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<section id="scalars">
<span id="arrays-scalars"></span><h1>Scalars<a class="headerlink" href="#scalars" title="Link to this heading">#</a></h1>
<p>Python defines only one type of a particular data class (there is only
one integer type, one floating-point type, etc.). This can be
convenient in applications that don’t need to be concerned with all
the ways data can be represented in a computer. For scientific
computing, however, more control is often needed.</p>
<p>In NumPy, there are 24 new fundamental Python types to describe
different types of scalars. These type descriptors are mostly based on
the types available in the C language that CPython is written in, with
several additional types compatible with Python’s types.</p>
<p>Array scalars have the same attributes and methods as <a class="reference internal" href="generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray"><code class="xref py py-class docutils literal notranslate"><span class="pre">ndarrays</span></code></a>. <a class="footnote-reference brackets" href="#id2" id="id1" role="doc-noteref"><span class="fn-bracket">[</span>1<span class="fn-bracket">]</span></a> This allows one to treat items of an array partly on
the same footing as arrays, smoothing out rough edges that result when
mixing scalar and array operations.</p>
<p>Array scalars live in a hierarchy (see the Figure below) of data
types. They can be detected using the hierarchy: For example,
<code class="docutils literal notranslate"><span class="pre">isinstance(val,</span> <span class="pre">np.generic)</span></code> will return <a class="reference external" href="https://docs.python.org/3/library/constants.html#True" title="(in Python v3.13)"><code class="xref py py-data docutils literal notranslate"><span class="pre">True</span></code></a> if <em>val</em> is
an array scalar object. Alternatively, what kind of array scalar is
present can be determined using other members of the data type
hierarchy. Thus, for example <code class="docutils literal notranslate"><span class="pre">isinstance(val,</span> <span class="pre">np.complexfloating)</span></code>
will return <a class="reference external" href="https://docs.python.org/3/library/constants.html#True" title="(in Python v3.13)"><code class="xref py py-data docutils literal notranslate"><span class="pre">True</span></code></a> if <em>val</em> is a complex valued type, while
<code class="docutils literal notranslate"><span class="pre">isinstance(val,</span> <span class="pre">np.flexible)</span></code> will return true if <em>val</em> is one
of the flexible itemsize array types (<a class="reference internal" href="#numpy.str_" title="numpy.str_"><code class="xref py py-class docutils literal notranslate"><span class="pre">str_</span></code></a>,
<a class="reference internal" href="#numpy.bytes_" title="numpy.bytes_"><code class="xref py py-class docutils literal notranslate"><span class="pre">bytes_</span></code></a>, <a class="reference internal" href="#numpy.void" title="numpy.void"><code class="xref py py-class docutils literal notranslate"><span class="pre">void</span></code></a>).</p>
<figure class="align-default" id="id4">
<img alt="../_images/dtype-hierarchy.png" src="../_images/dtype-hierarchy.png" />
<figcaption>
<p><span class="caption-text"><strong>Figure:</strong> Hierarchy of type objects representing the array data
types. Not shown are the two integer types <a class="reference internal" href="#numpy.intp" title="numpy.intp"><code class="xref py py-class docutils literal notranslate"><span class="pre">intp</span></code></a> and
<a class="reference internal" href="#numpy.uintp" title="numpy.uintp"><code class="xref py py-class docutils literal notranslate"><span class="pre">uintp</span></code></a> which are used for indexing (the same as the
default integer since NumPy 2).</span><a class="headerlink" href="#id4" title="Link to this image">#</a></p>
</figcaption>
</figure>
<aside class="footnote-list brackets">
<aside class="footnote brackets" id="id2" role="doc-footnote">
<span class="label"><span class="fn-bracket">[</span><a role="doc-backlink" href="#id1">1</a><span class="fn-bracket">]</span></span>
<p>However, array scalars are immutable, so none of the array
scalar attributes are settable.</p>
</aside>
</aside>
<section id="built-in-scalar-types">
<span id="arrays-scalars-built-in"></span><span id="arrays-scalars-character-codes"></span><h2>Built-in scalar types<a class="headerlink" href="#built-in-scalar-types" title="Link to this heading">#</a></h2>
<p>The built-in scalar types are shown below. The C-like names are associated with character codes,
which are shown in their descriptions. Use of the character codes, however,
is discouraged.</p>
<p>Some of the scalar types are essentially equivalent to fundamental
Python types and therefore inherit from them as well as from the
generic array scalar type:</p>
<div class="pst-scrollable-table-container"><table class="table">
<thead>
<tr class="row-odd"><th class="head"><p>Array scalar type</p></th>
<th class="head"><p>Related Python type</p></th>
<th class="head"><p>Inherits?</p></th>
</tr>
</thead>
<tbody>
<tr class="row-even"><td><p><a class="reference internal" href="#numpy.int_" title="numpy.int_"><code class="xref py py-class docutils literal notranslate"><span class="pre">int_</span></code></a></p></td>
<td><p><a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">int</span></code></a></p></td>
<td><p>Python 2 only</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#numpy.double" title="numpy.double"><code class="xref py py-class docutils literal notranslate"><span class="pre">double</span></code></a></p></td>
<td><p><a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">float</span></code></a></p></td>
<td><p>yes</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#numpy.cdouble" title="numpy.cdouble"><code class="xref py py-class docutils literal notranslate"><span class="pre">cdouble</span></code></a></p></td>
<td><p><a class="reference external" href="https://docs.python.org/3/library/functions.html#complex" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">complex</span></code></a></p></td>
<td><p>yes</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#numpy.bytes_" title="numpy.bytes_"><code class="xref py py-class docutils literal notranslate"><span class="pre">bytes_</span></code></a></p></td>
<td><p><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#bytes" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">bytes</span></code></a></p></td>
<td><p>yes</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#numpy.str_" title="numpy.str_"><code class="xref py py-class docutils literal notranslate"><span class="pre">str_</span></code></a></p></td>
<td><p><a class="reference external" href="https://docs.python.org/3/library/stdtypes.html#str" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">str</span></code></a></p></td>
<td><p>yes</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#numpy.bool_" title="numpy.bool_"><code class="xref py py-class docutils literal notranslate"><span class="pre">bool_</span></code></a></p></td>
<td><p><a class="reference internal" href="#numpy.bool" title="numpy.bool"><code class="xref py py-class docutils literal notranslate"><span class="pre">bool</span></code></a></p></td>
<td><p>no</p></td>
</tr>
<tr class="row-even"><td><p><a class="reference internal" href="#numpy.datetime64" title="numpy.datetime64"><code class="xref py py-class docutils literal notranslate"><span class="pre">datetime64</span></code></a></p></td>
<td><p><a class="reference external" href="https://docs.python.org/3/library/datetime.html#datetime.datetime" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">datetime.datetime</span></code></a></p></td>
<td><p>no</p></td>
</tr>
<tr class="row-odd"><td><p><a class="reference internal" href="#numpy.timedelta64" title="numpy.timedelta64"><code class="xref py py-class docutils literal notranslate"><span class="pre">timedelta64</span></code></a></p></td>
<td><p><a class="reference external" href="https://docs.python.org/3/library/datetime.html#datetime.timedelta" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">datetime.timedelta</span></code></a></p></td>
<td><p>no</p></td>
</tr>
</tbody>
</table>
</div>
<p>The <a class="reference internal" href="#numpy.bool_" title="numpy.bool_"><code class="xref py py-class docutils literal notranslate"><span class="pre">bool_</span></code></a> data type is very similar to the Python
<a class="reference internal" href="#numpy.bool" title="numpy.bool"><code class="xref py py-class docutils literal notranslate"><span class="pre">bool</span></code></a> but does not inherit from it because Python’s
<a class="reference internal" href="#numpy.bool" title="numpy.bool"><code class="xref py py-class docutils literal notranslate"><span class="pre">bool</span></code></a> does not allow itself to be inherited from, and
on the C-level the size of the actual bool data is not the same as a
Python Boolean scalar.</p>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>The <a class="reference internal" href="#numpy.int_" title="numpy.int_"><code class="xref py py-class docutils literal notranslate"><span class="pre">int_</span></code></a> type does <strong>not</strong> inherit from the
<a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">int</span></code></a> built-in under Python 3, because type <a class="reference external" href="https://docs.python.org/3/library/functions.html#int" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">int</span></code></a> is no
longer a fixed-width integer type.</p>
</div>
<div class="admonition tip">
<p class="admonition-title">Tip</p>
<p>The default data type in NumPy is <a class="reference internal" href="#numpy.double" title="numpy.double"><code class="xref py py-class docutils literal notranslate"><span class="pre">double</span></code></a>.</p>
</div>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.generic">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">generic</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.generic" title="Link to this definition">#</a></dt>
<dd><p>Base class for numpy scalar types.</p>
<p>Class from which most (all?) numpy scalar types are derived. For
consistency, exposes the same API as <a class="reference internal" href="generated/numpy.ndarray.html#numpy.ndarray" title="numpy.ndarray"><code class="xref py py-obj docutils literal notranslate"><span class="pre">ndarray</span></code></a>, despite many
consequent attributes being either “get-only,” or completely irrelevant.
This is the class from which it is strongly suggested users should derive
custom scalar types.</p>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.number">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">number</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.number" title="Link to this definition">#</a></dt>
<dd><p>Abstract base class of all numeric scalar types.</p>
</dd></dl>
<section id="integer-types">
<h3>Integer types<a class="headerlink" href="#integer-types" title="Link to this heading">#</a></h3>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.integer">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">integer</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.integer" title="Link to this definition">#</a></dt>
<dd><p>Abstract base class of all integer scalar types.</p>
</dd></dl>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>The numpy integer types mirror the behavior of C integers, and can therefore
be subject to <a class="reference internal" href="../user/basics.types.html#overflow-errors"><span class="std std-ref">Overflow errors</span></a>.</p>
</div>
<section id="signed-integer-types">
<h4>Signed integer types<a class="headerlink" href="#signed-integer-types" title="Link to this heading">#</a></h4>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.signedinteger">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">signedinteger</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.signedinteger" title="Link to this definition">#</a></dt>
<dd><p>Abstract base class of all signed integer scalar types.</p>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.byte">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">byte</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.byte" title="Link to this definition">#</a></dt>
<dd><p>Signed integer type, compatible with C <code class="docutils literal notranslate"><span class="pre">char</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Character code<span class="colon">:</span></dt>
<dd class="field-odd"><p><code class="docutils literal notranslate"><span class="pre">'b'</span></code></p>
</dd>
<dt class="field-even">Canonical name<span class="colon">:</span></dt>
<dd class="field-even"><p><a class="reference internal" href="#numpy.byte" title="numpy.byte"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.byte</span></code></a></p>
</dd>
<dt class="field-odd">Alias on this platform (Linux x86_64)<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference internal" href="#numpy.int8" title="numpy.int8"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.int8</span></code></a>: 8-bit signed integer (<code class="docutils literal notranslate"><span class="pre">-128</span></code> to <code class="docutils literal notranslate"><span class="pre">127</span></code>).</p>
</dd>
</dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.short">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">short</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.short" title="Link to this definition">#</a></dt>
<dd><p>Signed integer type, compatible with C <code class="docutils literal notranslate"><span class="pre">short</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Character code<span class="colon">:</span></dt>
<dd class="field-odd"><p><code class="docutils literal notranslate"><span class="pre">'h'</span></code></p>
</dd>
<dt class="field-even">Canonical name<span class="colon">:</span></dt>
<dd class="field-even"><p><a class="reference internal" href="#numpy.short" title="numpy.short"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.short</span></code></a></p>
</dd>
<dt class="field-odd">Alias on this platform (Linux x86_64)<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference internal" href="#numpy.int16" title="numpy.int16"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.int16</span></code></a>: 16-bit signed integer (<code class="docutils literal notranslate"><span class="pre">-32_768</span></code> to <code class="docutils literal notranslate"><span class="pre">32_767</span></code>).</p>
</dd>
</dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.intc">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">intc</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.intc" title="Link to this definition">#</a></dt>
<dd><p>Signed integer type, compatible with C <code class="docutils literal notranslate"><span class="pre">int</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Character code<span class="colon">:</span></dt>
<dd class="field-odd"><p><code class="docutils literal notranslate"><span class="pre">'i'</span></code></p>
</dd>
<dt class="field-even">Canonical name<span class="colon">:</span></dt>
<dd class="field-even"><p><a class="reference internal" href="#numpy.intc" title="numpy.intc"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.intc</span></code></a></p>
</dd>
<dt class="field-odd">Alias on this platform (Linux x86_64)<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference internal" href="#numpy.int32" title="numpy.int32"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.int32</span></code></a>: 32-bit signed integer (<code class="docutils literal notranslate"><span class="pre">-2_147_483_648</span></code> to <code class="docutils literal notranslate"><span class="pre">2_147_483_647</span></code>).</p>
</dd>
</dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.int_">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">int_</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.int_" title="Link to this definition">#</a></dt>
<dd><p>Default signed integer type, 64bit on 64bit systems and 32bit on 32bit
systems.</p>
<dl class="field-list simple">
<dt class="field-odd">Character code<span class="colon">:</span></dt>
<dd class="field-odd"><p><code class="docutils literal notranslate"><span class="pre">'l'</span></code></p>
</dd>
<dt class="field-even">Canonical name<span class="colon">:</span></dt>
<dd class="field-even"><p><a class="reference internal" href="#numpy.int_" title="numpy.int_"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.int_</span></code></a></p>
</dd>
<dt class="field-odd">Alias on this platform (Linux x86_64)<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference internal" href="#numpy.int64" title="numpy.int64"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.int64</span></code></a>: 64-bit signed integer (<code class="docutils literal notranslate"><span class="pre">-9_223_372_036_854_775_808</span></code> to <code class="docutils literal notranslate"><span class="pre">9_223_372_036_854_775_807</span></code>).</p>
</dd>
<dt class="field-even">Alias on this platform (Linux x86_64)<span class="colon">:</span></dt>
<dd class="field-even"><p><a class="reference internal" href="#numpy.intp" title="numpy.intp"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.intp</span></code></a>: Signed integer large enough to fit pointer, compatible with C <code class="docutils literal notranslate"><span class="pre">intptr_t</span></code>.</p>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="numpy.long">
<span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">long</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.long" title="Link to this definition">#</a></dt>
<dd><p>alias of <a class="reference internal" href="#numpy.int_" title="numpy.int_"><code class="xref py py-class docutils literal notranslate"><span class="pre">int_</span></code></a></p>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.longlong">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">longlong</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.longlong" title="Link to this definition">#</a></dt>
<dd><p>Signed integer type, compatible with C <code class="docutils literal notranslate"><span class="pre">long</span> <span class="pre">long</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Character code<span class="colon">:</span></dt>
<dd class="field-odd"><p><code class="docutils literal notranslate"><span class="pre">'q'</span></code></p>
</dd>
</dl>
</dd></dl>
</section>
<section id="unsigned-integer-types">
<h4>Unsigned integer types<a class="headerlink" href="#unsigned-integer-types" title="Link to this heading">#</a></h4>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.unsignedinteger">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">unsignedinteger</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.unsignedinteger" title="Link to this definition">#</a></dt>
<dd><p>Abstract base class of all unsigned integer scalar types.</p>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.ubyte">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">ubyte</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.ubyte" title="Link to this definition">#</a></dt>
<dd><p>Unsigned integer type, compatible with C <code class="docutils literal notranslate"><span class="pre">unsigned</span> <span class="pre">char</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Character code<span class="colon">:</span></dt>
<dd class="field-odd"><p><code class="docutils literal notranslate"><span class="pre">'B'</span></code></p>
</dd>
<dt class="field-even">Canonical name<span class="colon">:</span></dt>
<dd class="field-even"><p><a class="reference internal" href="#numpy.ubyte" title="numpy.ubyte"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.ubyte</span></code></a></p>
</dd>
<dt class="field-odd">Alias on this platform (Linux x86_64)<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference internal" href="#numpy.uint8" title="numpy.uint8"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.uint8</span></code></a>: 8-bit unsigned integer (<code class="docutils literal notranslate"><span class="pre">0</span></code> to <code class="docutils literal notranslate"><span class="pre">255</span></code>).</p>
</dd>
</dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.ushort">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">ushort</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.ushort" title="Link to this definition">#</a></dt>
<dd><p>Unsigned integer type, compatible with C <code class="docutils literal notranslate"><span class="pre">unsigned</span> <span class="pre">short</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Character code<span class="colon">:</span></dt>
<dd class="field-odd"><p><code class="docutils literal notranslate"><span class="pre">'H'</span></code></p>
</dd>
<dt class="field-even">Canonical name<span class="colon">:</span></dt>
<dd class="field-even"><p><a class="reference internal" href="#numpy.ushort" title="numpy.ushort"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.ushort</span></code></a></p>
</dd>
<dt class="field-odd">Alias on this platform (Linux x86_64)<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference internal" href="#numpy.uint16" title="numpy.uint16"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.uint16</span></code></a>: 16-bit unsigned integer (<code class="docutils literal notranslate"><span class="pre">0</span></code> to <code class="docutils literal notranslate"><span class="pre">65_535</span></code>).</p>
</dd>
</dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.uintc">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">uintc</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.uintc" title="Link to this definition">#</a></dt>
<dd><p>Unsigned integer type, compatible with C <code class="docutils literal notranslate"><span class="pre">unsigned</span> <span class="pre">int</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Character code<span class="colon">:</span></dt>
<dd class="field-odd"><p><code class="docutils literal notranslate"><span class="pre">'I'</span></code></p>
</dd>
<dt class="field-even">Canonical name<span class="colon">:</span></dt>
<dd class="field-even"><p><a class="reference internal" href="#numpy.uintc" title="numpy.uintc"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.uintc</span></code></a></p>
</dd>
<dt class="field-odd">Alias on this platform (Linux x86_64)<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference internal" href="#numpy.uint32" title="numpy.uint32"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.uint32</span></code></a>: 32-bit unsigned integer (<code class="docutils literal notranslate"><span class="pre">0</span></code> to <code class="docutils literal notranslate"><span class="pre">4_294_967_295</span></code>).</p>
</dd>
</dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.uint">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">uint</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.uint" title="Link to this definition">#</a></dt>
<dd><p>Unsigned signed integer type, 64bit on 64bit systems and 32bit on 32bit
systems.</p>
<dl class="field-list simple">
<dt class="field-odd">Character code<span class="colon">:</span></dt>
<dd class="field-odd"><p><code class="docutils literal notranslate"><span class="pre">'L'</span></code></p>
</dd>
<dt class="field-even">Canonical name<span class="colon">:</span></dt>
<dd class="field-even"><p><a class="reference internal" href="#numpy.uint" title="numpy.uint"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.uint</span></code></a></p>
</dd>
<dt class="field-odd">Alias on this platform (Linux x86_64)<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference internal" href="#numpy.uint64" title="numpy.uint64"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.uint64</span></code></a>: 64-bit unsigned integer (<code class="docutils literal notranslate"><span class="pre">0</span></code> to <code class="docutils literal notranslate"><span class="pre">18_446_744_073_709_551_615</span></code>).</p>
</dd>
<dt class="field-even">Alias on this platform (Linux x86_64)<span class="colon">:</span></dt>
<dd class="field-even"><p><a class="reference internal" href="#numpy.uintp" title="numpy.uintp"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.uintp</span></code></a>: Unsigned integer large enough to fit pointer, compatible with C <code class="docutils literal notranslate"><span class="pre">uintptr_t</span></code>.</p>
</dd>
</dl>
</dd></dl>
<dl class="py attribute">
<dt class="sig sig-object py" id="numpy.ulong">
<span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">ulong</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.ulong" title="Link to this definition">#</a></dt>
<dd><p>alias of <a class="reference internal" href="#numpy.uint" title="numpy.uint"><code class="xref py py-class docutils literal notranslate"><span class="pre">uint</span></code></a></p>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.ulonglong">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">ulonglong</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.ulonglong" title="Link to this definition">#</a></dt>
<dd><p>Signed integer type, compatible with C <code class="docutils literal notranslate"><span class="pre">unsigned</span> <span class="pre">long</span> <span class="pre">long</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Character code<span class="colon">:</span></dt>
<dd class="field-odd"><p><code class="docutils literal notranslate"><span class="pre">'Q'</span></code></p>
</dd>
</dl>
</dd></dl>
</section>
</section>
<section id="inexact-types">
<h3>Inexact types<a class="headerlink" href="#inexact-types" title="Link to this heading">#</a></h3>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.inexact">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">inexact</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.inexact" title="Link to this definition">#</a></dt>
<dd><p>Abstract base class of all numeric scalar types with a (potentially)
inexact representation of the values in its range, such as
floating-point numbers.</p>
</dd></dl>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>Inexact scalars are printed using the fewest decimal digits needed to
distinguish their value from other values of the same datatype,
by judicious rounding. See the <code class="docutils literal notranslate"><span class="pre">unique</span></code> parameter of
<a class="reference internal" href="generated/numpy.format_float_positional.html#numpy.format_float_positional" title="numpy.format_float_positional"><code class="xref py py-obj docutils literal notranslate"><span class="pre">format_float_positional</span></code></a> and <a class="reference internal" href="generated/numpy.format_float_scientific.html#numpy.format_float_scientific" title="numpy.format_float_scientific"><code class="xref py py-obj docutils literal notranslate"><span class="pre">format_float_scientific</span></code></a>.</p>
<p>This means that variables with equal binary values but whose datatypes are of
different precisions may display differently:</p>
<div class="try_examples_outer_container docutils container" id="9c21b858-c20b-4e5c-a851-ea09ea6b7cd6">
<div class="try_examples_button_container"><button class="try_examples_button" onclick="window.tryExamplesShowIframe('9c21b858-c20b-4e5c-a851-ea09ea6b7cd6','9564e546-8730-4696-8711-4c1b4a4c727d','7265387f-367a-40d1-bcd4-8cc7192c9686','../lite/tree/../notebooks/index.html?path=bcca2250_4323_4447_af6d_a2ebf39cff95.ipynb','None')">Try it in your browser!</button></div><div class="try_examples_content docutils container">
<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>
</pre></div>
</div>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">f16</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">float16</span><span class="p">(</span><span class="s2">"0.1"</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">f32</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">(</span><span class="n">f16</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">f64</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">float64</span><span class="p">(</span><span class="n">f32</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">f16</span> <span class="o">==</span> <span class="n">f32</span> <span class="o">==</span> <span class="n">f64</span>
<span class="go">True</span>
<span class="gp">>>> </span><span class="n">f16</span><span class="p">,</span> <span class="n">f32</span><span class="p">,</span> <span class="n">f64</span>
<span class="go">(0.1, 0.099975586, 0.0999755859375)</span>
</pre></div>
</div>
<p>Note that none of these floats hold the exact value <span class="math notranslate nohighlight">\(\frac{1}{10}\)</span>;
<code class="docutils literal notranslate"><span class="pre">f16</span></code> prints as <code class="docutils literal notranslate"><span class="pre">0.1</span></code> because it is as close to that value as possible,
whereas the other types do not as they have more precision and therefore have
closer values.</p>
<p>Conversely, floating-point scalars of different precisions which approximate
the same decimal value may compare unequal despite printing identically:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">f16</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">float16</span><span class="p">(</span><span class="s2">"0.1"</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">f32</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">float32</span><span class="p">(</span><span class="s2">"0.1"</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">f64</span> <span class="o">=</span> <span class="n">np</span><span class="o">.</span><span class="n">float64</span><span class="p">(</span><span class="s2">"0.1"</span><span class="p">)</span>
<span class="gp">>>> </span><span class="n">f16</span> <span class="o">==</span> <span class="n">f32</span> <span class="o">==</span> <span class="n">f64</span>
<span class="go">False</span>
<span class="gp">>>> </span><span class="n">f16</span><span class="p">,</span> <span class="n">f32</span><span class="p">,</span> <span class="n">f64</span>
<span class="go">(0.1, 0.1, 0.1)</span>
</pre></div>
</div>
</div>
</div>
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<section id="floating-point-types">
<h4>Floating-point types<a class="headerlink" href="#floating-point-types" title="Link to this heading">#</a></h4>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.floating">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">floating</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.floating" title="Link to this definition">#</a></dt>
<dd><p>Abstract base class of all floating-point scalar types.</p>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.half">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">half</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.half" title="Link to this definition">#</a></dt>
<dd><p>Half-precision floating-point number type.</p>
<dl class="field-list simple">
<dt class="field-odd">Character code<span class="colon">:</span></dt>
<dd class="field-odd"><p><code class="docutils literal notranslate"><span class="pre">'e'</span></code></p>
</dd>
<dt class="field-even">Canonical name<span class="colon">:</span></dt>
<dd class="field-even"><p><a class="reference internal" href="#numpy.half" title="numpy.half"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.half</span></code></a></p>
</dd>
<dt class="field-odd">Alias on this platform (Linux x86_64)<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference internal" href="#numpy.float16" title="numpy.float16"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.float16</span></code></a>: 16-bit-precision floating-point number type: sign bit, 5 bits exponent, 10 bits mantissa.</p>
</dd>
</dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.single">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">single</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.single" title="Link to this definition">#</a></dt>
<dd><p>Single-precision floating-point number type, compatible with C <code class="docutils literal notranslate"><span class="pre">float</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Character code<span class="colon">:</span></dt>
<dd class="field-odd"><p><code class="docutils literal notranslate"><span class="pre">'f'</span></code></p>
</dd>
<dt class="field-even">Canonical name<span class="colon">:</span></dt>
<dd class="field-even"><p><a class="reference internal" href="#numpy.single" title="numpy.single"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.single</span></code></a></p>
</dd>
<dt class="field-odd">Alias on this platform (Linux x86_64)<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference internal" href="#numpy.float32" title="numpy.float32"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.float32</span></code></a>: 32-bit-precision floating-point number type: sign bit, 8 bits exponent, 23 bits mantissa.</p>
</dd>
</dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.double">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">double</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">x</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">0</span></span></em>, <em class="sig-param"><span class="o"><span class="pre">/</span></span></em><span class="sig-paren">)</span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.double" title="Link to this definition">#</a></dt>
<dd><p>Double-precision floating-point number type, compatible with Python
<a class="reference external" href="https://docs.python.org/3/library/functions.html#float" title="(in Python v3.13)"><code class="xref py py-class docutils literal notranslate"><span class="pre">float</span></code></a> and C <code class="docutils literal notranslate"><span class="pre">double</span></code>.</p>
<dl class="field-list simple">
<dt class="field-odd">Character code<span class="colon">:</span></dt>
<dd class="field-odd"><p><code class="docutils literal notranslate"><span class="pre">'d'</span></code></p>
</dd>
<dt class="field-even">Canonical name<span class="colon">:</span></dt>
<dd class="field-even"><p><a class="reference internal" href="#numpy.double" title="numpy.double"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.double</span></code></a></p>
</dd>
<dt class="field-odd">Alias on this platform (Linux x86_64)<span class="colon">:</span></dt>
<dd class="field-odd"><p><a class="reference internal" href="#numpy.float64" title="numpy.float64"><code class="xref py py-obj docutils literal notranslate"><span class="pre">numpy.float64</span></code></a>: 64-bit precision floating-point number type: sign bit, 11 bits exponent, 52 bits mantissa.</p>
</dd>
</dl>
</dd></dl>
<dl class="py class">
<dt class="sig sig-object py" id="numpy.longdouble">
<em class="property"><span class="pre">class</span><span class="w"> </span></em><span class="sig-prename descclassname"><span class="pre">numpy.</span></span><span class="sig-name descname"><span class="pre">longdouble</span></span><a class="reference external" href="https://github.com/numpy/numpy/blob/main/numpy/_core/src/multiarray/scalartypes.c.src"><span class="viewcode-link"><span class="pre">[source]</span></span></a><a class="headerlink" href="#numpy.longdouble" title="Link to this definition">#</a></dt>
<dd><p>Extended-precision floating-point number type, compatible with C
<code class="docutils literal notranslate"><span class="pre">long</span> <span class="pre">double</span></code> but not necessarily with IEEE 754 quadruple-precision.</p>
<dl class="field-list simple">