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prerelease 1.8.1

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dr. M.S. (Matthijs) Berends
2022-03-14 16:43:15 +01:00
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docs/articles/PCA.html
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@ -44,11 +44,7 @@
</button>
<span class="navbar-brand">
<a class="navbar-link" href="../index.html">AMR (for R)</a>
<<<<<<< HEAD
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.1</span>
=======
<span class="version label label-default" data-toggle="tooltip" data-placement="bottom" title="Released version">1.8.0.9005</span>
>>>>>>> 8c9feea087f568fd4abbdb325140d1d628e6856f
</span>
</div>
@ -189,7 +185,7 @@
</header><script src="PCA_files/accessible-code-block-0.0.1/empty-anchor.js"></script><div class="row">
</header><div class="row">
<div class="col-md-9 contents">
<div class="page-header toc-ignore">
<h1 data-toc-skip>How to conduct principal component analysis
@ -203,12 +199,8 @@
<<<<<<< HEAD
<p><strong>NOTE: This page will be updated soon, as the pca() function
is currently being developed.</strong></p>
=======
<p><strong>NOTE: This page will be updated soon, as the pca() function is currently being developed.</strong></p>
>>>>>>> 8c9feea087f568fd4abbdb325140d1d628e6856f
<div class="section level2">
<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
</h2>
@ -216,16 +208,12 @@ is currently being developed.</strong></p>
<div class="section level2">
<h2 id="transforming">Transforming<a class="anchor" aria-label="anchor" href="#transforming"></a>
</h2>
<<<<<<< HEAD
<p>For PCA, we need to transform our AMR data first. This is what the
<code>example_isolates</code> data set in this package looks like:</p>
=======
<p>For PCA, we need to transform our AMR data first. This is what the <code>example_isolates</code> data set in this package looks like:</p>
>>>>>>> 8c9feea087f568fd4abbdb325140d1d628e6856f
<div class="sourceCode" id="cb1"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://msberends.github.io/AMR/">AMR</a></span><span class="op">)</span>
<span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">library</a></span><span class="op">(</span><span class="va"><a href="https://dplyr.tidyverse.org" class="external-link">dplyr</a></span><span class="op">)</span>
<span class="fu"><a href="https://dplyr.tidyverse.org/reference/glimpse.html" class="external-link">glimpse</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span>
<span class="fu"><a href="https://pillar.r-lib.org/reference/glimpse.html" class="external-link">glimpse</a></span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span>
<span class="co"># Rows: 2,000</span>
<span class="co"># Columns: 49</span>
<span class="co"># $ date <span style="color: #949494; font-style: italic;">&lt;date&gt;</span> 2002-01-02, 2002-01-03, 2002-01-07, 2002-01-07, 2002-…</span>
@ -302,13 +290,9 @@ per taxonomic order and genus:</p>
<div class="section level2">
<h2 id="perform-principal-component-analysis">Perform principal component analysis<a class="anchor" aria-label="anchor" href="#perform-principal-component-analysis"></a>
</h2>
<<<<<<< HEAD
<p>The new <code><a href="../reference/pca.html">pca()</a></code> function will automatically filter on rows
that contain numeric values in all selected variables, so we now only
need to do:</p>
=======
<p>The new <code><a href="../reference/pca.html">pca()</a></code> function will automatically filter on rows that contain numeric values in all selected variables, so we now only need to do:</p>
>>>>>>> 8c9feea087f568fd4abbdb325140d1d628e6856f
<div class="sourceCode" id="cb3"><pre class="downlit sourceCode r">
<code class="sourceCode R"><span class="va">pca_result</span> <span class="op">&lt;-</span> <span class="fu"><a href="../reference/pca.html">pca</a></span><span class="op">(</span><span class="va">resistance_data</span><span class="op">)</span>
<span class="co"># ℹ Columns selected for PCA: "AMC", "CAZ", "CTX", "CXM", "GEN", "SXT", "TMP"</span>
@ -370,12 +354,8 @@ Erwin E. A. Hassing.</p>
<div class="pkgdown">
<p></p>
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<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a>
2.0.2.</p>
=======
<p>Site built with <a href="https://pkgdown.r-lib.org/" class="external-link">pkgdown</a> 2.0.2.</p>
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</div>
</footer>