From 1f057ed1fe1588e3a6f65e6b7681a297632ee908 Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?Jure=20=C5=A0orn?= <sornjure@gmail.com>
Date: Sun, 25 Dec 2022 02:17:12 +0100
Subject: [PATCH] NumPy

---
 README.md  | 4 ++--
 index.html | 4 ++--
 2 files changed, 4 insertions(+), 4 deletions(-)

diff --git a/README.md b/README.md
index 95a1a71..2b797e8 100644
--- a/README.md
+++ b/README.md
@@ -2650,8 +2650,8 @@ import numpy as np
 ```
 
 ```python
-<array> = <array>.sum/min/mean/var/std(axis)            # Passed dimension gets aggregated.
-<array> = <array>.argmin(axis)                          # Returns indexes of smallest elements.
+<array> = <array>.sum/min/mean/var/std([axis])          # Passed dimension gets aggregated.
+<array> = <array>.argmin([axis])                        # Returns indexes of smallest elements.
 <array> = np.apply_along_axis(<func>, axis, <array>)    # Func can return a scalar or array.
 ```
 
diff --git a/index.html b/index.html
index 94621da..f8dd7b7 100644
--- a/index.html
+++ b/index.html
@@ -2164,8 +2164,8 @@ drawer = cg.output.GraphvizOutput(output_file=filename)
 &lt;array&gt; = &lt;array&gt;.flatten()                             <span class="hljs-comment"># Collapses array into one dimension.</span>
 &lt;view&gt;  = &lt;array&gt;.squeeze()                             <span class="hljs-comment"># Removes dimensions of length one.</span>
 </code></pre>
-<pre><code class="python language-python hljs">&lt;array&gt; = &lt;array&gt;.sum/min/mean/var/std(axis)            <span class="hljs-comment"># Passed dimension gets aggregated.</span>
-&lt;array&gt; = &lt;array&gt;.argmin(axis)                          <span class="hljs-comment"># Returns indexes of smallest elements.</span>
+<pre><code class="python language-python hljs">&lt;array&gt; = &lt;array&gt;.sum/min/mean/var/std([axis])          <span class="hljs-comment"># Passed dimension gets aggregated.</span>
+&lt;array&gt; = &lt;array&gt;.argmin([axis])                        <span class="hljs-comment"># Returns indexes of smallest elements.</span>
 &lt;array&gt; = np.apply_along_axis(&lt;func&gt;, axis, &lt;array&gt;)    <span class="hljs-comment"># Func can return a scalar or array.</span>
 </code></pre>
 <ul>