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<section id="module-numpy.rec">
<span id="record-arrays-numpy-rec"></span><span id="routines-rec"></span><h1>Record Arrays (<a class="reference internal" href="#module-numpy.rec" title="numpy.rec"><code class="xref py py-mod docutils literal notranslate"><span class="pre">numpy.rec</span></code></a>)<a class="headerlink" href="#module-numpy.rec" title="Link to this heading">#</a></h1>
<p>Record arrays expose the fields of structured arrays as properties.</p>
<p>Most commonly, ndarrays contain elements of a single type, e.g. floats,
integers, bools etc. However, it is possible for elements to be combinations
of these using structured types, such as:</p>
<div class="try_examples_outer_container docutils container" id="31ea79a8-aedb-49d0-8171-647a3f711462">
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<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="kn">import</span><span class="w"> </span><span class="nn">numpy</span><span class="w"> </span><span class="k">as</span><span class="w"> </span><span class="nn">np</span>
<span class="gp">>>> </span><span class="n">a</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">array</span><span class="p">([(</span><span class="mi">1</span><span class="p">,</span> <span class="mf">2.0</span><span class="p">),</span> <span class="p">(</span><span class="mi">1</span><span class="p">,</span> <span class="mf">2.0</span><span class="p">)],</span>
<span class="gp">... </span> <span class="n">dtype</span><span class="o">=</span><span class="p">[(</span><span class="s1">'x'</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">int64</span><span class="p">),</span> <span class="p">(</span><span class="s1">'y'</span><span class="p">,</span> <span class="n">np</span><span class="o">.</span><span class="n">float64</span><span class="p">)])</span>
<span class="gp">>>> </span><span class="n">a</span>
<span class="go">array([(1, 2.), (1, 2.)], dtype=[('x', '<i8'), ('y', '<f8')])</span>
</pre></div>
</div>
<p>Here, each element consists of two fields: x (and int), and y (a float).
This is known as a structured array. The different fields are analogous
to columns in a spread-sheet. The different fields can be accessed as
one would a dictionary:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">a</span><span class="p">[</span><span class="s1">'x'</span><span class="p">]</span>
<span class="go">array([1, 1])</span>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">a</span><span class="p">[</span><span class="s1">'y'</span><span class="p">]</span>
<span class="go">array([2., 2.])</span>
</pre></div>
</div>
<p>Record arrays allow us to access fields as properties:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">ar</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">rec</span><span class="o">.</span><span class="n">array</span><span class="p">(</span><span class="n">a</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">ar</span><span class="o">.</span><span class="n">x</span>
<span class="go">array([1, 1])</span>
<span class="gp">>>> </span><span class="n">ar</span><span class="o">.</span><span class="n">y</span>
<span class="go">array([2., 2.])</span>
</pre></div>
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<h2>Functions<a class="headerlink" href="#functions" title="Link to this heading">#</a></h2>
<div class="pst-scrollable-table-container"><table class="autosummary longtable table autosummary">
<tbody>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.rec.array.html#numpy.rec.array" title="numpy.rec.array"><code class="xref py py-obj docutils literal notranslate"><span class="pre">array</span></code></a>(obj[, dtype, shape, offset, strides, ...])</p></td>
<td><p>Construct a record array from a wide-variety of objects.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.rec.find_duplicate.html#numpy.rec.find_duplicate" title="numpy.rec.find_duplicate"><code class="xref py py-obj docutils literal notranslate"><span class="pre">find_duplicate</span></code></a>(list)</p></td>
<td><p>Find duplication in a list, return a list of duplicated elements</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.rec.format_parser.html#numpy.rec.format_parser" title="numpy.rec.format_parser"><code class="xref py py-obj docutils literal notranslate"><span class="pre">format_parser</span></code></a>(formats, names, titles[, ...])</p></td>
<td><p>Class to convert formats, names, titles description to a dtype.</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.rec.fromarrays.html#numpy.rec.fromarrays" title="numpy.rec.fromarrays"><code class="xref py py-obj docutils literal notranslate"><span class="pre">fromarrays</span></code></a>(arrayList[, dtype, shape, ...])</p></td>
<td><p>Create a record array from a (flat) list of arrays</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.rec.fromfile.html#numpy.rec.fromfile" title="numpy.rec.fromfile"><code class="xref py py-obj docutils literal notranslate"><span class="pre">fromfile</span></code></a>(fd[, dtype, shape, offset, ...])</p></td>
<td><p>Create an array from binary file data</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="generated/numpy.rec.fromrecords.html#numpy.rec.fromrecords" title="numpy.rec.fromrecords"><code class="xref py py-obj docutils literal notranslate"><span class="pre">fromrecords</span></code></a>(recList[, dtype, shape, ...])</p></td>
<td><p>Create a recarray from a list of records in text form.</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="generated/numpy.rec.fromstring.html#numpy.rec.fromstring" title="numpy.rec.fromstring"><code class="xref py py-obj docutils literal notranslate"><span class="pre">fromstring</span></code></a>(datastring[, dtype, shape, ...])</p></td>
<td><p>Create a record array from binary data</p></td>
</tr>
</tbody>
</table>
</div>
<p>Also, the <a class="reference internal" href="generated/numpy.recarray.html#numpy.recarray" title="numpy.recarray"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.recarray</span></code></a> class and the <a class="reference internal" href="generated/numpy.record.html#numpy.record" title="numpy.record"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.record</span></code></a> scalar dtype are present
in this namespace.</p>
</section>
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