deploy: 51674d6

Author: pryn-kb

_sources/docs/pandas/03_Pandas_subsets.ipynb

@@ -478,7 +478,7 @@ <h2>Code blocks and outputs<a class="headerlink" href="#code-blocks-and-outputs"
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;contextlib.ExitStack at 0x7fadd88b0350&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;contextlib.ExitStack at 0x7f1630b2f6e0&gt;
 </pre></div>
 </div>
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_sources/docs/pandas/03_pandas_subsets.ipynb

@@ -425,6 +425,7 @@ <h2> Contents </h2>
 <li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#combining-loc-and-iloc">Combining <code class="docutils literal notranslate"><span class="pre">loc</span></code> and <code class="docutils literal notranslate"><span class="pre">iloc</span></code></a></li>
 </ul>
 </li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#exercise"><i class="fa-solid fa-pencil"></i> Exercise</a></li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#key-points">Key points</a></li>
 </ul>
             </nav>
@@ -2287,6 +2288,40 @@ <h3>Combining <code class="docutils literal notranslate"><span class="pre">loc</
 </div>
 </section>
 </section>
+<section id="exercise">
+<h2><i class="fa-solid fa-pencil"></i> Exercise<a class="headerlink" href="#exercise" title="Link to this heading">#</a></h2>
+<ol class="arabic simple">
+<li><p>What is the number of matching records from:</p></li>
+</ol>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">titanic</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:</span><span class="mi">100</span><span class="p">]</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">titanic</span><span class="p">[</span><span class="s1">&#39;Age&#39;</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">35</span><span class="p">]</span>
+</pre></div>
+</div>
+<ol class="arabic simple" start="2">
+<li><p>What is the number of matching records from:</p></li>
+</ol>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">titanic</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">titanic</span><span class="p">[</span><span class="s1">&#39;Age&#39;</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">35</span><span class="p">]</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:</span><span class="mi">100</span><span class="p">]</span>
+</pre></div>
+</div>
+<ol class="arabic simple" start="3">
+<li><p>Reflect on and explain why the two statements return a different number of rows?</p></li>
+</ol>
+<div class="dropdown admonition">
+<p class="admonition-title">Solution</p>
+<p>(We can use the <code class="docutils literal notranslate"><span class="pre">len()</span></code> function to solve question 1 and 2.)</p>
+<ol class="arabic simple">
+<li><p>17 rows</p></li>
+<li><p>100 rows</p></li>
+<li><p>The two expressions differ in the <strong>order</strong> of filtering and slicing, which affects the final result:</p></li>
+</ol>
+<ul class="simple">
+<li><p><code class="docutils literal notranslate"><span class="pre">titanic.iloc[:100].loc[titanic['Age']</span> <span class="pre">&gt;</span> <span class="pre">35]</span></code><br />
+→ First selects the <strong>first 100 rows</strong>, then filters for rows where <code class="docutils literal notranslate"><span class="pre">Age</span> <span class="pre">&gt;</span> <span class="pre">35</span></code> <strong>within those 100</strong>.</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">titanic.loc[titanic['Age']</span> <span class="pre">&gt;</span> <span class="pre">35].iloc[:100]</span></code><br />
+→ First filters for <strong>all rows</strong> where <code class="docutils literal notranslate"><span class="pre">Age</span> <span class="pre">&gt;</span> <span class="pre">35</span></code>, then selects the <strong>first 100 rows</strong> from that filtered set.</p></li>
+</ul>
+<p>Thus, the main difference lies in <strong>whether you slice first or filter first</strong>, which can lead to <strong>very different subsets of data</strong>.</p>
+</div>
+</section>
 <hr class="docutils" />
 <section id="key-points">
 <h2>Key points<a class="headerlink" href="#key-points" title="Link to this heading">#</a></h2>
@@ -2385,6 +2420,7 @@ <h2>Key points<a class="headerlink" href="#key-points" title="Link to this headi
 <li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#combining-loc-and-iloc">Combining <code class="docutils literal notranslate"><span class="pre">loc</span></code> and <code class="docutils literal notranslate"><span class="pre">iloc</span></code></a></li>
 </ul>
 </li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#exercise"><i class="fa-solid fa-pencil"></i> Exercise</a></li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#key-points">Key points</a></li>
 </ul>
   </nav></div>

_to_be_deleted_later/notebooks.html

@@ -444,6 +444,7 @@ <h2> Contents </h2>
 <li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#combining-loc-and-iloc">Combining <code class="docutils literal notranslate"><span class="pre">loc</span></code> and <code class="docutils literal notranslate"><span class="pre">iloc</span></code></a></li>
 </ul>
 </li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#exercise"><i class="fa-solid fa-pencil"></i> Exercise</a></li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#key-points">Key points</a></li>
 </ul>
             </nav>
@@ -2306,6 +2307,40 @@ <h3>Combining <code class="docutils literal notranslate"><span class="pre">loc</
 </div>
 </section>
 </section>
+<section id="exercise">
+<h2><i class="fa-solid fa-pencil"></i> Exercise<a class="headerlink" href="#exercise" title="Link to this heading">#</a></h2>
+<ol class="arabic simple">
+<li><p>What is the number of matching records from:</p></li>
+</ol>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">titanic</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:</span><span class="mi">100</span><span class="p">]</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">titanic</span><span class="p">[</span><span class="s1">&#39;Age&#39;</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">35</span><span class="p">]</span>
+</pre></div>
+</div>
+<ol class="arabic simple" start="2">
+<li><p>What is the number of matching records from:</p></li>
+</ol>
+<div class="highlight-python notranslate"><div class="highlight"><pre><span></span><span class="n">titanic</span><span class="o">.</span><span class="n">loc</span><span class="p">[</span><span class="n">titanic</span><span class="p">[</span><span class="s1">&#39;Age&#39;</span><span class="p">]</span> <span class="o">&gt;</span> <span class="mi">35</span><span class="p">]</span><span class="o">.</span><span class="n">iloc</span><span class="p">[:</span><span class="mi">100</span><span class="p">]</span>
+</pre></div>
+</div>
+<ol class="arabic simple" start="3">
+<li><p>Reflect on and explain why the two statements return a different number of rows?</p></li>
+</ol>
+<div class="dropdown admonition">
+<p class="admonition-title">Solution</p>
+<p>(We can use the <code class="docutils literal notranslate"><span class="pre">len()</span></code> function to solve question 1 and 2.)</p>
+<ol class="arabic simple">
+<li><p>17 rows</p></li>
+<li><p>100 rows</p></li>
+<li><p>The two expressions differ in the <strong>order</strong> of filtering and slicing, which affects the final result:</p></li>
+</ol>
+<ul class="simple">
+<li><p><code class="docutils literal notranslate"><span class="pre">titanic.iloc[:100].loc[titanic['Age']</span> <span class="pre">&gt;</span> <span class="pre">35]</span></code><br />
+→ First selects the <strong>first 100 rows</strong>, then filters for rows where <code class="docutils literal notranslate"><span class="pre">Age</span> <span class="pre">&gt;</span> <span class="pre">35</span></code> <strong>within those 100</strong>.</p></li>
+<li><p><code class="docutils literal notranslate"><span class="pre">titanic.loc[titanic['Age']</span> <span class="pre">&gt;</span> <span class="pre">35].iloc[:100]</span></code><br />
+→ First filters for <strong>all rows</strong> where <code class="docutils literal notranslate"><span class="pre">Age</span> <span class="pre">&gt;</span> <span class="pre">35</span></code>, then selects the <strong>first 100 rows</strong> from that filtered set.</p></li>
+</ul>
+<p>Thus, the main difference lies in <strong>whether you slice first or filter first</strong>, which can lead to <strong>very different subsets of data</strong>.</p>
+</div>
+</section>
 <hr class="docutils" />
 <section id="key-points">
 <h2>Key points<a class="headerlink" href="#key-points" title="Link to this heading">#</a></h2>
@@ -2403,6 +2438,7 @@ <h2>Key points<a class="headerlink" href="#key-points" title="Link to this headi
 <li class="toc-h3 nav-item toc-entry"><a class="reference internal nav-link" href="#combining-loc-and-iloc">Combining <code class="docutils literal notranslate"><span class="pre">loc</span></code> and <code class="docutils literal notranslate"><span class="pre">iloc</span></code></a></li>
 </ul>
 </li>
+<li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#exercise"><i class="fa-solid fa-pencil"></i> Exercise</a></li>
 <li class="toc-h2 nav-item toc-entry"><a class="reference internal nav-link" href="#key-points">Key points</a></li>
 </ul>
   </nav></div>

docs/_test/vega.html

@@ -642,7 +642,7 @@ <h3>The explicit and the implicit interfaces<a class="headerlink" href="#the-exp
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-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.legend.Legend at 0x7faeac4b1130&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.legend.Legend at 0x7f69b3e66d20&gt;
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@@ -665,7 +665,7 @@ <h3>The explicit and the implicit interfaces<a class="headerlink" href="#the-exp
 </div>
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 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.legend.Legend at 0x7faeae829f70&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.legend.Legend at 0x7f69b3f23c80&gt;
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@@ -714,7 +714,7 @@ <h3>Making a helper functions<a class="headerlink" href="#making-a-helper-functi
 </div>
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 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[&lt;matplotlib.lines.Line2D at 0x7faeac409bb0&gt;]
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[&lt;matplotlib.lines.Line2D at 0x7f69b1db5be0&gt;]
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 <img alt="../../_images/be4b8c194bd74be420b45b4766c2bd2684124e5955e30308b1a60c6d70642526.png" src="../../_images/be4b8c194bd74be420b45b4766c2bd2684124e5955e30308b1a60c6d70642526.png" />
@@ -761,7 +761,7 @@ <h3>Colors<a class="headerlink" href="#colors" title="Link to this heading">#</a
 </div>
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 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.PathCollection at 0x7faeac2ca510&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.collections.PathCollection at 0x7f69b1c59b50&gt;
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 <img alt="../../_images/67108aa388b3ef345c342273e2d62593fad03232eeb46126dccf88e13dec7ca9.png" src="../../_images/67108aa388b3ef345c342273e2d62593fad03232eeb46126dccf88e13dec7ca9.png" />
@@ -791,7 +791,7 @@ <h3>Linewidths, linestyles, and markersizes<a class="headerlink" href="#linewidt
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.legend.Legend at 0x7faeac3baea0&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.legend.Legend at 0x7f69b1c727b0&gt;
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 <img alt="../../_images/30f81b0ffd312efc74103619e61c19e9543a242ae31f4da134797bd1fe7ca5b0.png" src="../../_images/30f81b0ffd312efc74103619e61c19e9543a242ae31f4da134797bd1fe7ca5b0.png" />
@@ -898,7 +898,7 @@ <h3>Legends<a class="headerlink" href="#legends" title="Link to this heading">#<
 </div>
 </div>
 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.legend.Legend at 0x7faeac12dc10&gt;
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>&lt;matplotlib.legend.Legend at 0x7f69b1c72de0&gt;
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 </div>
 <img alt="../../_images/e09ad3a7555c7fe744c15dd77c0217a5385b2ac7385278207b148323375e709c.png" src="../../_images/e09ad3a7555c7fe744c15dd77c0217a5385b2ac7385278207b148323375e709c.png" />
@@ -936,7 +936,7 @@ <h3>Scales<a class="headerlink" href="#scales" title="Link to this heading">#</a
 </div>
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 <div class="cell_output docutils container">
-<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[&lt;matplotlib.lines.Line2D at 0x7faeac02da30&gt;]
+<div class="output text_plain highlight-myst-ansi notranslate"><div class="highlight"><pre><span></span>[&lt;matplotlib.lines.Line2D at 0x7f69b19c9a60&gt;]
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 <img alt="../../_images/9b867617227a1c1ff48ff943888393786e48420237e271ae4220f24a2e3bac85.png" src="../../_images/9b867617227a1c1ff48ff943888393786e48420237e271ae4220f24a2e3bac85.png" />