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<section id="numpy-random-choice">
<h1>numpy.random.choice<a class="headerlink" href="#numpy-random-choice" title="Link to this heading">#</a></h1>
<dl class="py function">
<dt class="sig sig-object py" id="numpy.random.choice">
<span class="sig-prename descclassname"><span class="pre">random.</span></span><span class="sig-name descname"><span class="pre">choice</span></span><span class="sig-paren">(</span><em class="sig-param"><span class="n"><span class="pre">a</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">size</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">replace</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">True</span></span></em>, <em class="sig-param"><span class="n"><span class="pre">p</span></span><span class="o"><span class="pre">=</span></span><span class="default_value"><span class="pre">None</span></span></em><span class="sig-paren">)</span><a class="headerlink" href="#numpy.random.choice" title="Link to this definition">#</a></dt>
<dd><p>Generates a random sample from a given 1-D array</p>
<div class="admonition note">
<p class="admonition-title">Note</p>
<p>New code should use the <a class="reference internal" href="numpy.random.Generator.choice.html#numpy.random.Generator.choice" title="numpy.random.Generator.choice"><code class="xref py py-obj docutils literal notranslate"><span class="pre">choice</span></code></a>
method of a <a class="reference internal" href="../generator.html#numpy.random.Generator" title="numpy.random.Generator"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Generator</span></code></a> instance instead;
please see the <a class="reference internal" href="../index.html#random-quick-start"><span class="std std-ref">Quick start</span></a>.</p>
</div>
<div class="admonition warning">
<p class="admonition-title">Warning</p>
<p>This function uses the C-long dtype, which is 32bit on windows
and otherwise 64bit on 64bit platforms (and 32bit on 32bit ones).
Since NumPy 2.0, NumPy’s default integer is 32bit on 32bit platforms
and 64bit on 64bit platforms.</p>
</div>
<dl class="field-list simple">
<dt class="field-odd">Parameters<span class="colon">:</span></dt>
<dd class="field-odd"><dl class="simple">
<dt><strong>a</strong><span class="classifier">1-D array-like or int</span></dt><dd><p>If an ndarray, a random sample is generated from its elements.
If an int, the random sample is generated as if it were <code class="docutils literal notranslate"><span class="pre">np.arange(a)</span></code></p>
</dd>
<dt><strong>size</strong><span class="classifier">int or tuple of ints, optional</span></dt><dd><p>Output shape. If the given shape is, e.g., <code class="docutils literal notranslate"><span class="pre">(m,</span> <span class="pre">n,</span> <span class="pre">k)</span></code>, then
<code class="docutils literal notranslate"><span class="pre">m</span> <span class="pre">*</span> <span class="pre">n</span> <span class="pre">*</span> <span class="pre">k</span></code> samples are drawn. Default is None, in which case a
single value is returned.</p>
</dd>
<dt><strong>replace</strong><span class="classifier">boolean, optional</span></dt><dd><p>Whether the sample is with or without replacement. Default is True,
meaning that a value of <code class="docutils literal notranslate"><span class="pre">a</span></code> can be selected multiple times.</p>
</dd>
<dt><strong>p</strong><span class="classifier">1-D array-like, optional</span></dt><dd><p>The probabilities associated with each entry in a.
If not given, the sample assumes a uniform distribution over all
entries in <code class="docutils literal notranslate"><span class="pre">a</span></code>.</p>
</dd>
</dl>
</dd>
<dt class="field-even">Returns<span class="colon">:</span></dt>
<dd class="field-even"><dl class="simple">
<dt><strong>samples</strong><span class="classifier">single item or ndarray</span></dt><dd><p>The generated random samples</p>
</dd>
</dl>
</dd>
<dt class="field-odd">Raises<span class="colon">:</span></dt>
<dd class="field-odd"><dl class="simple">
<dt>ValueError</dt><dd><p>If a is an int and less than zero, if a or p are not 1-dimensional,
if a is an array-like of size 0, if p is not a vector of
probabilities, if a and p have different lengths, or if
replace=False and the sample size is greater than the population
size</p>
</dd>
</dl>
</dd>
</dl>
<div class="admonition seealso">
<p class="admonition-title">See also</p>
<dl class="simple">
<dt><a class="reference internal" href="numpy.random.randint.html#numpy.random.randint" title="numpy.random.randint"><code class="xref py py-obj docutils literal notranslate"><span class="pre">randint</span></code></a>, <a class="reference internal" href="numpy.random.shuffle.html#numpy.random.shuffle" title="numpy.random.shuffle"><code class="xref py py-obj docutils literal notranslate"><span class="pre">shuffle</span></code></a>, <a class="reference internal" href="numpy.random.permutation.html#numpy.random.permutation" title="numpy.random.permutation"><code class="xref py py-obj docutils literal notranslate"><span class="pre">permutation</span></code></a></dt><dd></dd>
<dt><a class="reference internal" href="numpy.random.Generator.choice.html#numpy.random.Generator.choice" title="numpy.random.Generator.choice"><code class="xref py py-obj docutils literal notranslate"><span class="pre">random.Generator.choice</span></code></a></dt><dd><p>which should be used in new code</p>
</dd>
</dl>
</div>
<p class="rubric">Notes</p>
<p>Setting user-specified probabilities through <code class="docutils literal notranslate"><span class="pre">p</span></code> uses a more general but less
efficient sampler than the default. The general sampler produces a different sample
than the optimized sampler even if each element of <code class="docutils literal notranslate"><span class="pre">p</span></code> is 1 / len(a).</p>
<p>Sampling random rows from a 2-D array is not possible with this function,
but is possible with <a class="reference internal" href="numpy.random.Generator.choice.html#numpy.random.Generator.choice" title="numpy.random.Generator.choice"><code class="xref py py-obj docutils literal notranslate"><span class="pre">Generator.choice</span></code></a> through its <code class="docutils literal notranslate"><span class="pre">axis</span></code> keyword.</p>
<p class="rubric">Examples</p>
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<p>Generate a uniform random sample from np.arange(5) of size 3:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">choice</span><span class="p">(</span><span class="mi">5</span><span class="p">,</span> <span class="mi">3</span><span class="p">)</span>
<span class="go">array([0, 3, 4]) # random</span>
<span class="gp">>>> </span><span class="c1">#This is equivalent to np.random.randint(0,5,3)</span>
</pre></div>
</div>
<p>Generate a non-uniform random sample from np.arange(5) of size 3:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">choice</span><span class="p">(</span><span class="mi">5</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="p">[</span><span class="mf">0.1</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mf">0.3</span><span class="p">,</span> <span class="mf">0.6</span><span class="p">,</span> <span class="mi">0</span><span class="p">])</span>
<span class="go">array([3, 3, 0]) # random</span>
</pre></div>
</div>
<p>Generate a uniform random sample from np.arange(5) of size 3 without
replacement:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">choice</span><span class="p">(</span><span class="mi">5</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">replace</span><span class="o">=</span><span class="kc">False</span><span class="p">)</span>
<span class="go">array([3,1,0]) # random</span>
<span class="gp">>>> </span><span class="c1">#This is equivalent to np.random.permutation(np.arange(5))[:3]</span>
</pre></div>
</div>
<p>Generate a non-uniform random sample from np.arange(5) of size
3 without replacement:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">choice</span><span class="p">(</span><span class="mi">5</span><span class="p">,</span> <span class="mi">3</span><span class="p">,</span> <span class="n">replace</span><span class="o">=</span><span class="kc">False</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="p">[</span><span class="mf">0.1</span><span class="p">,</span> <span class="mi">0</span><span class="p">,</span> <span class="mf">0.3</span><span class="p">,</span> <span class="mf">0.6</span><span class="p">,</span> <span class="mi">0</span><span class="p">])</span>
<span class="go">array([2, 3, 0]) # random</span>
</pre></div>
</div>
<p>Any of the above can be repeated with an arbitrary array-like
instead of just integers. For instance:</p>
<div class="doctest highlight-default notranslate"><div class="highlight"><pre><span></span><span class="gp">>>> </span><span class="n">aa_milne_arr</span> <span class="o">=</span> <span class="p">[</span><span class="s1">'pooh'</span><span class="p">,</span> <span class="s1">'rabbit'</span><span class="p">,</span> <span class="s1">'piglet'</span><span class="p">,</span> <span class="s1">'Christopher'</span><span class="p">]</span>
<span class="gp">>>> </span><span class="n">np</span><span class="o">.</span><span class="n">random</span><span class="o">.</span><span class="n">choice</span><span class="p">(</span><span class="n">aa_milne_arr</span><span class="p">,</span> <span class="mi">5</span><span class="p">,</span> <span class="n">p</span><span class="o">=</span><span class="p">[</span><span class="mf">0.5</span><span class="p">,</span> <span class="mf">0.1</span><span class="p">,</span> <span class="mf">0.1</span><span class="p">,</span> <span class="mf">0.3</span><span class="p">])</span>
<span class="go">array(['pooh', 'pooh', 'pooh', 'Christopher', 'piglet'], # random</span>
<span class="go"> dtype='<U11')</span>
</pre></div>
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