="Permalink to this headline">¶</a></h2> |
| <p>To convert a NumPy array to Arrow, one can simply call the <a class="reference internal" href="generated/pyarrow.array.html#pyarrow.array" title="pyarrow.array"><code class="xref py py-func docutils literal notranslate"><span class="pre">pyarrow.array()</span></code></a> |
| factory function.</p> |
| <div class="highlight-pycon notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="kn">as</span> <span class="nn">np</span> |
| <span class="gp">>>> </span><span class="kn">import</span> <span class="nn">pyarrow</span> <span class="kn">as</span> <span class="nn">pa</span> |
| <span class="gp">>>> </span><span class="n">data</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">arange</span><span class="p">(</span><span class="mi">10</span><span class="p">,</span> <span class="n">dtype</span><span class="o">=</span><span class="s1">'int16'</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">arr</span> <span class="o">=</span> <span class="n">pa</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">data</span><span class="p">)</span> |
| <span class="gp">>>> </span><span class="n">arr</span> |
| <span class="go"><pyarrow.lib.Int16Array object at 0x7fb1d1e6ae58></span> |
| <span class="go">[</span> |
| <span class="go"> 0,</span> |
| <span class="go"> 1,</span> |
| <span class="go"> 2,</span> |
| <span class="go"> 3,</span> |
| <span class="go"> 4,</span> |
| <span class="go"> 5,</span> |
| <span class="go"> 6,</span> |
| <span class="go"> 7,</span> |
| <span class="go"> 8,</span> |
| <span class="go"> 9</span> |
| <span class="go">]</span> |
| </pre></div> |
| </div> |
| <p>Converting from NumPy supports a wide range of input dtypes, including |
| structured dtypes or strings.</p> |
| </div> |
| <div class="section" id="arrow-to-numpy"> |
| <h2>Arrow to NumPy<a class="headerlink" href="#arrow-to-numpy" title="Permalink to this headline">¶</a></h2> |
| <p>In the reverse direction, it is possible to produce a view of an Arrow Array |
| for use with NumPy using the <a class="reference internal" href="generated/pyarrow.Array.html#pyarrow.Array.to_numpy" title="pyarrow.Array.to_numpy"><code class="xref py py-meth docutils literal notranslate"><span class="pre">to_numpy()</span></code></a> method. |
| This is limited to primitive types for which NumPy has the same physical |
| representation as Arrow, and assuming the Arrow data has no nulls.</p> |
| <div class="highlight-pycon notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span> <span class="nn">numpy</span> <span class="kn">as</span> <span class="nn">np</span> |
| <span class="gp">>>> </span><span class="kn">import</span> <span class="nn">pyarrow</span> <span class="kn">as</span> <span class="nn">pa</span> |
| <span class="gp">>>> </span><span class="n">arr</span> <span class="o">=</span> <span class="n">pa</span><span class="o">.</span><span class="n">array</span><span class="p">([</span><span class="mi">4</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="mi">6</span><span class="p">],</span> <span class="nb">type</span><span class="o">=</span><span class="n">pa</span><span class="o">.</span><span class="n">int32</span><span class="p">())</span> |
| <span class="gp">>>> </span><span class="n">view</span> <span class="o">=</span> <span class="n">arr</span><span class="o">.</span><span class="n">to_numpy</span><span class="p">()</span> |
| <span class="gp">>>> </span><span class="n">view</span> |
| <span class="go">array([4, 5, 6], dtype=int32)</span> |
| </pre></div> |
| </div> |
| <p>For more complex data types, you have to use the <a class="reference internal" href="generated/pyarrow.Array.html#pyarrow.Array.to_pandas" title="pyarrow.Array.to_pandas"><code class="xref py py-meth docutils literal notranslate"><span class="pre">to_pandas()</span></code></a> |
| method (which will construct a Numpy array with Pandas semantics for, e.g., |
| representation of null values).</p> |
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