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@ -32,7 +32,7 @@
<a class="navbar-brand me-2" href="https://msberends.github.io/AMR/index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9215</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9216</small>
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9215</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9216</small>
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@ -31,7 +31,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9215</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9216</small>
<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@ -93,7 +93,7 @@
website update since they are based on randomly created values and the
page was written in <a href="https://rmarkdown.rstudio.com/" class="external-link">R
Markdown</a>. However, the methodology remains unchanged. This page was
generated on 16 March 2025.</p>
generated on 17 March 2025.</p>
<div class="section level2">
<h2 id="introduction">Introduction<a class="anchor" aria-label="anchor" href="#introduction"></a>
</h2>
@ -149,21 +149,21 @@ make the structure of your data generally look like this:</p>
</tr></thead>
<tbody>
<tr class="odd">
<td align="center">2025-03-16</td>
<td align="center">2025-03-17</td>
<td align="center">abcd</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">S</td>
</tr>
<tr class="even">
<td align="center">2025-03-16</td>
<td align="center">2025-03-17</td>
<td align="center">abcd</td>
<td align="center">Escherichia coli</td>
<td align="center">S</td>
<td align="center">R</td>
</tr>
<tr class="odd">
<td align="center">2025-03-16</td>
<td align="center">2025-03-17</td>
<td align="center">efgh</td>
<td align="center">Escherichia coli</td>
<td align="center">R</td>

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@ -31,7 +31,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9215</small>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9216</small>
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@ -104,27 +104,40 @@ need to have R installed, Python users can now easily work with AMR data
directly through Python code.</p>
</div>
<div class="section level2">
<h2 id="install">Install<a class="anchor" aria-label="anchor" href="#install"></a>
<h2 id="prerequisites">Prerequisites<a class="anchor" aria-label="anchor" href="#prerequisites"></a>
</h2>
<p>This package was only tested with <a href="https://docs.python.org/3/library/venv.html" class="external-link"><code>venv</code></a>.
You can set up such a virtual environment by running:</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb1-1"><a href="#cb1-1" tabindex="-1"></a><span class="co"># for linux and macOS:</span></span>
<span id="cb1-2"><a href="#cb1-2" tabindex="-1"></a>python <span class="op">-</span>m venv <span class="op">/</span>path<span class="op">/</span>to<span class="op">/</span>new<span class="op">/</span>virtual<span class="op">/</span>environment</span>
<span id="cb1-3"><a href="#cb1-3" tabindex="-1"></a><span class="co"># for Windows:</span></span>
<span id="cb1-4"><a href="#cb1-4" tabindex="-1"></a>python <span class="op">-</span>m venv C:\path\to\new\virtual\environment</span></code></pre></div>
<p>Then you can <a href="https://docs.python.org/3/library/venv.html#how-venvs-work" class="external-link">activate
the environment</a>, after the which the virtual environment is ready to
work with.</p>
</div>
<div class="section level2">
<h2 id="install-amr">Install AMR<a class="anchor" aria-label="anchor" href="#install-amr"></a>
</h2>
<ol style="list-style-type: decimal">
<li>
<p>Since the Python package is available on the official <a href="https://pypi.org/project/AMR/" class="external-link">Python Package Index</a>, you can
just run:</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode bash"><code class="sourceCode bash"><span id="cb1-1"><a href="#cb1-1" tabindex="-1"></a><span class="ex">pip</span> install AMR</span></code></pre></div>
<div class="sourceCode" id="cb2"><pre class="sourceCode bash"><code class="sourceCode bash"><span id="cb2-1"><a href="#cb2-1" tabindex="-1"></a><span class="ex">pip</span> install AMR</span></code></pre></div>
</li>
<li>
<p>Make sure you have R installed. There is <strong>no need to
install the <code>AMR</code> R package</strong>, as it will be installed
automatically.</p>
<p>For Linux:</p>
<div class="sourceCode" id="cb2"><pre class="sourceCode bash"><code class="sourceCode bash"><span id="cb2-1"><a href="#cb2-1" tabindex="-1"></a><span class="co"># Ubuntu / Debian</span></span>
<span id="cb2-2"><a href="#cb2-2" tabindex="-1"></a><span class="fu">sudo</span> apt install r-base</span>
<span id="cb2-3"><a href="#cb2-3" tabindex="-1"></a><span class="co"># Fedora:</span></span>
<span id="cb2-4"><a href="#cb2-4" tabindex="-1"></a><span class="fu">sudo</span> dnf install R</span>
<span id="cb2-5"><a href="#cb2-5" tabindex="-1"></a><span class="co"># CentOS/RHEL</span></span>
<span id="cb2-6"><a href="#cb2-6" tabindex="-1"></a><span class="fu">sudo</span> yum install R</span></code></pre></div>
<div class="sourceCode" id="cb3"><pre class="sourceCode bash"><code class="sourceCode bash"><span id="cb3-1"><a href="#cb3-1" tabindex="-1"></a><span class="co"># Ubuntu / Debian</span></span>
<span id="cb3-2"><a href="#cb3-2" tabindex="-1"></a><span class="fu">sudo</span> apt install r-base</span>
<span id="cb3-3"><a href="#cb3-3" tabindex="-1"></a><span class="co"># Fedora:</span></span>
<span id="cb3-4"><a href="#cb3-4" tabindex="-1"></a><span class="fu">sudo</span> dnf install R</span>
<span id="cb3-5"><a href="#cb3-5" tabindex="-1"></a><span class="co"># CentOS/RHEL</span></span>
<span id="cb3-6"><a href="#cb3-6" tabindex="-1"></a><span class="fu">sudo</span> yum install R</span></code></pre></div>
<p>For macOS (using <a href="https://brew.sh" class="external-link">Homebrew</a>):</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode bash"><code class="sourceCode bash"><span id="cb3-1"><a href="#cb3-1" tabindex="-1"></a><span class="ex">brew</span> install r</span></code></pre></div>
<div class="sourceCode" id="cb4"><pre class="sourceCode bash"><code class="sourceCode bash"><span id="cb4-1"><a href="#cb4-1" tabindex="-1"></a><span class="ex">brew</span> install r</span></code></pre></div>
<p>For Windows, visit the <a href="https://cran.r-project.org" class="external-link">CRAN
download page</a> to download and install R.</p>
</li>
@ -138,22 +151,22 @@ download page</a> to download and install R.</p>
</h3>
<p>Here’s an example that demonstrates how to clean microorganism and
drug names using the <code>AMR</code> Python package:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb4-1"><a href="#cb4-1" tabindex="-1"></a><span class="im">import</span> pandas <span class="im">as</span> pd</span>
<span id="cb4-2"><a href="#cb4-2" tabindex="-1"></a><span class="im">import</span> AMR</span>
<span id="cb4-3"><a href="#cb4-3" tabindex="-1"></a></span>
<span id="cb4-4"><a href="#cb4-4" tabindex="-1"></a><span class="co"># Sample data</span></span>
<span id="cb4-5"><a href="#cb4-5" tabindex="-1"></a>data <span class="op">=</span> {</span>
<span id="cb4-6"><a href="#cb4-6" tabindex="-1"></a> <span class="st">"MOs"</span>: [<span class="st">'E. coli'</span>, <span class="st">'ESCCOL'</span>, <span class="st">'esco'</span>, <span class="st">'Esche coli'</span>],</span>
<span id="cb4-7"><a href="#cb4-7" tabindex="-1"></a> <span class="st">"Drug"</span>: [<span class="st">'Cipro'</span>, <span class="st">'CIP'</span>, <span class="st">'J01MA02'</span>, <span class="st">'Ciproxin'</span>]</span>
<span id="cb4-8"><a href="#cb4-8" tabindex="-1"></a>}</span>
<span id="cb4-9"><a href="#cb4-9" tabindex="-1"></a>df <span class="op">=</span> pd.DataFrame(data)</span>
<span id="cb4-10"><a href="#cb4-10" tabindex="-1"></a></span>
<span id="cb4-11"><a href="#cb4-11" tabindex="-1"></a><span class="co"># Use AMR functions to clean microorganism and drug names</span></span>
<span id="cb4-12"><a href="#cb4-12" tabindex="-1"></a>df[<span class="st">'MO_clean'</span>] <span class="op">=</span> AMR.mo_name(df[<span class="st">'MOs'</span>])</span>
<span id="cb4-13"><a href="#cb4-13" tabindex="-1"></a>df[<span class="st">'Drug_clean'</span>] <span class="op">=</span> AMR.ab_name(df[<span class="st">'Drug'</span>])</span>
<span id="cb4-14"><a href="#cb4-14" tabindex="-1"></a></span>
<span id="cb4-15"><a href="#cb4-15" tabindex="-1"></a><span class="co"># Display the results</span></span>
<span id="cb4-16"><a href="#cb4-16" tabindex="-1"></a><span class="bu">print</span>(df)</span></code></pre></div>
<div class="sourceCode" id="cb5"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb5-1"><a href="#cb5-1" tabindex="-1"></a><span class="im">import</span> pandas <span class="im">as</span> pd</span>
<span id="cb5-2"><a href="#cb5-2" tabindex="-1"></a><span class="im">import</span> AMR</span>
<span id="cb5-3"><a href="#cb5-3" tabindex="-1"></a></span>
<span id="cb5-4"><a href="#cb5-4" tabindex="-1"></a><span class="co"># Sample data</span></span>
<span id="cb5-5"><a href="#cb5-5" tabindex="-1"></a>data <span class="op">=</span> {</span>
<span id="cb5-6"><a href="#cb5-6" tabindex="-1"></a> <span class="st">"MOs"</span>: [<span class="st">'E. coli'</span>, <span class="st">'ESCCOL'</span>, <span class="st">'esco'</span>, <span class="st">'Esche coli'</span>],</span>
<span id="cb5-7"><a href="#cb5-7" tabindex="-1"></a> <span class="st">"Drug"</span>: [<span class="st">'Cipro'</span>, <span class="st">'CIP'</span>, <span class="st">'J01MA02'</span>, <span class="st">'Ciproxin'</span>]</span>
<span id="cb5-8"><a href="#cb5-8" tabindex="-1"></a>}</span>
<span id="cb5-9"><a href="#cb5-9" tabindex="-1"></a>df <span class="op">=</span> pd.DataFrame(data)</span>
<span id="cb5-10"><a href="#cb5-10" tabindex="-1"></a></span>
<span id="cb5-11"><a href="#cb5-11" tabindex="-1"></a><span class="co"># Use AMR functions to clean microorganism and drug names</span></span>
<span id="cb5-12"><a href="#cb5-12" tabindex="-1"></a>df[<span class="st">'MO_clean'</span>] <span class="op">=</span> AMR.mo_name(df[<span class="st">'MOs'</span>])</span>
<span id="cb5-13"><a href="#cb5-13" tabindex="-1"></a>df[<span class="st">'Drug_clean'</span>] <span class="op">=</span> AMR.ab_name(df[<span class="st">'Drug'</span>])</span>
<span id="cb5-14"><a href="#cb5-14" tabindex="-1"></a></span>
<span id="cb5-15"><a href="#cb5-15" tabindex="-1"></a><span class="co"># Display the results</span></span>
<span id="cb5-16"><a href="#cb5-16" tabindex="-1"></a><span class="bu">print</span>(df)</span></code></pre></div>
<table class="table">
<thead><tr class="header">
<th>MOs</th>
@ -207,12 +220,12 @@ the standard name, “Ciprofloxacin”.</p></li>
<div class="section level3">
<h3 id="calculating-amr">Calculating AMR<a class="anchor" aria-label="anchor" href="#calculating-amr"></a>
</h3>
<div class="sourceCode" id="cb5"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb5-1"><a href="#cb5-1" tabindex="-1"></a><span class="im">import</span> AMR</span>
<span id="cb5-2"><a href="#cb5-2" tabindex="-1"></a><span class="im">import</span> pandas <span class="im">as</span> pd</span>
<span id="cb5-3"><a href="#cb5-3" tabindex="-1"></a></span>
<span id="cb5-4"><a href="#cb5-4" tabindex="-1"></a>df <span class="op">=</span> AMR.example_isolates</span>
<span id="cb5-5"><a href="#cb5-5" tabindex="-1"></a>result <span class="op">=</span> AMR.resistance(df[<span class="st">"AMX"</span>])</span>
<span id="cb5-6"><a href="#cb5-6" tabindex="-1"></a><span class="bu">print</span>(result)</span></code></pre></div>
<div class="sourceCode" id="cb6"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb6-1"><a href="#cb6-1" tabindex="-1"></a><span class="im">import</span> AMR</span>
<span id="cb6-2"><a href="#cb6-2" tabindex="-1"></a><span class="im">import</span> pandas <span class="im">as</span> pd</span>
<span id="cb6-3"><a href="#cb6-3" tabindex="-1"></a></span>
<span id="cb6-4"><a href="#cb6-4" tabindex="-1"></a>df <span class="op">=</span> AMR.example_isolates</span>
<span id="cb6-5"><a href="#cb6-5" tabindex="-1"></a>result <span class="op">=</span> AMR.resistance(df[<span class="st">"AMX"</span>])</span>
<span id="cb6-6"><a href="#cb6-6" tabindex="-1"></a><span class="bu">print</span>(result)</span></code></pre></div>
<pre><code>[0.59555556]</code></pre>
</div>
<div class="section level3">
@ -222,8 +235,8 @@ the standard name, “Ciprofloxacin”.</p></li>
generating an antibiogram, a table that summarises the antimicrobial
susceptibility of bacterial isolates. Here’s how you can generate an
antibiogram from Python:</p>
<div class="sourceCode" id="cb7"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb7-1"><a href="#cb7-1" tabindex="-1"></a>result2a <span class="op">=</span> AMR.antibiogram(df[[<span class="st">"mo"</span>, <span class="st">"AMX"</span>, <span class="st">"CIP"</span>, <span class="st">"TZP"</span>]])</span>
<span id="cb7-2"><a href="#cb7-2" tabindex="-1"></a><span class="bu">print</span>(result2a)</span></code></pre></div>
<div class="sourceCode" id="cb8"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb8-1"><a href="#cb8-1" tabindex="-1"></a>result2a <span class="op">=</span> AMR.antibiogram(df[[<span class="st">"mo"</span>, <span class="st">"AMX"</span>, <span class="st">"CIP"</span>, <span class="st">"TZP"</span>]])</span>
<span id="cb8-2"><a href="#cb8-2" tabindex="-1"></a><span class="bu">print</span>(result2a)</span></code></pre></div>
<table class="table">
<colgroup>
<col width="22%">
@ -294,8 +307,8 @@ antibiogram from Python:</p>
</tr>
</tbody>
</table>
<div class="sourceCode" id="cb8"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb8-1"><a href="#cb8-1" tabindex="-1"></a>result2b <span class="op">=</span> AMR.antibiogram(df[[<span class="st">"mo"</span>, <span class="st">"AMX"</span>, <span class="st">"CIP"</span>, <span class="st">"TZP"</span>]], mo_transform <span class="op">=</span> <span class="st">"gramstain"</span>)</span>
<span id="cb8-2"><a href="#cb8-2" tabindex="-1"></a><span class="bu">print</span>(result2b)</span></code></pre></div>
<div class="sourceCode" id="cb9"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb9-1"><a href="#cb9-1" tabindex="-1"></a>result2b <span class="op">=</span> AMR.antibiogram(df[[<span class="st">"mo"</span>, <span class="st">"AMX"</span>, <span class="st">"CIP"</span>, <span class="st">"TZP"</span>]], mo_transform <span class="op">=</span> <span class="st">"gramstain"</span>)</span>
<span id="cb9-2"><a href="#cb9-2" tabindex="-1"></a><span class="bu">print</span>(result2b)</span></code></pre></div>
<table class="table">
<colgroup>
<col width="20%">
@ -335,7 +348,7 @@ the <code>AMR</code> R package, <code>microorganisms</code>,
<code>antimicrobials</code>, <code>clinical_breakpoints</code>, and
<code>example_isolates</code>, are now available as regular Python data
frames:</p>
<div class="sourceCode" id="cb9"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb9-1"><a href="#cb9-1" tabindex="-1"></a>AMR.microorganisms</span></code></pre></div>
<div class="sourceCode" id="cb10"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb10-1"><a href="#cb10-1" tabindex="-1"></a>AMR.microorganisms</span></code></pre></div>
<table class="table">
<colgroup>
<col width="11%">
@ -470,7 +483,7 @@ frames:</p>
</tr>
</tbody>
</table>
<div class="sourceCode" id="cb10"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb10-1"><a href="#cb10-1" tabindex="-1"></a>AMR.antimicrobials</span></code></pre></div>
<div class="sourceCode" id="cb11"><pre class="sourceCode python"><code class="sourceCode python"><span id="cb11-1"><a href="#cb11-1" tabindex="-1"></a>AMR.antimicrobials</span></code></pre></div>
<table style="width:100%;" class="table">
<colgroup>
<col width="4%">

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@ -31,7 +31,7 @@
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@ -31,7 +31,7 @@
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@ -31,7 +31,7 @@
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@ -31,7 +31,7 @@
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@ -31,7 +31,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9215</small>
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<button class="navbar-toggler" type="button" data-bs-toggle="collapse" data-bs-target="#navbar" aria-controls="navbar" aria-expanded="false" aria-label="Toggle navigation">
@ -82,7 +82,7 @@
<main id="main" class="col-md-9"><div class="page-header">
<img src="../logo.svg" class="logo" alt=""><h1>Data sets for download / own use</h1>
<h4 data-toc-skip class="date">16 March 2025</h4>
<h4 data-toc-skip class="date">17 March 2025</h4>
<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/main/vignettes/datasets.Rmd" class="external-link"><code>vignettes/datasets.Rmd</code></a></small>
<div class="d-none name"><code>datasets.Rmd</code></div>

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@ -34,7 +34,7 @@
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@ -7,7 +7,7 @@
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@ -50,19 +50,19 @@
</div>
<div class="section level2">
<h2 class="pkg-version" data-toc-text="2.1.1.9215" id="amr-2119215">AMR 2.1.1.9215<a class="anchor" aria-label="anchor" href="#amr-2119215"></a></h2>
<h2 class="pkg-version" data-toc-text="2.1.1.9216" id="amr-2119216">AMR 2.1.1.9216<a class="anchor" aria-label="anchor" href="#amr-2119216"></a></h2>
<p><em>(this beta version will eventually become v3.0. We’re happy to reach a new major milestone soon, which will be all about the new One Health support! Install this beta using <a href="https://msberends.github.io/AMR/#latest-development-version">the instructions here</a>.)</em></p>
<div class="section level5">
<h5 id="a-new-milestone-amr-v30-with-one-health-support--human--veterinary--environmental-2-1-1-9215">A New Milestone: AMR v3.0 with One Health Support (= Human + Veterinary + Environmental)<a class="anchor" aria-label="anchor" href="#a-new-milestone-amr-v30-with-one-health-support--human--veterinary--environmental-2-1-1-9215"></a></h5>
<h5 id="a-new-milestone-amr-v30-with-one-health-support--human--veterinary--environmental-2-1-1-9216">A New Milestone: AMR v3.0 with One Health Support (= Human + Veterinary + Environmental)<a class="anchor" aria-label="anchor" href="#a-new-milestone-amr-v30-with-one-health-support--human--veterinary--environmental-2-1-1-9216"></a></h5>
<p>This package now supports not only tools for AMR data analysis in clinical settings, but also for veterinary and environmental microbiology. This was made possible through a collaboration with the <a href="https://www.upei.ca/avc" class="external-link">University of Prince Edward Island’s Atlantic Veterinary College</a>, Canada. To celebrate this great improvement of the package, we also updated the package logo to reflect this change.</p>
</div>
<div class="section level3">
<h3 id="breaking-2-1-1-9215">Breaking<a class="anchor" aria-label="anchor" href="#breaking-2-1-1-9215"></a></h3>
<h3 id="breaking-2-1-1-9216">Breaking<a class="anchor" aria-label="anchor" href="#breaking-2-1-1-9216"></a></h3>
<ul><li>Dataset <code>antibiotics</code> has been renamed to <code>antimicrobials</code> as the data set contains more than just antibiotics. Using <code>antibiotics</code> will still work, but now returns a warning.</li>
<li>Removed all functions and references that used the deprecated <code>rsi</code> class, which were all replaced with their <code>sir</code> equivalents over two years ago.</li>
</ul></div>
<div class="section level3">
<h3 id="new-2-1-1-9215">New<a class="anchor" aria-label="anchor" href="#new-2-1-1-9215"></a></h3>
<h3 id="new-2-1-1-9216">New<a class="anchor" aria-label="anchor" href="#new-2-1-1-9216"></a></h3>
<ul><li>
<strong>One Health implementation</strong>
<ul><li>Function <code><a href="../reference/as.sir.html">as.sir()</a></code> now has extensive support for veterinary breakpoints from CLSI. Use <code>breakpoint_type = "animal"</code> and set the <code>host</code> argument to a variable that contains animal species names.</li>
@ -114,7 +114,7 @@
</ul></li>
</ul></div>
<div class="section level3">
<h3 id="changed-2-1-1-9215">Changed<a class="anchor" aria-label="anchor" href="#changed-2-1-1-9215"></a></h3>
<h3 id="changed-2-1-1-9216">Changed<a class="anchor" aria-label="anchor" href="#changed-2-1-1-9216"></a></h3>
<ul><li>SIR interpretation
<ul><li>It is now possible to use column names for argument <code>ab</code>, <code>mo</code>, and <code>uti</code>: <code>as.sir(..., ab = "column1", mo = "column2", uti = "column3")</code>. This greatly improves the flexibility for users.</li>
<li>Users can now set their own criteria (using regular expressions) as to what should be considered S, I, R, SDD, and NI.</li>
@ -188,7 +188,7 @@
<li>Added console colours support of <code>sir</code> class for Positron</li>
</ul></div>
<div class="section level3">
<h3 id="other-2-1-1-9215">Other<a class="anchor" aria-label="anchor" href="#other-2-1-1-9215"></a></h3>
<h3 id="other-2-1-1-9216">Other<a class="anchor" aria-label="anchor" href="#other-2-1-1-9216"></a></h3>
<ul><li>Added Dr. Larisse Bolton and Aislinn Cook as contributors for their fantastic implementation of WISCA in a mathematically solid way</li>
<li>Added Matthew Saab, Dr. Jordan Stull, and Prof. Javier Sanchez as contributors for their tremendous input on veterinary breakpoints and interpretations</li>
<li>Greatly improved <code>vctrs</code> integration, a Tidyverse package working in the background for many Tidyverse functions. For users, this means that functions such as <code>dplyr</code>’s <code><a href="https://dplyr.tidyverse.org/reference/bind_rows.html" class="external-link">bind_rows()</a></code>, <code><a href="https://dplyr.tidyverse.org/reference/rowwise.html" class="external-link">rowwise()</a></code> and <code><a href="https://dplyr.tidyverse.org/reference/c_across.html" class="external-link">c_across()</a></code> are now supported for e.g. columns of class <code>mic</code>. Despite this, this <code>AMR</code> package is still zero-dependent on any other package, including <code>dplyr</code> and <code>vctrs</code>.</li>
@ -196,7 +196,7 @@
<li>Stopped support for SAS (<code>.xpt</code>) files, since their file structure and extremely inefficient and requires more disk space than GitHub allows in a single commit.</li>
</ul></div>
<div class="section level3">
<h3 id="older-versions-2-1-1-9215">Older Versions<a class="anchor" aria-label="anchor" href="#older-versions-2-1-1-9215"></a></h3>
<h3 id="older-versions-2-1-1-9216">Older Versions<a class="anchor" aria-label="anchor" href="#older-versions-2-1-1-9216"></a></h3>
<p>This changelog only contains changes from AMR v3.0 (March 2025) and later.</p>
<ul><li>For prior v2 versions, please see <a href="https://github.com/msberends/AMR/blob/v2.1.1/NEWS.md" class="external-link">our v2 archive</a>.</li>
<li>For prior v1 versions, please see <a href="https://github.com/msberends/AMR/blob/v1.8.2/NEWS.md" class="external-link">our v1 archive</a>.</li>

2
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@ -12,7 +12,7 @@ articles:
resistance_predict: resistance_predict.html
welcome_to_AMR: welcome_to_AMR.html
WHONET: WHONET.html
last_built: 2025-03-16T17:54Z
last_built: 2025-03-17T08:00Z
urls:
reference: https://msberends.github.io/AMR/reference
article: https://msberends.github.io/AMR/articles

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@ -21,7 +21,7 @@ The AMR package is available in English, Chinese, Czech, Danish, Dutch, Finnish,
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@ -7,7 +7,7 @@
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@ -7,7 +7,7 @@
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@ -7,7 +7,7 @@
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@ -113,16 +113,16 @@
<span class="r-in"><span></span></span>
<span class="r-in"><span><span class="va">df</span></span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> birth_date age age_exact age_at_y2k</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1 1999-06-30 25 25.70959 0</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2 1968-01-29 57 57.12603 31</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3 1965-12-05 59 59.27671 34</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4 1980-03-01 45 45.04110 19</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 5 1949-11-01 75 75.36986 50</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 6 1947-02-14 78 78.08219 52</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 7 1940-02-19 85 85.06849 59</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 8 1988-01-10 37 37.17808 11</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 9 1997-08-27 27 27.55068 2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 10 1978-01-26 47 47.13425 21</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 1 1999-06-30 25 25.71233 0</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 2 1968-01-29 57 57.12877 31</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 3 1965-12-05 59 59.27945 34</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 4 1980-03-01 45 45.04384 19</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 5 1949-11-01 75 75.37260 50</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 6 1947-02-14 78 78.08493 52</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 7 1940-02-19 85 85.07123 59</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 8 1988-01-10 37 37.18082 11</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 9 1997-08-27 27 27.55342 2</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> 10 1978-01-26 47 47.13699 21</span>
</code></pre></div>
</div>
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@ -7,7 +7,7 @@
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20
reference/as.sir.html
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@ -21,7 +21,7 @@ All breakpoints used for interpretation are available in our clinical_breakpoint
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@ -816,16 +816,16 @@ A microorganism is categorised as "Resistant" when there is a high likelihood of
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># A tibble: 65 × 16</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> datetime index ab_given mo_given host_given ab mo </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494; font-style: italic;">&lt;dttm&gt;</span> <span style="color: #949494; font-style: italic;">&lt;int&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;chr&gt;</span> <span style="color: #949494; font-style: italic;">&lt;ab&gt;</span> <span style="color: #949494; font-style: italic;">&lt;mo&gt;</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 2025-03-16 <span style="color: #949494;">17:55:23</span> 1 ampicillin Strep p… human AMP <span style="color: #949494;">B_</span>STRPT<span style="color: #949494;">_</span>PNMN </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 2025-03-16 <span style="color: #949494;">17:55:23</span> 1 AMP Escheri… human AMP <span style="color: #949494;">B_</span>[ORD]<span style="color: #949494;">_</span>ENTRBC…</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> 2025-03-16 <span style="color: #949494;">17:55:23</span> 1 AMP Escheri… human AMP <span style="color: #949494;">B_</span>[ORD]<span style="color: #949494;">_</span>ENTRBC…</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 1</span> 2025-03-17 <span style="color: #949494;">08:01:05</span> 1 ampicillin Strep p… human AMP <span style="color: #949494;">B_</span>STRPT<span style="color: #949494;">_</span>PNMN </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 2</span> 2025-03-17 <span style="color: #949494;">08:01:05</span> 1 AMP Escheri… human AMP <span style="color: #949494;">B_</span>[ORD]<span style="color: #949494;">_</span>ENTRBC…</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 3</span> 2025-03-17 <span style="color: #949494;">08:01:05</span> 1 AMP Escheri… human AMP <span style="color: #949494;">B_</span>[ORD]<span style="color: #949494;">_</span>ENTRBC…</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 4</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;">NA</span> <span style="color: #BB0000;"> NA</span> </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 2025-03-16 <span style="color: #949494;">17:55:24</span> 1 GEN Escheri… human GEN <span style="color: #949494;">B_</span>[ORD]<span style="color: #949494;">_</span>ENTRBC…</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 2025-03-16 <span style="color: #949494;">17:55:24</span> 1 TOB Escheri… human TOB <span style="color: #949494;">B_</span>[ORD]<span style="color: #949494;">_</span>ENTRBC…</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 2025-03-16 <span style="color: #949494;">17:55:24</span> 1 AMX B_STRPT… human AMX <span style="color: #949494;">B_</span>STRPT<span style="color: #949494;">_</span>PNMN </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 2025-03-16 <span style="color: #949494;">17:55:25</span> 1 AMX B_STRPT… human AMX <span style="color: #949494;">B_</span>STRPT<span style="color: #949494;">_</span>PNMN </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 2025-03-16 <span style="color: #949494;">17:55:25</span> 2 AMX B_STRPT… human AMX <span style="color: #949494;">B_</span>STRPT<span style="color: #949494;">_</span>PNMN </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 2025-03-16 <span style="color: #949494;">17:55:25</span> 3 AMX B_STRPT… human AMX <span style="color: #949494;">B_</span>STRPT<span style="color: #949494;">_</span>PNMN </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 5</span> 2025-03-17 <span style="color: #949494;">08:01:06</span> 1 GEN Escheri… human GEN <span style="color: #949494;">B_</span>[ORD]<span style="color: #949494;">_</span>ENTRBC…</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 6</span> 2025-03-17 <span style="color: #949494;">08:01:06</span> 1 TOB Escheri… human TOB <span style="color: #949494;">B_</span>[ORD]<span style="color: #949494;">_</span>ENTRBC…</span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 7</span> 2025-03-17 <span style="color: #949494;">08:01:07</span> 1 AMX B_STRPT… human AMX <span style="color: #949494;">B_</span>STRPT<span style="color: #949494;">_</span>PNMN </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 8</span> 2025-03-17 <span style="color: #949494;">08:01:07</span> 1 AMX B_STRPT… human AMX <span style="color: #949494;">B_</span>STRPT<span style="color: #949494;">_</span>PNMN </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;"> 9</span> 2025-03-17 <span style="color: #949494;">08:01:07</span> 2 AMX B_STRPT… human AMX <span style="color: #949494;">B_</span>STRPT<span style="color: #949494;">_</span>PNMN </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #BCBCBC;">10</span> 2025-03-17 <span style="color: #949494;">08:01:07</span> 3 AMX B_STRPT… human AMX <span style="color: #949494;">B_</span>STRPT<span style="color: #949494;">_</span>PNMN </span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 55 more rows</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># ℹ 9 more variables: host &lt;chr&gt;, method &lt;chr&gt;, input &lt;chr&gt;, outcome &lt;sir&gt;,</span></span>
<span class="r-out co"><span class="r-pr">#&gt;</span> <span style="color: #949494;"># notes &lt;chr&gt;, guideline &lt;chr&gt;, ref_table &lt;chr&gt;, uti &lt;lgl&gt;,</span></span>

2
reference/atc_online.html
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@ -7,7 +7,7 @@
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reference/av_from_text.html
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@ -7,7 +7,7 @@
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reference/av_property.html
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@ -7,7 +7,7 @@
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reference/availability.html
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@ -7,7 +7,7 @@
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reference/bug_drug_combinations.html
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@ -7,7 +7,7 @@
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reference/clinical_breakpoints.html
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@ -21,7 +21,7 @@ Use as.sir() to transform MICs or disks measurements to SIR values."><meta prope
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reference/count.html
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@ -9,7 +9,7 @@ count_resistant() should be used to count resistant isolates, count_susceptible(
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reference/custom_eucast_rules.html
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@ -7,7 +7,7 @@
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reference/dosage.html
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@ -7,7 +7,7 @@
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reference/eucast_rules.html
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@ -9,7 +9,7 @@ To improve the interpretation of the antibiogram before EUCAST rules are applied
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reference/example_isolates.html
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@ -7,7 +7,7 @@
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reference/example_isolates_unclean.html
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@ -7,7 +7,7 @@
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reference/export_ncbi_biosample.html
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@ -7,7 +7,7 @@
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reference/first_isolate.html
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@ -9,7 +9,7 @@
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reference/g.test.html
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reference/get_episode.html
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@ -7,7 +7,7 @@
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reference/ggplot_pca.html
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reference/ggplot_sir.html
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reference/index.html
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reference/intrinsic_resistant.html
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reference/join.html
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reference/like.html
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@ -7,7 +7,7 @@
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reference/mdro.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9215</small>
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reference/mean_amr_distance.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/microorganisms.codes.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/microorganisms.groups.html
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@ -7,7 +7,7 @@
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reference/microorganisms.html
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@ -9,7 +9,7 @@ This data set is carefully crafted, yet made 100% reproducible from public and a
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reference/mo_matching_score.html
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@ -7,7 +7,7 @@
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reference/mo_property.html
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@ -7,7 +7,7 @@
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reference/mo_source.html
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@ -9,7 +9,7 @@ This is the fastest way to have your organisation (or analysis) specific codes p
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reference/pca.html
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@ -7,7 +7,7 @@
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reference/plot.html
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@ -9,7 +9,7 @@ Especially the scale_*_mic() functions are relevant wrappers to plot MIC values
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
<small class="nav-text text-muted me-auto" data-bs-toggle="tooltip" data-bs-placement="bottom" title="">2.1.1.9215</small>
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reference/proportion.html
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@ -9,7 +9,7 @@ resistance() should be used to calculate resistance, susceptibility() should be
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reference/random.html
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@ -7,7 +7,7 @@
<a class="navbar-brand me-2" href="../index.html">AMR (for R)</a>
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reference/resistance_predict.html
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@ -7,7 +7,7 @@
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reference/skewness.html
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@ -9,7 +9,7 @@ When negative ('left-skewed'): the left tail is longer; the mass of the distribu
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reference/top_n_microorganisms.html
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reference/translate.html
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search.json
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