Deploying to main from @ numpy/numpy.org@cda4ca9 🚀

Author: mattip

index.xml

@@ -177,15 +177,19 @@ like <a href="http://stackoverflow.com/questions/tagged/numpy">StackOverflow&
 these sites, or answer questions directly, but the volume is a little
 overwhelming!</p>
 <h3 id="stackoverflowhttpstackoverflowcomquestionstaggednumpy"><a href="http://stackoverflow.com/questions/tagged/numpy">StackOverflow</a><a class="headerlink" href="#stackoverflowhttpstackoverflowcomquestionstaggednumpy" title="Link to this heading">#</a></h3>
-&lt;p>A forum for asking usage questions, e.g. &amp;ldquo;How do I do X in NumPy?”. Please &lt;a href="https://stackoverflow.com/help/tagging">use the &lt;code>#numpy&lt;/code> tag&lt;/a>&lt;/p></description></item><item><title>History of NumPy</title><link>https://numpy.org/history/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://numpy.org/history/</guid><description>&lt;p>NumPy is a foundational Python library that provides array data structures and related fast numerical routines. When started, the library had little funding, and was written mainly by graduate students—many of them without computer science education, and often without a blessing of their advisors. To even imagine that a small group of “rogue” student programmers could upend the already well-established ecosystem of research software—backed by millions in funding and many hundreds of highly qualified engineers — was preposterous. Yet, the philosophical motivations behind a fully open tool stack, in combination with the excited, friendly community with a singular focus, have proven auspicious in the long run. Nowadays, NumPy is relied upon by scientists, engineers, and many other professionals around the world. For example, the published scripts used in the analysis of gravitational waves import NumPy, and the M87 black hole imaging project directly cites NumPy.&lt;/p></description></item><item><title>Installing NumPy</title><link>https://numpy.org/install/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://numpy.org/install/</guid><description>&lt;p>The only prerequisite for installing NumPy is Python itself. If you don&amp;rsquo;t have
+&lt;p>A forum for asking usage questions, e.g. &amp;ldquo;How do I do X in NumPy?”. Please &lt;a href="https://stackoverflow.com/help/tagging">use the &lt;code>#numpy&lt;/code> tag&lt;/a>&lt;/p></description></item><item><title>History of NumPy</title><link>https://numpy.org/history/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://numpy.org/history/</guid><description>&lt;p>NumPy is a foundational Python library that provides array data structures and related fast numerical routines. When started, the library had little funding, and was written mainly by graduate students—many of them without computer science education, and often without a blessing of their advisors. To even imagine that a small group of “rogue” student programmers could upend the already well-established ecosystem of research software—backed by millions in funding and many hundreds of highly qualified engineers — was preposterous. Yet, the philosophical motivations behind a fully open tool stack, in combination with the excited, friendly community with a singular focus, have proven auspicious in the long run. Nowadays, NumPy is relied upon by scientists, engineers, and many other professionals around the world. For example, the published scripts used in the analysis of gravitational waves import NumPy, and the M87 black hole imaging project directly cites NumPy.&lt;/p></description></item><item><title>Installing NumPy</title><link>https://numpy.org/install/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://numpy.org/install/</guid><description>&lt;div class="admonition tip">
+ &lt;div class="admonition-title"> Tip&lt;/div>
+ &lt;p>
+ This page assumes you are comfortable using a terminal and are familiar with package managers.
+The only prerequisite for installing NumPy is Python itself. If you don&amp;rsquo;t have
 Python yet and want the simplest way to get started, we recommend you use the
 &lt;a href="https://www.anaconda.com/download">Anaconda Distribution&lt;/a> - it includes
 Python, NumPy, and many other commonly used packages for scientific computing
-and data science.&lt;/p>
-&lt;p>NumPy can be installed with &lt;code>conda&lt;/code>, with &lt;code>pip&lt;/code>, with a package manager on
-macOS and Linux, or &lt;a href="https://numpy.org/devdocs/building">from source&lt;/a>.
-For more detailed instructions, consult our &lt;a href="https://numpy.org/install/#python-numpy-install-guide">Python and NumPy
-installation guide&lt;/a> below.&lt;/p></description></item><item><title>Learn</title><link>https://numpy.org/learn/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://numpy.org/learn/</guid><description>&lt;p>For the &lt;strong>official NumPy documentation&lt;/strong> visit &lt;a href="https://numpy.org/doc/stable">numpy.org/doc/stable&lt;/a>.&lt;/p>
+and data science.
+ &lt;/p>
+&lt;/div>
+
+&lt;p>The recommended method of installing NumPy depends on your preferred workflow. Below, we break down the installation methods into the following categories:&lt;/p></description></item><item><title>Learn</title><link>https://numpy.org/learn/</link><pubDate>Mon, 01 Jan 0001 00:00:00 +0000</pubDate><guid>https://numpy.org/learn/</guid><description>&lt;p>For the &lt;strong>official NumPy documentation&lt;/strong> visit &lt;a href="https://numpy.org/doc/stable">numpy.org/doc/stable&lt;/a>.&lt;/p>
 &lt;hr>
 &lt;p>Below is a curated collection of educational resources, both for self-learning and teaching others, developed by NumPy contributors and vetted by the community.&lt;/p>
 &lt;h2 id="beginners">Beginners&lt;a class="headerlink" href="#beginners" title="Link to this heading">#&lt;/a>&lt;/h2>