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<h1>Deprecated functions</h1>
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<p>These functions are <a href='https://www.rdocumentation.org/packages/base/topics/Deprecated'>Deprecated</a>. They will be removed in a future release. Using the functions will give a warning with the name of the function it has been replaced by.</p>
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<pre class="usage"><span class='fu'>ratio</span>(<span class='no'>x</span>, <span class='no'>ratio</span>)</pre>
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<h1>The <code>AMR</code> Package</h1>
<div class="hidden name"><code>AMR.Rd</code></div>
</div>
<div class="ref-description">
<p>Welcome to the <code>AMR</code> package. This page gives some additional contact information about the authors.</p>
</div>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>This package was intended to simplify the analysis and prediction of Antimicrobial Resistance (AMR) and ti work with antibiotic properties by using evidence-based methods.</p>
<p>This package was created for academic research by PhD students of the Faculty of Medical Sciences of the University of Groningen and the Medical Microbiology &amp; Infection Prevention (MMBI) department of the University Medical Center Groningen (UMCG).</p>
<h2 class="hasAnchor" id="authors"><a class="anchor" href="#authors"></a>Authors</h2>
<p>Matthijs S. Berends[1,2] Christian F. Luz[1], Erwin E.A. Hassing[2], Corinna Glasner[1], Alex W. Friedrich[1], Bhanu Sinha[1] <br /></p>
<p>[1] Department of Medical Microbiology, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands - <a href='rug.nl'>rug.nl</a> <a href='umcg.nl'>umcg.nl</a> <br />
[2] Certe Medical Diagnostics &amp; Advice, Groningen, the Netherlands - <a href='certe.nl'>certe.nl</a></p>
<h2 class="hasAnchor" id="contact-us"><a class="anchor" href="#contact-us"></a>Contact us</h2>
<p>For suggestions, comments or questions, please contact us at:</p>
<p>Matthijs S. Berends <br />
m.s.berends [at] umcg [dot] nl <br />
Department of Medical Microbiology, University of Groningen <br />
University Medical Center Groningen <br />
Post Office Box 30001 <br />
9700 RB Groningen</p>
<p>If you have found a bug, please file a new issue at: <br />
<a href='https://gitlab.com/msberends/AMR/issues'>https://gitlab.com/msberends/AMR/issues</a></p>
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<h1>Property of an antibiotic</h1>
<div class="hidden name"><code>ab_property.Rd</code></div>
</div>
<div class="ref-description">
<p>Use these functions to return a specific property of an antibiotic from the <code><a href='antibiotics.html'>antibiotics</a></code> data set, based on their ATC code. Get such a code with <code><a href='as.atc.html'>as.atc</a></code>.</p>
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<pre class="usage"><span class='fu'>ab_property</span>(<span class='no'>x</span>, <span class='kw'>property</span> <span class='kw'>=</span> <span class='st'>"official"</span>)
<span class='fu'>ab_atc</span>(<span class='no'>x</span>)
<span class='fu'>ab_official</span>(<span class='no'>x</span>, <span class='kw'>language</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)
<span class='fu'>ab_name</span>(<span class='no'>x</span>, <span class='kw'>language</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)
<span class='fu'>ab_trivial_nl</span>(<span class='no'>x</span>)
<span class='fu'>ab_certe</span>(<span class='no'>x</span>)
<span class='fu'>ab_umcg</span>(<span class='no'>x</span>)
<span class='fu'>ab_tradenames</span>(<span class='no'>x</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>x</th>
<td><p>a (vector of a) valid <code><a href='as.atc.html'>atc</a></code> code or any text that can be coerced to a valid atc with <code><a href='as.atc.html'>as.atc</a></code></p></td>
</tr>
<tr>
<th>property</th>
<td><p>one of the column names of one of the <code><a href='antibiotics.html'>antibiotics</a></code> data set, like <code>"atc"</code> and <code>"official"</code></p></td>
</tr>
<tr>
<th>language</th>
<td><p>language of the returned text, defaults to English (<code>"en"</code>) and can be set with <code><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a>("AMR_locale")</code>. Either one of <code>"en"</code> (English) or <code>"nl"</code> (Dutch).</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>A vector of values. In case of <code>ab_tradenames</code>, if <code>x</code> is of length one, a vector will be returned. Otherwise a <code><a href='https://www.rdocumentation.org/packages/base/topics/list'>list</a></code>, with <code>x</code> as names.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='antibiotics.html'>antibiotics</a></code></p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='fu'>ab_atc</span>(<span class='st'>"amcl"</span>) <span class='co'># J01CR02</span></div><div class='output co'>#&gt; [1] "J01CR02"</div><div class='input'><span class='fu'>ab_name</span>(<span class='st'>"amcl"</span>) <span class='co'># Amoxicillin and beta-lactamase inhibitor</span></div><div class='output co'>#&gt; [1] "Amoxicillin and beta-lactamase inhibitor"</div><div class='input'><span class='fu'>ab_name</span>(<span class='st'>"amcl"</span>, <span class='st'>"nl"</span>) <span class='co'># Amoxicilline met enzymremmer</span></div><div class='output co'>#&gt; [1] "Amoxicilline met enzymremmer"</div><div class='input'><span class='fu'>ab_trivial_nl</span>(<span class='st'>"amcl"</span>) <span class='co'># Amoxicilline/clavulaanzuur</span></div><div class='output co'>#&gt; [1] "Amoxicilline/clavulaanzuur"</div><div class='input'><span class='fu'>ab_certe</span>(<span class='st'>"amcl"</span>) <span class='co'># amcl</span></div><div class='output co'>#&gt; [1] "amcl"</div><div class='input'><span class='fu'>ab_umcg</span>(<span class='st'>"amcl"</span>) <span class='co'># AMCL</span></div><div class='output co'>#&gt; [1] "AMCL"</div></pre>
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<h1>Name of an antibiotic</h1>
<div class="hidden name"><code>abname.Rd</code></div>
</div>
<div class="ref-description">
<p>Convert antibiotic codes to a (trivial) antibiotic name or ATC code, or vice versa. This uses the data from <code><a href='antibiotics.html'>antibiotics</a></code>.</p>
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<pre class="usage"><span class='fu'>abname</span>(<span class='no'>abcode</span>, <span class='kw'>from</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"guess"</span>, <span class='st'>"atc"</span>, <span class='st'>"certe"</span>, <span class='st'>"umcg"</span>),
<span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"official"</span>, <span class='kw'>textbetween</span> <span class='kw'>=</span> <span class='st'>" + "</span>, <span class='kw'>tolower</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>abcode</th>
<td><p>a code or name, like <code>"AMOX"</code>, <code>"AMCL"</code> or <code>"J01CA04"</code></p></td>
</tr>
<tr>
<th>from, to</th>
<td><p>type to transform from and to. See <code><a href='antibiotics.html'>antibiotics</a></code> for its column names. WIth <code>from = "guess"</code> the from will be guessed from <code>"atc"</code>, <code>"certe"</code> and <code>"umcg"</code>. When using <code>to = "atc"</code>, the ATC code will be searched using <code><a href='as.atc.html'>as.atc</a></code>.</p></td>
</tr>
<tr>
<th>textbetween</th>
<td><p>text to put between multiple returned texts</p></td>
</tr>
<tr>
<th>tolower</th>
<td><p>return output as lower case with function <code><a href='https://www.rdocumentation.org/packages/base/topics/chartr'>tolower</a></code>.</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p><code><a href='antibiotics.html'>antibiotics</a></code></p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p><strong>The <code><a href='ab_property.html'>ab_property</a></code> functions are faster and more concise</strong>, but do not support concatenated strings, like <code>abname("AMCL+GENT"</code>.</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='fu'>abname</span>(<span class='st'>"AMCL"</span>)</div><div class='output co'>#&gt; [1] "Amoxicillin and beta-lactamase inhibitor"</div><div class='input'><span class='co'># "Amoxicillin and beta-lactamase inhibitor"</span>
<span class='co'># It is quite flexible at default (having `from = "guess"`)</span>
<span class='fu'>abname</span>(<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"amox"</span>, <span class='st'>"J01CA04"</span>, <span class='st'>"Trimox"</span>, <span class='st'>"dispermox"</span>, <span class='st'>"Amoxil"</span>))</div><div class='output co'>#&gt; [1] "Amoxicillin" "Amoxicillin" "Amoxicillin" "Amoxicillin" "Amoxicillin"</div><div class='input'><span class='co'># "Amoxicillin" "Amoxicillin" "Amoxicillin" "Amoxicillin" "Amoxicillin"</span>
<span class='co'># Multiple antibiotics can be combined with "+".</span>
<span class='co'># The second antibiotic will be set to lower case when `tolower` was not set:</span>
<span class='fu'>abname</span>(<span class='st'>"AMCL+GENT"</span>, <span class='kw'>textbetween</span> <span class='kw'>=</span> <span class='st'>"/"</span>)</div><div class='output co'>#&gt; [1] "Amoxicillin and beta-lactamase inhibitor/gentamicin"</div><div class='input'><span class='co'># "amoxicillin and enzyme inhibitor/gentamicin"</span>
<span class='fu'>abname</span>(<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"AMCL"</span>, <span class='st'>"GENT"</span>))</div><div class='output co'>#&gt; [1] "Amoxicillin and beta-lactamase inhibitor"
#&gt; [2] "Gentamicin" </div><div class='input'><span class='co'># "Amoxicillin and beta-lactamase inhibitor" "Gentamicin"</span>
<span class='fu'>abname</span>(<span class='st'>"AMCL"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"trivial_nl"</span>)</div><div class='output co'>#&gt; [1] "Amoxicilline/clavulaanzuur"</div><div class='input'><span class='co'># "Amoxicilline/clavulaanzuur"</span>
<span class='fu'>abname</span>(<span class='st'>"AMCL"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"atc"</span>)</div><div class='output co'>#&gt; [1] "J01CR02"</div><div class='input'><span class='co'># "J01CR02"</span>
<span class='co'># specific codes for University Medical Center Groningen (UMCG):</span>
<span class='fu'>abname</span>(<span class='st'>"J01CR02"</span>, <span class='kw'>from</span> <span class='kw'>=</span> <span class='st'>"atc"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"umcg"</span>)</div><div class='output co'>#&gt; [1] "AMCL"</div><div class='input'><span class='co'># "AMCL"</span>
<span class='co'># specific codes for Certe:</span>
<span class='fu'>abname</span>(<span class='st'>"J01CR02"</span>, <span class='kw'>from</span> <span class='kw'>=</span> <span class='st'>"atc"</span>, <span class='kw'>to</span> <span class='kw'>=</span> <span class='st'>"certe"</span>)</div><div class='output co'>#&gt; [1] "amcl"</div><div class='input'># "amcl"
</div></pre>
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<h1>Age in years of individuals</h1>
<div class="hidden name"><code>age.Rd</code></div>
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<div class="ref-description">
<p>Calculates age in years based on a reference date, which is the sytem time at default.</p>
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<pre class="usage"><span class='fu'>age</span>(<span class='no'>x</span>, <span class='kw'>reference</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/Sys.time'>Sys.Date</a></span>())</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
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<colgroup><col class="name" /><col class="desc" /></colgroup>
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<th>x</th>
<td><p>date(s), will be coerced with <code><a href='https://www.rdocumentation.org/packages/base/topics/as.POSIXlt'>as.POSIXlt</a></code></p></td>
</tr>
<tr>
<th>reference</th>
<td><p>reference date(s) (defaults to today), will be coerced with <code><a href='https://www.rdocumentation.org/packages/base/topics/as.POSIXlt'>as.POSIXlt</a></code></p></td>
</tr>
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<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>Integer (no decimals)</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='age_groups.html'>age_groups</a></code> to splits age into groups</p></div>
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<h1>Split ages into age groups</h1>
<div class="hidden name"><code>age_groups.Rd</code></div>
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<p>Split ages into age groups defined by the <code>split</code> parameter. This allows for easier demographic (antimicrobial resistance) analysis.</p>
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<pre class="usage"><span class='fu'>age_groups</span>(<span class='no'>x</span>, <span class='kw'>split_at</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='fl'>12</span>, <span class='fl'>25</span>, <span class='fl'>55</span>, <span class='fl'>75</span>))</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
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<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>x</th>
<td><p>age, e.g. calculated with <code><a href='age.html'>age</a></code></p></td>
</tr>
<tr>
<th>split_at</th>
<td><p>values to split <code>x</code> at, defaults to age groups 0-11, 12-24, 26-54, 55-74 and 75+. See Details.</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>Ordered <code><a href='https://www.rdocumentation.org/packages/base/topics/factor'>factor</a></code></p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>To split ages, the input can be:</p><ul>
<li><p>A numeric vector. A vector of <code><a href='https://www.rdocumentation.org/packages/base/topics/c'>c(10, 20)</a></code> will split on 0-9, 10-19 and 20+. A value of only <code>50</code> will split on 0-49 and 50+.
The default is to split on young children (0-11), youth (12-24), young adults (26-54), middle-aged adults (55-74) and elderly (75+).</p></li>
<li><p>A character:</p><ul>
<li><p><code>"children"</code>, equivalent of: <code><a href='https://www.rdocumentation.org/packages/base/topics/c'>c(0, 1, 2, 4, 6, 13, 18)</a></code>. This will split on 0, 1, 2-3, 4-5, 6-12, 13-17 and 18+.</p></li>
<li><p><code>"elderly"</code> or <code>"seniors"</code>, equivalent of: <code><a href='https://www.rdocumentation.org/packages/base/topics/c'>c(65, 75, 85, 95)</a></code>. This will split on 0-64, 65-74, 75-84, 85-94 and 95+.</p></li>
<li><p><code>"fives"</code>, equivalent of: <code>1:20 * 5</code>. This will split on 0-4, 5-9, 10-14, 15-19 and so forth.</p></li>
<li><p><code>"tens"</code>, equivalent of: <code>1:10 * 10</code>. This will split on 0-9, 10-19, 20-29 and so forth.</p></li>
</ul></li>
</ul>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='age.html'>age</a></code> to determine ages based on one or more reference dates</p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='no'>ages</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='fl'>3</span>, <span class='fl'>8</span>, <span class='fl'>16</span>, <span class='fl'>54</span>, <span class='fl'>31</span>, <span class='fl'>76</span>, <span class='fl'>101</span>, <span class='fl'>43</span>, <span class='fl'>21</span>)
<span class='co'># split into 0-49 and 50+</span>
<span class='fu'>age_groups</span>(<span class='no'>ages</span>, <span class='fl'>50</span>)</div><div class='output co'>#&gt; [1] 0-49 0-49 0-49 50+ 0-49 50+ 50+ 0-49 0-49
#&gt; Levels: 0-49 &lt; 50+</div><div class='input'>
<span class='co'># split into 0-19, 20-49 and 50+</span>
<span class='fu'>age_groups</span>(<span class='no'>ages</span>, <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='fl'>20</span>, <span class='fl'>50</span>))</div><div class='output co'>#&gt; [1] 0-19 0-19 0-19 50+ 20-49 50+ 50+ 20-49 20-49
#&gt; Levels: 0-19 &lt; 20-49 &lt; 50+</div><div class='input'>
<span class='co'># split into groups of ten years</span>
<span class='fu'>age_groups</span>(<span class='no'>ages</span>, <span class='fl'>1</span>:<span class='fl'>10</span> * <span class='fl'>10</span>)</div><div class='output co'>#&gt; [1] 0-9 0-9 10-19 50-59 30-39 70-79 100+ 40-49 20-29
#&gt; 11 Levels: 0-9 &lt; 10-19 &lt; 20-29 &lt; 30-39 &lt; 40-49 &lt; 50-59 &lt; 60-69 &lt; ... &lt; 100+</div><div class='input'><span class='fu'>age_groups</span>(<span class='no'>ages</span>, <span class='kw'>split_at</span> <span class='kw'>=</span> <span class='st'>"tens"</span>)</div><div class='output co'>#&gt; [1] 0-9 0-9 10-19 50-59 30-39 70-79 100+ 40-49 20-29
#&gt; 11 Levels: 0-9 &lt; 10-19 &lt; 20-29 &lt; 30-39 &lt; 40-49 &lt; 50-59 &lt; 60-69 &lt; ... &lt; 100+</div><div class='input'>
<span class='co'># split into groups of five years</span>
<span class='fu'>age_groups</span>(<span class='no'>ages</span>, <span class='fl'>1</span>:<span class='fl'>20</span> * <span class='fl'>5</span>)</div><div class='output co'>#&gt; [1] 0-4 5-9 15-19 50-54 30-34 75-79 100+ 40-44 20-24
#&gt; 21 Levels: 0-4 &lt; 5-9 &lt; 10-14 &lt; 15-19 &lt; 20-24 &lt; 25-29 &lt; 30-34 &lt; ... &lt; 100+</div><div class='input'><span class='fu'>age_groups</span>(<span class='no'>ages</span>, <span class='kw'>split_at</span> <span class='kw'>=</span> <span class='st'>"fives"</span>)</div><div class='output co'>#&gt; [1] 0-4 5-9 15-19 50-54 30-34 75-79 100+ 40-44 20-24
#&gt; 21 Levels: 0-4 &lt; 5-9 &lt; 10-14 &lt; 15-19 &lt; 20-24 &lt; 25-29 &lt; 30-34 &lt; ... &lt; 100+</div><div class='input'>
<span class='co'># split specifically for children</span>
<span class='fu'>age_groups</span>(<span class='no'>ages</span>, <span class='st'>"children"</span>)</div><div class='output co'>#&gt; [1] 2-3 6-12 13-17 18+ 18+ 18+ 18+ 18+ 18+
#&gt; Levels: 0 &lt; 1 &lt; 2-3 &lt; 4-5 &lt; 6-12 &lt; 13-17 &lt; 18+</div><div class='input'><span class='co'># same:</span>
<span class='fu'>age_groups</span>(<span class='no'>ages</span>, <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='fl'>1</span>, <span class='fl'>2</span>, <span class='fl'>4</span>, <span class='fl'>6</span>, <span class='fl'>13</span>, <span class='fl'>17</span>))</div><div class='output co'>#&gt; [1] 2-3 6-12 13-16 17+ 17+ 17+ 17+ 17+ 17+
#&gt; Levels: 0 &lt; 1 &lt; 2-3 &lt; 4-5 &lt; 6-12 &lt; 13-16 &lt; 17+</div><div class='input'>
<span class='co'># resistance of ciprofloxacine per age group</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)</div><div class='output co'>#&gt; <span class='message'></span>
#&gt; <span class='message'>Attaching package: ‘dplyr’</span></div><div class='output co'>#&gt; <span class='message'>The following object is masked from ‘package:testthat’:</span>
#&gt; <span class='message'></span>
#&gt; <span class='message'> matches</span></div><div class='output co'>#&gt; <span class='message'>The following objects are masked from ‘package:stats’:</span>
#&gt; <span class='message'></span>
#&gt; <span class='message'> filter, lag</span></div><div class='output co'>#&gt; <span class='message'>The following objects are masked from ‘package:base’:</span>
#&gt; <span class='message'></span>
#&gt; <span class='message'> intersect, setdiff, setequal, union</span></div><div class='input'><span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>first_isolate</span> <span class='kw'>=</span> <span class='fu'><a href='first_isolate.html'>first_isolate</a></span>(<span class='no'>.</span>)) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>first_isolate</span> <span class='kw'>==</span> <span class='fl'>TRUE</span>,
<span class='no'>mo</span> <span class='kw'>==</span> <span class='fu'><a href='as.mo.html'>as.mo</a></span>(<span class='st'>"E. coli"</span>)) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='kw'>age_group</span> <span class='kw'>=</span> <span class='fu'>age_groups</span>(<span class='no'>age</span>)) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>age_group</span>,
<span class='no'>cipr</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='ggplot_rsi.html'>ggplot_rsi</a></span>(<span class='kw'>x</span> <span class='kw'>=</span> <span class='st'>"age_group"</span>)</div><div class='output co'>#&gt; <span class='message'><span style='color: #0000BB;'>NOTE: Using column `</span><span style='color: #0000BB;font-weight: bold;'>mo</span><span style='color: #0000BB;'>` as input for `col_mo`.</span><span></span></div><div class='output co'>#&gt; <span class='message'></span><span style='color: #0000BB;'>NOTE: Using column `</span><span style='color: #0000BB;font-weight: bold;'>date</span><span style='color: #0000BB;'>` as input for `col_date`.</span><span></span></div><div class='output co'>#&gt; <span class='message'></span><span style='color: #0000BB;'>NOTE: Using column `</span><span style='color: #0000BB;font-weight: bold;'>patient_id</span><span style='color: #0000BB;'>` as input for `col_patient_id`.</span><span></span></div><div class='output co'>#&gt; <span class='message'>=&gt; Found </span><span style='font-weight: bold;'>1,315 first isolates</span><span> (65.8% of total)</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Removed 3 rows containing missing values (geom_bar).</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Removed 3 rows containing missing values (geom_text).</span></div><div class='img'><img src='age_groups-1.png' alt='' width='700' height='433' /></div></span></pre>
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<h1>Data set with 423 antibiotics</h1>
<div class="hidden name"><code>antibiotics.Rd</code></div>
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<div class="ref-description">
<p>A data set containing all antibiotics with a J0 code and some other antimicrobial agents, with their DDDs. Except for trade names and abbreviations, all properties were downloaded from the WHO, see Source.</p>
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<pre class="usage"><span class='no'>antibiotics</span></pre>
<h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
<p>A <code><a href='https://www.rdocumentation.org/packages/base/topics/data.frame'>data.frame</a></code> with 423 observations and 18 variables:</p><dl class='dl-horizontal'>
<dt><code>atc</code></dt><dd><p>ATC code, like <code>J01CR02</code></p></dd>
<dt><code>certe</code></dt><dd><p>Certe code, like <code>amcl</code></p></dd>
<dt><code>umcg</code></dt><dd><p>UMCG code, like <code>AMCL</code></p></dd>
<dt><code>abbr</code></dt><dd><p>Abbreviation as used by many countries, used internally by <code><a href='as.atc.html'>as.atc</a></code></p></dd>
<dt><code>official</code></dt><dd><p>Official name by the WHO, like <code>"Amoxicillin and beta-lactamase inhibitor"</code></p></dd>
<dt><code>official_nl</code></dt><dd><p>Official name in the Netherlands, like <code>"Amoxicilline met enzymremmer"</code></p></dd>
<dt><code>trivial_nl</code></dt><dd><p>Trivial name in Dutch, like <code>"Amoxicilline/clavulaanzuur"</code></p></dd>
<dt><code>trade_name</code></dt><dd><p>Trade name as used by many countries (a total of 294), used internally by <code><a href='as.atc.html'>as.atc</a></code></p></dd>
<dt><code>oral_ddd</code></dt><dd><p>Defined Daily Dose (DDD), oral treatment</p></dd>
<dt><code>oral_units</code></dt><dd><p>Units of <code>ddd_units</code></p></dd>
<dt><code>iv_ddd</code></dt><dd><p>Defined Daily Dose (DDD), parenteral treatment</p></dd>
<dt><code>iv_units</code></dt><dd><p>Units of <code>iv_ddd</code></p></dd>
<dt><code>atc_group1</code></dt><dd><p>ATC group, like <code>"Macrolides, lincosamides and streptogramins"</code></p></dd>
<dt><code>atc_group2</code></dt><dd><p>Subgroup of <code>atc_group1</code>, like <code>"Macrolides"</code></p></dd>
<dt><code>atc_group1_nl</code></dt><dd><p>ATC group in Dutch, like <code>"Macroliden, lincosamiden en streptograminen"</code></p></dd>
<dt><code>atc_group2_nl</code></dt><dd><p>Subgroup of <code>atc_group1</code> in Dutch, like <code>"Macroliden"</code></p></dd>
<dt><code>useful_gramnegative</code></dt><dd><p><code>FALSE</code> if not useful according to EUCAST, <code>NA</code> otherwise (see Source)</p></dd>
<dt><code>useful_grampositive</code></dt><dd><p><code>FALSE</code> if not useful according to EUCAST, <code>NA</code> otherwise (see Source)</p></dd>
</dl>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p>- World Health Organization: <a href='https://www.whocc.no/atc_ddd_index/'>https://www.whocc.no/atc_ddd_index/</a> <br /> - EUCAST - Expert rules intrinsic exceptional V3.1 <br /> - MOLIS (LIS of Certe): <a href='https://www.certe.nl'>https://www.certe.nl</a> <br /> - GLIMS (LIS of UMCG): <a href='https://www.umcg.nl'>https://www.umcg.nl</a></p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='microorganisms.html'>microorganisms</a></code></p></div>
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<h1>Transform to ATC code</h1>
<div class="hidden name"><code>as.atc.Rd</code></div>
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<div class="ref-description">
<p>Use this function to determine the ATC code of one or more antibiotics. The data set <code><a href='antibiotics.html'>antibiotics</a></code> will be searched for abbreviations, official names and trade names.</p>
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<pre class="usage"><span class='fu'>as.atc</span>(<span class='no'>x</span>)
<span class='fu'>guess_atc</span>(<span class='no'>x</span>)
<span class='fu'>is.atc</span>(<span class='no'>x</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
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<th>x</th>
<td><p>character vector to determine <code>ATC</code> code</p></td>
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<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>Character (vector) with class <code>"act"</code>. Unknown values will return <code>NA</code>.</p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>Use the <code><a href='ab_property.html'>ab_property</a></code> functions to get properties based on the returned ATC code, see Examples.</p>
<p>In the ATC classification system, the active substances are classified in a hierarchy with five different levels. The system has fourteen main anatomical/pharmacological groups or 1st levels. Each ATC main group is divided into 2nd levels which could be either pharmacological or therapeutic groups. The 3rd and 4th levels are chemical, pharmacological or therapeutic subgroups and the 5th level is the chemical substance. The 2nd, 3rd and 4th levels are often used to identify pharmacological subgroups when that is considered more appropriate than therapeutic or chemical subgroups.
Source: <a href='https://www.whocc.no/atc/structure_and_principles/'>https://www.whocc.no/atc/structure_and_principles/</a></p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='antibiotics.html'>antibiotics</a></code> for the dataframe that is being used to determine ATCs.</p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='co'># These examples all return "J01FA01", the ATC code of Erythromycin:</span>
<span class='fu'>as.atc</span>(<span class='st'>"J01FA01"</span>)</div><div class='output co'>#&gt; Class 'atc'
#&gt; [1] J01FA01</div><div class='input'><span class='fu'>as.atc</span>(<span class='st'>"Erythromycin"</span>)</div><div class='output co'>#&gt; Class 'atc'
#&gt; [1] J01FA01</div><div class='input'><span class='fu'>as.atc</span>(<span class='st'>"eryt"</span>)</div><div class='output co'>#&gt; Class 'atc'
#&gt; [1] J01FA01</div><div class='input'><span class='fu'>as.atc</span>(<span class='st'>" eryt 123"</span>)</div><div class='output co'>#&gt; Class 'atc'
#&gt; [1] J01FA01</div><div class='input'><span class='fu'>as.atc</span>(<span class='st'>"ERYT"</span>)</div><div class='output co'>#&gt; Class 'atc'
#&gt; [1] J01FA01</div><div class='input'><span class='fu'>as.atc</span>(<span class='st'>"ERY"</span>)</div><div class='output co'>#&gt; Class 'atc'
#&gt; [1] J01FA01</div><div class='input'><span class='fu'>as.atc</span>(<span class='st'>"Erythrocin"</span>) <span class='co'># Trade name</span></div><div class='output co'>#&gt; Class 'atc'
#&gt; [1] J01FA01</div><div class='input'><span class='fu'>as.atc</span>(<span class='st'>"Eryzole"</span>) <span class='co'># Trade name</span></div><div class='output co'>#&gt; Class 'atc'
#&gt; [1] J01FA01</div><div class='input'><span class='fu'>as.atc</span>(<span class='st'>"Pediamycin"</span>) <span class='co'># Trade name</span></div><div class='output co'>#&gt; Class 'atc'
#&gt; [1] J01FA01</div><div class='input'>
<span class='co'># Use ab_* functions to get a specific property based on an ATC code</span>
<span class='no'>Cipro</span> <span class='kw'>&lt;-</span> <span class='fu'>as.atc</span>(<span class='st'>"cipro"</span>) <span class='co'># returns `J01MA02`</span>
<span class='fu'><a href='ab_property.html'>ab_official</a></span>(<span class='no'>Cipro</span>) <span class='co'># returns "Ciprofloxacin"</span></div><div class='output co'>#&gt; [1] "Ciprofloxacin"</div><div class='input'><span class='fu'><a href='ab_property.html'>ab_umcg</a></span>(<span class='no'>Cipro</span>) <span class='co'># returns "CIPR", the code used in the UMCG</span></div><div class='output co'>#&gt; [1] "CIPR"</div></pre>
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<meta property="og:description" content="This transforms a vector to a new class mic, which is an ordered factor with valid MIC values as levels. Invalid MIC values will be translated as NA with a warning." />
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<h1>Class 'mic'</h1>
<div class="hidden name"><code>as.mic.Rd</code></div>
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<p>This transforms a vector to a new class <code>mic</code>, which is an ordered factor with valid MIC values as levels. Invalid MIC values will be translated as <code>NA</code> with a warning.</p>
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<pre class="usage"><span class='fu'>as.mic</span>(<span class='no'>x</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='fu'>is.mic</span>(<span class='no'>x</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
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<th>x</th>
<td><p>vector</p></td>
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<tr>
<th>na.rm</th>
<td><p>a logical indicating whether missing values should be removed</p></td>
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<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>Ordered factor with new class <code>mic</code></p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='as.rsi.html'>as.rsi</a></code></p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='no'>mic_data</span> <span class='kw'>&lt;-</span> <span class='fu'>as.mic</span>(<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"&gt;=32"</span>, <span class='st'>"1.0"</span>, <span class='st'>"1"</span>, <span class='st'>"1.00"</span>, <span class='fl'>8</span>, <span class='st'>"&lt;=0.128"</span>, <span class='st'>"8"</span>, <span class='st'>"16"</span>, <span class='st'>"16"</span>))</div><div class='output co'>#&gt; <span class='warning'>Warning: 1 results truncated (11%) that were invalid MICs: "1.00"</span></div><div class='input'><span class='fu'>is.mic</span>(<span class='no'>mic_data</span>)</div><div class='output co'>#&gt; [1] TRUE</div><div class='input'>
<span class='co'># this can also coerce combined MIC/RSI values:</span>
<span class='fu'>as.mic</span>(<span class='st'>"&lt;=0.002; S"</span>) <span class='co'># will return &lt;=0.002</span></div><div class='output co'>#&gt; Class 'mic'
#&gt; [1] &lt;=0.002</div><div class='input'>
<span class='fu'><a href='https://www.rdocumentation.org/packages/graphics/topics/plot'>plot</a></span>(<span class='no'>mic_data</span>)</div><div class='output co'>#&gt; <span class='warning'>Warning: Factor `mic` contains implicit NA, consider using `forcats::fct_explicit_na`</span></div><div class='input'><span class='fu'><a href='https://www.rdocumentation.org/packages/graphics/topics/barplot'>barplot</a></span>(<span class='no'>mic_data</span>)</div><div class='output co'>#&gt; <span class='warning'>Warning: Factor `mic` contains implicit NA, consider using `forcats::fct_explicit_na`</span></div><div class='img'><img src='as.mic-1.png' alt='' width='700' height='433' /></div><div class='input'><span class='fu'><a href='freq.html'>freq</a></span>(<span class='no'>mic_data</span>)</div><div class='output co'>#&gt;
#&gt;
#&gt; **Frequency table**
#&gt;
#&gt;
#&gt; | |Item | Count| Percent| Cum. Count| Cum. Percent|
#&gt; |:--|:-------|-----:|-------:|----------:|------------:|
#&gt; |1 |1 | 2| 25.0%| 2| 25.0%|
#&gt; |2 |8 | 2| 25.0%| 4| 50.0%|
#&gt; |3 |16 | 2| 25.0%| 6| 75.0%|
#&gt; |4 |&lt;=0.128 | 1| 12.5%| 7| 87.5%|
#&gt; |5 |&gt;=32 | 1| 12.5%| 8| 100.0%|
#&gt;
#&gt; </div></pre>
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<meta property="og:description" content="Use this function to determine a valid microorganism ID (mo). Determination is done using Artificial Intelligence (AI) and the complete taxonomic kingdoms Bacteria, Fungi and Protozoa (see Source), so the input can be almost anything: a full name (like &quot;Staphylococcus aureus&quot;), an abbreviated name (like &quot;S. aureus&quot;), an abbreviation known in the field (like &quot;MRSA&quot;), or just a genus. You could also select a genus and species column, zie Examples." />
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<h1>Transform to microorganism ID</h1>
<div class="hidden name"><code>as.mo.Rd</code></div>
</div>
<div class="ref-description">
<p>Use this function to determine a valid microorganism ID (<code>mo</code>). Determination is done using Artificial Intelligence (AI) and the complete taxonomic kingdoms <em>Bacteria</em>, <em>Fungi</em> and <em>Protozoa</em> (see Source), so the input can be almost anything: a full name (like <code>"Staphylococcus aureus"</code>), an abbreviated name (like <code>"S. aureus"</code>), an abbreviation known in the field (like <code>"MRSA"</code>), or just a genus. You could also <code>select</code> a genus and species column, zie Examples.</p>
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<pre class="usage"><span class='fu'>as.mo</span>(<span class='no'>x</span>, <span class='kw'>Becker</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>Lancefield</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>allow_uncertain</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
<span class='kw'>reference_df</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)
<span class='fu'>is.mo</span>(<span class='no'>x</span>)
<span class='fu'>guess_mo</span>(<span class='no'>x</span>, <span class='kw'>Becker</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>Lancefield</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
<span class='kw'>allow_uncertain</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>reference_df</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
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<th>x</th>
<td><p>a character vector or a <code>data.frame</code> with one or two columns</p></td>
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<tr>
<th>Becker</th>
<td><p>a logical to indicate whether <em>Staphylococci</em> should be categorised into Coagulase Negative <em>Staphylococci</em> ("CoNS") and Coagulase Positive <em>Staphylococci</em> ("CoPS") instead of their own species, according to Karsten Becker <em>et al.</em> [1].</p>
<p>This excludes <em>Staphylococcus aureus</em> at default, use <code>Becker = "all"</code> to also categorise <em>S. aureus</em> as "CoPS".</p></td>
</tr>
<tr>
<th>Lancefield</th>
<td><p>a logical to indicate whether beta-haemolytic <em>Streptococci</em> should be categorised into Lancefield groups instead of their own species, according to Rebecca C. Lancefield [2]. These <em>Streptococci</em> will be categorised in their first group, e.g. <em>Streptococcus dysgalactiae</em> will be group C, although officially it was also categorised into groups G and L.</p>
<p>This excludes <em>Enterococci</em> at default (who are in group D), use <code>Lancefield = "all"</code> to also categorise all <em>Enterococci</em> as group D.</p></td>
</tr>
<tr>
<th>allow_uncertain</th>
<td><p>a logical to indicate whether the input should be checked for less possible results, see Details</p></td>
</tr>
<tr>
<th>reference_df</th>
<td><p>a <code>data.frame</code> to use for extra reference when translating <code>x</code> to a valid <code>mo</code>. The first column can be any microbial name, code or ID (used in your analysis or organisation), the second column must be a valid <code>mo</code> as found in the <code><a href='microorganisms.html'>microorganisms</a></code> data set.</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>Character (vector) with class <code>"mo"</code>. Unknown values will return <code>NA</code>.</p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>A microbial ID from this package (class: <code>mo</code>) typically looks like these examples:<br /></p><pre>
Code Full name
--------------- --------------------------------------
B_KLBSL Klebsiella
B_KLBSL_PNE Klebsiella pneumoniae
B_KLBSL_PNE_RHI Klebsiella pneumoniae rhinoscleromatis
| | | |
| | | |
| | | ----&gt; subspecies, a 3-4 letter acronym
| | ----&gt; species, a 3-4 letter acronym
| ----&gt; genus, a 5-7 letter acronym, mostly without vowels
----&gt; taxonomic kingdom, either B (Bacteria), F (Fungi) or P (Protozoa)
</pre>
<p>Use the <code><a href='mo_property.html'>mo_property</a></code> functions to get properties based on the returned code, see Examples.</p>
<p>This function uses Artificial Intelligence (AI) to help getting fast and logical results. It tries to find matches in this order:</p><ul>
<li><p>Taxonomic kingdom: it first searches in bacteria, then fungi, then protozoa</p></li>
<li><p>Human pathogenic prevalence: it first searches in more prevalent microorganisms, then less prevalent ones</p></li>
<li><p>Valid MO codes and full names: it first searches in already valid MO code and known genus/species combinations</p></li>
<li><p>Breakdown of input values: from here it starts to breakdown input values to find possible matches</p></li>
</ul>
<p>A couple of effects because of these rules:</p><ul>
<li><p><code>"E. coli"</code> will return the ID of <em>Escherichia coli</em> and not <em>Entamoeba coli</em>, although the latter would alphabetically come first</p></li>
<li><p><code>"H. influenzae"</code> will return the ID of <em>Haemophilus influenzae</em> and not <em>Haematobacter influenzae</em> for the same reason</p></li>
<li><p>Something like <code>"p aer"</code> will return the ID of <em>Pseudomonas aeruginosa</em> and not <em>Pasteurella aerogenes</em></p></li>
<li><p>Something like <code>"stau"</code> or <code>"S aur"</code> will return the ID of <em>Staphylococcus aureus</em> and not <em>Staphylococcus auricularis</em></p></li>
</ul><p>This means that looking up human pathogenic microorganisms takes less time than looking up human <strong>non</strong>-pathogenic microorganisms.</p>
<p>When using <code>allow_uncertain = TRUE</code> (which is the default setting), it will use additional rules if all previous AI rules failed to get valid results. Examples:</p><ul>
<li><p><code>"Streptococcus group B (known as S. agalactiae)"</code>. The text between brackets will be removed and a warning will be thrown that the result <em>Streptococcus group B</em> (<code>B_STRPTC_GRB</code>) needs review.</p></li>
<li><p><code>"S. aureus - please mind: MRSA"</code>. The last word will be stripped, after which the function will try to find a match. If it does not, the second last word will be stripped, etc. Again, a warning will be thrown that the result <em>Staphylococcus aureus</em> (<code>B_STPHY_AUR</code>) needs review.</p></li>
<li><p><code>"D. spartina"</code>. This is the abbreviation of an old taxonomic name: <em>Didymosphaeria spartinae</em> (the last "e" was missing from the input). This fungus was renamed to <em>Leptosphaeria obiones</em>, so a warning will be thrown that this result (<code>F_LPTSP_OBI</code>) needs review.</p></li>
</ul>
<p><code>guess_mo</code> is an alias of <code>as.mo</code>.</p>
<h2 class="hasAnchor" id="itis"><a class="anchor" href="#itis"></a>ITIS</h2>
<p><img src='figures/itis_logo.jpg' height=60px style=margin-bottom:5px /> <br />
This package contains the <strong>complete microbial taxonomic data</strong> (with all nine taxonomic ranks - from kingdom to subspecies) from the publicly available Integrated Taxonomic Information System (ITIS, <a href='https://www.itis.gov'>https://www.itis.gov</a>).</p>
<p>All (sub)species from <strong>the taxonomic kingdoms Bacteria, Fungi and Protozoa are included in this package</strong>, as well as all previously accepted names known to ITIS. Furthermore, the responsible authors and year of publication are available. This allows users to use authoritative taxonomic information for their data analysis on any microorganism, not only human pathogens. It also helps to quickly determine the Gram stain of bacteria, since all bacteria are classified into subkingdom Negibacteria or Posibacteria.</p>
<p>ITIS is a partnership of U.S., Canadian, and Mexican agencies and taxonomic specialists [3].</p>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p>[1] Becker K <em>et al.</em> <strong>Coagulase-Negative Staphylococci</strong>. 2014. Clin Microbiol Rev. 27(4): 870–926. <a href='https://dx.doi.org/10.1128/CMR.00109-13'>https://dx.doi.org/10.1128/CMR.00109-13</a></p>
<p>[2] Lancefield RC <strong>A serological differentiation of human and other groups of hemolytic streptococci</strong>. 1933. J Exp Med. 57(4): 571–95. <a href='https://dx.doi.org/10.1084/jem.57.4.571'>https://dx.doi.org/10.1084/jem.57.4.571</a></p>
<p>[3] Integrated Taxonomic Information System (ITIS). Retrieved September 2018. <a href='http://www.itis.gov'>http://www.itis.gov</a></p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='microorganisms.html'>microorganisms</a></code> for the <code>data.frame</code> with ITIS content that is being used to determine ID's. <br />
The <code><a href='mo_property.html'>mo_property</a></code> functions (like <code><a href='mo_property.html'>mo_genus</a></code>, <code><a href='mo_property.html'>mo_gramstain</a></code>) to get properties based on the returned code.</p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='co'># These examples all return "B_STPHY_AUR", the ID of S. aureus:</span>
<span class='fu'>as.mo</span>(<span class='st'>"stau"</span>)</div><div class='output co'>#&gt; Class 'mo'
#&gt; [1] B_STPHY_AUR</div><div class='input'><span class='fu'>as.mo</span>(<span class='st'>"STAU"</span>)</div><div class='output co'>#&gt; Class 'mo'
#&gt; [1] B_STPHY_AUR</div><div class='input'><span class='fu'>as.mo</span>(<span class='st'>"staaur"</span>)</div><div class='output co'>#&gt; Class 'mo'
#&gt; [1] B_STPHY_AUR</div><div class='input'><span class='fu'>as.mo</span>(<span class='st'>"S. aureus"</span>)</div><div class='output co'>#&gt; Class 'mo'
#&gt; [1] B_STPHY_AUR</div><div class='input'><span class='fu'>as.mo</span>(<span class='st'>"S aureus"</span>)</div><div class='output co'>#&gt; Class 'mo'
#&gt; [1] B_STPHY_AUR</div><div class='input'><span class='fu'>as.mo</span>(<span class='st'>"Staphylococcus aureus"</span>)</div><div class='output co'>#&gt; Class 'mo'
#&gt; [1] B_STPHY_AUR</div><div class='input'><span class='fu'>as.mo</span>(<span class='st'>"Staphylococcus aureus (MRSA)"</span>)</div><div class='output co'>#&gt; <span class='warning'>Warning: <span style='color: #BB0000;'>UNCERTAIN - "Staphylococcus aureus (MRSA)" -&gt; </span><span style='color: #BB0000;font-style: italic;'>Staphylococcus aureus</span><span style='color: #BB0000;'> (B_STPHY_AUR)</span><span></span></div><div class='output co'>#&gt; Class 'mo'
#&gt; [1] B_STPHY_AUR</div><div class='input'><span class='fu'>as.mo</span>(<span class='st'>"MRSA"</span>) <span class='co'># Methicillin Resistant S. aureus</span></div><div class='output co'>#&gt; Class 'mo'
#&gt; [1] B_STPHY_AUR</div><div class='input'><span class='fu'>as.mo</span>(<span class='st'>"VISA"</span>) <span class='co'># Vancomycin Intermediate S. aureus</span></div><div class='output co'>#&gt; Class 'mo'
#&gt; [1] B_STPHY_AUR</div><div class='input'><span class='fu'>as.mo</span>(<span class='st'>"VRSA"</span>) <span class='co'># Vancomycin Resistant S. aureus</span></div><div class='output co'>#&gt; Class 'mo'
#&gt; [1] B_STPHY_AUR</div><div class='input'><span class='fu'>as.mo</span>(<span class='fl'>369</span>) <span class='co'># Search on TSN (Taxonomic Serial Number), a unique identifier</span></div><div class='output co'>#&gt; Class 'mo'
#&gt; [1] B_STPHY_AUR</div><div class='input'> <span class='co'># for the Integrated Taxonomic Information System (ITIS)</span>
<span class='fu'>as.mo</span>(<span class='st'>"Streptococcus group A"</span>)</div><div class='output co'>#&gt; Class 'mo'
#&gt; [1] B_STRPTC_GRA</div><div class='input'><span class='fu'>as.mo</span>(<span class='st'>"GAS"</span>) <span class='co'># Group A Streptococci</span></div><div class='output co'>#&gt; Class 'mo'
#&gt; [1] B_STRPTC_GRA</div><div class='input'><span class='fu'>as.mo</span>(<span class='st'>"GBS"</span>) <span class='co'># Group B Streptococci</span></div><div class='output co'>#&gt; Class 'mo'
#&gt; [1] B_STRPTC_GRB</div><div class='input'>
<span class='co'># guess_mo is an alias of as.mo and works the same</span>
<span class='fu'>guess_mo</span>(<span class='st'>"S. epidermidis"</span>) <span class='co'># will remain species: B_STPHY_EPI</span></div><div class='output co'>#&gt; Class 'mo'
#&gt; [1] B_STPHY_EPI</div><div class='input'><span class='fu'>guess_mo</span>(<span class='st'>"S. epidermidis"</span>, <span class='kw'>Becker</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) <span class='co'># will not remain species: B_STPHY_CNS</span></div><div class='output co'>#&gt; Class 'mo'
#&gt; [1] B_STPHY_CNS</div><div class='input'>
<span class='fu'>guess_mo</span>(<span class='st'>"S. pyogenes"</span>) <span class='co'># will remain species: B_STRPTC_PYO</span></div><div class='output co'>#&gt; Class 'mo'
#&gt; [1] B_STRPTC_PYO</div><div class='input'><span class='fu'>guess_mo</span>(<span class='st'>"S. pyogenes"</span>, <span class='kw'>Lancefield</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) <span class='co'># will not remain species: B_STRPTC_GRA</span></div><div class='output co'>#&gt; Class 'mo'
#&gt; [1] B_STRPTC_GRA</div><div class='input'>
<span class='co'># Use mo_* functions to get a specific property based on `mo`</span>
<span class='no'>Ecoli</span> <span class='kw'>&lt;-</span> <span class='fu'>as.mo</span>(<span class='st'>"E. coli"</span>) <span class='co'># returns `B_ESCHR_COL`</span>
<span class='fu'><a href='mo_property.html'>mo_genus</a></span>(<span class='no'>Ecoli</span>) <span class='co'># returns "Escherichia"</span></div><div class='output co'>#&gt; [1] "Escherichia"</div><div class='input'><span class='fu'><a href='mo_property.html'>mo_gramstain</a></span>(<span class='no'>Ecoli</span>) <span class='co'># returns "Gram negative"</span></div><div class='output co'>#&gt; [1] "Gram-negatief"</div><div class='input'><span class='co'># but it uses as.mo internally too, so you could also just use:</span>
<span class='fu'><a href='mo_property.html'>mo_genus</a></span>(<span class='st'>"E. coli"</span>) <span class='co'># returns "Escherichia"</span></div><div class='output co'>#&gt; [1] "Escherichia"</div><div class='input'>
</div></span><span class='co'># NOT RUN {</span>
<span class='no'>df</span>$<span class='no'>mo</span> <span class='kw'>&lt;-</span> <span class='fu'>as.mo</span>(<span class='no'>df</span>$<span class='no'>microorganism_name</span>)
<span class='co'># the select function of tidyverse is also supported:</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='no'>df</span>$<span class='no'>mo</span> <span class='kw'>&lt;-</span> <span class='no'>df</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>microorganism_name</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>as.mo</span>()
<span class='co'># and can even contain 2 columns, which is convenient for genus/species combinations:</span>
<span class='no'>df</span>$<span class='no'>mo</span> <span class='kw'>&lt;-</span> <span class='no'>df</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>genus</span>, <span class='no'>species</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>as.mo</span>()
<span class='co'># although this works easier and does the same:</span>
<span class='no'>df</span> <span class='kw'>&lt;-</span> <span class='no'>df</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>mo</span> <span class='kw'>=</span> <span class='fu'>as.mo</span>(<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/paste'>paste</a></span>(<span class='no'>genus</span>, <span class='no'>species</span>)))
<span class='co'># }</span></pre>
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<li><a href="#arguments">Arguments</a></li>
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<li><a href="#examples">Examples</a></li>
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<h1>Properties of an ATC code</h1>
<div class="hidden name"><code>atc_property.Rd</code></div>
</div>
<div class="ref-description">
<p>Gets data from the WHO to determine properties of an ATC (e.g. an antibiotic) like name, defined daily dose (DDD) or standard unit. <br /> <strong>This function requires an internet connection.</strong></p>
</div>
<pre class="usage"><span class='fu'>atc_property</span>(<span class='no'>atc_code</span>, <span class='no'>property</span>, <span class='kw'>administration</span> <span class='kw'>=</span> <span class='st'>"O"</span>,
<span class='kw'>url</span> <span class='kw'>=</span> <span class='st'>"https://www.whocc.no/atc_ddd_index/?code=%s&amp;showdescription=no"</span>)
<span class='fu'>atc_groups</span>(<span class='no'>atc_code</span>, <span class='no'>...</span>)
<span class='fu'>atc_ddd</span>(<span class='no'>atc_code</span>, <span class='no'>...</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>atc_code</th>
<td><p>a character or character vector with ATC code(s) of antibiotic(s)</p></td>
</tr>
<tr>
<th>property</th>
<td><p>property of an ATC code. Valid values are <code>"ATC"</code>, <code>"Name"</code>, <code>"DDD"</code>, <code>"U"</code> (<code>"unit"</code>), <code>"Adm.R"</code>, <code>"Note"</code> and <code>groups</code>. For this last option, all hierarchical groups of an ATC code will be returned, see Examples.</p></td>
</tr>
<tr>
<th>administration</th>
<td><p>type of administration when using <code>property = "Adm.R"</code>, see Details</p></td>
</tr>
<tr>
<th>url</th>
<td><p>url of website of the WHO. The sign <code>%s</code> can be used as a placeholder for ATC codes.</p></td>
</tr>
<tr>
<th>...</th>
<td><p>parameters to pass on to <code>atc_property</code></p></td>
</tr>
</table>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p><a href='https://www.whocc.no/atc_ddd_alterations__cumulative/ddd_alterations/abbrevations/'>https://www.whocc.no/atc_ddd_alterations__cumulative/ddd_alterations/abbrevations/</a></p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>Options for parameter <code>administration</code>:</p><ul>
<li><p><code>"Implant"</code> = Implant</p></li>
<li><p><code>"Inhal"</code> = Inhalation</p></li>
<li><p><code>"Instill"</code> = Instillation</p></li>
<li><p><code>"N"</code> = nasal</p></li>
<li><p><code>"O"</code> = oral</p></li>
<li><p><code>"P"</code> = parenteral</p></li>
<li><p><code>"R"</code> = rectal</p></li>
<li><p><code>"SL"</code> = sublingual/buccal</p></li>
<li><p><code>"TD"</code> = transdermal</p></li>
<li><p><code>"V"</code> = vaginal</p></li>
</ul>
<p>Abbreviations of return values when using <code>property = "U"</code> (unit):</p><ul>
<li><p><code>"g"</code> = gram</p></li>
<li><p><code>"mg"</code> = milligram</p></li>
<li><p><code>"mcg"</code> = microgram</p></li>
<li><p><code>"U"</code> = unit</p></li>
<li><p><code>"TU"</code> = thousand units</p></li>
<li><p><code>"MU"</code> = million units</p></li>
<li><p><code>"mmol"</code> = millimole</p></li>
<li><p><code>"ml"</code> = milliliter (e.g. eyedrops)</p></li>
</ul>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='co'># What's the ATC of amoxicillin?</span>
<span class='fu'><a href='as.atc.html'>guess_atc</a></span>(<span class='st'>"Amoxicillin"</span>)</div><div class='output co'>#&gt; Class 'atc'
#&gt; [1] J01CA04</div><div class='input'><span class='co'># [1] "J01CA04"</span>
<span class='co'># oral DDD (Defined Daily Dose) of amoxicillin</span>
<span class='fu'>atc_property</span>(<span class='st'>"J01CA04"</span>, <span class='st'>"DDD"</span>, <span class='st'>"O"</span>)</div><div class='output co'>#&gt; [1] 1.5</div><div class='input'><span class='co'># parenteral DDD (Defined Daily Dose) of amoxicillin</span>
<span class='fu'>atc_property</span>(<span class='st'>"J01CA04"</span>, <span class='st'>"DDD"</span>, <span class='st'>"P"</span>)</div><div class='output co'>#&gt; [1] 3</div><div class='input'>
<span class='fu'>atc_property</span>(<span class='st'>"J01CA04"</span>, <span class='kw'>property</span> <span class='kw'>=</span> <span class='st'>"groups"</span>) <span class='co'># search hierarchical groups of amoxicillin</span></div><div class='output co'>#&gt; [1] "ANTIINFECTIVES FOR SYSTEMIC USE"
#&gt; [2] "ANTIBACTERIALS FOR SYSTEMIC USE"
#&gt; [3] "BETA-LACTAM ANTIBACTERIALS, PENICILLINS"
#&gt; [4] "Penicillins with extended spectrum" </div><div class='input'># [1] "ANTIINFECTIVES FOR SYSTEMIC USE"
# [2] "ANTIBACTERIALS FOR SYSTEMIC USE"
# [3] "BETA-LACTAM ANTIBACTERIALS, PENICILLINS"
# [4] "Penicillins with extended spectrum"
</div></pre>
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<meta property="og:description" content="These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in dplyrs summarise and support grouped variables, see Examples.
count_R and count_IR can be used to count resistant isolates, count_S and count_SI can be used to count susceptible isolates." />
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<h1>Count isolates</h1>
<div class="hidden name"><code>count.Rd</code></div>
</div>
<div class="ref-description">
<p>These functions can be used to count resistant/susceptible microbial isolates. All functions support quasiquotation with pipes, can be used in <code>dplyr</code>s <code><a href='http://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></code> and support grouped variables, see <em>Examples</em>.</p>
<p><code>count_R</code> and <code>count_IR</code> can be used to count resistant isolates, <code>count_S</code> and <code>count_SI</code> can be used to count susceptible isolates.<br /></p>
</div>
<pre class="usage"><span class='fu'>count_R</span>(<span class='no'>...</span>, <span class='kw'>also_single_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='fu'>count_IR</span>(<span class='no'>...</span>, <span class='kw'>also_single_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='fu'>count_I</span>(<span class='no'>...</span>, <span class='kw'>also_single_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='fu'>count_SI</span>(<span class='no'>...</span>, <span class='kw'>also_single_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='fu'>count_S</span>(<span class='no'>...</span>, <span class='kw'>also_single_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='fu'>count_all</span>(<span class='no'>...</span>)
<span class='fu'>n_rsi</span>(<span class='no'>...</span>)
<span class='fu'>count_df</span>(<span class='no'>data</span>, <span class='kw'>translate_ab</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a></span>(<span class='st'>"get_antibiotic_names"</span>,
<span class='st'>"official"</span>), <span class='kw'>combine_IR</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>...</th>
<td><p>one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with <code><a href='as.rsi.html'>as.rsi</a></code> if needed.</p></td>
</tr>
<tr>
<th>also_single_tested</th>
<td><p>a logical to indicate whether (in combination therapies) also observations should be included where not all antibiotics were tested, but at least one of the tested antibiotics contains a target interpretation (e.g. S in case of <code>portion_S</code> and R in case of <code>portion_R</code>). <strong>This would lead to selection bias in almost all cases.</strong></p></td>
</tr>
<tr>
<th>data</th>
<td><p>a <code>data.frame</code> containing columns with class <code>rsi</code> (see <code><a href='as.rsi.html'>as.rsi</a></code>)</p></td>
</tr>
<tr>
<th>translate_ab</th>
<td><p>a column name of the <code><a href='antibiotics.html'>antibiotics</a></code> data set to translate the antibiotic abbreviations to, using <code><a href='abname.html'>abname</a></code>. This can be set with <code><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a>("get_antibiotic_names")</code>.</p></td>
</tr>
<tr>
<th>combine_IR</th>
<td><p>a logical to indicate whether all values of I and R must be merged into one, so the output only consists of S vs. IR (susceptible vs. non-susceptible)</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p>Wickham H. <strong>Tidy Data.</strong> The Journal of Statistical Software, vol. 59, 2014. <a href='http://vita.had.co.nz/papers/tidy-data.html'>http://vita.had.co.nz/papers/tidy-data.html</a></p>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>Integer</p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>These functions are meant to count isolates. Use the <code><a href='portion.html'>portion</a>_*</code> functions to calculate microbial resistance.</p>
<p><code>n_rsi</code> is an alias of <code>count_all</code>. They can be used to count all available isolates, i.e. where all input antibiotics have an available result (S, I or R). Their use is equal to <code><a href='http://dplyr.tidyverse.org/reference/n_distinct.html'>n_distinct</a></code>. Their function is equal to <code>count_S(...) + count_IR(...)</code>.</p>
<p><code>count_df</code> takes any variable from <code>data</code> that has an <code>"rsi"</code> class (created with <code><a href='as.rsi.html'>as.rsi</a></code>) and counts the amounts of R, I and S. The resulting <em>tidy data</em> (see Source) <code>data.frame</code> will have three rows (S/I/R) and a column for each variable with class <code>"rsi"</code>.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='portion.html'>portion</a>_*</code> to calculate microbial resistance and susceptibility.</p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='co'># septic_patients is a data set available in the AMR package. It is true, genuine data.</span>
?<span class='no'>septic_patients</span></div><div class='output co'>#&gt; <span class='message'>Rendering development documentation for 'septic_patients'</span></div><div class='input'>
<span class='co'># Count resistant isolates</span>
<span class='fu'>count_R</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)</div><div class='output co'>#&gt; [1] 683</div><div class='input'><span class='fu'>count_IR</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)</div><div class='output co'>#&gt; [1] 686</div><div class='input'>
<span class='co'># Or susceptible isolates</span>
<span class='fu'>count_S</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)</div><div class='output co'>#&gt; [1] 486</div><div class='input'><span class='fu'>count_SI</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)</div><div class='output co'>#&gt; [1] 489</div><div class='input'>
<span class='co'># Count all available isolates</span>
<span class='fu'>count_all</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)</div><div class='output co'>#&gt; [1] 1172</div><div class='input'><span class='fu'>n_rsi</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)</div><div class='output co'>#&gt; [1] 1172</div><div class='input'>
<span class='co'># Since n_rsi counts available isolates, you can</span>
<span class='co'># calculate back to count e.g. non-susceptible isolates.</span>
<span class='co'># This results in the same:</span>
<span class='fu'>count_IR</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)</div><div class='output co'>#&gt; [1] 686</div><div class='input'><span class='fu'><a href='portion.html'>portion_IR</a></span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>) * <span class='fu'>n_rsi</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)</div><div class='output co'>#&gt; [1] 686</div><div class='input'>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></span>(<span class='kw'>R</span> <span class='kw'>=</span> <span class='fu'>count_R</span>(<span class='no'>cipr</span>),
<span class='kw'>I</span> <span class='kw'>=</span> <span class='fu'>count_I</span>(<span class='no'>cipr</span>),
<span class='kw'>S</span> <span class='kw'>=</span> <span class='fu'>count_S</span>(<span class='no'>cipr</span>),
<span class='kw'>n1</span> <span class='kw'>=</span> <span class='fu'>count_all</span>(<span class='no'>cipr</span>), <span class='co'># the actual total; sum of all three</span>
<span class='kw'>n2</span> <span class='kw'>=</span> <span class='fu'>n_rsi</span>(<span class='no'>cipr</span>), <span class='co'># same - analogous to n_distinct</span>
<span class='kw'>total</span> <span class='kw'>=</span> <span class='fu'><a href='http://dplyr.tidyverse.org/reference/n.html'>n</a></span>()) <span class='co'># NOT the amount of tested isolates!</span></div><div class='output co'>#&gt; <span style='color: #949494;'># A tibble: 4 x 7</span><span>
#&gt; hospital_id R I S n1 n2 total
#&gt; </span><span style='color: #949494;font-style: italic;'>&lt;fct&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;int&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;int&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;int&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;int&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;int&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;int&gt;</span><span>
#&gt; </span><span style='color: #BCBCBC;'>1</span><span> A 26 3 178 207 207 321
#&gt; </span><span style='color: #BCBCBC;'>2</span><span> B 85 35 379 499 499 663
#&gt; </span><span style='color: #BCBCBC;'>3</span><span> C 41 22 139 202 202 254
#&gt; </span><span style='color: #BCBCBC;'>4</span><span> D 76 9 416 501 501 762</div><div class='input'>
<span class='co'># Count co-resistance between amoxicillin/clav acid and gentamicin,</span>
<span class='co'># so we can see that combination therapy does a lot more than mono therapy.</span>
<span class='co'># Please mind that `portion_S` calculates percentages right away instead.</span>
<span class='fu'>count_S</span>(<span class='no'>septic_patients</span>$<span class='no'>amcl</span>) <span class='co'># S = 1057 (67.1%)</span></div><div class='output co'>#&gt; [1] 1291</div><div class='input'><span class='fu'>count_all</span>(<span class='no'>septic_patients</span>$<span class='no'>amcl</span>) <span class='co'># n = 1576</span></div><div class='output co'>#&gt; [1] 1828</div><div class='input'>
<span class='fu'>count_S</span>(<span class='no'>septic_patients</span>$<span class='no'>gent</span>) <span class='co'># S = 1372 (74.0%)</span></div><div class='output co'>#&gt; [1] 1372</div><div class='input'><span class='fu'>count_all</span>(<span class='no'>septic_patients</span>$<span class='no'>gent</span>) <span class='co'># n = 1855</span></div><div class='output co'>#&gt; [1] 1855</div><div class='input'>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/with'>with</a></span>(<span class='no'>septic_patients</span>,
<span class='fu'>count_S</span>(<span class='no'>amcl</span>, <span class='no'>gent</span>)) <span class='co'># S = 1396 (92.0%)</span></div><div class='output co'>#&gt; [1] 1609</div><div class='input'><span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/with'>with</a></span>(<span class='no'>septic_patients</span>, <span class='co'># n = 1517</span>
<span class='fu'>n_rsi</span>(<span class='no'>amcl</span>, <span class='no'>gent</span>))</div><div class='output co'>#&gt; [1] 1747</div><div class='input'>
<span class='co'># Get portions S/I/R immediately of all rsi columns</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>amox</span>, <span class='no'>cipr</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>count_df</span>(<span class='kw'>translate</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</div><div class='output co'>#&gt; Interpretation Antibiotic Value
#&gt; 1 S amox 486
#&gt; 2 I amox 3
#&gt; 3 R amox 683
#&gt; 4 S cipr 1112
#&gt; 5 I cipr 69
#&gt; 6 R cipr 228</div><div class='input'>
<span class='co'># It also supports grouping variables</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>hospital_id</span>, <span class='no'>amox</span>, <span class='no'>cipr</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>count_df</span>(<span class='kw'>translate</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</div><div class='output co'>#&gt; </span><span style='color: #949494;'># A tibble: 24 x 4</span><span>
#&gt; Interpretation hospital_id Antibiotic Value
#&gt; </span><span style='color: #949494;font-style: italic;'>&lt;ord&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;fct&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;chr&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;int&gt;</span><span>
#&gt; </span><span style='color: #BCBCBC;'> 1</span><span> S A amox 63
#&gt; </span><span style='color: #BCBCBC;'> 2</span><span> S B amox 141
#&gt; </span><span style='color: #BCBCBC;'> 3</span><span> S C amox 59
#&gt; </span><span style='color: #BCBCBC;'> 4</span><span> S D amox 223
#&gt; </span><span style='color: #BCBCBC;'> 5</span><span> I A amox 0
#&gt; </span><span style='color: #BCBCBC;'> 6</span><span> I B amox 1
#&gt; </span><span style='color: #BCBCBC;'> 7</span><span> I C amox 0
#&gt; </span><span style='color: #BCBCBC;'> 8</span><span> I D amox 2
#&gt; </span><span style='color: #BCBCBC;'> 9</span><span> R A amox 87
#&gt; </span><span style='color: #BCBCBC;'>10</span><span> R B amox 231
#&gt; </span><span style='color: #949494;'># ... with 14 more rows</span><span></div><div class='input'>
</div></span></pre>
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<h2>Contents</h2>
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<h1>EUCAST rules</h1>
<div class="hidden name"><code>eucast_rules.Rd</code></div>
</div>
<div class="ref-description">
<p>Apply susceptibility rules as defined by the European Committee on Antimicrobial Susceptibility Testing (EUCAST, <a href='http://eucast.org'>http://eucast.org</a>), see <em>Source</em>. This includes (1) expert rules, (2) intrinsic resistance and (3) inferred resistance as defined in their breakpoint tables.</p>
</div>
<pre class="usage"><span class='fu'>eucast_rules</span>(<span class='no'>tbl</span>, <span class='kw'>col_mo</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>info</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
<span class='kw'>rules</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"breakpoints"</span>, <span class='st'>"expert"</span>, <span class='st'>"other"</span>, <span class='st'>"all"</span>), <span class='kw'>verbose</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
<span class='kw'>amcl</span> <span class='kw'>=</span> <span class='st'>"amcl"</span>, <span class='kw'>amik</span> <span class='kw'>=</span> <span class='st'>"amik"</span>, <span class='kw'>amox</span> <span class='kw'>=</span> <span class='st'>"amox"</span>, <span class='kw'>ampi</span> <span class='kw'>=</span> <span class='st'>"ampi"</span>,
<span class='kw'>azit</span> <span class='kw'>=</span> <span class='st'>"azit"</span>, <span class='kw'>azlo</span> <span class='kw'>=</span> <span class='st'>"azlo"</span>, <span class='kw'>aztr</span> <span class='kw'>=</span> <span class='st'>"aztr"</span>, <span class='kw'>cefa</span> <span class='kw'>=</span> <span class='st'>"cefa"</span>,
<span class='kw'>cfep</span> <span class='kw'>=</span> <span class='st'>"cfep"</span>, <span class='kw'>cfot</span> <span class='kw'>=</span> <span class='st'>"cfot"</span>, <span class='kw'>cfox</span> <span class='kw'>=</span> <span class='st'>"cfox"</span>, <span class='kw'>cfra</span> <span class='kw'>=</span> <span class='st'>"cfra"</span>,
<span class='kw'>cfta</span> <span class='kw'>=</span> <span class='st'>"cfta"</span>, <span class='kw'>cftr</span> <span class='kw'>=</span> <span class='st'>"cftr"</span>, <span class='kw'>cfur</span> <span class='kw'>=</span> <span class='st'>"cfur"</span>, <span class='kw'>chlo</span> <span class='kw'>=</span> <span class='st'>"chlo"</span>,
<span class='kw'>cipr</span> <span class='kw'>=</span> <span class='st'>"cipr"</span>, <span class='kw'>clar</span> <span class='kw'>=</span> <span class='st'>"clar"</span>, <span class='kw'>clin</span> <span class='kw'>=</span> <span class='st'>"clin"</span>, <span class='kw'>clox</span> <span class='kw'>=</span> <span class='st'>"clox"</span>,
<span class='kw'>coli</span> <span class='kw'>=</span> <span class='st'>"coli"</span>, <span class='kw'>czol</span> <span class='kw'>=</span> <span class='st'>"czol"</span>, <span class='kw'>dapt</span> <span class='kw'>=</span> <span class='st'>"dapt"</span>, <span class='kw'>doxy</span> <span class='kw'>=</span> <span class='st'>"doxy"</span>,
<span class='kw'>erta</span> <span class='kw'>=</span> <span class='st'>"erta"</span>, <span class='kw'>eryt</span> <span class='kw'>=</span> <span class='st'>"eryt"</span>, <span class='kw'>fosf</span> <span class='kw'>=</span> <span class='st'>"fosf"</span>, <span class='kw'>fusi</span> <span class='kw'>=</span> <span class='st'>"fusi"</span>,
<span class='kw'>gent</span> <span class='kw'>=</span> <span class='st'>"gent"</span>, <span class='kw'>imip</span> <span class='kw'>=</span> <span class='st'>"imip"</span>, <span class='kw'>kana</span> <span class='kw'>=</span> <span class='st'>"kana"</span>, <span class='kw'>levo</span> <span class='kw'>=</span> <span class='st'>"levo"</span>,
<span class='kw'>linc</span> <span class='kw'>=</span> <span class='st'>"linc"</span>, <span class='kw'>line</span> <span class='kw'>=</span> <span class='st'>"line"</span>, <span class='kw'>mero</span> <span class='kw'>=</span> <span class='st'>"mero"</span>, <span class='kw'>mezl</span> <span class='kw'>=</span> <span class='st'>"mezl"</span>,
<span class='kw'>mino</span> <span class='kw'>=</span> <span class='st'>"mino"</span>, <span class='kw'>moxi</span> <span class='kw'>=</span> <span class='st'>"moxi"</span>, <span class='kw'>nali</span> <span class='kw'>=</span> <span class='st'>"nali"</span>, <span class='kw'>neom</span> <span class='kw'>=</span> <span class='st'>"neom"</span>,
<span class='kw'>neti</span> <span class='kw'>=</span> <span class='st'>"neti"</span>, <span class='kw'>nitr</span> <span class='kw'>=</span> <span class='st'>"nitr"</span>, <span class='kw'>norf</span> <span class='kw'>=</span> <span class='st'>"norf"</span>, <span class='kw'>novo</span> <span class='kw'>=</span> <span class='st'>"novo"</span>,
<span class='kw'>oflo</span> <span class='kw'>=</span> <span class='st'>"oflo"</span>, <span class='kw'>oxac</span> <span class='kw'>=</span> <span class='st'>"oxac"</span>, <span class='kw'>peni</span> <span class='kw'>=</span> <span class='st'>"peni"</span>, <span class='kw'>pipe</span> <span class='kw'>=</span> <span class='st'>"pipe"</span>,
<span class='kw'>pita</span> <span class='kw'>=</span> <span class='st'>"pita"</span>, <span class='kw'>poly</span> <span class='kw'>=</span> <span class='st'>"poly"</span>, <span class='kw'>pris</span> <span class='kw'>=</span> <span class='st'>"pris"</span>, <span class='kw'>qida</span> <span class='kw'>=</span> <span class='st'>"qida"</span>,
<span class='kw'>rifa</span> <span class='kw'>=</span> <span class='st'>"rifa"</span>, <span class='kw'>roxi</span> <span class='kw'>=</span> <span class='st'>"roxi"</span>, <span class='kw'>siso</span> <span class='kw'>=</span> <span class='st'>"siso"</span>, <span class='kw'>teic</span> <span class='kw'>=</span> <span class='st'>"teic"</span>,
<span class='kw'>tetr</span> <span class='kw'>=</span> <span class='st'>"tetr"</span>, <span class='kw'>tica</span> <span class='kw'>=</span> <span class='st'>"tica"</span>, <span class='kw'>tige</span> <span class='kw'>=</span> <span class='st'>"tige"</span>, <span class='kw'>tobr</span> <span class='kw'>=</span> <span class='st'>"tobr"</span>,
<span class='kw'>trim</span> <span class='kw'>=</span> <span class='st'>"trim"</span>, <span class='kw'>trsu</span> <span class='kw'>=</span> <span class='st'>"trsu"</span>, <span class='kw'>vanc</span> <span class='kw'>=</span> <span class='st'>"vanc"</span>)
<span class='fu'>EUCAST_rules</span>(<span class='no'>...</span>)
<span class='fu'>interpretive_reading</span>(<span class='no'>...</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>tbl</th>
<td><p>table with antibiotic columns, like e.g. <code>amox</code> and <code>amcl</code></p></td>
</tr>
<tr>
<th>col_mo</th>
<td><p>column name of the unique IDs of the microorganisms (see <code><a href='as.mo.html'>mo</a></code>), defaults to the first column of class <code>mo</code>. Values will be coerced using <code><a href='as.mo.html'>as.mo</a></code>.</p></td>
</tr>
<tr>
<th>info</th>
<td><p>print progress</p></td>
</tr>
<tr>
<th>rules</th>
<td><p>a character vector that specifies which rules should be applied - one or more of <code><a href='https://www.rdocumentation.org/packages/base/topics/c'>c("breakpoints", "expert", "other", "all")</a></code></p></td>
</tr>
<tr>
<th>verbose</th>
<td><p>a logical to indicate whether extensive info should be returned as a <code>data.frame</code> with info about which rows and columns are effected</p></td>
</tr>
<tr>
<th>amcl, amik, amox, ampi, azit, azlo, aztr, cefa, cfep, cfot, cfox, cfra, cfta, cftr, cfur, chlo, cipr, clar, clin, clox, coli, czol, dapt, doxy, erta, eryt, fosf, fusi, gent, imip, kana, levo, linc, line, mero, mezl, mino, moxi, nali, neom, neti, nitr, norf, novo, oflo, oxac, peni, pipe, pita, poly, pris, qida, rifa, roxi, siso, teic, tetr, tica, tige, tobr, trim, trsu, vanc</th>
<td><p>column name of an antibiotic, see Antibiotics</p></td>
</tr>
<tr>
<th>...</th>
<td><p>parameters that are passed on to <code>eucast_rules</code></p></td>
</tr>
</table>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<ul>
<li><p>EUCAST Expert Rules. Version 2.0, 2012. <br />
Leclercq et al. <strong>EUCAST expert rules in antimicrobial susceptibility testing.</strong> <em>Clin Microbiol Infect.</em> 2013;19(2):141-60. <br />
<a href='https://doi.org/10.1111/j.1469-0691.2011.03703.x'>https://doi.org/10.1111/j.1469-0691.2011.03703.x</a></p></li>
<li><p>EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes Tables. Version 3.1, 2016. <br />
<a href='http://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf'>http://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Expert_Rules/Expert_rules_intrinsic_exceptional_V3.1.pdf</a></p></li>
<li><p>EUCAST Breakpoint tables for interpretation of MICs and zone diameters. Version 8.1, 2018. <br />
<a href='http://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_8.1_Breakpoint_Tables.xlsx'>http://www.eucast.org/fileadmin/src/media/PDFs/EUCAST_files/Breakpoint_tables/v_8.1_Breakpoint_Tables.xlsx</a></p></li>
</ul>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>The input of <code>tbl</code>, possibly with edited values of antibiotics. Or, if <code>verbose = TRUE</code>, a <code>data.frame</code> with verbose info.</p>
<h2 class="hasAnchor" id="antibiotics"><a class="anchor" href="#antibiotics"></a>Antibiotics</h2>
<p>To define antibiotics column names, input a text (case-insensitive) or use <code>NULL</code> to skip a column (e.g. <code>tica = NULL</code>). Non-existing columns will anyway be skipped with a warning.</p>
<p>Abbrevations of the column containing antibiotics in the form: <strong>abbreviation</strong>: generic name (<em>ATC code</em>)</p>
<p><strong>amcl</strong>: amoxicillin+clavulanic acid (<em>J01CR02</em>),
<strong>amik</strong>: amikacin (<em>J01GB06</em>),
<strong>amox</strong>: amoxicillin (<em>J01CA04</em>),
<strong>ampi</strong>: ampicillin (<em>J01CA01</em>),
<strong>azit</strong>: azithromycin (<em>J01FA10</em>),
<strong>azlo</strong>: azlocillin (<em>J01CA09</em>),
<strong>aztr</strong>: aztreonam (<em>J01DF01</em>),
<strong>cefa</strong>: cefaloridine (<em>J01DB02</em>),
<strong>cfep</strong>: cefepime (<em>J01DE01</em>),
<strong>cfot</strong>: cefotaxime (<em>J01DD01</em>),
<strong>cfox</strong>: cefoxitin (<em>J01DC01</em>),
<strong>cfra</strong>: cefradine (<em>J01DB09</em>),
<strong>cfta</strong>: ceftazidime (<em>J01DD02</em>),
<strong>cftr</strong>: ceftriaxone (<em>J01DD04</em>),
<strong>cfur</strong>: cefuroxime (<em>J01DC02</em>),
<strong>chlo</strong>: chloramphenicol (<em>J01BA01</em>),
<strong>cipr</strong>: ciprofloxacin (<em>J01MA02</em>),
<strong>clar</strong>: clarithromycin (<em>J01FA09</em>),
<strong>clin</strong>: clindamycin (<em>J01FF01</em>),
<strong>clox</strong>: flucloxacillin (<em>J01CF05</em>),
<strong>coli</strong>: colistin (<em>J01XB01</em>),
<strong>czol</strong>: cefazolin (<em>J01DB04</em>),
<strong>dapt</strong>: daptomycin (<em>J01XX09</em>),
<strong>doxy</strong>: doxycycline (<em>J01AA02</em>),
<strong>erta</strong>: ertapenem (<em>J01DH03</em>),
<strong>eryt</strong>: erythromycin (<em>J01FA01</em>),
<strong>fosf</strong>: fosfomycin (<em>J01XX01</em>),
<strong>fusi</strong>: fusidic acid (<em>J01XC01</em>),
<strong>gent</strong>: gentamicin (<em>J01GB03</em>),
<strong>imip</strong>: imipenem (<em>J01DH51</em>),
<strong>kana</strong>: kanamycin (<em>J01GB04</em>),
<strong>levo</strong>: levofloxacin (<em>J01MA12</em>),
<strong>linc</strong>: lincomycin (<em>J01FF02</em>),
<strong>line</strong>: linezolid (<em>J01XX08</em>),
<strong>mero</strong>: meropenem (<em>J01DH02</em>),
<strong>mezl</strong>: mezlocillin (<em>J01CA10</em>),
<strong>mino</strong>: minocycline (<em>J01AA08</em>),
<strong>moxi</strong>: moxifloxacin (<em>J01MA14</em>),
<strong>nali</strong>: nalidixic acid (<em>J01MB02</em>),
<strong>neom</strong>: neomycin (<em>J01GB05</em>),
<strong>neti</strong>: netilmicin (<em>J01GB07</em>),
<strong>nitr</strong>: nitrofurantoin (<em>J01XE01</em>),
<strong>norf</strong>: norfloxacin (<em>J01MA06</em>),
<strong>novo</strong>: novobiocin (an ATCvet code: <em>QJ01XX95</em>),
<strong>oflo</strong>: ofloxacin (<em>J01MA01</em>),
<strong>peni</strong>: penicillin (<em>J01RA01</em>),
<strong>pipe</strong>: piperacillin (<em>J01CA12</em>),
<strong>pita</strong>: piperacillin+tazobactam (<em>J01CR05</em>),
<strong>poly</strong>: polymyxin B (<em>J01XB02</em>),
<strong>pris</strong>: pristinamycin (<em>J01FG01</em>),
<strong>qida</strong>: quinupristin/dalfopristin (<em>J01FG02</em>),
<strong>rifa</strong>: rifampicin (<em>J04AB02</em>),
<strong>roxi</strong>: roxithromycin (<em>J01FA06</em>),
<strong>siso</strong>: sisomicin (<em>J01GB08</em>),
<strong>teic</strong>: teicoplanin (<em>J01XA02</em>),
<strong>tetr</strong>: tetracycline (<em>J01AA07</em>),
<strong>tica</strong>: ticarcillin (<em>J01CA13</em>),
<strong>tige</strong>: tigecycline (<em>J01AA12</em>),
<strong>tobr</strong>: tobramycin (<em>J01GB01</em>),
<strong>trim</strong>: trimethoprim (<em>J01EA01</em>),
<strong>trsu</strong>: sulfamethoxazole and trimethoprim (<em>J01EE01</em>),
<strong>vanc</strong>: vancomycin (<em>J01XA01</em>).</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='no'>a</span> <span class='kw'>&lt;-</span> <span class='fu'>eucast_rules</span>(<span class='no'>septic_patients</span>)</div><div class='output co'>#&gt; <span class='message'><span style='color: #0000BB;'>NOTE: Using column `</span><span style='color: #0000BB;font-weight: bold;'>mo</span><span style='color: #0000BB;'>` as input for `col_mo`.</span><span></span></div><div class='output co'>#&gt; <span class='warning'>Warning: These columns do not exist and will be ignored: azlo, aztr, cefa, cfra, clar, dapt, erta, fusi, levo, linc, mezl, mino, nali, neom, neti, novo, norf, oflo, pipe, poly, pris, qida, roxi, siso, tica.</span>
#&gt; <span class='warning'>THIS MAY STRONGLY INFLUENCE THE OUTCOME.</span></div><div class='output co'>#&gt; Rules by the European Committee on Antimicrobial Susceptibility Testing (EUCAST)
#&gt; </span><span style='font-weight: bold;'>
#&gt; EUCAST Clinical Breakpoints (v8.1, 2018)
#&gt; </span><span>Enterobacteriales (Order)</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-style: italic;'>Staphylococcus</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-style: italic;'>Enterococcus</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-style: italic;'>Streptococcus</span><span> groups A, B, C, G</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-style: italic;'>Streptococcus pneumoniae</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Viridans group streptococci</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-style: italic;'>Haemophilus influenzae</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-style: italic;'>Moraxella catarrhalis</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Anaerobic Gram positives</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Anaerobic Gram negatives</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-style: italic;'>Pasteurella multocida</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-style: italic;'>Campylobacter jejuni</span><span> and </span><span style='font-style: italic;'>C. coli</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-style: italic;'>Aerococcus sanguinicola</span><span> and </span><span style='font-style: italic;'>A. urinae</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-style: italic;'>Kingella kingae</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-weight: bold;'>
#&gt; EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes (v3.1, 2016)
#&gt; </span><span>Table 1: Intrinsic resistance in </span><span style='font-style: italic;'>Enterobacteriaceae</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Table 2: Intrinsic resistance in non-fermentative Gram-negative bacteria</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Table 3: Intrinsic resistance in other Gram-negative bacteria</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Table 4: Intrinsic resistance in Gram-positive bacteria</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Table 8: Interpretive rules for B-lactam agents and Gram-positive cocci</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Table 9: Interpretive rules for B-lactam agents and Gram-negative rods</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Table 10: Interpretive rules for B-lactam agents and other Gram-negative bacteria</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Table 11: Interpretive rules for macrolides, lincosamides, and streptogramins</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Table 12: Interpretive rules for aminoglycosides</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Table 13: Interpretive rules for quinolones</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-weight: bold;'>
#&gt; Other rules
#&gt; </span><span>Non-EUCAST: ampicillin = R where amoxicillin/clav acid = R</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Non-EUCAST: piperacillin = R where piperacillin/tazobactam = R</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Non-EUCAST: trimethoprim = R where trimethoprim/sulfa = R</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Non-EUCAST: amoxicillin/clav acid = S where ampicillin = S</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Non-EUCAST: piperacillin/tazobactam = S where piperacillin = S</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Non-EUCAST: trimethoprim/sulfa = S where trimethoprim = S</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-weight: bold;'>
#&gt; =&gt; EUCAST rules affected 1,980 out of 2,000 rows -&gt; </span><span style='color: #00BB00;font-weight: bold;'>changed 0 test results.
#&gt;
#&gt; </span><span></div><div class='input'>
<span class='no'>a</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/data.frame'>data.frame</a></span>(<span class='kw'>mo</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"Staphylococcus aureus"</span>,
<span class='st'>"Enterococcus faecalis"</span>,
<span class='st'>"Escherichia coli"</span>,
<span class='st'>"Klebsiella pneumoniae"</span>,
<span class='st'>"Pseudomonas aeruginosa"</span>),
<span class='kw'>vanc</span> <span class='kw'>=</span> <span class='st'>"-"</span>, <span class='co'># Vancomycin</span>
<span class='kw'>amox</span> <span class='kw'>=</span> <span class='st'>"-"</span>, <span class='co'># Amoxicillin</span>
<span class='kw'>coli</span> <span class='kw'>=</span> <span class='st'>"-"</span>, <span class='co'># Colistin</span>
<span class='kw'>cfta</span> <span class='kw'>=</span> <span class='st'>"-"</span>, <span class='co'># Ceftazidime</span>
<span class='kw'>cfur</span> <span class='kw'>=</span> <span class='st'>"-"</span>, <span class='co'># Cefuroxime</span>
<span class='kw'>peni</span> <span class='kw'>=</span> <span class='st'>"S"</span>, <span class='co'># Benzylpenicillin</span>
<span class='kw'>cfox</span> <span class='kw'>=</span> <span class='st'>"S"</span>, <span class='co'># Cefoxitin</span>
<span class='kw'>stringsAsFactors</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='no'>a</span></div><div class='output co'>#&gt; mo vanc amox coli cfta cfur peni cfox
#&gt; 1 Staphylococcus aureus - - - - - S S
#&gt; 2 Enterococcus faecalis - - - - - S S
#&gt; 3 Escherichia coli - - - - - S S
#&gt; 4 Klebsiella pneumoniae - - - - - S S
#&gt; 5 Pseudomonas aeruginosa - - - - - S S</div><div class='input'><span class='co'># mo vanc amox coli cfta cfur peni cfox</span>
<span class='co'># 1 Staphylococcus aureus - - - - - S S</span>
<span class='co'># 2 Enterococcus faecalis - - - - - S S</span>
<span class='co'># 3 Escherichia coli - - - - - S S</span>
<span class='co'># 4 Klebsiella pneumoniae - - - - - S S</span>
<span class='co'># 5 Pseudomonas aeruginosa - - - - - S S</span>
<span class='no'>b</span> <span class='kw'>&lt;-</span> <span class='fu'>eucast_rules</span>(<span class='no'>a</span>, <span class='st'>"mo"</span>) <span class='co'># 18 results are forced as R or S</span></div><div class='output co'>#&gt; <span class='warning'>Warning: These columns do not exist and will be ignored: amcl, amik, ampi, azit, azlo, aztr, cefa, cfra, cfep, cfot, cftr, chlo, cipr, clar, clin, clox, czol, dapt, doxy, erta, eryt, fosf, fusi, gent, imip, kana, levo, linc, line, mero, mezl, mino, moxi, nali, neom, neti, nitr, novo, norf, oflo, oxac, pipe, pita, poly, pris, qida, rifa, roxi, siso, teic, tetr, tica, tige, tobr, trim, trsu.</span>
#&gt; <span class='warning'>THIS MAY STRONGLY INFLUENCE THE OUTCOME.</span></div><div class='output co'>#&gt; Rules by the European Committee on Antimicrobial Susceptibility Testing (EUCAST)
#&gt; </span><span style='font-weight: bold;'>
#&gt; EUCAST Clinical Breakpoints (v8.1, 2018)
#&gt; </span><span>Enterobacteriales (Order)</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-style: italic;'>Staphylococcus</span><span style='color: #0000BB;'> (2 changes)
#&gt; </span><span style='font-style: italic;'>Enterococcus</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-style: italic;'>Streptococcus</span><span> groups A, B, C, G</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-style: italic;'>Streptococcus pneumoniae</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Viridans group streptococci</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-style: italic;'>Haemophilus influenzae</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-style: italic;'>Moraxella catarrhalis</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Anaerobic Gram positives</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Anaerobic Gram negatives</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-style: italic;'>Pasteurella multocida</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-style: italic;'>Campylobacter jejuni</span><span> and </span><span style='font-style: italic;'>C. coli</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-style: italic;'>Aerococcus sanguinicola</span><span> and </span><span style='font-style: italic;'>A. urinae</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-style: italic;'>Kingella kingae</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-weight: bold;'>
#&gt; EUCAST Expert Rules, Intrinsic Resistance and Exceptional Phenotypes (v3.1, 2016)
#&gt; </span><span>Table 1: Intrinsic resistance in </span><span style='font-style: italic;'>Enterobacteriaceae</span><span style='color: #0000BB;'> (5 changes)
#&gt; </span><span>Table 2: Intrinsic resistance in non-fermentative Gram-negative bacteria</span><span style='color: #0000BB;'> (5 changes)
#&gt; </span><span>Table 3: Intrinsic resistance in other Gram-negative bacteria</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Table 4: Intrinsic resistance in Gram-positive bacteria</span><span style='color: #0000BB;'> (6 changes)
#&gt; </span><span>Table 8: Interpretive rules for B-lactam agents and Gram-positive cocci</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Table 9: Interpretive rules for B-lactam agents and Gram-negative rods</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Table 10: Interpretive rules for B-lactam agents and other Gram-negative bacteria</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Table 11: Interpretive rules for macrolides, lincosamides, and streptogramins</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Table 12: Interpretive rules for aminoglycosides</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Table 13: Interpretive rules for quinolones</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-weight: bold;'>
#&gt; Other rules
#&gt; </span><span>Non-EUCAST: ampicillin = R where amoxicillin/clav acid = R</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Non-EUCAST: piperacillin = R where piperacillin/tazobactam = R</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Non-EUCAST: trimethoprim = R where trimethoprim/sulfa = R</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Non-EUCAST: amoxicillin/clav acid = S where ampicillin = S</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Non-EUCAST: piperacillin/tazobactam = S where piperacillin = S</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span>Non-EUCAST: trimethoprim/sulfa = S where trimethoprim = S</span><span style='color: #00BB00;'> (no changes)
#&gt; </span><span style='font-weight: bold;'>
#&gt; =&gt; EUCAST rules affected 5 out of 5 rows -&gt; </span><span style='color: #0000BB;font-weight: bold;'>changed 18 test results.
#&gt;
#&gt; </span><span></div><div class='input'>
<span class='no'>b</span></div><div class='output co'>#&gt; mo vanc amox coli cfta cfur peni cfox
#&gt; 1 Staphylococcus aureus - S R R S S S
#&gt; 2 Enterococcus faecalis - - R R R S R
#&gt; 3 Escherichia coli R - - - - R S
#&gt; 4 Klebsiella pneumoniae R R - - - R S
#&gt; 5 Pseudomonas aeruginosa R R - - R R R</div><div class='input'># mo vanc amox coli cfta cfur peni cfox
# 1 Staphylococcus aureus - S R R S S S
# 2 Enterococcus faecalis - - R R R S R
# 3 Escherichia coli R - - - - R S
# 4 Klebsiella pneumoniae R R - - - R S
# 5 Pseudomonas aeruginosa R R - - R R R
</div></span></pre>
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<h1>Frequency table</h1>
<div class="hidden name"><code>freq.Rd</code></div>
</div>
<div class="ref-description">
<p>Create a frequency table of a vector with items or a data frame. Supports quasiquotation and markdown for reports. <code>top_freq</code> can be used to get the top/bottom <em>n</em> items of a frequency table, with counts as names.</p>
</div>
<pre class="usage"><span class='fu'>frequency_tbl</span>(<span class='no'>x</span>, <span class='no'>...</span>, <span class='kw'>sort.count</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
<span class='kw'>nmax</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a></span>(<span class='st'>"max.print.freq"</span>), <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>row.names</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
<span class='kw'>markdown</span> <span class='kw'>=</span> !<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/interactive'>interactive</a></span>(), <span class='kw'>digits</span> <span class='kw'>=</span> <span class='fl'>2</span>, <span class='kw'>quote</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
<span class='kw'>header</span> <span class='kw'>=</span> !<span class='no'>markdown</span>, <span class='kw'>title</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>na</span> <span class='kw'>=</span> <span class='st'>"&lt;NA&gt;"</span>, <span class='kw'>droplevels</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
<span class='kw'>sep</span> <span class='kw'>=</span> <span class='st'>" "</span>, <span class='kw'>decimal.mark</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a></span>(<span class='st'>"OutDec"</span>),
<span class='kw'>big.mark</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/ifelse'>ifelse</a></span>(<span class='no'>decimal.mark</span> <span class='kw'>!=</span> <span class='st'>","</span>, <span class='st'>","</span>, <span class='st'>"."</span>))
<span class='fu'>freq</span>(<span class='no'>x</span>, <span class='no'>...</span>, <span class='kw'>sort.count</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>nmax</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a></span>(<span class='st'>"max.print.freq"</span>),
<span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>row.names</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>markdown</span> <span class='kw'>=</span> !<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/interactive'>interactive</a></span>(),
<span class='kw'>digits</span> <span class='kw'>=</span> <span class='fl'>2</span>, <span class='kw'>quote</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>header</span> <span class='kw'>=</span> !<span class='no'>markdown</span>, <span class='kw'>title</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
<span class='kw'>na</span> <span class='kw'>=</span> <span class='st'>"&lt;NA&gt;"</span>, <span class='kw'>droplevels</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>sep</span> <span class='kw'>=</span> <span class='st'>" "</span>,
<span class='kw'>decimal.mark</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a></span>(<span class='st'>"OutDec"</span>), <span class='kw'>big.mark</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/ifelse'>ifelse</a></span>(<span class='no'>decimal.mark</span> <span class='kw'>!=</span>
<span class='st'>","</span>, <span class='st'>","</span>, <span class='st'>"."</span>))
<span class='fu'>top_freq</span>(<span class='no'>f</span>, <span class='no'>n</span>)
<span class='co'># S3 method for frequency_tbl</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/print'>print</a></span>(<span class='no'>x</span>, <span class='kw'>nmax</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a></span>(<span class='st'>"max.print.freq"</span>,
<span class='kw'>default</span> <span class='kw'>=</span> <span class='fl'>15</span>), <span class='kw'>markdown</span> <span class='kw'>=</span> !<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/interactive'>interactive</a></span>(), <span class='kw'>header</span> <span class='kw'>=</span> !<span class='no'>markdown</span>,
<span class='kw'>decimal.mark</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a></span>(<span class='st'>"OutDec"</span>), <span class='kw'>big.mark</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/ifelse'>ifelse</a></span>(<span class='no'>decimal.mark</span> <span class='kw'>!=</span>
<span class='st'>","</span>, <span class='st'>","</span>, <span class='st'>"."</span>), <span class='no'>...</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>x</th>
<td><p>vector of any class or a <code><a href='https://www.rdocumentation.org/packages/base/topics/data.frame'>data.frame</a></code>, <code>tibble</code> (may contain a grouping variable) or <code><a href='https://www.rdocumentation.org/packages/base/topics/table'>table</a></code></p></td>
</tr>
<tr>
<th>...</th>
<td><p>up to nine different columns of <code>x</code> when <code>x</code> is a <code>data.frame</code> or <code>tibble</code>, to calculate frequencies from - see Examples</p></td>
</tr>
<tr>
<th>sort.count</th>
<td><p>sort on count, i.e. frequencies. This will be <code>TRUE</code> at default for everything except when using grouping variables.</p></td>
</tr>
<tr>
<th>nmax</th>
<td><p>number of row to print. The default, <code>15</code>, uses <code><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a>("max.print.freq")</code>. Use <code>nmax = 0</code>, <code>nmax = Inf</code>, <code>nmax = NULL</code> or <code>nmax = NA</code> to print all rows.</p></td>
</tr>
<tr>
<th>na.rm</th>
<td><p>a logical value indicating whether <code>NA</code> values should be removed from the frequency table. The header (if set) will always print the amount of <code>NA</code>s.</p></td>
</tr>
<tr>
<th>row.names</th>
<td><p>a logical value indicating whether row indices should be printed as <code>1:nrow(x)</code></p></td>
</tr>
<tr>
<th>markdown</th>
<td><p>a logical value indicating whether the frequency table should be printed in markdown format. This will print all rows and is default behaviour in non-interactive R sessions (like when knitting RMarkdown files).</p></td>
</tr>
<tr>
<th>digits</th>
<td><p>how many significant digits are to be used for numeric values in the header (not for the items themselves, that depends on <code><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a>("digits")</code>)</p></td>
</tr>
<tr>
<th>quote</th>
<td><p>a logical value indicating whether or not strings should be printed with surrounding quotes</p></td>
</tr>
<tr>
<th>header</th>
<td><p>a logical value indicating whether an informative header should be printed</p></td>
</tr>
<tr>
<th>title</th>
<td><p>text to show above frequency table, at default to tries to coerce from the variables passed to <code>x</code></p></td>
</tr>
<tr>
<th>na</th>
<td><p>a character string to should be used to show empty (<code>NA</code>) values (only useful when <code>na.rm = FALSE</code>)</p></td>
</tr>
<tr>
<th>droplevels</th>
<td><p>a logical value indicating whether in factors empty levels should be dropped</p></td>
</tr>
<tr>
<th>sep</th>
<td><p>a character string to separate the terms when selecting multiple columns</p></td>
</tr>
<tr>
<th>decimal.mark</th>
<td><p><!-- % -->
used for prettying (longish) numerical and complex sequences.
Passed to <code><a href='https://www.rdocumentation.org/packages/base/topics/formatc'>prettyNum</a></code>: that help page explains the details.</p></td>
</tr>
<tr>
<th>big.mark</th>
<td><p><!-- % -->
used for prettying (longish) numerical and complex sequences.
Passed to <code><a href='https://www.rdocumentation.org/packages/base/topics/formatc'>prettyNum</a></code>: that help page explains the details.</p></td>
</tr>
<tr>
<th>f</th>
<td><p>a frequency table</p></td>
</tr>
<tr>
<th>n</th>
<td><p>number of top <em>n</em> items to return, use -n for the bottom <em>n</em> items. It will include more than <code>n</code> rows if there are ties.</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>A <code>data.frame</code> (with an additional class <code>"frequency_tbl"</code>) with five columns: <code>item</code>, <code>count</code>, <code>percent</code>, <code>cum_count</code> and <code>cum_percent</code>.</p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>Frequency tables (or frequency distributions) are summaries of the distribution of values in a sample. With the `freq` function, you can create univariate frequency tables. Multiple variables will be pasted into one variable, so it forces a univariate distribution. This package also has a vignette available to explain the use of this function further, run <code><a href='https://www.rdocumentation.org/packages/utils/topics/browseVignettes'>browseVignettes("AMR")</a></code> to read it.</p>
<p>For numeric values of any class, these additional values will all be calculated with <code>na.rm = TRUE</code> and shown into the header:</p><ul>
<li><p>Mean, using <code><a href='https://www.rdocumentation.org/packages/base/topics/mean'>mean</a></code></p></li>
<li><p>Standard Deviation, using <code><a href='https://www.rdocumentation.org/packages/stats/topics/sd'>sd</a></code></p></li>
<li><p>Coefficient of Variation (CV), the standard deviation divided by the mean</p></li>
<li><p>Mean Absolute Deviation (MAD), using <code><a href='https://www.rdocumentation.org/packages/stats/topics/mad'>mad</a></code></p></li>
<li><p>Tukey Five-Number Summaries (minimum, Q1, median, Q3, maximum), using <code><a href='https://www.rdocumentation.org/packages/stats/topics/fivenum'>fivenum</a></code></p></li>
<li><p>Interquartile Range (IQR) calculated as <code>Q3 - Q1</code> using the Tukey Five-Number Summaries, i.e. <strong>not</strong> using the <code><a href='https://www.rdocumentation.org/packages/stats/topics/quantile'>quantile</a></code> function</p></li>
<li><p>Coefficient of Quartile Variation (CQV, sometimes called coefficient of dispersion), calculated as <code>(Q3 - Q1) / (Q3 + Q1)</code> using the Tukey Five-Number Summaries</p></li>
<li><p>Outliers (total count and unique count), using <code><a href='https://www.rdocumentation.org/packages/grDevices/topics/boxplot.stats'>boxplot.stats</a></code></p></li>
</ul>
<p>For dates and times of any class, these additional values will be calculated with <code>na.rm = TRUE</code> and shown into the header:</p><ul>
<li><p>Oldest, using <code><a href='https://www.rdocumentation.org/packages/base/topics/Extremes'>min</a></code></p></li>
<li><p>Newest, using <code><a href='https://www.rdocumentation.org/packages/base/topics/Extremes'>max</a></code>, with difference between newest and oldest</p></li>
<li><p>Median, using <code><a href='https://www.rdocumentation.org/packages/stats/topics/median'>median</a></code>, with percentage since oldest</p></li>
</ul>
<p>In factors, all factor levels that are not existing in the input data will be dropped.</p>
<p>The function <code>top_freq</code> uses <code><a href='http://dplyr.tidyverse.org/reference/top_n.html'>top_n</a></code> internally and will include more than <code>n</code> rows if there are ties.</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='co'># this all gives the same result:</span>
<span class='fu'>freq</span>(<span class='no'>septic_patients</span>$<span class='no'>hospital_id</span>)</div><div class='output co'>#&gt;
#&gt;
#&gt; **Frequency table**
#&gt;
#&gt;
#&gt; | |Item | Count| Percent| Cum. Count| Cum. Percent|
#&gt; |:--|:----|-----:|-------:|----------:|------------:|
#&gt; |1 |D | 762| 38.1%| 762| 38.1%|
#&gt; |2 |B | 663| 33.2%| 1,425| 71.3%|
#&gt; |3 |A | 321| 16.1%| 1,746| 87.3%|
#&gt; |4 |C | 254| 12.7%| 2,000| 100.0%|
#&gt;
#&gt; </div><div class='input'><span class='fu'>freq</span>(<span class='no'>septic_patients</span>[, <span class='st'>"hospital_id"</span>])</div><div class='output co'>#&gt;
#&gt;
#&gt; **Frequency table**
#&gt;
#&gt;
#&gt; | |Item | Count| Percent| Cum. Count| Cum. Percent|
#&gt; |:--|:----|-----:|-------:|----------:|------------:|
#&gt; |1 |D | 762| 38.1%| 762| 38.1%|
#&gt; |2 |B | 663| 33.2%| 1,425| 71.3%|
#&gt; |3 |A | 321| 16.1%| 1,746| 87.3%|
#&gt; |4 |C | 254| 12.7%| 2,000| 100.0%|
#&gt;
#&gt; </div><div class='input'><span class='no'>septic_patients</span>$<span class='no'>hospital_id</span> <span class='kw'>%&gt;%</span> <span class='fu'>freq</span>()</div><div class='output co'>#&gt;
#&gt;
#&gt; **Frequency table**
#&gt;
#&gt;
#&gt; | |Item | Count| Percent| Cum. Count| Cum. Percent|
#&gt; |:--|:----|-----:|-------:|----------:|------------:|
#&gt; |1 |D | 762| 38.1%| 762| 38.1%|
#&gt; |2 |B | 663| 33.2%| 1,425| 71.3%|
#&gt; |3 |A | 321| 16.1%| 1,746| 87.3%|
#&gt; |4 |C | 254| 12.7%| 2,000| 100.0%|
#&gt;
#&gt; </div><div class='input'><span class='no'>septic_patients</span>[, <span class='st'>"hospital_id"</span>] <span class='kw'>%&gt;%</span> <span class='fu'>freq</span>()</div><div class='output co'>#&gt;
#&gt;
#&gt; **Frequency table**
#&gt;
#&gt;
#&gt; | |Item | Count| Percent| Cum. Count| Cum. Percent|
#&gt; |:--|:----|-----:|-------:|----------:|------------:|
#&gt; |1 |D | 762| 38.1%| 762| 38.1%|
#&gt; |2 |B | 663| 33.2%| 1,425| 71.3%|
#&gt; |3 |A | 321| 16.1%| 1,746| 87.3%|
#&gt; |4 |C | 254| 12.7%| 2,000| 100.0%|
#&gt;
#&gt; </div><div class='input'><span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span> <span class='fu'>freq</span>(<span class='st'>"hospital_id"</span>)</div><div class='output co'>#&gt;
#&gt;
#&gt; **Frequency table of `hospital_id`**
#&gt;
#&gt;
#&gt; | |Item | Count| Percent| Cum. Count| Cum. Percent|
#&gt; |:--|:----|-----:|-------:|----------:|------------:|
#&gt; |1 |D | 762| 38.1%| 762| 38.1%|
#&gt; |2 |B | 663| 33.2%| 1,425| 71.3%|
#&gt; |3 |A | 321| 16.1%| 1,746| 87.3%|
#&gt; |4 |C | 254| 12.7%| 2,000| 100.0%|
#&gt;
#&gt; </div><div class='input'><span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span> <span class='fu'>freq</span>(<span class='no'>hospital_id</span>) <span class='co'>#&lt;- easiest to remember (tidyverse)</span></div><div class='output co'>#&gt;
#&gt;
#&gt; **Frequency table of `hospital_id`**
#&gt;
#&gt;
#&gt; | |Item | Count| Percent| Cum. Count| Cum. Percent|
#&gt; |:--|:----|-----:|-------:|----------:|------------:|
#&gt; |1 |D | 762| 38.1%| 762| 38.1%|
#&gt; |2 |B | 663| 33.2%| 1,425| 71.3%|
#&gt; |3 |A | 321| 16.1%| 1,746| 87.3%|
#&gt; |4 |C | 254| 12.7%| 2,000| 100.0%|
#&gt;
#&gt; </div><div class='input'>
<span class='co'># you could also use `select` or `pull` to get your variables</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>hospital_id</span> <span class='kw'>==</span> <span class='st'>"A"</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>mo</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>()</div><div class='output co'>#&gt;
#&gt;
#&gt; **Frequency table**
#&gt;
#&gt;
#&gt; | |Item | Count| Percent| Cum. Count| Cum. Percent|
#&gt; |:--|:------------|-----:|-------:|----------:|------------:|
#&gt; |1 |B_ESCHR_COL | 62| 19.3%| 62| 19.3%|
#&gt; |2 |B_STPHY_EPI | 46| 14.3%| 108| 33.6%|
#&gt; |3 |B_STPHY_CNS | 38| 11.8%| 146| 45.5%|
#&gt; |4 |B_STPHY_AUR | 35| 10.9%| 181| 56.4%|
#&gt; |5 |B_STPHY_HOM | 25| 7.8%| 206| 64.2%|
#&gt; |6 |B_STRPTC_PNE | 12| 3.7%| 218| 67.9%|
#&gt; |7 |B_PROTS_MIR | 11| 3.4%| 229| 71.3%|
#&gt; |8 |B_ENTRC_FAE | 10| 3.1%| 239| 74.5%|
#&gt; |9 |B_KLBSL_PNE | 8| 2.5%| 247| 76.9%|
#&gt; |10 |B_STRPTC_PYO | 7| 2.2%| 254| 79.1%|
#&gt; |11 |B_BCTRD_FRA | 5| 1.6%| 259| 80.7%|
#&gt; |12 |B_KLBSL_OXY | 5| 1.6%| 264| 82.2%|
#&gt; |13 |B_STRPTC | 5| 1.6%| 269| 83.8%|
#&gt; |14 |B_ENTRC_IUM | 4| 1.2%| 273| 85.0%|
#&gt; |15 |B_STRPTC_MIT | 4| 1.2%| 277| 86.3%|
#&gt; |16 |B_CRYNB | 3| 0.9%| 280| 87.2%|
#&gt; |17 |B_PDMNS_AER | 3| 0.9%| 283| 88.2%|
#&gt; |18 |B_STPHY_CAP | 3| 0.9%| 286| 89.1%|
#&gt; |19 |B_STRPTC_DYS | 3| 0.9%| 289| 90.0%|
#&gt; |20 |F_CANDD_GLB | 3| 0.9%| 292| 91.0%|
#&gt; |21 |B_ACNTB | 2| 0.6%| 294| 91.6%|
#&gt; |22 |B_ENTRB_CLO | 2| 0.6%| 296| 92.2%|
#&gt; |23 |B_HMPHL_INF | 2| 0.6%| 298| 92.8%|
#&gt; |24 |B_MCRCCC | 2| 0.6%| 300| 93.5%|
#&gt; |25 |B_PROTS_VUL | 2| 0.6%| 302| 94.1%|
#&gt; |26 |B_SERRT_MAR | 2| 0.6%| 304| 94.7%|
#&gt; |27 |B_STPHY_COH | 2| 0.6%| 306| 95.3%|
#&gt; |28 |B_STRPTC_BOV | 2| 0.6%| 308| 96.0%|
#&gt; |29 |B_AMYCS_ODO | 1| 0.3%| 309| 96.3%|
#&gt; |30 |B_ARCCC_URI | 1| 0.3%| 310| 96.6%|
#&gt; |31 |B_CTRDM_PER | 1| 0.3%| 311| 96.9%|
#&gt; |32 |B_CTRDM_SEP | 1| 0.3%| 312| 97.2%|
#&gt; |33 |B_STPHY_SCH | 1| 0.3%| 313| 97.5%|
#&gt; |34 |B_STRPTC_AGA | 1| 0.3%| 314| 97.8%|
#&gt; |35 |B_STRPTC_EQU | 1| 0.3%| 315| 98.1%|
#&gt; |36 |B_STRPTC_GRA | 1| 0.3%| 316| 98.4%|
#&gt; |37 |B_STRPTC_GRB | 1| 0.3%| 317| 98.8%|
#&gt; |38 |B_STRPTC_SAN | 1| 0.3%| 318| 99.1%|
#&gt; |39 |B_VLLNL_PAR | 1| 0.3%| 319| 99.4%|
#&gt; |40 |F_CANDD_ALB | 1| 0.3%| 320| 99.7%|
#&gt; |41 |F_CANDD_TRO | 1| 0.3%| 321| 100.0%|
#&gt;
#&gt; </div><div class='input'>
<span class='co'># multiple selected variables will be pasted together</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='no'>left_join_microorganisms</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>hospital_id</span> <span class='kw'>==</span> <span class='st'>"A"</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>genus</span>, <span class='no'>species</span>)</div><div class='output co'>#&gt; <span class='message'>Joining, by = "mo"</span></div><div class='output co'>#&gt;
#&gt;
#&gt; **Frequency table of `genus` and `species`**
#&gt;
#&gt;
#&gt; | |Item | Count| Percent| Cum. Count| Cum. Percent|
#&gt; |:--|:---------------------------------|-----:|-------:|----------:|------------:|
#&gt; |1 |Escherichia coli | 62| 19.3%| 62| 19.3%|
#&gt; |2 |Staphylococcus epidermidis | 46| 14.3%| 108| 33.6%|
#&gt; |3 |Staphylococcus coagulase negative | 38| 11.8%| 146| 45.5%|
#&gt; |4 |Staphylococcus aureus | 35| 10.9%| 181| 56.4%|
#&gt; |5 |Staphylococcus hominis | 25| 7.8%| 206| 64.2%|
#&gt; |6 |Streptococcus pneumoniae | 12| 3.7%| 218| 67.9%|
#&gt; |7 |Proteus mirabilis | 11| 3.4%| 229| 71.3%|
#&gt; |8 |Enterococcus faecalis | 10| 3.1%| 239| 74.5%|
#&gt; |9 |Klebsiella pneumoniae | 8| 2.5%| 247| 76.9%|
#&gt; |10 |Streptococcus pyogenes | 7| 2.2%| 254| 79.1%|
#&gt; |11 |Bacteroides fragilis | 5| 1.6%| 259| 80.7%|
#&gt; |12 |Klebsiella oxytoca | 5| 1.6%| 264| 82.2%|
#&gt; |13 |Streptococcus species | 5| 1.6%| 269| 83.8%|
#&gt; |14 |Enterococcus faecium | 4| 1.2%| 273| 85.0%|
#&gt; |15 |Streptococcus mitis | 4| 1.2%| 277| 86.3%|
#&gt; |16 |Candida glabrata | 3| 0.9%| 280| 87.2%|
#&gt; |17 |Corynebacterium species | 3| 0.9%| 283| 88.2%|
#&gt; |18 |Pseudomonas aeruginosa | 3| 0.9%| 286| 89.1%|
#&gt; |19 |Staphylococcus capitis | 3| 0.9%| 289| 90.0%|
#&gt; |20 |Streptococcus dysgalactiae | 3| 0.9%| 292| 91.0%|
#&gt; |21 |Acinetobacter species | 2| 0.6%| 294| 91.6%|
#&gt; |22 |Enterobacter cloacae | 2| 0.6%| 296| 92.2%|
#&gt; |23 |Haemophilus influenzae | 2| 0.6%| 298| 92.8%|
#&gt; |24 |Micrococcus species | 2| 0.6%| 300| 93.5%|
#&gt; |25 |Proteus vulgaris | 2| 0.6%| 302| 94.1%|
#&gt; |26 |Serratia marcescens | 2| 0.6%| 304| 94.7%|
#&gt; |27 |Staphylococcus cohnii | 2| 0.6%| 306| 95.3%|
#&gt; |28 |Streptococcus bovis | 2| 0.6%| 308| 96.0%|
#&gt; |29 |Actinomyces odontolyticus | 1| 0.3%| 309| 96.3%|
#&gt; |30 |Aerococcus urinae | 1| 0.3%| 310| 96.6%|
#&gt; |31 |Candida albicans | 1| 0.3%| 311| 96.9%|
#&gt; |32 |Candida tropicalis | 1| 0.3%| 312| 97.2%|
#&gt; |33 |Clostridium perfringens | 1| 0.3%| 313| 97.5%|
#&gt; |34 |Clostridium septicum | 1| 0.3%| 314| 97.8%|
#&gt; |35 |Staphylococcus schleiferi | 1| 0.3%| 315| 98.1%|
#&gt; |36 |Streptococcus agalactiae | 1| 0.3%| 316| 98.4%|
#&gt; |37 |Streptococcus equi | 1| 0.3%| 317| 98.8%|
#&gt; |38 |Streptococcus group A | 1| 0.3%| 318| 99.1%|
#&gt; |39 |Streptococcus group B | 1| 0.3%| 319| 99.4%|
#&gt; |40 |Streptococcus sanguinis | 1| 0.3%| 320| 99.7%|
#&gt; |41 |Veillonella parvula | 1| 0.3%| 321| 100.0%|
#&gt;
#&gt; </div><div class='input'>
<span class='co'># group a variable and analyse another</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>gender</span>)</div><div class='output co'>#&gt;
#&gt;
#&gt; **Frequency table of `gender` (grouped by `hospital_id`)**
#&gt;
#&gt;
#&gt; | |Group |Item | Count| Percent| Cum. Count| Cum. Percent|
#&gt; |:--|:-----|:----|-----:|-------:|----------:|------------:|
#&gt; |1 |1 |F | 148| 7.4%| 148| 7.4%|
#&gt; |2 | |M | 173| 8.7%| 321| 16.1%|
#&gt; |3 |2 |F | 332| 16.6%| 332| 16.6%|
#&gt; |4 | |M | 331| 16.6%| 663| 33.2%|
#&gt; |5 |3 |F | 121| 6.1%| 121| 6.1%|
#&gt; |6 | |M | 133| 6.7%| 254| 12.7%|
#&gt; |7 |4 |F | 368| 18.4%| 368| 18.4%|
#&gt; |8 | |M | 394| 19.7%| 762| 38.1%|
#&gt;
#&gt; </div><div class='input'>
<span class='co'># get top 10 bugs of hospital A as a vector</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>hospital_id</span> <span class='kw'>==</span> <span class='st'>"A"</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>mo</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>top_freq</span>(<span class='fl'>10</span>)</div><div class='output co'>#&gt; 62 46 38 35 25
#&gt; "B_ESCHR_COL" "B_STPHY_EPI" "B_STPHY_CNS" "B_STPHY_AUR" "B_STPHY_HOM"
#&gt; 12 11 10 8 7
#&gt; "B_STRPTC_PNE" "B_PROTS_MIR" "B_ENTRC_FAE" "B_KLBSL_PNE" "B_STRPTC_PYO" </div><div class='input'>
<span class='co'># save frequency table to an object</span>
<span class='no'>years</span> <span class='kw'>&lt;-</span> <span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>year</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/format'>format</a></span>(<span class='no'>date</span>, <span class='st'>"%Y"</span>)) <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>year</span>)
<span class='co'># show only the top 5</span>
<span class='no'>years</span> <span class='kw'>%&gt;%</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/print'>print</a></span>(<span class='kw'>nmax</span> <span class='kw'>=</span> <span class='fl'>5</span>)</div><div class='output co'>#&gt;
#&gt;
#&gt; **Frequency table of `year`**
#&gt;
#&gt;
#&gt; | |Item | Count| Percent| Cum. Count| Cum. Percent|
#&gt; |:--|:----|-----:|-------:|----------:|------------:|
#&gt; |1 |2017 | 168| 8.4%| 168| 8.4%|
#&gt; |2 |2004 | 167| 8.4%| 335| 16.8%|
#&gt; |3 |2016 | 143| 7.2%| 478| 23.9%|
#&gt; |4 |2002 | 136| 6.8%| 614| 30.7%|
#&gt; |5 |2003 | 135| 6.8%| 749| 37.5%|
#&gt; |6 |2006 | 134| 6.7%| 883| 44.2%|
#&gt; |7 |2005 | 127| 6.4%| 1,010| 50.5%|
#&gt; |8 |2008 | 125| 6.3%| 1,135| 56.8%|
#&gt; |9 |2011 | 123| 6.2%| 1,258| 62.9%|
#&gt; |10 |2015 | 117| 5.9%| 1,375| 68.8%|
#&gt; |11 |2007 | 116| 5.8%| 1,491| 74.6%|
#&gt; |12 |2014 | 105| 5.3%| 1,596| 79.8%|
#&gt; |13 |2010 | 103| 5.2%| 1,699| 85.0%|
#&gt; |14 |2009 | 102| 5.1%| 1,801| 90.1%|
#&gt; |15 |2013 | 101| 5.1%| 1,902| 95.1%|
#&gt; |16 |2012 | 98| 4.9%| 2,000| 100.0%|
#&gt;
#&gt; </div><div class='input'>
<span class='co'># save to an object with formatted percentages</span>
<span class='no'>years</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/format'>format</a></span>(<span class='no'>years</span>)
<span class='co'># print a histogram of numeric values</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>age</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/graphics/topics/hist'>hist</a></span>()</div><div class='img'><img src='freq-1.png' alt='' width='700' height='433' /></div><div class='input'>
<span class='co'># or print all points to a regular plot</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>age</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/graphics/topics/plot'>plot</a></span>()</div><div class='img'><img src='freq-2.png' alt='' width='700' height='433' /></div><div class='input'>
<span class='co'># transform to a data.frame or tibble</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>age</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/as.data.frame'>as.data.frame</a></span>()</div><div class='output co'>#&gt; item count percent cum_count cum_percent
#&gt; 1 83 102 0.0510 102 0.0510
#&gt; 2 80 75 0.0375 177 0.0885
#&gt; 3 75 72 0.0360 249 0.1245
#&gt; 4 79 72 0.0360 321 0.1605
#&gt; 5 78 70 0.0350 391 0.1955
#&gt; 6 76 65 0.0325 456 0.2280
#&gt; 7 82 62 0.0310 518 0.2590
#&gt; 8 86 61 0.0305 579 0.2895
#&gt; 9 81 58 0.0290 637 0.3185
#&gt; 10 87 57 0.0285 694 0.3470
#&gt; 11 74 54 0.0270 748 0.3740
#&gt; 12 73 53 0.0265 801 0.4005
#&gt; 13 77 52 0.0260 853 0.4265
#&gt; 14 67 51 0.0255 904 0.4520
#&gt; 15 88 51 0.0255 955 0.4775
#&gt; 16 70 50 0.0250 1005 0.5025
#&gt; 17 69 49 0.0245 1054 0.5270
#&gt; 18 71 47 0.0235 1101 0.5505
#&gt; 19 72 45 0.0225 1146 0.5730
#&gt; 20 65 43 0.0215 1189 0.5945
#&gt; 21 66 42 0.0210 1231 0.6155
#&gt; 22 85 42 0.0210 1273 0.6365
#&gt; 23 68 41 0.0205 1314 0.6570
#&gt; 24 47 39 0.0195 1353 0.6765
#&gt; 25 90 35 0.0175 1388 0.6940
#&gt; 26 89 34 0.0170 1422 0.7110
#&gt; 27 84 33 0.0165 1455 0.7275
#&gt; 28 62 32 0.0160 1487 0.7435
#&gt; 29 59 31 0.0155 1518 0.7590
#&gt; 30 64 31 0.0155 1549 0.7745
#&gt; 31 57 29 0.0145 1578 0.7890
#&gt; 32 63 28 0.0140 1606 0.8030
#&gt; 33 51 27 0.0135 1633 0.8165
#&gt; 34 52 25 0.0125 1658 0.8290
#&gt; 35 60 25 0.0125 1683 0.8415
#&gt; 36 53 23 0.0115 1706 0.8530
#&gt; 37 58 23 0.0115 1729 0.8645
#&gt; 38 50 22 0.0110 1751 0.8755
#&gt; 39 56 21 0.0105 1772 0.8860
#&gt; 40 45 20 0.0100 1792 0.8960
#&gt; 41 55 17 0.0085 1809 0.9045
#&gt; 42 61 17 0.0085 1826 0.9130
#&gt; 43 93 16 0.0080 1842 0.9210
#&gt; 44 43 15 0.0075 1857 0.9285
#&gt; 45 44 13 0.0065 1870 0.9350
#&gt; 46 46 13 0.0065 1883 0.9415
#&gt; 47 41 10 0.0050 1893 0.9465
#&gt; 48 48 10 0.0050 1903 0.9515
#&gt; 49 30 9 0.0045 1912 0.9560
#&gt; 50 54 9 0.0045 1921 0.9605
#&gt; 51 92 9 0.0045 1930 0.9650
#&gt; 52 91 8 0.0040 1938 0.9690
#&gt; 53 42 7 0.0035 1945 0.9725
#&gt; 54 38 6 0.0030 1951 0.9755
#&gt; 55 94 6 0.0030 1957 0.9785
#&gt; 56 20 4 0.0020 1961 0.9805
#&gt; 57 39 4 0.0020 1965 0.9825
#&gt; 58 49 4 0.0020 1969 0.9845
#&gt; 59 19 3 0.0015 1972 0.9860
#&gt; 60 29 3 0.0015 1975 0.9875
#&gt; 61 33 3 0.0015 1978 0.9890
#&gt; 62 37 3 0.0015 1981 0.9905
#&gt; 63 40 3 0.0015 1984 0.9920
#&gt; 64 18 2 0.0010 1986 0.9930
#&gt; 65 24 2 0.0010 1988 0.9940
#&gt; 66 31 2 0.0010 1990 0.9950
#&gt; 67 36 2 0.0010 1992 0.9960
#&gt; 68 97 2 0.0010 1994 0.9970
#&gt; 69 14 1 0.0005 1995 0.9975
#&gt; 70 22 1 0.0005 1996 0.9980
#&gt; 71 32 1 0.0005 1997 0.9985
#&gt; 72 34 1 0.0005 1998 0.9990
#&gt; 73 35 1 0.0005 1999 0.9995
#&gt; 74 95 1 0.0005 2000 1.0000</div><div class='input'>
<span class='co'># or transform (back) to a vector</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>age</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/vector'>as.vector</a></span>()</div><div class='output co'>#&gt; [1] 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83
#&gt; [25] 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83
#&gt; [49] 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83
#&gt; [73] 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83 83
#&gt; [97] 83 83 83 83 83 83 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80
#&gt; [121] 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80
#&gt; [145] 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80 80
#&gt; [169] 80 80 80 80 80 80 80 80 80 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75
#&gt; [193] 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75
#&gt; [217] 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75 75
#&gt; [241] 75 75 75 75 75 75 75 75 75 79 79 79 79 79 79 79 79 79 79 79 79 79 79 79
#&gt; [265] 79 79 79 79 79 79 79 79 79 79 79 79 79 79 79 79 79 79 79 79 79 79 79 79
#&gt; [289] 79 79 79 79 79 79 79 79 79 79 79 79 79 79 79 79 79 79 79 79 79 79 79 79
#&gt; [313] 79 79 79 79 79 79 79 79 79 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78
#&gt; [337] 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78
#&gt; [361] 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78 78
#&gt; [385] 78 78 78 78 78 78 78 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76
#&gt; [409] 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76
#&gt; [433] 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76 76
#&gt; [457] 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82
#&gt; [481] 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82 82
#&gt; [505] 82 82 82 82 82 82 82 82 82 82 82 82 82 82 86 86 86 86 86 86 86 86 86 86
#&gt; [529] 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86
#&gt; [553] 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86 86
#&gt; [577] 86 86 86 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81
#&gt; [601] 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81 81
#&gt; [625] 81 81 81 81 81 81 81 81 81 81 81 81 81 87 87 87 87 87 87 87 87 87 87 87
#&gt; [649] 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87
#&gt; [673] 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 87 74 74
#&gt; [697] 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74
#&gt; [721] 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74 74
#&gt; [745] 74 74 74 74 73 73 73 73 73 73 73 73 73 73 73 73 73 73 73 73 73 73 73 73
#&gt; [769] 73 73 73 73 73 73 73 73 73 73 73 73 73 73 73 73 73 73 73 73 73 73 73 73
#&gt; [793] 73 73 73 73 73 73 73 73 73 77 77 77 77 77 77 77 77 77 77 77 77 77 77 77
#&gt; [817] 77 77 77 77 77 77 77 77 77 77 77 77 77 77 77 77 77 77 77 77 77 77 77 77
#&gt; [841] 77 77 77 77 77 77 77 77 77 77 77 77 77 67 67 67 67 67 67 67 67 67 67 67
#&gt; [865] 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67
#&gt; [889] 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 67 88 88 88 88 88 88 88 88
#&gt; [913] 88 88 88 88 88 88 88 88 88 88 88 88 88 88 88 88 88 88 88 88 88 88 88 88
#&gt; [937] 88 88 88 88 88 88 88 88 88 88 88 88 88 88 88 88 88 88 88 70 70 70 70 70
#&gt; [961] 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70
#&gt; [985] 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 70 69 69 69
#&gt; [1009] 69 69 69 69 69 69 69 69 69 69 69 69 69 69 69 69 69 69 69 69 69 69 69 69
#&gt; [1033] 69 69 69 69 69 69 69 69 69 69 69 69 69 69 69 69 69 69 69 69 69 69 71 71
#&gt; [1057] 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71
#&gt; [1081] 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 71 72 72 72
#&gt; [1105] 72 72 72 72 72 72 72 72 72 72 72 72 72 72 72 72 72 72 72 72 72 72 72 72
#&gt; [1129] 72 72 72 72 72 72 72 72 72 72 72 72 72 72 72 72 72 72 65 65 65 65 65 65
#&gt; [1153] 65 65 65 65 65 65 65 65 65 65 65 65 65 65 65 65 65 65 65 65 65 65 65 65
#&gt; [1177] 65 65 65 65 65 65 65 65 65 65 65 65 65 66 66 66 66 66 66 66 66 66 66 66
#&gt; [1201] 66 66 66 66 66 66 66 66 66 66 66 66 66 66 66 66 66 66 66 66 66 66 66 66
#&gt; [1225] 66 66 66 66 66 66 66 85 85 85 85 85 85 85 85 85 85 85 85 85 85 85 85 85
#&gt; [1249] 85 85 85 85 85 85 85 85 85 85 85 85 85 85 85 85 85 85 85 85 85 85 85 85
#&gt; [1273] 85 68 68 68 68 68 68 68 68 68 68 68 68 68 68 68 68 68 68 68 68 68 68 68
#&gt; [1297] 68 68 68 68 68 68 68 68 68 68 68 68 68 68 68 68 68 68 47 47 47 47 47 47
#&gt; [1321] 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47 47
#&gt; [1345] 47 47 47 47 47 47 47 47 47 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90
#&gt; [1369] 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 90 89 89 89 89
#&gt; [1393] 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89 89
#&gt; [1417] 89 89 89 89 89 89 84 84 84 84 84 84 84 84 84 84 84 84 84 84 84 84 84 84
#&gt; [1441] 84 84 84 84 84 84 84 84 84 84 84 84 84 84 84 62 62 62 62 62 62 62 62 62
#&gt; [1465] 62 62 62 62 62 62 62 62 62 62 62 62 62 62 62 62 62 62 62 62 62 62 62 59
#&gt; [1489] 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59 59
#&gt; [1513] 59 59 59 59 59 59 64 64 64 64 64 64 64 64 64 64 64 64 64 64 64 64 64 64
#&gt; [1537] 64 64 64 64 64 64 64 64 64 64 64 64 64 57 57 57 57 57 57 57 57 57 57 57
#&gt; [1561] 57 57 57 57 57 57 57 57 57 57 57 57 57 57 57 57 57 57 63 63 63 63 63 63
#&gt; [1585] 63 63 63 63 63 63 63 63 63 63 63 63 63 63 63 63 63 63 63 63 63 63 51 51
#&gt; [1609] 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51 51
#&gt; [1633] 51 52 52 52 52 52 52 52 52 52 52 52 52 52 52 52 52 52 52 52 52 52 52 52
#&gt; [1657] 52 52 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60 60
#&gt; [1681] 60 60 60 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53 53
#&gt; [1705] 53 53 58 58 58 58 58 58 58 58 58 58 58 58 58 58 58 58 58 58 58 58 58 58
#&gt; [1729] 58 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 50 56
#&gt; [1753] 56 56 56 56 56 56 56 56 56 56 56 56 56 56 56 56 56 56 56 56 45 45 45 45
#&gt; [1777] 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 45 55 55 55 55 55 55 55 55
#&gt; [1801] 55 55 55 55 55 55 55 55 55 61 61 61 61 61 61 61 61 61 61 61 61 61 61 61
#&gt; [1825] 61 61 93 93 93 93 93 93 93 93 93 93 93 93 93 93 93 93 43 43 43 43 43 43
#&gt; [1849] 43 43 43 43 43 43 43 43 43 44 44 44 44 44 44 44 44 44 44 44 44 44 46 46
#&gt; [1873] 46 46 46 46 46 46 46 46 46 46 46 41 41 41 41 41 41 41 41 41 41 48 48 48
#&gt; [1897] 48 48 48 48 48 48 48 30 30 30 30 30 30 30 30 30 54 54 54 54 54 54 54 54
#&gt; [1921] 54 92 92 92 92 92 92 92 92 92 91 91 91 91 91 91 91 91 42 42 42 42 42 42
#&gt; [1945] 42 38 38 38 38 38 38 94 94 94 94 94 94 20 20 20 20 39 39 39 39 49 49 49
#&gt; [1969] 49 19 19 19 29 29 29 33 33 33 37 37 37 40 40 40 18 18 24 24 31 31 36 36
#&gt; [1993] 97 97 14 22 32 34 35 95</div><div class='input'>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/identical'>identical</a></span>(<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>age</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/vector'>as.vector</a></span>() <span class='kw'>%&gt;%</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/sort'>sort</a></span>(),
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/sort'>sort</a></span>(<span class='no'>septic_patients</span>$<span class='no'>age</span>)) <span class='co'># TRUE</span></div><div class='output co'>#&gt; [1] TRUE</div><div class='input'>
<span class='co'># it also supports `table` objects</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/table'>table</a></span>(<span class='no'>septic_patients</span>$<span class='no'>gender</span>,
<span class='no'>septic_patients</span>$<span class='no'>age</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='kw'>sep</span> <span class='kw'>=</span> <span class='st'>" **sep** "</span>)</div><div class='output co'>#&gt;
#&gt;
#&gt; **Frequency table of a `table` object**
#&gt;
#&gt;
#&gt; | |Item | Count| Percent| Cum. Count| Cum. Percent|
#&gt; |:---|:------------|-----:|-------:|----------:|------------:|
#&gt; |1 |F **sep** 83 | 55| 2.8%| 55| 2.8%|
#&gt; |2 |M **sep** 78 | 51| 2.6%| 106| 5.3%|
#&gt; |3 |M **sep** 83 | 47| 2.4%| 153| 7.7%|
#&gt; |4 |M **sep** 82 | 43| 2.2%| 196| 9.8%|
#&gt; |5 |M **sep** 79 | 42| 2.1%| 238| 11.9%|
#&gt; |6 |F **sep** 80 | 41| 2.1%| 279| 14.0%|
#&gt; |7 |F **sep** 76 | 39| 2.0%| 318| 15.9%|
#&gt; |8 |F **sep** 75 | 38| 1.9%| 356| 17.8%|
#&gt; |9 |F **sep** 86 | 38| 1.9%| 394| 19.7%|
#&gt; |10 |M **sep** 71 | 35| 1.8%| 429| 21.5%|
#&gt; |11 |M **sep** 75 | 34| 1.7%| 463| 23.2%|
#&gt; |12 |M **sep** 77 | 34| 1.7%| 497| 24.9%|
#&gt; |13 |M **sep** 80 | 34| 1.7%| 531| 26.6%|
#&gt; |14 |F **sep** 81 | 33| 1.7%| 564| 28.2%|
#&gt; |15 |M **sep** 88 | 31| 1.6%| 595| 29.8%|
#&gt; |16 |F **sep** 79 | 30| 1.5%| 625| 31.3%|
#&gt; |17 |M **sep** 74 | 30| 1.5%| 655| 32.8%|
#&gt; |18 |M **sep** 87 | 30| 1.5%| 685| 34.3%|
#&gt; |19 |F **sep** 65 | 29| 1.5%| 714| 35.7%|
#&gt; |20 |M **sep** 73 | 29| 1.5%| 743| 37.2%|
#&gt; |21 |M **sep** 69 | 28| 1.4%| 771| 38.6%|
#&gt; |22 |M **sep** 72 | 28| 1.4%| 799| 40.0%|
#&gt; |23 |F **sep** 67 | 27| 1.4%| 826| 41.3%|
#&gt; |24 |F **sep** 87 | 27| 1.4%| 853| 42.7%|
#&gt; |25 |M **sep** 76 | 26| 1.3%| 879| 44.0%|
#&gt; |26 |F **sep** 66 | 25| 1.3%| 904| 45.2%|
#&gt; |27 |F **sep** 70 | 25| 1.3%| 929| 46.5%|
#&gt; |28 |M **sep** 70 | 25| 1.3%| 954| 47.7%|
#&gt; |29 |M **sep** 81 | 25| 1.3%| 979| 49.0%|
#&gt; |30 |F **sep** 47 | 24| 1.2%| 1,003| 50.1%|
#&gt; |31 |F **sep** 73 | 24| 1.2%| 1,027| 51.4%|
#&gt; |32 |F **sep** 74 | 24| 1.2%| 1,051| 52.6%|
#&gt; |33 |M **sep** 67 | 24| 1.2%| 1,075| 53.8%|
#&gt; |34 |M **sep** 86 | 23| 1.2%| 1,098| 54.9%|
#&gt; |35 |F **sep** 89 | 22| 1.1%| 1,120| 56.0%|
#&gt; |36 |M **sep** 68 | 22| 1.1%| 1,142| 57.1%|
#&gt; |37 |M **sep** 85 | 22| 1.1%| 1,164| 58.2%|
#&gt; |38 |F **sep** 69 | 21| 1.1%| 1,185| 59.3%|
#&gt; |39 |M **sep** 62 | 21| 1.1%| 1,206| 60.3%|
#&gt; |40 |F **sep** 85 | 20| 1.0%| 1,226| 61.3%|
#&gt; |41 |F **sep** 88 | 20| 1.0%| 1,246| 62.3%|
#&gt; |42 |F **sep** 90 | 20| 1.0%| 1,266| 63.3%|
#&gt; |43 |M **sep** 64 | 20| 1.0%| 1,286| 64.3%|
#&gt; |44 |F **sep** 68 | 19| 1.0%| 1,305| 65.3%|
#&gt; |45 |F **sep** 78 | 19| 1.0%| 1,324| 66.2%|
#&gt; |46 |F **sep** 82 | 19| 1.0%| 1,343| 67.2%|
#&gt; |47 |F **sep** 45 | 18| 0.9%| 1,361| 68.1%|
#&gt; |48 |F **sep** 60 | 18| 0.9%| 1,379| 69.0%|
#&gt; |49 |F **sep** 77 | 18| 0.9%| 1,397| 69.9%|
#&gt; |50 |F **sep** 84 | 18| 0.9%| 1,415| 70.8%|
#&gt; |51 |M **sep** 51 | 18| 0.9%| 1,433| 71.7%|
#&gt; |52 |M **sep** 52 | 18| 0.9%| 1,451| 72.6%|
#&gt; |53 |F **sep** 57 | 17| 0.9%| 1,468| 73.4%|
#&gt; |54 |F **sep** 72 | 17| 0.9%| 1,485| 74.3%|
#&gt; |55 |M **sep** 66 | 17| 0.9%| 1,502| 75.1%|
#&gt; |56 |F **sep** 58 | 16| 0.8%| 1,518| 75.9%|
#&gt; |57 |F **sep** 59 | 16| 0.8%| 1,534| 76.7%|
#&gt; |58 |M **sep** 56 | 16| 0.8%| 1,550| 77.5%|
#&gt; |59 |M **sep** 47 | 15| 0.8%| 1,565| 78.3%|
#&gt; |60 |M **sep** 59 | 15| 0.8%| 1,580| 79.0%|
#&gt; |61 |M **sep** 84 | 15| 0.8%| 1,595| 79.8%|
#&gt; |62 |M **sep** 90 | 15| 0.8%| 1,610| 80.5%|
#&gt; |63 |F **sep** 63 | 14| 0.7%| 1,624| 81.2%|
#&gt; |64 |M **sep** 53 | 14| 0.7%| 1,638| 81.9%|
#&gt; |65 |M **sep** 63 | 14| 0.7%| 1,652| 82.6%|
#&gt; |66 |M **sep** 65 | 14| 0.7%| 1,666| 83.3%|
#&gt; |67 |M **sep** 61 | 13| 0.7%| 1,679| 84.0%|
#&gt; |68 |F **sep** 50 | 12| 0.6%| 1,691| 84.6%|
#&gt; |69 |F **sep** 71 | 12| 0.6%| 1,703| 85.2%|
#&gt; |70 |M **sep** 57 | 12| 0.6%| 1,715| 85.8%|
#&gt; |71 |M **sep** 89 | 12| 0.6%| 1,727| 86.4%|
#&gt; |72 |M **sep** 93 | 12| 0.6%| 1,739| 87.0%|
#&gt; |73 |F **sep** 62 | 11| 0.6%| 1,750| 87.5%|
#&gt; |74 |F **sep** 64 | 11| 0.6%| 1,761| 88.1%|
#&gt; |75 |M **sep** 50 | 10| 0.5%| 1,771| 88.6%|
#&gt; |76 |F **sep** 43 | 9| 0.5%| 1,780| 89.0%|
#&gt; |77 |F **sep** 46 | 9| 0.5%| 1,789| 89.5%|
#&gt; |78 |F **sep** 51 | 9| 0.5%| 1,798| 89.9%|
#&gt; |79 |F **sep** 53 | 9| 0.5%| 1,807| 90.4%|
#&gt; |80 |F **sep** 55 | 9| 0.5%| 1,816| 90.8%|
#&gt; |81 |M **sep** 30 | 9| 0.5%| 1,825| 91.3%|
#&gt; |82 |F **sep** 44 | 8| 0.4%| 1,833| 91.7%|
#&gt; |83 |M **sep** 55 | 8| 0.4%| 1,841| 92.1%|
#&gt; |84 |F **sep** 41 | 7| 0.4%| 1,848| 92.4%|
#&gt; |85 |F **sep** 48 | 7| 0.4%| 1,855| 92.8%|
#&gt; |86 |F **sep** 52 | 7| 0.4%| 1,862| 93.1%|
#&gt; |87 |M **sep** 58 | 7| 0.4%| 1,869| 93.5%|
#&gt; |88 |M **sep** 60 | 7| 0.4%| 1,876| 93.8%|
#&gt; |89 |F **sep** 92 | 6| 0.3%| 1,882| 94.1%|
#&gt; |90 |M **sep** 43 | 6| 0.3%| 1,888| 94.4%|
#&gt; |91 |F **sep** 38 | 5| 0.3%| 1,893| 94.7%|
#&gt; |92 |F **sep** 42 | 5| 0.3%| 1,898| 94.9%|
#&gt; |93 |F **sep** 56 | 5| 0.3%| 1,903| 95.2%|
#&gt; |94 |M **sep** 44 | 5| 0.3%| 1,908| 95.4%|
#&gt; |95 |M **sep** 54 | 5| 0.3%| 1,913| 95.7%|
#&gt; |96 |F **sep** 20 | 4| 0.2%| 1,917| 95.9%|
#&gt; |97 |F **sep** 54 | 4| 0.2%| 1,921| 96.1%|
#&gt; |98 |F **sep** 61 | 4| 0.2%| 1,925| 96.3%|
#&gt; |99 |F **sep** 91 | 4| 0.2%| 1,929| 96.5%|
#&gt; |100 |F **sep** 93 | 4| 0.2%| 1,933| 96.7%|
#&gt; |101 |F **sep** 94 | 4| 0.2%| 1,937| 96.9%|
#&gt; |102 |M **sep** 46 | 4| 0.2%| 1,941| 97.1%|
#&gt; |103 |M **sep** 91 | 4| 0.2%| 1,945| 97.3%|
#&gt; |104 |F **sep** 39 | 3| 0.2%| 1,948| 97.4%|
#&gt; |105 |M **sep** 19 | 3| 0.2%| 1,951| 97.6%|
#&gt; |106 |M **sep** 33 | 3| 0.2%| 1,954| 97.7%|
#&gt; |107 |M **sep** 41 | 3| 0.2%| 1,957| 97.9%|
#&gt; |108 |M **sep** 48 | 3| 0.2%| 1,960| 98.0%|
#&gt; |109 |M **sep** 92 | 3| 0.2%| 1,963| 98.2%|
#&gt; |110 |F **sep** 31 | 2| 0.1%| 1,965| 98.3%|
#&gt; |111 |F **sep** 49 | 2| 0.1%| 1,967| 98.4%|
#&gt; |112 |M **sep** 18 | 2| 0.1%| 1,969| 98.5%|
#&gt; |113 |M **sep** 24 | 2| 0.1%| 1,971| 98.6%|
#&gt; |114 |M **sep** 29 | 2| 0.1%| 1,973| 98.7%|
#&gt; |115 |M **sep** 36 | 2| 0.1%| 1,975| 98.8%|
#&gt; |116 |M **sep** 37 | 2| 0.1%| 1,977| 98.9%|
#&gt; |117 |M **sep** 40 | 2| 0.1%| 1,979| 99.0%|
#&gt; |118 |M **sep** 42 | 2| 0.1%| 1,981| 99.1%|
#&gt; |119 |M **sep** 45 | 2| 0.1%| 1,983| 99.2%|
#&gt; |120 |M **sep** 49 | 2| 0.1%| 1,985| 99.3%|
#&gt; |121 |M **sep** 94 | 2| 0.1%| 1,987| 99.4%|
#&gt; |122 |M **sep** 97 | 2| 0.1%| 1,989| 99.5%|
#&gt; |123 |F **sep** 22 | 1| 0.1%| 1,990| 99.5%|
#&gt; |124 |F **sep** 29 | 1| 0.1%| 1,991| 99.6%|
#&gt; |125 |F **sep** 34 | 1| 0.1%| 1,992| 99.6%|
#&gt; |126 |F **sep** 35 | 1| 0.1%| 1,993| 99.7%|
#&gt; |127 |F **sep** 37 | 1| 0.1%| 1,994| 99.7%|
#&gt; |128 |F **sep** 40 | 1| 0.1%| 1,995| 99.8%|
#&gt; |129 |M **sep** 14 | 1| 0.1%| 1,996| 99.8%|
#&gt; |130 |M **sep** 32 | 1| 0.1%| 1,997| 99.9%|
#&gt; |131 |M **sep** 38 | 1| 0.1%| 1,998| 99.9%|
#&gt; |132 |M **sep** 39 | 1| 0.1%| 1,999| 100.0%|
#&gt; |133 |M **sep** 95 | 1| 0.1%| 2,000| 100.0%|
#&gt;
#&gt; </div><div class='input'>
<span class='co'># only get selected columns</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>item</span>, <span class='no'>percent</span>)</div><div class='output co'>#&gt;
#&gt;
#&gt; **Frequency table of `hospital_id`**
#&gt;
#&gt;
#&gt; | |Item | Percent|
#&gt; |:--|:----|-------:|
#&gt; |1 |D | 38.1%|
#&gt; |2 |B | 33.2%|
#&gt; |3 |A | 16.1%|
#&gt; |4 |C | 12.7%|
#&gt;
#&gt; </div><div class='input'>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'>freq</span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/select.html'>select</a></span>(-<span class='no'>count</span>, -<span class='no'>cum_count</span>)</div><div class='output co'>#&gt;
#&gt;
#&gt; **Frequency table of `hospital_id`**
#&gt;
#&gt;
#&gt; | |Item | Percent| Cum. Percent|
#&gt; |:--|:----|-------:|------------:|
#&gt; |1 |D | 38.1%| 38.1%|
#&gt; |2 |B | 33.2%| 71.3%|
#&gt; |3 |A | 16.1%| 87.3%|
#&gt; |4 |C | 12.7%| 100.0%|
#&gt;
#&gt; </div><div class='input'>
<span class='co'># check differences between frequency tables</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/diff'>diff</a></span>(<span class='fu'>freq</span>(<span class='no'>septic_patients</span>$<span class='no'>trim</span>),
<span class='fu'>freq</span>(<span class='no'>septic_patients</span>$<span class='no'>trsu</span>))</div><div class='output co'>#&gt; Differences between frequency tables
#&gt;
#&gt; |Item | Count #1| Count #2| Difference| Diff. percent|
#&gt; |:----|--------:|--------:|----------:|-------------:|
#&gt; |S | 918| 1392| +474| +51.6%|
#&gt; |R | 571| 361| -210| -36.8%|
#&gt; |I | 10| 6| -4| -40.0%|</div></pre>
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<h1><em>G</em>-test for Count Data</h1>
<div class="hidden name"><code>g.test.Rd</code></div>
</div>
<div class="ref-description">
<p><code>g.test</code> performs chi-squared contingency table tests and goodness-of-fit tests, just like <code><a href='https://www.rdocumentation.org/packages/stats/topics/chisq.test'>chisq.test</a></code> but is more reliable [1]. A <em>G</em>-test can be used to see whether the number of observations in each category fits a theoretical expectation (called a <strong><em>G</em>-test of goodness-of-fit</strong>), or to see whether the proportions of one variable are different for different values of the other variable (called a <strong><em>G</em>-test of independence</strong>).</p>
</div>
<pre class="usage"><span class='fu'>g.test</span>(<span class='no'>x</span>, <span class='kw'>y</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>p</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/rep'>rep</a></span>(<span class='fl'>1</span>/<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/length'>length</a></span>(<span class='no'>x</span>), <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/length'>length</a></span>(<span class='no'>x</span>)),
<span class='kw'>rescale.p</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>x</th>
<td><p>a numeric vector or matrix. <code>x</code> and <code>y</code> can also
both be factors.</p></td>
</tr>
<tr>
<th>y</th>
<td><p>a numeric vector; ignored if <code>x</code> is a matrix. If
<code>x</code> is a factor, <code>y</code> should be a factor of the same length.</p></td>
</tr>
<tr>
<th>p</th>
<td><p>a vector of probabilities of the same length of <code>x</code>.
An error is given if any entry of <code>p</code> is negative.</p></td>
</tr>
<tr>
<th>rescale.p</th>
<td><p>a logical scalar; if TRUE then <code>p</code> is rescaled
(if necessary) to sum to 1. If <code>rescale.p</code> is FALSE, and
<code>p</code> does not sum to 1, an error is given.</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p>This code is almost identical to <code><a href='https://www.rdocumentation.org/packages/stats/topics/chisq.test'>chisq.test</a></code>, except that:</p><ul>
<li><p>The calculation of the statistic was changed to <code>2 * sum(x * log(x / E))</code></p></li>
<li><p>Yates' continuity correction was removed as it does not apply to a <em>G</em>-test</p></li>
<li><p>The possibility to simulate p values with <code>simulate.p.value</code> was removed</p></li>
</ul>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>A list with class <code>"htest"</code> containing the following
components:</p>
<dt>statistic</dt><dd><p>the value the chi-squared test statistic.</p></dd>
<dt>parameter</dt><dd><p>the degrees of freedom of the approximate
chi-squared distribution of the test statistic, <code>NA</code> if the
p-value is computed by Monte Carlo simulation.</p></dd>
<dt>p.value</dt><dd><p>the p-value for the test.</p></dd>
<dt>method</dt><dd><p>a character string indicating the type of test
performed, and whether Monte Carlo simulation or continuity
correction was used.</p></dd>
<dt>data.name</dt><dd><p>a character string giving the name(s) of the data.</p></dd>
<dt>observed</dt><dd><p>the observed counts.</p></dd>
<dt>expected</dt><dd><p>the expected counts under the null hypothesis.</p></dd>
<dt>residuals</dt><dd><p>the Pearson residuals,
<code>(observed - expected) / sqrt(expected)</code>.</p></dd>
<dt>stdres</dt><dd><p>standardized residuals,
<code>(observed - expected) / sqrt(V)</code>, where <code>V</code> is the residual cell variance (Agresti, 2007,
section 2.4.5 for the case where <code>x</code> is a matrix, <code>n * p * (1 - p)</code> otherwise).</p></dd>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>If <code>x</code> is a matrix with one row or column, or if <code>x</code> is a vector and <code>y</code> is not given, then a <em>goodness-of-fit test</em> is performed (<code>x</code> is treated as a one-dimensional contingency table). The entries of <code>x</code> must be non-negative integers. In this case, the hypothesis tested is whether the population probabilities equal those in <code>p</code>, or are all equal if <code>p</code> is not given.</p>
<p>If <code>x</code> is a matrix with at least two rows and columns, it is taken as a two-dimensional contingency table: the entries of <code>x</code> must be non-negative integers. Otherwise, <code>x</code> and <code>y</code> must be vectors or factors of the same length; cases with missing values are removed, the objects are coerced to factors, and the contingency table is computed from these. Then Pearson's chi-squared test is performed of the null hypothesis that the joint distribution of the cell counts in a 2-dimensional contingency table is the product of the row and column marginals.</p>
<p>The p-value is computed from the asymptotic chi-squared distribution of the test statistic.</p>
<p>In the contingency table case simulation is done by random sampling from the set of all contingency tables with given marginals, and works only if the marginals are strictly positive. Note that this is not the usual sampling situation assumed for a chi-squared test (like the <em>G</em>-test) but rather that for Fisher's exact test.</p>
<p>In the goodness-of-fit case simulation is done by random sampling from the discrete distribution specified by <code>p</code>, each sample being of size <code>n = sum(x)</code>. This simulation is done in <span style="R">R</span> and may be slow.</p>
<h2 class="hasAnchor" id="g-test-of-goodness-of-fit-likelihood-ratio-test-"><a class="anchor" href="#g-test-of-goodness-of-fit-likelihood-ratio-test-"></a><em>G</em>-test of goodness-of-fit (likelihood ratio test)</h2>
<p>Use the <em>G</em>-test of goodness-of-fit when you have one nominal variable with two or more values (such as male and female, or red, pink and white flowers). You compare the observed counts of numbers of observations in each category with the expected counts, which you calculate using some kind of theoretical expectation (such as a 1:1 sex ratio or a 1:2:1 ratio in a genetic cross).</p>
<p>If the expected number of observations in any category is too small, the <em>G</em>-test may give inaccurate results, and you should use an exact test instead (<code><a href='https://www.rdocumentation.org/packages/stats/topics/fisher.test'>fisher.test</a></code>).</p>
<p>The <em>G</em>-test of goodness-of-fit is an alternative to the chi-square test of goodness-of-fit (<code><a href='https://www.rdocumentation.org/packages/stats/topics/chisq.test'>chisq.test</a></code>); each of these tests has some advantages and some disadvantages, and the results of the two tests are usually very similar.</p>
<h2 class="hasAnchor" id="g-test-of-independence"><a class="anchor" href="#g-test-of-independence"></a><em>G</em>-test of independence</h2>
<p>Use the <em>G</em>-test of independence when you have two nominal variables, each with two or more possible values. You want to know whether the proportions for one variable are different among values of the other variable.</p>
<p>It is also possible to do a <em>G</em>-test of independence with more than two nominal variables. For example, Jackson et al. (2013) also had data for children under 3, so you could do an analysis of old vs. young, thigh vs. arm, and reaction vs. no reaction, all analyzed together.</p>
<p>Fisher's exact test (<code><a href='https://www.rdocumentation.org/packages/stats/topics/fisher.test'>fisher.test</a></code>) is more accurate than the <em>G</em>-test of independence when the expected numbers are small, so it is recommend to only use the <em>G</em>-test if your total sample size is greater than 1000.</p>
<p>The <em>G</em>-test of independence is an alternative to the chi-square test of independence (<code><a href='https://www.rdocumentation.org/packages/stats/topics/chisq.test'>chisq.test</a></code>), and they will give approximately the same results.</p>
<h2 class="hasAnchor" id="how-the-test-works"><a class="anchor" href="#how-the-test-works"></a>How the test works</h2>
<p>Unlike the exact test of goodness-of-fit (<code><a href='https://www.rdocumentation.org/packages/stats/topics/fisher.test'>fisher.test</a></code>), the <em>G</em>-test does not directly calculate the probability of obtaining the observed results or something more extreme. Instead, like almost all statistical tests, the <em>G</em>-test has an intermediate step; it uses the data to calculate a test statistic that measures how far the observed data are from the null expectation. You then use a mathematical relationship, in this case the chi-square distribution, to estimate the probability of obtaining that value of the test statistic.</p>
<p>The <em>G</em>-test uses the log of the ratio of two likelihoods as the test statistic, which is why it is also called a likelihood ratio test or log-likelihood ratio test. The formula to calculate a <em>G</em>-statistic is:</p>
<p><code>G &lt;- 2 * sum(x * log(x / E))</code></p>
<p>where <code>E</code> are the expected values. Since this is chi-square distributed, the p value can be calculated with:</p>
<p><code>p &lt;- stats::pchisq(G, df, lower.tail = FALSE)</code></p>
<p>where <code>df</code> are the degrees of freedom.</p>
<p>If there are more than two categories and you want to find out which ones are significantly different from their null expectation, you can use the same method of testing each category vs. the sum of all categories, with the Bonferroni correction. You use <em>G</em>-tests for each category, of course.</p>
<h2 class="hasAnchor" id="references"><a class="anchor" href="#references"></a>References</h2>
<p>[1] McDonald, J.H. 2014. <strong>Handbook of Biological Statistics (3rd ed.)</strong>. Sparky House Publishing, Baltimore, Maryland. <a href='http://www.biostathandbook.com/gtestgof.html'>http://www.biostathandbook.com/gtestgof.html</a>.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='https://www.rdocumentation.org/packages/stats/topics/chisq.test'>chisq.test</a></code></p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='co'># = EXAMPLE 1 =</span>
<span class='co'># Shivrain et al. (2006) crossed clearfield rice (which are resistant</span>
<span class='co'># to the herbicide imazethapyr) with red rice (which are susceptible to</span>
<span class='co'># imazethapyr). They then crossed the hybrid offspring and examined the</span>
<span class='co'># F2 generation, where they found 772 resistant plants, 1611 moderately</span>
<span class='co'># resistant plants, and 737 susceptible plants. If resistance is controlled</span>
<span class='co'># by a single gene with two co-dominant alleles, you would expect a 1:2:1</span>
<span class='co'># ratio.</span>
<span class='no'>x</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='fl'>772</span>, <span class='fl'>1611</span>, <span class='fl'>737</span>)<span class='co'>#'</span>
<span class='no'>G</span> <span class='kw'>&lt;-</span> <span class='fu'>g.test</span>(<span class='no'>x</span>, <span class='kw'>p</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='fl'>1</span>, <span class='fl'>2</span>, <span class='fl'>1</span>) / <span class='fl'>4</span>)
<span class='co'># G$p.value = 0.12574.</span>
<span class='co'># There is no significant difference from a 1:2:1 ratio.</span>
<span class='co'># Meaning: resistance controlled by a single gene with two co-dominant</span>
<span class='co'># alleles, is plausible.</span>
<span class='co'># = EXAMPLE 2 =</span>
<span class='co'># Red crossbills (Loxia curvirostra) have the tip of the upper bill either</span>
<span class='co'># right or left of the lower bill, which helps them extract seeds from pine</span>
<span class='co'># cones. Some have hypothesized that frequency-dependent selection would</span>
<span class='co'># keep the number of right and left-billed birds at a 1:1 ratio. Groth (1992)</span>
<span class='co'># observed 1752 right-billed and 1895 left-billed crossbills.</span>
<span class='no'>x</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='fl'>1752</span>, <span class='fl'>1895</span>)
<span class='fu'>g.test</span>(<span class='no'>x</span>)</div><div class='output co'>#&gt;
#&gt; G-test of goodness-of-fit (likelihood ratio test)
#&gt;
#&gt; data: x
#&gt; X-squared = 5.6085, df = 1, p-value = 0.01787
#&gt; </div><div class='input'># p = 0.01787343
# There is a significant difference from a 1:1 ratio.
# Meaning: there are significantly more left-billed birds.
</div></pre>
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<h1>Get language for AMR</h1>
<div class="hidden name"><code>get_locale.Rd</code></div>
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<p>Determines the system language to be used for language-dependent output of AMR functions, like <code><a href='mo_property.html'>mo_gramstain</a></code> and <code><a href='mo_property.html'>mo_type</a></code>.</p>
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<pre class="usage"><span class='fu'>get_locale</span>()</pre>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>The system language can be overwritten with <code><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a>("AMR_locale")</code>.</p>
<h2 class="hasAnchor" id="supported-languages"><a class="anchor" href="#supported-languages"></a>Supported languages</h2>
<p>Supported languages are <code>"en"</code> (English), <code>"de"</code> (German), <code>"nl"</code> (Dutch), <code>"es"</code> (Spanish), <code>"it"</code> (Italian), <code>"fr"</code> (French), and <code>"pt"</code> (Portuguese).</p>
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<h1>AMR bar plots with <code>ggplot</code></h1>
<div class="hidden name"><code>ggplot_rsi.Rd</code></div>
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<p>Use these functions to create bar plots for antimicrobial resistance analysis. All functions rely on internal <code><a href='https://ggplot2.tidyverse.org/reference/ggplot.html'>ggplot</a></code> functions.</p>
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<pre class="usage"><span class='fu'>ggplot_rsi</span>(<span class='no'>data</span>, <span class='kw'>position</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>x</span> <span class='kw'>=</span> <span class='st'>"Antibiotic"</span>,
<span class='kw'>fill</span> <span class='kw'>=</span> <span class='st'>"Interpretation"</span>, <span class='kw'>facet</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>breaks</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/seq'>seq</a></span>(<span class='fl'>0</span>, <span class='fl'>1</span>, <span class='fl'>0.1</span>),
<span class='kw'>limits</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>translate_ab</span> <span class='kw'>=</span> <span class='st'>"official"</span>, <span class='kw'>fun</span> <span class='kw'>=</span> <span class='no'>count_df</span>,
<span class='kw'>nrow</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>datalabels</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>datalabels.size</span> <span class='kw'>=</span> <span class='fl'>3</span>,
<span class='kw'>datalabels.colour</span> <span class='kw'>=</span> <span class='st'>"grey15"</span>, <span class='no'>...</span>)
<span class='fu'>geom_rsi</span>(<span class='kw'>position</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>x</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"Antibiotic"</span>, <span class='st'>"Interpretation"</span>),
<span class='kw'>fill</span> <span class='kw'>=</span> <span class='st'>"Interpretation"</span>, <span class='kw'>translate_ab</span> <span class='kw'>=</span> <span class='st'>"official"</span>, <span class='kw'>fun</span> <span class='kw'>=</span> <span class='no'>count_df</span>,
<span class='no'>...</span>)
<span class='fu'>facet_rsi</span>(<span class='kw'>facet</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"Interpretation"</span>, <span class='st'>"Antibiotic"</span>), <span class='kw'>nrow</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)
<span class='fu'>scale_y_percent</span>(<span class='kw'>breaks</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/seq'>seq</a></span>(<span class='fl'>0</span>, <span class='fl'>1</span>, <span class='fl'>0.1</span>), <span class='kw'>limits</span> <span class='kw'>=</span> <span class='kw'>NULL</span>)
<span class='fu'>scale_rsi_colours</span>()
<span class='fu'>theme_rsi</span>()
<span class='fu'>labels_rsi_count</span>(<span class='kw'>position</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>x</span> <span class='kw'>=</span> <span class='st'>"Antibiotic"</span>,
<span class='kw'>datalabels.size</span> <span class='kw'>=</span> <span class='fl'>3</span>, <span class='kw'>datalabels.colour</span> <span class='kw'>=</span> <span class='st'>"grey15"</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>data</th>
<td><p>a <code>data.frame</code> with column(s) of class <code>"rsi"</code> (see <code><a href='as.rsi.html'>as.rsi</a></code>)</p></td>
</tr>
<tr>
<th>position</th>
<td><p>position adjustment of bars, either <code>"fill"</code> (default when <code>fun</code> is <code><a href='count.html'>count_df</a></code>), <code>"stack"</code> (default when <code>fun</code> is <code><a href='portion.html'>portion_df</a></code>) or <code>"dodge"</code></p></td>
</tr>
<tr>
<th>x</th>
<td><p>variable to show on x axis, either <code>"Antibiotic"</code> (default) or <code>"Interpretation"</code> or a grouping variable</p></td>
</tr>
<tr>
<th>fill</th>
<td><p>variable to categorise using the plots legend, either <code>"Antibiotic"</code> (default) or <code>"Interpretation"</code> or a grouping variable</p></td>
</tr>
<tr>
<th>facet</th>
<td><p>variable to split plots by, either <code>"Interpretation"</code> (default) or <code>"Antibiotic"</code> or a grouping variable</p></td>
</tr>
<tr>
<th>breaks</th>
<td><p>numeric vector of positions</p></td>
</tr>
<tr>
<th>limits</th>
<td><p>numeric vector of length two providing limits of the scale, use <code>NA</code> to refer to the existing minimum or maximum</p></td>
</tr>
<tr>
<th>translate_ab</th>
<td><p>a column name of the <code><a href='antibiotics.html'>antibiotics</a></code> data set to translate the antibiotic abbreviations into, using <code><a href='abname.html'>abname</a></code>. Default behaviour is to translate to official names according to the WHO. Use <code>translate_ab = FALSE</code> to disable translation.</p></td>
</tr>
<tr>
<th>fun</th>
<td><p>function to transform <code>data</code>, either <code><a href='count.html'>count_df</a></code> (default) or <code><a href='portion.html'>portion_df</a></code></p></td>
</tr>
<tr>
<th>nrow</th>
<td><p>(when using <code>facet</code>) number of rows</p></td>
</tr>
<tr>
<th>datalabels</th>
<td><p>show datalabels using <code>labels_rsi_count</code>, will at default only be shown when <code>fun = count_df</code></p></td>
</tr>
<tr>
<th>datalabels.size</th>
<td><p>size of the datalabels</p></td>
</tr>
<tr>
<th>datalabels.colour</th>
<td><p>colour of the datalabels</p></td>
</tr>
<tr>
<th>...</th>
<td><p>other parameters passed on to <code>geom_rsi</code></p></td>
</tr>
</table>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>At default, the names of antibiotics will be shown on the plots using <code><a href='abname.html'>abname</a></code>. This can be set with the option <code>get_antibiotic_names</code> (a logical value), so change it e.g. to <code>FALSE</code> with <code><a href='https://www.rdocumentation.org/packages/base/topics/options'>options(get_antibiotic_names = FALSE)</a></code>.</p>
<p><strong>The functions</strong><br />
<code>geom_rsi</code> will take any variable from the data that has an <code>rsi</code> class (created with <code><a href='as.rsi.html'>as.rsi</a></code>) using <code>fun</code> (<code><a href='count.html'>count_df</a></code> at default, can also be <code><a href='portion.html'>portion_df</a></code>) and will plot bars with the percentage R, I and S. The default behaviour is to have the bars stacked and to have the different antibiotics on the x axis.</p>
<p><code>facet_rsi</code> creates 2d plots (at default based on S/I/R) using <code><a href='https://ggplot2.tidyverse.org/reference/facet_wrap.html'>facet_wrap</a></code>.</p>
<p><code>scale_y_percent</code> transforms the y axis to a 0 to 100% range using <code>scale_continuous</code>.</p>
<p><code>scale_rsi_colours</code> sets colours to the bars: green for S, yellow for I and red for R, using <code>scale_brewer</code>.</p>
<p><code>theme_rsi</code> is a <code>ggplot <a href='https://ggplot2.tidyverse.org/reference/theme.html'>theme</a></code> with minimal distraction.</p>
<p><code>labels_rsi_count</code> print datalabels on the bars with percentage and amount of isolates using <code><a href='https://ggplot2.tidyverse.org/reference/geom_text.html'>geom_text</a></code></p>
<p><code>ggplot_rsi</code> is a wrapper around all above functions that uses data as first input. This makes it possible to use this function after a pipe (<code>%&gt;%</code>). See Examples.</p>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>ggplot2</span>)
<span class='co'># get antimicrobial results for drugs against a UTI:</span>
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/ggplot.html'>ggplot</a></span>(<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span> <span class='fu'><a href='http://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>amox</span>, <span class='no'>nitr</span>, <span class='no'>fosf</span>, <span class='no'>trim</span>, <span class='no'>cipr</span>)) +
<span class='fu'>geom_rsi</span>()</div><div class='img'><img src='ggplot_rsi-1.png' alt='' width='700' height='433' /></div><div class='input'>
<span class='co'># prettify the plot using some additional functions:</span>
<span class='no'>df</span> <span class='kw'>&lt;-</span> <span class='no'>septic_patients</span>[, <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"amox"</span>, <span class='st'>"nitr"</span>, <span class='st'>"fosf"</span>, <span class='st'>"trim"</span>, <span class='st'>"cipr"</span>)]
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/ggplot.html'>ggplot</a></span>(<span class='no'>df</span>) +
<span class='fu'>geom_rsi</span>() +
<span class='fu'>scale_y_percent</span>() +
<span class='fu'>scale_rsi_colours</span>() +
<span class='fu'>labels_rsi_count</span>() +
<span class='fu'>theme_rsi</span>()</div><div class='img'><img src='ggplot_rsi-2.png' alt='' width='700' height='433' /></div><div class='input'>
<span class='co'># or better yet, simplify this using the wrapper function - a single command:</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>amox</span>, <span class='no'>nitr</span>, <span class='no'>fosf</span>, <span class='no'>trim</span>, <span class='no'>cipr</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>ggplot_rsi</span>()</div><div class='img'><img src='ggplot_rsi-3.png' alt='' width='700' height='433' /></div><div class='input'>
<span class='co'># get only portions and no counts:</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>amox</span>, <span class='no'>nitr</span>, <span class='no'>fosf</span>, <span class='no'>trim</span>, <span class='no'>cipr</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>ggplot_rsi</span>(<span class='kw'>fun</span> <span class='kw'>=</span> <span class='no'>portion_df</span>)</div><div class='img'><img src='ggplot_rsi-4.png' alt='' width='700' height='433' /></div><div class='input'>
<span class='co'># add other ggplot2 parameters as you like:</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>amox</span>, <span class='no'>nitr</span>, <span class='no'>fosf</span>, <span class='no'>trim</span>, <span class='no'>cipr</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>ggplot_rsi</span>(<span class='kw'>width</span> <span class='kw'>=</span> <span class='fl'>0.5</span>,
<span class='kw'>colour</span> <span class='kw'>=</span> <span class='st'>"black"</span>,
<span class='kw'>size</span> <span class='kw'>=</span> <span class='fl'>1</span>,
<span class='kw'>linetype</span> <span class='kw'>=</span> <span class='fl'>2</span>,
<span class='kw'>alpha</span> <span class='kw'>=</span> <span class='fl'>0.25</span>)</div><div class='img'><img src='ggplot_rsi-5.png' alt='' width='700' height='433' /></div><div class='input'>
<span class='co'># resistance of ciprofloxacine per age group</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>first_isolate</span> <span class='kw'>=</span> <span class='fu'><a href='first_isolate.html'>first_isolate</a></span>(<span class='no'>.</span>)) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>first_isolate</span> <span class='kw'>==</span> <span class='fl'>TRUE</span>,
<span class='no'>mo</span> <span class='kw'>==</span> <span class='fu'><a href='as.mo.html'>as.mo</a></span>(<span class='st'>"E. coli"</span>)) <span class='kw'>%&gt;%</span>
<span class='co'># `age_group` is also a function of this package:</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='kw'>age_group</span> <span class='kw'>=</span> <span class='fu'><a href='age_groups.html'>age_groups</a></span>(<span class='no'>age</span>)) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>age_group</span>,
<span class='no'>cipr</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>ggplot_rsi</span>(<span class='kw'>x</span> <span class='kw'>=</span> <span class='st'>"age_group"</span>)</div><div class='output co'>#&gt; <span class='message'><span style='color: #0000BB;'>NOTE: Using column `</span><span style='color: #0000BB;font-weight: bold;'>mo</span><span style='color: #0000BB;'>` as input for `col_mo`.</span><span></span></div><div class='output co'>#&gt; <span class='message'></span><span style='color: #0000BB;'>NOTE: Using column `</span><span style='color: #0000BB;font-weight: bold;'>date</span><span style='color: #0000BB;'>` as input for `col_date`.</span><span></span></div><div class='output co'>#&gt; <span class='message'></span><span style='color: #0000BB;'>NOTE: Using column `</span><span style='color: #0000BB;font-weight: bold;'>patient_id</span><span style='color: #0000BB;'>` as input for `col_patient_id`.</span><span></span></div><div class='output co'>#&gt; <span class='message'>=&gt; Found </span><span style='font-weight: bold;'>1,315 first isolates</span><span> (65.8% of total)</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Removed 3 rows containing missing values (geom_bar).</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Removed 3 rows containing missing values (geom_text).</span></div><div class='img'><img src='ggplot_rsi-6.png' alt='' width='700' height='433' /></div></span><div class='input'>
<span class='co'># for colourblind mode, use divergent colours from the viridis package:</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>amox</span>, <span class='no'>nitr</span>, <span class='no'>fosf</span>, <span class='no'>trim</span>, <span class='no'>cipr</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>ggplot_rsi</span>() + <span class='fu'><a href='https://ggplot2.tidyverse.org/reference/scale_viridis.html'>scale_fill_viridis_d</a></span>()</div><div class='output co'>#&gt; <span class='message'>Scale for 'fill' is already present. Adding another scale for 'fill', which</span>
#&gt; <span class='message'>will replace the existing scale.</span></div><div class='img'><img src='ggplot_rsi-7.png' alt='' width='700' height='433' /></div><div class='input'>
<span class='co'># it also supports groups (don't forget to use the group var on `x` or `facet`):</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>hospital_id</span>, <span class='no'>amox</span>, <span class='no'>nitr</span>, <span class='no'>fosf</span>, <span class='no'>trim</span>, <span class='no'>cipr</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>ggplot_rsi</span>(<span class='kw'>x</span> <span class='kw'>=</span> <span class='no'>hospital_id</span>,
<span class='kw'>facet</span> <span class='kw'>=</span> <span class='no'>Antibiotic</span>,
<span class='kw'>nrow</span> <span class='kw'>=</span> <span class='fl'>1</span>) +
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/labs.html'>labs</a></span>(<span class='kw'>title</span> <span class='kw'>=</span> <span class='st'>"AMR of Anti-UTI Drugs Per Hospital"</span>,
<span class='kw'>x</span> <span class='kw'>=</span> <span class='st'>"Hospital"</span>)</div><div class='output co'>#&gt; <span class='error'>Error in ggplot_rsi(., x = hospital_id, facet = Antibiotic, nrow = 1): object 'hospital_id' not found</span></div><div class='input'>
<span class='co'># genuine analysis: check 2 most prevalent microorganisms</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='co'># create new bacterial ID's, with all CoNS under the same group (Becker et al.)</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>mo</span> <span class='kw'>=</span> <span class='fu'><a href='as.mo.html'>as.mo</a></span>(<span class='no'>mo</span>, <span class='kw'>Becker</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)) <span class='kw'>%&gt;%</span>
<span class='co'># filter on top three bacterial ID's</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>mo</span> <span class='kw'>%in%</span> <span class='fu'><a href='freq.html'>top_freq</a></span>(<span class='fu'><a href='freq.html'>freq</a></span>(<span class='no'>.</span>$<span class='no'>mo</span>), <span class='fl'>3</span>)) <span class='kw'>%&gt;%</span>
<span class='co'># determine first isolates</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>first_isolate</span> <span class='kw'>=</span> <span class='fu'><a href='first_isolate.html'>first_isolate</a></span>(<span class='no'>.</span>,
<span class='kw'>col_date</span> <span class='kw'>=</span> <span class='st'>"date"</span>,
<span class='kw'>col_patient_id</span> <span class='kw'>=</span> <span class='st'>"patient_id"</span>,
<span class='kw'>col_mo</span> <span class='kw'>=</span> <span class='st'>"mo"</span>)) <span class='kw'>%&gt;%</span>
<span class='co'># filter on first isolates</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>first_isolate</span> <span class='kw'>==</span> <span class='fl'>TRUE</span>) <span class='kw'>%&gt;%</span>
<span class='co'># get short MO names (like "E. coli")</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>mo</span> <span class='kw'>=</span> <span class='fu'><a href='mo_property.html'>mo_shortname</a></span>(<span class='no'>mo</span>, <span class='kw'>Becker</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)) <span class='kw'>%&gt;%</span>
<span class='co'># select this short name and some antiseptic drugs</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>mo</span>, <span class='no'>cfur</span>, <span class='no'>gent</span>, <span class='no'>cipr</span>) <span class='kw'>%&gt;%</span>
<span class='co'># group by MO</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>mo</span>) <span class='kw'>%&gt;%</span>
<span class='co'># plot the thing, putting MOs on the facet</span>
<span class='fu'>ggplot_rsi</span>(<span class='kw'>x</span> <span class='kw'>=</span> <span class='no'>Antibiotic</span>,
<span class='kw'>facet</span> <span class='kw'>=</span> <span class='no'>mo</span>,
<span class='kw'>translate_ab</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
<span class='kw'>nrow</span> <span class='kw'>=</span> <span class='fl'>1</span>) +
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/labs.html'>labs</a></span>(<span class='kw'>title</span> <span class='kw'>=</span> <span class='st'>"AMR of Top Three Microorganisms In Blood Culture Isolates"</span>,
<span class='kw'>subtitle</span> <span class='kw'>=</span> <span class='st'>"Only First Isolates, CoNS grouped according to Becker et al. (2014)"</span>,
<span class='kw'>x</span> <span class='kw'>=</span> <span class='st'>"Microorganisms"</span>)</div><div class='output co'>#&gt; <span class='message'>=&gt; Found <span style='font-weight: bold;'>780 first isolates</span><span> (59.8% of total)</span></div><div class='output co'>#&gt; <span class='error'>Error in ggplot_rsi(., x = Antibiotic, facet = mo, translate_ab = FALSE, nrow = 1): object 'Antibiotic' not found</span></div></span></pre>
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<p><code><a href="AMR.html">AMR</a></code> </p>
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<td><p>The <code>AMR</code> Package</p></td>
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<td>
<p><code><a href="ab_property.html">ab_property()</a></code> <code><a href="ab_property.html">ab_atc()</a></code> <code><a href="ab_property.html">ab_official()</a></code> <code><a href="ab_property.html">ab_name()</a></code> <code><a href="ab_property.html">ab_trivial_nl()</a></code> <code><a href="ab_property.html">ab_certe()</a></code> <code><a href="ab_property.html">ab_umcg()</a></code> <code><a href="ab_property.html">ab_tradenames()</a></code> </p>
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<td><p>Property of an antibiotic</p></td>
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<td>
<p><code><a href="abname.html">abname()</a></code> </p>
</td>
<td><p>Name of an antibiotic</p></td>
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<td>
<p><code><a href="age.html">age()</a></code> </p>
</td>
<td><p>Age in years of individuals</p></td>
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<td>
<p><code><a href="age_groups.html">age_groups()</a></code> </p>
</td>
<td><p>Split ages into age groups</p></td>
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<td>
<p><code><a href="antibiotics.html">antibiotics</a></code> </p>
</td>
<td><p>Data set with 423 antibiotics</p></td>
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<td>
<p><code><a href="as.atc.html">as.atc()</a></code> <code><a href="as.atc.html">guess_atc()</a></code> <code><a href="as.atc.html">is.atc()</a></code> </p>
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<td><p>Transform to ATC code</p></td>
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<p><code><a href="as.mic.html">as.mic()</a></code> <code><a href="as.mic.html">is.mic()</a></code> </p>
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<td><p>Class 'mic'</p></td>
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<p><code><a href="as.mo.html">as.mo()</a></code> <code><a href="as.mo.html">is.mo()</a></code> <code><a href="as.mo.html">guess_mo()</a></code> </p>
</td>
<td><p>Transform to microorganism ID</p></td>
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<p><code><a href="as.rsi.html">as.rsi()</a></code> <code><a href="as.rsi.html">is.rsi()</a></code> <code><a href="as.rsi.html">is.rsi.eligible()</a></code> </p>
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<td><p>Class 'rsi'</p></td>
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<td>
<p><code><a href="atc_property.html">atc_property()</a></code> <code><a href="atc_property.html">atc_groups()</a></code> <code><a href="atc_property.html">atc_ddd()</a></code> </p>
</td>
<td><p>Properties of an ATC code</p></td>
</tr><tr>
<td>
<p><code><a href="count.html">count_R()</a></code> <code><a href="count.html">count_IR()</a></code> <code><a href="count.html">count_I()</a></code> <code><a href="count.html">count_SI()</a></code> <code><a href="count.html">count_S()</a></code> <code><a href="count.html">count_all()</a></code> <code><a href="count.html">n_rsi()</a></code> <code><a href="count.html">count_df()</a></code> </p>
</td>
<td><p>Count isolates</p></td>
</tr><tr>
<td>
<p><code><a href="eucast_rules.html">eucast_rules()</a></code> <code><a href="eucast_rules.html">EUCAST_rules()</a></code> <code><a href="eucast_rules.html">interpretive_reading()</a></code> </p>
</td>
<td><p>EUCAST rules</p></td>
</tr><tr>
<td>
<p><code><a href="first_isolate.html">first_isolate()</a></code> <code><a href="first_isolate.html">filter_first_isolate()</a></code> <code><a href="first_isolate.html">filter_first_weighted_isolate()</a></code> </p>
</td>
<td><p>Determine first (weighted) isolates</p></td>
</tr><tr>
<td>
<p><code><a href="freq.html">frequency_tbl()</a></code> <code><a href="freq.html">freq()</a></code> <code><a href="freq.html">top_freq()</a></code> <code><a href="freq.html">print(<i>&lt;frequency_tbl&gt;</i>)</a></code> </p>
</td>
<td><p>Frequency table</p></td>
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<td>
<p><code><a href="g.test.html">g.test()</a></code> </p>
</td>
<td><p><em>G</em>-test for Count Data</p></td>
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<td>
<p><code><a href="get_locale.html">get_locale()</a></code> </p>
</td>
<td><p>Get language for AMR</p></td>
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<td>
<p><code><a href="ggplot_rsi.html">ggplot_rsi()</a></code> <code><a href="ggplot_rsi.html">geom_rsi()</a></code> <code><a href="ggplot_rsi.html">facet_rsi()</a></code> <code><a href="ggplot_rsi.html">scale_y_percent()</a></code> <code><a href="ggplot_rsi.html">scale_rsi_colours()</a></code> <code><a href="ggplot_rsi.html">theme_rsi()</a></code> <code><a href="ggplot_rsi.html">labels_rsi_count()</a></code> </p>
</td>
<td><p>AMR bar plots with <code>ggplot</code></p></td>
</tr><tr>
<td>
<p><code><a href="join.html">inner_join_microorganisms()</a></code> <code><a href="join.html">left_join_microorganisms()</a></code> <code><a href="join.html">right_join_microorganisms()</a></code> <code><a href="join.html">full_join_microorganisms()</a></code> <code><a href="join.html">semi_join_microorganisms()</a></code> <code><a href="join.html">anti_join_microorganisms()</a></code> </p>
</td>
<td><p>Join a table with <code>microorganisms</code></p></td>
</tr><tr>
<td>
<p><code><a href="key_antibiotics.html">key_antibiotics()</a></code> <code><a href="key_antibiotics.html">key_antibiotics_equal()</a></code> </p>
</td>
<td><p>Key antibiotics for first <em>weighted</em> isolates</p></td>
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<td>
<p><code><a href="kurtosis.html">kurtosis()</a></code> </p>
</td>
<td><p>Kurtosis of the sample</p></td>
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<td>
<p><code><a href="like.html">like()</a></code> <code><a href="like.html">`%like%`</a></code> </p>
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<td><p>Pattern Matching</p></td>
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<td>
<p><code><a href="mdro.html">mdro()</a></code> <code><a href="mdro.html">brmo()</a></code> <code><a href="mdro.html">mrgn()</a></code> <code><a href="mdro.html">eucast_exceptional_phenotypes()</a></code> </p>
</td>
<td><p>Determine multidrug-resistant organisms (MDRO)</p></td>
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<td>
<p><code><a href="microorganisms.html">microorganisms</a></code> </p>
</td>
<td><p>Data set with taxonomic data from ITIS</p></td>
</tr><tr>
<td>
<p><code><a href="microorganisms.certe.html">microorganisms.certe</a></code> </p>
</td>
<td><p>Translation table for Certe</p></td>
</tr><tr>
<td>
<p><code><a href="microorganisms.old.html">microorganisms.old</a></code> </p>
</td>
<td><p>Data set with old taxonomic data from ITIS</p></td>
</tr><tr>
<td>
<p><code><a href="microorganisms.umcg.html">microorganisms.umcg</a></code> </p>
</td>
<td><p>Translation table for UMCG</p></td>
</tr><tr>
<td>
<p><code><a href="mo_failures.html">mo_failures()</a></code> </p>
</td>
<td><p>Vector of failed coercion attempts</p></td>
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<td>
<p><code><a href="mo_property.html">mo_fullname()</a></code> <code><a href="mo_property.html">mo_shortname()</a></code> <code><a href="mo_property.html">mo_subspecies()</a></code> <code><a href="mo_property.html">mo_species()</a></code> <code><a href="mo_property.html">mo_genus()</a></code> <code><a href="mo_property.html">mo_family()</a></code> <code><a href="mo_property.html">mo_order()</a></code> <code><a href="mo_property.html">mo_class()</a></code> <code><a href="mo_property.html">mo_phylum()</a></code> <code><a href="mo_property.html">mo_subkingdom()</a></code> <code><a href="mo_property.html">mo_kingdom()</a></code> <code><a href="mo_property.html">mo_type()</a></code> <code><a href="mo_property.html">mo_gramstain()</a></code> <code><a href="mo_property.html">mo_TSN()</a></code> <code><a href="mo_property.html">mo_ref()</a></code> <code><a href="mo_property.html">mo_authors()</a></code> <code><a href="mo_property.html">mo_year()</a></code> <code><a href="mo_property.html">mo_taxonomy()</a></code> <code><a href="mo_property.html">mo_property()</a></code> </p>
</td>
<td><p>Property of a microorganism</p></td>
</tr><tr>
<td>
<p><code><a href="mo_renamed.html">mo_renamed()</a></code> </p>
</td>
<td><p>Vector of taxonomic renamed items</p></td>
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<td>
<p><code><a href="p.symbol.html">p.symbol()</a></code> </p>
</td>
<td><p>Symbol of a p value</p></td>
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<td>
<p><code><a href="portion.html">portion_R()</a></code> <code><a href="portion.html">portion_IR()</a></code> <code><a href="portion.html">portion_I()</a></code> <code><a href="portion.html">portion_SI()</a></code> <code><a href="portion.html">portion_S()</a></code> <code><a href="portion.html">portion_df()</a></code> </p>
</td>
<td><p>Calculate resistance of isolates</p></td>
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<td>
<p><code><a href="read.4D.html">read.4D()</a></code> </p>
</td>
<td><p>Read data from 4D database</p></td>
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<td>
<p><code><a href="resistance_predict.html">resistance_predict()</a></code> <code><a href="resistance_predict.html">rsi_predict()</a></code> </p>
</td>
<td><p>Predict antimicrobial resistance</p></td>
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<td>
<p><code><a href="rsi.html">rsi()</a></code> </p>
</td>
<td><p>Calculate resistance of isolates</p></td>
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<td>
<p><code><a href="septic_patients.html">septic_patients</a></code> </p>
</td>
<td><p>Data set with 2000 blood culture isolates of septic patients</p></td>
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<td>
<p><code><a href="skewness.html">skewness()</a></code> </p>
</td>
<td><p>Skewness of the sample</p></td>
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<td>
<p><code><a href="supplementary_data.html">microorganismsDT</a></code> <code><a href="supplementary_data.html">microorganisms.prevDT</a></code> <code><a href="supplementary_data.html">microorganisms.unprevDT</a></code> <code><a href="supplementary_data.html">microorganisms.oldDT</a></code> </p>
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<td><p>Supplementary Data</p></td>
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<h1>Key antibiotics for first <em>weighted</em> isolates</h1>
<div class="hidden name"><code>key_antibiotics.Rd</code></div>
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<div class="ref-description">
<p>These function can be used to determine first isolates (see <code><a href='first_isolate.html'>first_isolate</a></code>). Using key antibiotics to determine first isolates is more reliable than without key antibiotics. These selected isolates will then be called first <em>weighted</em> isolates.</p>
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<pre class="usage"><span class='fu'>key_antibiotics</span>(<span class='no'>tbl</span>, <span class='kw'>col_mo</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>universal_1</span> <span class='kw'>=</span> <span class='st'>"amox"</span>,
<span class='kw'>universal_2</span> <span class='kw'>=</span> <span class='st'>"amcl"</span>, <span class='kw'>universal_3</span> <span class='kw'>=</span> <span class='st'>"cfur"</span>, <span class='kw'>universal_4</span> <span class='kw'>=</span> <span class='st'>"pita"</span>,
<span class='kw'>universal_5</span> <span class='kw'>=</span> <span class='st'>"cipr"</span>, <span class='kw'>universal_6</span> <span class='kw'>=</span> <span class='st'>"trsu"</span>, <span class='kw'>GramPos_1</span> <span class='kw'>=</span> <span class='st'>"vanc"</span>,
<span class='kw'>GramPos_2</span> <span class='kw'>=</span> <span class='st'>"teic"</span>, <span class='kw'>GramPos_3</span> <span class='kw'>=</span> <span class='st'>"tetr"</span>, <span class='kw'>GramPos_4</span> <span class='kw'>=</span> <span class='st'>"eryt"</span>,
<span class='kw'>GramPos_5</span> <span class='kw'>=</span> <span class='st'>"oxac"</span>, <span class='kw'>GramPos_6</span> <span class='kw'>=</span> <span class='st'>"rifa"</span>, <span class='kw'>GramNeg_1</span> <span class='kw'>=</span> <span class='st'>"gent"</span>,
<span class='kw'>GramNeg_2</span> <span class='kw'>=</span> <span class='st'>"tobr"</span>, <span class='kw'>GramNeg_3</span> <span class='kw'>=</span> <span class='st'>"coli"</span>, <span class='kw'>GramNeg_4</span> <span class='kw'>=</span> <span class='st'>"cfot"</span>,
<span class='kw'>GramNeg_5</span> <span class='kw'>=</span> <span class='st'>"cfta"</span>, <span class='kw'>GramNeg_6</span> <span class='kw'>=</span> <span class='st'>"mero"</span>, <span class='kw'>warnings</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='no'>...</span>)
<span class='fu'>key_antibiotics_equal</span>(<span class='no'>x</span>, <span class='no'>y</span>, <span class='kw'>type</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"keyantibiotics"</span>, <span class='st'>"points"</span>),
<span class='kw'>ignore_I</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>points_threshold</span> <span class='kw'>=</span> <span class='fl'>2</span>, <span class='kw'>info</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>tbl</th>
<td><p>table with antibiotics coloms, like <code>amox</code> and <code>amcl</code>.</p></td>
</tr>
<tr>
<th>col_mo</th>
<td><p>column name of the unique IDs of the microorganisms (see <code><a href='as.mo.html'>mo</a></code>), defaults to the first column of class <code>mo</code>. Values will be coerced using <code><a href='as.mo.html'>as.mo</a></code>.</p></td>
</tr>
<tr>
<th>universal_1, universal_2, universal_3, universal_4, universal_5, universal_6</th>
<td><p>column names of <strong>broad-spectrum</strong> antibiotics, case-insensitive</p></td>
</tr>
<tr>
<th>GramPos_1, GramPos_2, GramPos_3, GramPos_4, GramPos_5, GramPos_6</th>
<td><p>column names of antibiotics for <strong>Gram positives</strong>, case-insensitive</p></td>
</tr>
<tr>
<th>GramNeg_1, GramNeg_2, GramNeg_3, GramNeg_4, GramNeg_5, GramNeg_6</th>
<td><p>column names of antibiotics for <strong>Gram negatives</strong>, case-insensitive</p></td>
</tr>
<tr>
<th>warnings</th>
<td><p>give warning about missing antibiotic columns, they will anyway be ignored</p></td>
</tr>
<tr>
<th>...</th>
<td><p>other parameters passed on to function</p></td>
</tr>
<tr>
<th>x, y</th>
<td><p>characters to compare</p></td>
</tr>
<tr>
<th>type</th>
<td><p>type to determine weighed isolates; can be <code>"keyantibiotics"</code> or <code>"points"</code>, see Details</p></td>
</tr>
<tr>
<th>ignore_I</th>
<td><p>logical to determine whether antibiotic interpretations with <code>"I"</code> will be ignored when <code>type = "keyantibiotics"</code>, see Details</p></td>
</tr>
<tr>
<th>points_threshold</th>
<td><p>points until the comparison of key antibiotics will lead to inclusion of an isolate when <code>type = "points"</code>, see Details</p></td>
</tr>
<tr>
<th>info</th>
<td><p>print progress</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>The function <code>key_antibiotics</code> returns a character vector with 12 antibiotic results for every isolate. These isolates can then be compared using <code>key_antibiotics_equal</code>, to check if two isolates have generally the same antibiogram. Missing and invalid values are replaced with a dot (<code>"."</code>). The <code><a href='first_isolate.html'>first_isolate</a></code> function only uses this function on the same microbial species from the same patient. Using this, an MRSA will be included after a susceptible <em>S. aureus</em> (MSSA) found within the same episode (see <code>episode</code> parameter of <code><a href='first_isolate.html'>first_isolate</a></code>). Without key antibiotic comparison it wouldn't.</p>
<p>At default, the antibiotics that are used for <strong>Gram positive bacteria</strong> are (colum names): <br />
<code>"amox"</code>, <code>"amcl"</code>, <code>"cfur"</code>, <code>"pita"</code>, <code>"cipr"</code>, <code>"trsu"</code> (until here is universal), <code>"vanc"</code>, <code>"teic"</code>, <code>"tetr"</code>, <code>"eryt"</code>, <code>"oxac"</code>, <code>"rifa"</code>.</p>
<p>At default, the antibiotics that are used for <strong>Gram negative bacteria</strong> are (colum names): <br />
<code>"amox"</code>, <code>"amcl"</code>, <code>"cfur"</code>, <code>"pita"</code>, <code>"cipr"</code>, <code>"trsu"</code> (until here is universal), <code>"gent"</code>, <code>"tobr"</code>, <code>"coli"</code>, <code>"cfot"</code>, <code>"cfta"</code>, <code>"mero"</code>.</p>
<p>The function <code>key_antibiotics_equal</code> checks the characters returned by <code>key_antibiotics</code> for equality, and returns a logical vector.</p>
<h2 class="hasAnchor" id="key-antibiotics"><a class="anchor" href="#key-antibiotics"></a>Key antibiotics</h2>
<p>There are two ways to determine whether isolates can be included as first <em>weighted</em> isolates which will give generally the same results: <br /></p>
<p><strong>1. Using</strong> <code>type = "keyantibiotics"</code> <strong>and parameter</strong> <code>ignore_I</code> <br />
Any difference from S to R (or vice versa) will (re)select an isolate as a first weighted isolate. With <code>ignore_I = FALSE</code>, also differences from I to S|R (or vice versa) will lead to this. This is a reliable method and 30-35 times faster than method 2. <br /></p>
<p><strong>2. Using</strong> <code>type = "points"</code> <strong>and parameter</strong> <code>points_threshold</code> <br />
A difference from I to S|R (or vice versa) means 0.5 points, a difference from S to R (or vice versa) means 1 point. When the sum of points exceeds <code>points_threshold</code>, an isolate will be (re)selected as a first weighted isolate.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='first_isolate.html'>first_isolate</a></code></p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='co'># septic_patients is a dataset available in the AMR package</span>
?<span class='no'>septic_patients</span></div><div class='output co'>#&gt; <span class='message'>Rendering development documentation for 'septic_patients'</span></div><div class='input'><span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='co'># set key antibiotics to a new variable</span>
<span class='no'>my_patients</span> <span class='kw'>&lt;-</span> <span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>keyab</span> <span class='kw'>=</span> <span class='fu'>key_antibiotics</span>(<span class='no'>.</span>)) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(
<span class='co'># now calculate first isolates</span>
<span class='kw'>first_regular</span> <span class='kw'>=</span> <span class='fu'><a href='first_isolate.html'>first_isolate</a></span>(<span class='no'>.</span>, <span class='kw'>col_keyantibiotics</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>),
<span class='co'># and first WEIGHTED isolates</span>
<span class='kw'>first_weighted</span> <span class='kw'>=</span> <span class='fu'><a href='first_isolate.html'>first_isolate</a></span>(<span class='no'>.</span>, <span class='kw'>col_keyantibiotics</span> <span class='kw'>=</span> <span class='st'>"keyab"</span>)
)</div><div class='output co'>#&gt; <span class='message'><span style='color: #0000BB;'>NOTE: Using column `</span><span style='color: #0000BB;font-weight: bold;'>mo</span><span style='color: #0000BB;'>` as input for `col_mo`.</span><span></span></div><div class='output co'>#&gt; <span class='message'></span><span style='color: #0000BB;'>NOTE: Using column `</span><span style='color: #0000BB;font-weight: bold;'>mo</span><span style='color: #0000BB;'>` as input for `col_mo`.</span><span></span></div><div class='output co'>#&gt; <span class='message'></span><span style='color: #0000BB;'>NOTE: Using column `</span><span style='color: #0000BB;font-weight: bold;'>date</span><span style='color: #0000BB;'>` as input for `col_date`.</span><span></span></div><div class='output co'>#&gt; <span class='message'></span><span style='color: #0000BB;'>NOTE: Using column `</span><span style='color: #0000BB;font-weight: bold;'>patient_id</span><span style='color: #0000BB;'>` as input for `col_patient_id`.</span><span></span></div><div class='output co'>#&gt; <span class='message'>=&gt; Found </span><span style='font-weight: bold;'>1,315 first isolates</span><span> (65.8% of total)</span></div><div class='output co'>#&gt; <span class='message'></span><span style='color: #0000BB;'>NOTE: Using column `</span><span style='color: #0000BB;font-weight: bold;'>mo</span><span style='color: #0000BB;'>` as input for `col_mo`.</span><span></span></div><div class='output co'>#&gt; <span class='message'></span><span style='color: #0000BB;'>NOTE: Using column `</span><span style='color: #0000BB;font-weight: bold;'>date</span><span style='color: #0000BB;'>` as input for `col_date`.</span><span></span></div><div class='output co'>#&gt; <span class='message'></span><span style='color: #0000BB;'>NOTE: Using column `</span><span style='color: #0000BB;font-weight: bold;'>patient_id</span><span style='color: #0000BB;'>` as input for `col_patient_id`.</span><span></span></div><div class='output co'>#&gt; [Criterion] Inclusion based on key antibiotics, ignoring I.</div><div class='output co'>#&gt; <span class='message'>=&gt; Found </span><span style='font-weight: bold;'>1,411 first weighted isolates</span><span> (70.6% of total)</span></div><div class='input'>
<span class='co'># Check the difference, in this data set it results in 7% more isolates:</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/sum'>sum</a></span>(<span class='no'>my_patients</span>$<span class='no'>first_regular</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='output co'>#&gt; [1] 1315</div><div class='input'><span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/sum'>sum</a></span>(<span class='no'>my_patients</span>$<span class='no'>first_weighted</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</div><div class='output co'>#&gt; [1] 1411</div><div class='input'>
<span class='co'># output of the `key_antibiotics` function could be like this:</span>
<span class='no'>strainA</span> <span class='kw'>&lt;-</span> <span class='st'>"SSSRR.S.R..S"</span>
<span class='no'>strainB</span> <span class='kw'>&lt;-</span> <span class='st'>"SSSIRSSSRSSS"</span>
<span class='fu'>key_antibiotics_equal</span>(<span class='no'>strainA</span>, <span class='no'>strainB</span>)</div><div class='output co'>#&gt; [1] TRUE</div><div class='input'><span class='co'># TRUE, because I is ignored (as well as missing values)</span>
<span class='fu'>key_antibiotics_equal</span>(<span class='no'>strainA</span>, <span class='no'>strainB</span>, <span class='kw'>ignore_I</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</div><div class='output co'>#&gt; [1] FALSE</div><div class='input'># FALSE, because I is not ignored and so the 4th value differs
</div></span></pre>
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<li><a href="#arguments">Arguments</a></li>
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<h1>Kurtosis of the sample</h1>
<div class="hidden name"><code>kurtosis.Rd</code></div>
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<div class="ref-description">
<p>Kurtosis is a measure of the "tailedness" of the probability distribution of a real-valued random variable.</p>
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<pre class="usage"><span class='fu'>kurtosis</span>(<span class='no'>x</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='co'># S3 method for default</span>
<span class='fu'>kurtosis</span>(<span class='no'>x</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='co'># S3 method for matrix</span>
<span class='fu'>kurtosis</span>(<span class='no'>x</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='co'># S3 method for data.frame</span>
<span class='fu'>kurtosis</span>(<span class='no'>x</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
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<th>x</th>
<td><p>a vector of values, a <code>matrix</code> or a <code>data frame</code></p></td>
</tr>
<tr>
<th>na.rm</th>
<td><p>a logical value indicating whether <code>NA</code> values should be stripped before the computation proceeds.</p></td>
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<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
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<h1>Pattern Matching</h1>
<div class="hidden name"><code>like.Rd</code></div>
</div>
<div class="ref-description">
<p>Convenient wrapper around <code><a href='https://www.rdocumentation.org/packages/base/topics/grep'>grep</a></code> to match a pattern: <code>a %like% b</code>. It always returns a <code>logical</code> vector and is always case-insensitive. Also, <code>pattern</code> (<code>b</code>) can be as long as <code>x</code> (<code>a</code>) to compare items of each index in both vectors.</p>
</div>
<pre class="usage"><span class='fu'>like</span>(<span class='no'>x</span>, <span class='no'>pattern</span>)
<span class='no'>x</span> <span class='kw'>%like%</span> <span class='no'>pattern</span></pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>x</th>
<td><p>a character vector where matches are sought, or an
object which can be coerced by <code>as.character</code> to a character
vector. <a href='https://www.rdocumentation.org/packages/base/topics/LongVectors'>Long vectors</a> are supported.</p></td>
</tr>
<tr>
<th>pattern</th>
<td><p>character string containing a <a href='https://www.rdocumentation.org/packages/base/topics/regex'>regular expression</a>
(or character string for <code>fixed = TRUE</code>) to be matched
in the given character vector. Coerced by
<code><a href='https://www.rdocumentation.org/packages/base/topics/character'>as.character</a></code> to a character string if possible. If a
character vector of length 2 or more is supplied, the first element
is used with a warning. Missing values are allowed except for
<code>regexpr</code> and <code>gregexpr</code>.</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p>Idea from the <a href='https://github.com/Rdatatable/data.table/blob/master/R/like.R'><code>like</code> function from the <code>data.table</code> package</a>, but made it case insensitive at default and let it support multiple patterns.</p>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>A <code>logical</code> vector</p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>Using RStudio? This function can also be inserted from the Addins menu and can have its own Keyboard Shortcut like Ctrl+Shift+L or Cmd+Shift+L (see Tools &gt; Modify Keyboard Shortcuts...).</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='https://www.rdocumentation.org/packages/base/topics/grep'>grep</a></code></p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='co'># simple test</span>
<span class='no'>a</span> <span class='kw'>&lt;-</span> <span class='st'>"This is a test"</span>
<span class='no'>b</span> <span class='kw'>&lt;-</span> <span class='st'>"TEST"</span>
<span class='no'>a</span> <span class='kw'>%like%</span> <span class='no'>b</span></div><div class='output co'>#&gt; [1] TRUE</div><div class='input'><span class='co'>#&gt; TRUE</span>
<span class='no'>b</span> <span class='kw'>%like%</span> <span class='no'>a</span></div><div class='output co'>#&gt; [1] FALSE</div><div class='input'><span class='co'>#&gt; FALSE</span>
<span class='co'># also supports multiple patterns, length must be equal to x</span>
<span class='no'>a</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"Test case"</span>, <span class='st'>"Something different"</span>, <span class='st'>"Yet another thing"</span>)
<span class='no'>b</span> <span class='kw'>&lt;-</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"case"</span>, <span class='st'>"diff"</span>, <span class='st'>"yet"</span>)
<span class='no'>a</span> <span class='kw'>%like%</span> <span class='no'>b</span></div><div class='output co'>#&gt; [1] TRUE TRUE TRUE</div><div class='input'><span class='co'>#&gt; TRUE TRUE TRUE</span>
<span class='co'># get frequencies of bacteria whose name start with 'Ent' or 'ent'</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='join.html'>left_join_microorganisms</a></span>() <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>genus</span> <span class='kw'>%like%</span> <span class='st'>'^ent'</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='freq.html'>freq</a></span>(<span class='no'>genus</span>, <span class='no'>species</span>)</div><div class='output co'>#&gt; <span class='message'>Joining, by = "mo"</span></div><div class='output co'>#&gt;
#&gt;
#&gt; **Frequency table of `genus` and `species`**
#&gt;
#&gt;
#&gt; | |Item | Count| Percent| Cum. Count| Cum. Percent|
#&gt; |:--|:--------------------------|-----:|-------:|----------:|------------:|
#&gt; |1 |Enterococcus faecalis | 39| 35.8%| 39| 35.8%|
#&gt; |2 |Enterobacter cloacae | 23| 21.1%| 62| 56.9%|
#&gt; |3 |Enterococcus faecium | 21| 19.3%| 83| 76.1%|
#&gt; |4 |Enterococcus species | 20| 18.3%| 103| 94.5%|
#&gt; |5 |Enterobacter aerogenes | 3| 2.8%| 106| 97.2%|
#&gt; |6 |Enterococcus avium | 2| 1.8%| 108| 99.1%|
#&gt; |7 |Enterococcus casseliflavus | 1| 0.9%| 109| 100.0%|
#&gt;
#&gt; </div></pre>
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<div class="hidden name"><code>microorganisms.certe.Rd</code></div>
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<p>A data set containing all bacteria codes of Certe MMB. These codes can be joined to data with an ID from <code><a href='microorganisms.html'>microorganisms</a>$mo</code> (using <code><a href='join.html'>left_join_microorganisms</a></code>). GLIMS codes can also be translated to valid <code>MO</code>s with <code><a href='as.mo.html'>guess_mo</a></code>.</p>
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<pre class="usage"><span class='no'>microorganisms.certe</span></pre>
<h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
<p>A <code><a href='https://www.rdocumentation.org/packages/base/topics/data.frame'>data.frame</a></code> with 2,665 observations and 2 variables:</p><dl class='dl-horizontal'>
<dt><code>certe</code></dt><dd><p>Code of microorganism according to Certe MMB</p></dd>
<dt><code>mo</code></dt><dd><p>Code of microorganism in <code><a href='microorganisms.html'>microorganisms</a></code></p></dd>
</dl>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='as.mo.html'>as.mo</a></code> <code><a href='microorganisms.html'>microorganisms</a></code></p></div>
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<h1>Data set with taxonomic data from ITIS</h1>
<div class="hidden name"><code>microorganisms.Rd</code></div>
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<div class="ref-description">
<p>A data set containing the complete microbial taxonomy of the kingdoms Bacteria, Fungi and Protozoa. MO codes can be looked up using <code><a href='as.mo.html'>as.mo</a></code>.</p>
</div>
<pre class="usage"><span class='no'>microorganisms</span></pre>
<h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
<p>A <code><a href='https://www.rdocumentation.org/packages/base/topics/data.frame'>data.frame</a></code> with 18,833 observations and 15 variables:</p><dl class='dl-horizontal'>
<dt><code>mo</code></dt><dd><p>ID of microorganism</p></dd>
<dt><code>tsn</code></dt><dd><p>Taxonomic Serial Number (TSN), as defined by ITIS</p></dd>
<dt><code>genus</code></dt><dd><p>Taxonomic genus of the microorganism as found in ITIS, see Source</p></dd>
<dt><code>species</code></dt><dd><p>Taxonomic species of the microorganism as found in ITIS, see Source</p></dd>
<dt><code>subspecies</code></dt><dd><p>Taxonomic subspecies of the microorganism as found in ITIS, see Source</p></dd>
<dt><code>fullname</code></dt><dd><p>Full name, like <code>"Echerichia coli"</code></p></dd>
<dt><code>family</code></dt><dd><p>Taxonomic family of the microorganism as found in ITIS, see Source</p></dd>
<dt><code>order</code></dt><dd><p>Taxonomic order of the microorganism as found in ITIS, see Source</p></dd>
<dt><code>class</code></dt><dd><p>Taxonomic class of the microorganism as found in ITIS, see Source</p></dd>
<dt><code>phylum</code></dt><dd><p>Taxonomic phylum of the microorganism as found in ITIS, see Source</p></dd>
<dt><code>subkingdom</code></dt><dd><p>Taxonomic subkingdom of the microorganism as found in ITIS, see Source</p></dd>
<dt><code>kingdom</code></dt><dd><p>Taxonomic kingdom of the microorganism as found in ITIS, see Source</p></dd>
<dt><code>gramstain</code></dt><dd><p>Gram of microorganism, like <code>"Gram negative"</code></p></dd>
<dt><code>prevalence</code></dt><dd><p>An integer based on estimated prevalence of the microorganism in humans. Used internally by <code><a href='as.mo.html'>as.mo</a></code>, otherwise quite meaningless. It has a value of 25 for manually added items and a value of 1000 for all unprevalent microorganisms whose genus was somewhere in the top 250 (with another species).</p></dd>
<dt><code>ref</code></dt><dd><p>Author(s) and year of concerning publication as found in ITIS, see Source</p></dd>
</dl>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p>[3] Integrated Taxonomic Information System (ITIS) on-line database, <a href='https://www.itis.gov'>https://www.itis.gov</a>.</p>
<h2 class="hasAnchor" id="itis"><a class="anchor" href="#itis"></a>ITIS</h2>
<p><img src='figures/itis_logo.jpg' height=60px style=margin-bottom:5px /> <br />
This package contains the <strong>complete microbial taxonomic data</strong> (with all nine taxonomic ranks - from kingdom to subspecies) from the publicly available Integrated Taxonomic Information System (ITIS, <a href='https://www.itis.gov'>https://www.itis.gov</a>).</p>
<p>All (sub)species from <strong>the taxonomic kingdoms Bacteria, Fungi and Protozoa are included in this package</strong>, as well as all previously accepted names known to ITIS. Furthermore, the responsible authors and year of publication are available. This allows users to use authoritative taxonomic information for their data analysis on any microorganism, not only human pathogens. It also helps to quickly determine the Gram stain of bacteria, since all bacteria are classified into subkingdom Negibacteria or Posibacteria.</p>
<p>ITIS is a partnership of U.S., Canadian, and Mexican agencies and taxonomic specialists [3].</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='as.mo.html'>as.mo</a></code> <code><a href='mo_property.html'>mo_property</a></code> <code><a href='microorganisms.umcg.html'>microorganisms.umcg</a></code></p></div>
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<h1>Data set with old taxonomic data from ITIS</h1>
<div class="hidden name"><code>microorganisms.old.Rd</code></div>
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<div class="ref-description">
<p>A data set containing old (previously valid or accepted) taxonomic names according to ITIS. This data set is used internally by <code><a href='as.mo.html'>as.mo</a></code>.</p>
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<pre class="usage"><span class='no'>microorganisms.old</span></pre>
<h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
<p>A <code><a href='https://www.rdocumentation.org/packages/base/topics/data.frame'>data.frame</a></code> with 2,383 observations and 4 variables:</p><dl class='dl-horizontal'>
<dt><code>tsn</code></dt><dd><p>Old Taxonomic Serial Number (TSN), as defined by ITIS</p></dd>
<dt><code>name</code></dt><dd><p>Old taxonomic name of the microorganism as found in ITIS, see Source</p></dd>
<dt><code>tsn_new</code></dt><dd><p>New Taxonomic Serial Number (TSN), as defined by ITIS</p></dd>
<dt><code>ref</code></dt><dd><p>Author(s) and year of concerning publication as found in ITIS, see Source</p></dd>
</dl>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p>[3] Integrated Taxonomic Information System (ITIS) on-line database, <a href='https://www.itis.gov'>https://www.itis.gov</a>.</p>
<h2 class="hasAnchor" id="itis"><a class="anchor" href="#itis"></a>ITIS</h2>
<p><img src='figures/itis_logo.jpg' height=60px style=margin-bottom:5px /> <br />
This package contains the <strong>complete microbial taxonomic data</strong> (with all nine taxonomic ranks - from kingdom to subspecies) from the publicly available Integrated Taxonomic Information System (ITIS, <a href='https://www.itis.gov'>https://www.itis.gov</a>).</p>
<p>All (sub)species from <strong>the taxonomic kingdoms Bacteria, Fungi and Protozoa are included in this package</strong>, as well as all previously accepted names known to ITIS. Furthermore, the responsible authors and year of publication are available. This allows users to use authoritative taxonomic information for their data analysis on any microorganism, not only human pathogens. It also helps to quickly determine the Gram stain of bacteria, since all bacteria are classified into subkingdom Negibacteria or Posibacteria.</p>
<p>ITIS is a partnership of U.S., Canadian, and Mexican agencies and taxonomic specialists [3].</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='as.mo.html'>as.mo</a></code> <code><a href='mo_property.html'>mo_property</a></code> <code><a href='microorganisms.html'>microorganisms</a></code></p></div>
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<li><a href="#format">Format</a></li>
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<h1>Translation table for UMCG</h1>
<div class="hidden name"><code>microorganisms.umcg.Rd</code></div>
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<p>A data set containing all bacteria codes of UMCG MMB. These codes can be joined to data with an ID from <code><a href='microorganisms.html'>microorganisms</a>$mo</code> (using <code><a href='join.html'>left_join_microorganisms</a></code>). GLIMS codes can also be translated to valid <code>MO</code>s with <code><a href='as.mo.html'>guess_mo</a></code>.</p>
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<pre class="usage"><span class='no'>microorganisms.umcg</span></pre>
<h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
<p>A <code><a href='https://www.rdocumentation.org/packages/base/topics/data.frame'>data.frame</a></code> with 1,095 observations and 2 variables:</p><dl class='dl-horizontal'>
<dt><code>umcg</code></dt><dd><p>Code of microorganism according to UMCG MMB</p></dd>
<dt><code>certe</code></dt><dd><p>Code of microorganism according to Certe MMB</p></dd>
</dl>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='as.mo.html'>as.mo</a></code> <code><a href='microorganisms.certe.html'>microorganisms.certe</a></code> <code><a href='microorganisms.html'>microorganisms</a></code></p></div>
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<h1>Vector of failed coercion attempts</h1>
<div class="hidden name"><code>mo_failures.Rd</code></div>
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<p>Returns a vector of all failed attempts to coerce values to a valid MO code with <code><a href='as.mo.html'>as.mo</a></code>.</p>
</div>
<pre class="usage"><span class='fu'>mo_failures</span>()</pre>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
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<h1>Property of a microorganism</h1>
<div class="hidden name"><code>mo_property.Rd</code></div>
</div>
<div class="ref-description">
<p>Use these functions to return a specific property of a microorganism from the <code><a href='microorganisms.html'>microorganisms</a></code> data set. All input values will be evaluated internally with <code><a href='as.mo.html'>as.mo</a></code>.</p>
</div>
<pre class="usage"><span class='fu'>mo_fullname</span>(<span class='no'>x</span>, <span class='kw'>language</span> <span class='kw'>=</span> <span class='fu'><a href='get_locale.html'>get_locale</a></span>(), <span class='no'>...</span>)
<span class='fu'>mo_shortname</span>(<span class='no'>x</span>, <span class='kw'>language</span> <span class='kw'>=</span> <span class='fu'><a href='get_locale.html'>get_locale</a></span>(), <span class='no'>...</span>)
<span class='fu'>mo_subspecies</span>(<span class='no'>x</span>, <span class='kw'>language</span> <span class='kw'>=</span> <span class='fu'><a href='get_locale.html'>get_locale</a></span>(), <span class='no'>...</span>)
<span class='fu'>mo_species</span>(<span class='no'>x</span>, <span class='kw'>language</span> <span class='kw'>=</span> <span class='fu'><a href='get_locale.html'>get_locale</a></span>(), <span class='no'>...</span>)
<span class='fu'>mo_genus</span>(<span class='no'>x</span>, <span class='kw'>language</span> <span class='kw'>=</span> <span class='fu'><a href='get_locale.html'>get_locale</a></span>(), <span class='no'>...</span>)
<span class='fu'>mo_family</span>(<span class='no'>x</span>, <span class='no'>...</span>)
<span class='fu'>mo_order</span>(<span class='no'>x</span>, <span class='no'>...</span>)
<span class='fu'>mo_class</span>(<span class='no'>x</span>, <span class='no'>...</span>)
<span class='fu'>mo_phylum</span>(<span class='no'>x</span>, <span class='no'>...</span>)
<span class='fu'>mo_subkingdom</span>(<span class='no'>x</span>, <span class='no'>...</span>)
<span class='fu'>mo_kingdom</span>(<span class='no'>x</span>, <span class='no'>...</span>)
<span class='fu'>mo_type</span>(<span class='no'>x</span>, <span class='kw'>language</span> <span class='kw'>=</span> <span class='fu'><a href='get_locale.html'>get_locale</a></span>(), <span class='no'>...</span>)
<span class='fu'>mo_gramstain</span>(<span class='no'>x</span>, <span class='kw'>language</span> <span class='kw'>=</span> <span class='fu'><a href='get_locale.html'>get_locale</a></span>(), <span class='no'>...</span>)
<span class='fu'>mo_TSN</span>(<span class='no'>x</span>, <span class='no'>...</span>)
<span class='fu'>mo_ref</span>(<span class='no'>x</span>, <span class='no'>...</span>)
<span class='fu'>mo_authors</span>(<span class='no'>x</span>, <span class='no'>...</span>)
<span class='fu'>mo_year</span>(<span class='no'>x</span>, <span class='no'>...</span>)
<span class='fu'>mo_taxonomy</span>(<span class='no'>x</span>, <span class='no'>...</span>)
<span class='fu'>mo_property</span>(<span class='no'>x</span>, <span class='kw'>property</span> <span class='kw'>=</span> <span class='st'>"fullname"</span>, <span class='kw'>language</span> <span class='kw'>=</span> <span class='fu'><a href='get_locale.html'>get_locale</a></span>(), <span class='no'>...</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>x</th>
<td><p>any (vector of) text that can be coerced to a valid microorganism code with <code><a href='as.mo.html'>as.mo</a></code></p></td>
</tr>
<tr>
<th>language</th>
<td><p>language of the returned text, defaults to system language (see <code><a href='get_locale.html'>get_locale</a></code>) and can also be set with <code><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a>("AMR_locale")</code>. Use <code>language = NULL</code> or <code>language = ""</code> to prevent translation.</p></td>
</tr>
<tr>
<th>...</th>
<td><p>other parameters passed on to <code><a href='as.mo.html'>as.mo</a></code></p></td>
</tr>
<tr>
<th>property</th>
<td><p>one of the column names of one of the <code><a href='microorganisms.html'>microorganisms</a></code> data set or <code>"shortname"</code></p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<ul>
<li><p>An <code>integer</code> in case of <code>mo_TSN</code> and <code>mo_year</code></p></li>
<li><p>A <code>list</code> in case of <code>mo_taxonomy</code></p></li>
<li><p>A <code>character</code> in all other cases</p></li>
</ul>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>All functions will return the most recently known taxonomic property according to ITIS, except for <code>mo_ref</code>, <code>mo_authors</code> and <code>mo_year</code>. This leads to the following results:</p><ul>
<li><p><code>mo_fullname("Chlamydia psittaci")</code> will return <code>"Chlamydophila psittaci"</code> (with a warning about the renaming)</p></li>
<li><p><code>mo_ref("Chlamydia psittaci")</code> will return <code>"Page, 1968"</code> (with a warning about the renaming)</p></li>
<li><p><code>mo_ref("Chlamydophila psittaci")</code> will return <code>"Everett et al., 1999"</code> (without a warning)</p></li>
</ul>
<h2 class="hasAnchor" id="supported-languages"><a class="anchor" href="#supported-languages"></a>Supported languages</h2>
<p>Supported languages are <code>"en"</code> (English), <code>"de"</code> (German), <code>"nl"</code> (Dutch), <code>"es"</code> (Spanish), <code>"it"</code> (Italian), <code>"fr"</code> (French), and <code>"pt"</code> (Portuguese).</p>
<h2 class="hasAnchor" id="itis"><a class="anchor" href="#itis"></a>ITIS</h2>
<p><img src='figures/itis_logo.jpg' height=60px style=margin-bottom:5px /> <br />
This package contains the <strong>complete microbial taxonomic data</strong> (with all nine taxonomic ranks - from kingdom to subspecies) from the publicly available Integrated Taxonomic Information System (ITIS, <a href='https://www.itis.gov'>https://www.itis.gov</a>).</p>
<p>All (sub)species from <strong>the taxonomic kingdoms Bacteria, Fungi and Protozoa are included in this package</strong>, as well as all previously accepted names known to ITIS. Furthermore, the responsible authors and year of publication are available. This allows users to use authoritative taxonomic information for their data analysis on any microorganism, not only human pathogens. It also helps to quickly determine the Gram stain of bacteria, since all bacteria are classified into subkingdom Negibacteria or Posibacteria.</p>
<p>ITIS is a partnership of U.S., Canadian, and Mexican agencies and taxonomic specialists [3].</p>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p>[1] Becker K <em>et al.</em> <strong>Coagulase-Negative Staphylococci</strong>. 2014. Clin Microbiol Rev. 27(4): 870–926. <a href='https://dx.doi.org/10.1128/CMR.00109-13'>https://dx.doi.org/10.1128/CMR.00109-13</a></p>
<p>[2] Lancefield RC <strong>A serological differentiation of human and other groups of hemolytic streptococci</strong>. 1933. J Exp Med. 57(4): 571–95. <a href='https://dx.doi.org/10.1084/jem.57.4.571'>https://dx.doi.org/10.1084/jem.57.4.571</a></p>
<p>[3] Integrated Taxonomic Information System (ITIS). Retrieved September 2018. <a href='http://www.itis.gov'>http://www.itis.gov</a></p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='microorganisms.html'>microorganisms</a></code></p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='co'># All properties of Escherichia coli</span>
<span class='co'>## taxonomic properties</span>
<span class='fu'>mo_kingdom</span>(<span class='st'>"E. coli"</span>) <span class='co'># "Bacteria"</span></div><div class='output co'>#&gt; [1] "Bacteria"</div><div class='input'><span class='fu'>mo_subkingdom</span>(<span class='st'>"E. coli"</span>) <span class='co'># "Negibacteria"</span></div><div class='output co'>#&gt; [1] "Negibacteria"</div><div class='input'><span class='fu'>mo_phylum</span>(<span class='st'>"E. coli"</span>) <span class='co'># "Proteobacteria"</span></div><div class='output co'>#&gt; [1] "Proteobacteria"</div><div class='input'><span class='fu'>mo_class</span>(<span class='st'>"E. coli"</span>) <span class='co'># "Gammaproteobacteria"</span></div><div class='output co'>#&gt; [1] "Gammaproteobacteria"</div><div class='input'><span class='fu'>mo_order</span>(<span class='st'>"E. coli"</span>) <span class='co'># "Enterobacteriales"</span></div><div class='output co'>#&gt; [1] "Enterobacteriales"</div><div class='input'><span class='fu'>mo_family</span>(<span class='st'>"E. coli"</span>) <span class='co'># "Enterobacteriaceae"</span></div><div class='output co'>#&gt; [1] "Enterobacteriaceae"</div><div class='input'><span class='fu'>mo_genus</span>(<span class='st'>"E. coli"</span>) <span class='co'># "Escherichia"</span></div><div class='output co'>#&gt; [1] "Escherichia"</div><div class='input'><span class='fu'>mo_species</span>(<span class='st'>"E. coli"</span>) <span class='co'># "coli"</span></div><div class='output co'>#&gt; [1] "coli"</div><div class='input'><span class='fu'>mo_subspecies</span>(<span class='st'>"E. coli"</span>) <span class='co'># NA</span></div><div class='output co'>#&gt; [1] NA</div><div class='input'><span class='fu'>mo_TSN</span>(<span class='st'>"E. coli"</span>) <span class='co'># 285 (Taxonomic Serial Number)</span></div><div class='output co'>#&gt; [1] 285</div><div class='input'>
<span class='co'>## colloquial properties</span>
<span class='fu'>mo_fullname</span>(<span class='st'>"E. coli"</span>) <span class='co'># "Escherichia coli"</span></div><div class='output co'>#&gt; [1] "Escherichia coli"</div><div class='input'><span class='fu'>mo_shortname</span>(<span class='st'>"E. coli"</span>) <span class='co'># "E. coli"</span></div><div class='output co'>#&gt; [1] "E. coli"</div><div class='input'>
<span class='co'>## other properties</span>
<span class='fu'>mo_gramstain</span>(<span class='st'>"E. coli"</span>) <span class='co'># "Gram negative"</span></div><div class='output co'>#&gt; [1] "Gram-negatief"</div><div class='input'><span class='fu'>mo_type</span>(<span class='st'>"E. coli"</span>) <span class='co'># "Bacteria" (equal to kingdom)</span></div><div class='output co'>#&gt; [1] "Bacteriën"</div><div class='input'>
<span class='co'>## scientific reference</span>
<span class='fu'>mo_ref</span>(<span class='st'>"E. coli"</span>) <span class='co'># "Castellani and Chalmers, 1919"</span></div><div class='output co'>#&gt; [1] "Castellani and Chalmers, 1919"</div><div class='input'><span class='fu'>mo_authors</span>(<span class='st'>"E. coli"</span>) <span class='co'># "Castellani and Chalmers"</span></div><div class='output co'>#&gt; [1] "Castellani and Chalmers"</div><div class='input'><span class='fu'>mo_year</span>(<span class='st'>"E. coli"</span>) <span class='co'># 1919</span></div><div class='output co'>#&gt; [1] 1919</div><div class='input'>
<span class='co'># Abbreviations known in the field</span>
<span class='fu'>mo_genus</span>(<span class='st'>"MRSA"</span>) <span class='co'># "Staphylococcus"</span></div><div class='output co'>#&gt; [1] "Staphylococcus"</div><div class='input'><span class='fu'>mo_species</span>(<span class='st'>"MRSA"</span>) <span class='co'># "aureus"</span></div><div class='output co'>#&gt; [1] "aureus"</div><div class='input'><span class='fu'>mo_shortname</span>(<span class='st'>"MRSA"</span>) <span class='co'># "S. aureus"</span></div><div class='output co'>#&gt; [1] "S. aureus"</div><div class='input'><span class='fu'>mo_gramstain</span>(<span class='st'>"MRSA"</span>) <span class='co'># "Gram positive"</span></div><div class='output co'>#&gt; [1] "Gram-positief"</div><div class='input'>
<span class='fu'>mo_genus</span>(<span class='st'>"VISA"</span>) <span class='co'># "Staphylococcus"</span></div><div class='output co'>#&gt; [1] "Staphylococcus"</div><div class='input'><span class='fu'>mo_species</span>(<span class='st'>"VISA"</span>) <span class='co'># "aureus"</span></div><div class='output co'>#&gt; [1] "aureus"</div><div class='input'>
<span class='co'># Known subspecies</span>
<span class='fu'>mo_genus</span>(<span class='st'>"doylei"</span>) <span class='co'># "Campylobacter"</span></div><div class='output co'>#&gt; <span class='warning'>Warning: <span style='color: #BB0000;'>These 1 values could not be coerced to a valid MO code: "doylei". See mo_failures() to review them.</span><span></span></div><div class='output co'>#&gt; [1] NA</div><div class='input'><span class='fu'>mo_species</span>(<span class='st'>"doylei"</span>) <span class='co'># "jejuni"</span></div><div class='output co'>#&gt; <span class='warning'>Warning: </span><span style='color: #BB0000;'>These 1 values could not be coerced to a valid MO code: "doylei". See mo_failures() to review them.</span><span></span></div><div class='output co'>#&gt; [1] NA</div><div class='input'><span class='fu'>mo_fullname</span>(<span class='st'>"doylei"</span>) <span class='co'># "Campylobacter jejuni doylei"</span></div><div class='output co'>#&gt; <span class='warning'>Warning: </span><span style='color: #BB0000;'>These 1 values could not be coerced to a valid MO code: "doylei". See mo_failures() to review them.</span><span></span></div><div class='output co'>#&gt; [1] NA</div><div class='input'>
<span class='fu'>mo_fullname</span>(<span class='st'>"K. pneu rh"</span>) <span class='co'># "Klebsiella pneumoniae rhinoscleromatis"</span></div><div class='output co'>#&gt; [1] "Klebsiella pneumoniae rhinoscleromatis"</div><div class='input'><span class='fu'>mo_shortname</span>(<span class='st'>"K. pneu rh"</span>) <span class='co'># "K. pneumoniae"</span></div><div class='output co'>#&gt; [1] "K. pneumoniae"</div><div class='input'>
<span class='co'># Becker classification, see ?as.mo</span>
<span class='fu'>mo_fullname</span>(<span class='st'>"S. epi"</span>) <span class='co'># "Staphylococcus epidermidis"</span></div><div class='output co'>#&gt; [1] "Staphylococcus epidermidis"</div><div class='input'><span class='fu'>mo_fullname</span>(<span class='st'>"S. epi"</span>, <span class='kw'>Becker</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) <span class='co'># "Coagulase Negative Staphylococcus (CoNS)"</span></div><div class='output co'>#&gt; [1] "Coagulase-negatieve Staphylococcus (CNS)"</div><div class='input'><span class='fu'>mo_shortname</span>(<span class='st'>"S. epi"</span>) <span class='co'># "S. epidermidis"</span></div><div class='output co'>#&gt; [1] "S. epidermidis"</div><div class='input'><span class='fu'>mo_shortname</span>(<span class='st'>"S. epi"</span>, <span class='kw'>Becker</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) <span class='co'># "CoNS"</span></div><div class='output co'>#&gt; [1] "CNS"</div><div class='input'>
<span class='co'># Lancefield classification, see ?as.mo</span>
<span class='fu'>mo_fullname</span>(<span class='st'>"S. pyo"</span>) <span class='co'># "Streptococcus pyogenes"</span></div><div class='output co'>#&gt; [1] "Streptococcus pyogenes"</div><div class='input'><span class='fu'>mo_fullname</span>(<span class='st'>"S. pyo"</span>, <span class='kw'>Lancefield</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) <span class='co'># "Streptococcus group A"</span></div><div class='output co'>#&gt; [1] "Streptococcus groep A"</div><div class='input'><span class='fu'>mo_shortname</span>(<span class='st'>"S. pyo"</span>) <span class='co'># "S. pyogenes"</span></div><div class='output co'>#&gt; [1] "S. pyogenes"</div><div class='input'><span class='fu'>mo_shortname</span>(<span class='st'>"S. pyo"</span>, <span class='kw'>Lancefield</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>) <span class='co'># "GAS" ('Group A streptococci')</span></div><div class='output co'>#&gt; [1] "GAS"</div><div class='input'>
<span class='co'># Language support for German, Dutch, Spanish, Portuguese, Italian and French</span>
<span class='fu'>mo_gramstain</span>(<span class='st'>"E. coli"</span>, <span class='kw'>language</span> <span class='kw'>=</span> <span class='st'>"de"</span>) <span class='co'># "Gramnegativ"</span></div><div class='output co'>#&gt; [1] "Gramnegativ"</div><div class='input'><span class='fu'>mo_gramstain</span>(<span class='st'>"E. coli"</span>, <span class='kw'>language</span> <span class='kw'>=</span> <span class='st'>"nl"</span>) <span class='co'># "Gram-negatief"</span></div><div class='output co'>#&gt; [1] "Gram-negatief"</div><div class='input'><span class='fu'>mo_gramstain</span>(<span class='st'>"E. coli"</span>, <span class='kw'>language</span> <span class='kw'>=</span> <span class='st'>"es"</span>) <span class='co'># "Gram negativo"</span></div><div class='output co'>#&gt; [1] "Gram negativo"</div><div class='input'>
<span class='co'># mo_type is equal to mo_kingdom, but mo_kingdom will remain official</span>
<span class='fu'>mo_kingdom</span>(<span class='st'>"E. coli"</span>) <span class='co'># "Bacteria" on a German system</span></div><div class='output co'>#&gt; [1] "Bacteria"</div><div class='input'><span class='fu'>mo_type</span>(<span class='st'>"E. coli"</span>) <span class='co'># "Bakterien" on a German system</span></div><div class='output co'>#&gt; [1] "Bacteriën"</div><div class='input'><span class='fu'>mo_type</span>(<span class='st'>"E. coli"</span>) <span class='co'># "Bacteria" on an English system</span></div><div class='output co'>#&gt; [1] "Bacteriën"</div><div class='input'>
<span class='fu'>mo_fullname</span>(<span class='st'>"S. pyogenes"</span>,
<span class='kw'>Lancefield</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
<span class='kw'>language</span> <span class='kw'>=</span> <span class='st'>"de"</span>) <span class='co'># "Streptococcus Gruppe A"</span></div><div class='output co'>#&gt; [1] "Streptococcus Gruppe A"</div><div class='input'><span class='fu'>mo_fullname</span>(<span class='st'>"S. pyogenes"</span>,
<span class='kw'>Lancefield</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
<span class='kw'>language</span> <span class='kw'>=</span> <span class='st'>"nl"</span>) <span class='co'># "Streptococcus groep A"</span></div><div class='output co'>#&gt; [1] "Streptococcus groep A"</div><div class='input'>
<span class='co'># Get a list with the complete taxonomy (subkingdom to subspecies)</span>
<span class='fu'>mo_taxonomy</span>(<span class='st'>"E. coli"</span>)</div><div class='output co'>#&gt; $kingdom
#&gt; [1] "Bacteria"
#&gt;
#&gt; $subkingdom
#&gt; [1] "Negibacteria"
#&gt;
#&gt; $phylum
#&gt; [1] "Proteobacteria"
#&gt;
#&gt; $class
#&gt; [1] "Gammaproteobacteria"
#&gt;
#&gt; $order
#&gt; [1] "Enterobacteriales"
#&gt;
#&gt; $family
#&gt; [1] "Enterobacteriaceae"
#&gt;
#&gt; $genus
#&gt; [1] "Escherichia"
#&gt;
#&gt; $species
#&gt; [1] "coli"
#&gt;
#&gt; $subspecies
#&gt; [1] NA
#&gt; </div></span></pre>
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<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
<li><a href="#arguments">Arguments</a></li>
<li><a href="#value">Value</a></li>
<li><a href="#details">Details</a></li>
<li><a href="#supported-languages">Supported languages</a></li>
<li><a href="#itis">ITIS</a></li>
<li><a href="#source">Source</a></li>
<li><a href="#see-also">See also</a></li>
<li><a href="#examples">Examples</a></li>
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<p>Returns a vector of all renamed items of the last coercion to valid MO codes with <code><a href='as.mo.html'>as.mo</a></code>.</p>
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<pre class="usage"><span class='fu'>mo_renamed</span>()</pre>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
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<p>Return the symbol related to the p value: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1. Values above <code>p = 1</code> will return <code>NA</code>.</p>
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<pre class="usage"><span class='fu'>p.symbol</span>(<span class='no'>p</span>, <span class='kw'>emptychar</span> <span class='kw'>=</span> <span class='st'>" "</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
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<th>p</th>
<td><p>p value</p></td>
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<th>emptychar</th>
<td><p>text to show when <code>p &gt; 0.1</code></p></td>
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<meta property="og:description" content="These functions can be used to calculate the (co-)resistance of microbial isolates (i.e. percentage S, SI, I, IR or R). All functions support quasiquotation with pipes, can be used in dplyrs summarise and support grouped variables, see Examples.
portion_R and portion_IR can be used to calculate resistance, portion_S and portion_SI can be used to calculate susceptibility." />
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<h1>Calculate resistance of isolates</h1>
<div class="hidden name"><code>portion.Rd</code></div>
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<div class="ref-description">
<p>These functions can be used to calculate the (co-)resistance of microbial isolates (i.e. percentage S, SI, I, IR or R). All functions support quasiquotation with pipes, can be used in <code>dplyr</code>s <code><a href='http://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></code> and support grouped variables, see <em>Examples</em>.</p>
<p><code>portion_R</code> and <code>portion_IR</code> can be used to calculate resistance, <code>portion_S</code> and <code>portion_SI</code> can be used to calculate susceptibility.<br /></p>
</div>
<pre class="usage"><span class='fu'>portion_R</span>(<span class='no'>...</span>, <span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>30</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
<span class='kw'>also_single_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='fu'>portion_IR</span>(<span class='no'>...</span>, <span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>30</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
<span class='kw'>also_single_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='fu'>portion_I</span>(<span class='no'>...</span>, <span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>30</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
<span class='kw'>also_single_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='fu'>portion_SI</span>(<span class='no'>...</span>, <span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>30</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
<span class='kw'>also_single_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='fu'>portion_S</span>(<span class='no'>...</span>, <span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>30</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
<span class='kw'>also_single_tested</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='fu'>portion_df</span>(<span class='no'>data</span>, <span class='kw'>translate_ab</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a></span>(<span class='st'>"get_antibiotic_names"</span>,
<span class='st'>"official"</span>), <span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>30</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='kw'>combine_IR</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>...</th>
<td><p>one or more vectors (or columns) with antibiotic interpretations. They will be transformed internally with <code><a href='as.rsi.html'>as.rsi</a></code> if needed. Use multiple columns to calculate (the lack of) co-resistance: the probability where one of two drugs have a resistant or susceptible result. See Examples.</p></td>
</tr>
<tr>
<th>minimum</th>
<td><p>the minimal amount of available isolates. Any number lower than <code>minimum</code> will return <code>NA</code> with a warning. The default number of <code>30</code> isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see Source.</p></td>
</tr>
<tr>
<th>as_percent</th>
<td><p>a logical to indicate whether the output must be returned as a hundred fold with % sign (a character). A value of <code>0.123456</code> will then be returned as <code>"12.3%"</code>.</p></td>
</tr>
<tr>
<th>also_single_tested</th>
<td><p>a logical to indicate whether (in combination therapies) also observations should be included where not all antibiotics were tested, but at least one of the tested antibiotics contains a target interpretation (e.g. S in case of <code>portion_S</code> and R in case of <code>portion_R</code>). <strong>This would lead to selection bias in almost all cases.</strong></p></td>
</tr>
<tr>
<th>data</th>
<td><p>a <code>data.frame</code> containing columns with class <code>rsi</code> (see <code><a href='as.rsi.html'>as.rsi</a></code>)</p></td>
</tr>
<tr>
<th>translate_ab</th>
<td><p>a column name of the <code><a href='antibiotics.html'>antibiotics</a></code> data set to translate the antibiotic abbreviations to, using <code><a href='abname.html'>abname</a></code>. This can be set with <code><a href='https://www.rdocumentation.org/packages/base/topics/options'>getOption</a>("get_antibiotic_names")</code>.</p></td>
</tr>
<tr>
<th>combine_IR</th>
<td><p>a logical to indicate whether all values of I and R must be merged into one, so the output only consists of S vs. IR (susceptible vs. non-susceptible)</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="source"><a class="anchor" href="#source"></a>Source</h2>
<p><strong>M39 Analysis and Presentation of Cumulative Antimicrobial Susceptibility Test Data, 4th Edition</strong>, 2014, <em>Clinical and Laboratory Standards Institute (CLSI)</em>. <a href='https://clsi.org/standards/products/microbiology/documents/m39/'>https://clsi.org/standards/products/microbiology/documents/m39/</a>.</p>
<p>Wickham H. <strong>Tidy Data.</strong> The Journal of Statistical Software, vol. 59, 2014. <a href='http://vita.had.co.nz/papers/tidy-data.html'>http://vita.had.co.nz/papers/tidy-data.html</a></p>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p>Double or, when <code>as_percent = TRUE</code>, a character.</p>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p><strong>Remember that you should filter your table to let it contain only first isolates!</strong> Use <code><a href='first_isolate.html'>first_isolate</a></code> to determine them in your data set.</p>
<p>These functions are not meant to count isolates, but to calculate the portion of resistance/susceptibility. Use the <code><a href='count.html'>count</a></code> functions to count isolates. <em>Low counts can infuence the outcome - these <code>portion</code> functions may camouflage this, since they only return the portion albeit being dependent on the <code>minimum</code> parameter.</em></p>
<p><code>portion_df</code> takes any variable from <code>data</code> that has an <code>"rsi"</code> class (created with <code><a href='as.rsi.html'>as.rsi</a></code>) and calculates the portions R, I and S. The resulting <em>tidy data</em> (see Source) <code>data.frame</code> will have three rows (S/I/R) and a column for each variable with class <code>"rsi"</code>.</p>
<p>The old <code><a href='rsi.html'>rsi</a></code> function is still available for backwards compatibility but is deprecated.
<br /><br />
To calculate the probability (<em>p</em>) of susceptibility of one antibiotic, we use this formula:
<div style="text-align: center"><img src='figures/mono_therapy.png' alt='' /></div>
To calculate the probability (<em>p</em>) of susceptibility of more antibiotics (i.e. combination therapy), we need to check whether one of them has a susceptible result (as numerator) and count all cases where all antibiotics were tested (as denominator). <br />
<br />
For two antibiotics:
<div style="text-align: center"><img src='figures/combi_therapy_2.png' alt='' /></div>
<br />
For three antibiotics:
<div style="text-align: center"><img src='figures/combi_therapy_3.png' alt='' /></div>
<br />
And so on.</p>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='count.html'>count</a>_*</code> to count resistant and susceptible isolates.</p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='co'># septic_patients is a data set available in the AMR package. It is true, genuine data.</span>
?<span class='no'>septic_patients</span></div><div class='output co'>#&gt; <span class='message'>Rendering development documentation for 'septic_patients'</span></div><div class='input'>
<span class='co'># Calculate resistance</span>
<span class='fu'>portion_R</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)</div><div class='output co'>#&gt; [1] 0.5827645</div><div class='input'><span class='fu'>portion_IR</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)</div><div class='output co'>#&gt; [1] 0.5853242</div><div class='input'>
<span class='co'># Or susceptibility</span>
<span class='fu'>portion_S</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)</div><div class='output co'>#&gt; [1] 0.4146758</div><div class='input'><span class='fu'>portion_SI</span>(<span class='no'>septic_patients</span>$<span class='no'>amox</span>)</div><div class='output co'>#&gt; [1] 0.4172355</div><div class='input'>
<span class='co'># Do the above with pipes:</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span> <span class='fu'>portion_R</span>(<span class='no'>amox</span>)</div><div class='output co'>#&gt; [1] 0.5827645</div><div class='input'><span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span> <span class='fu'>portion_IR</span>(<span class='no'>amox</span>)</div><div class='output co'>#&gt; [1] 0.5853242</div><div class='input'><span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span> <span class='fu'>portion_S</span>(<span class='no'>amox</span>)</div><div class='output co'>#&gt; [1] 0.4146758</div><div class='input'><span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span> <span class='fu'>portion_SI</span>(<span class='no'>amox</span>)</div><div class='output co'>#&gt; [1] 0.4172355</div><div class='input'>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></span>(<span class='kw'>p</span> <span class='kw'>=</span> <span class='fu'>portion_S</span>(<span class='no'>cipr</span>),
<span class='kw'>n</span> <span class='kw'>=</span> <span class='fu'><a href='count.html'>n_rsi</a></span>(<span class='no'>cipr</span>)) <span class='co'># n_rsi works like n_distinct in dplyr</span></div><div class='output co'>#&gt; <span style='color: #949494;'># A tibble: 4 x 3</span><span>
#&gt; hospital_id p n
#&gt; </span><span style='color: #949494;font-style: italic;'>&lt;fct&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;dbl&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;int&gt;</span><span>
#&gt; </span><span style='color: #BCBCBC;'>1</span><span> A 0.860 207
#&gt; </span><span style='color: #BCBCBC;'>2</span><span> B 0.760 499
#&gt; </span><span style='color: #BCBCBC;'>3</span><span> C 0.688 202
#&gt; </span><span style='color: #BCBCBC;'>4</span><span> D 0.830 501</div><div class='input'>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></span>(<span class='kw'>R</span> <span class='kw'>=</span> <span class='fu'>portion_R</span>(<span class='no'>cipr</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
<span class='kw'>I</span> <span class='kw'>=</span> <span class='fu'>portion_I</span>(<span class='no'>cipr</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
<span class='kw'>S</span> <span class='kw'>=</span> <span class='fu'>portion_S</span>(<span class='no'>cipr</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
<span class='kw'>n</span> <span class='kw'>=</span> <span class='fu'><a href='count.html'>n_rsi</a></span>(<span class='no'>cipr</span>), <span class='co'># works like n_distinct in dplyr</span>
<span class='kw'>total</span> <span class='kw'>=</span> <span class='fu'><a href='http://dplyr.tidyverse.org/reference/n.html'>n</a></span>()) <span class='co'># NOT the amount of tested isolates!</span></div><div class='output co'>#&gt; </span><span style='color: #949494;'># A tibble: 4 x 6</span><span>
#&gt; hospital_id R I S n total
#&gt; </span><span style='color: #949494;font-style: italic;'>&lt;fct&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;chr&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;chr&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;chr&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;int&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;int&gt;</span><span>
#&gt; </span><span style='color: #BCBCBC;'>1</span><span> A 12.6% 1.4% 86.0% 207 321
#&gt; </span><span style='color: #BCBCBC;'>2</span><span> B 17.0% 7.0% 76.0% 499 663
#&gt; </span><span style='color: #BCBCBC;'>3</span><span> C 20.3% 10.9% 68.8% 202 254
#&gt; </span><span style='color: #BCBCBC;'>4</span><span> D 15.2% 1.8% 83.0% 501 762</div><div class='input'>
<span class='co'># Calculate co-resistance between amoxicillin/clav acid and gentamicin,</span>
<span class='co'># so we can see that combination therapy does a lot more than mono therapy:</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span> <span class='fu'>portion_S</span>(<span class='no'>amcl</span>) <span class='co'># S = 67.1%</span></div><div class='output co'>#&gt; [1] 0.7062363</div><div class='input'><span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span> <span class='fu'><a href='count.html'>count_all</a></span>(<span class='no'>amcl</span>) <span class='co'># n = 1576</span></div><div class='output co'>#&gt; [1] 1828</div><div class='input'>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span> <span class='fu'>portion_S</span>(<span class='no'>gent</span>) <span class='co'># S = 74.0%</span></div><div class='output co'>#&gt; [1] 0.7396226</div><div class='input'><span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span> <span class='fu'><a href='count.html'>count_all</a></span>(<span class='no'>gent</span>) <span class='co'># n = 1855</span></div><div class='output co'>#&gt; [1] 1855</div><div class='input'>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span> <span class='fu'>portion_S</span>(<span class='no'>amcl</span>, <span class='no'>gent</span>) <span class='co'># S = 92.0%</span></div><div class='output co'>#&gt; [1] 0.9210074</div><div class='input'><span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span> <span class='fu'><a href='count.html'>count_all</a></span>(<span class='no'>amcl</span>, <span class='no'>gent</span>) <span class='co'># n = 1517</span></div><div class='output co'>#&gt; [1] 1747</div><div class='input'>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></span>(<span class='kw'>cipro_p</span> <span class='kw'>=</span> <span class='fu'>portion_S</span>(<span class='no'>cipr</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
<span class='kw'>cipro_n</span> <span class='kw'>=</span> <span class='fu'><a href='count.html'>count_all</a></span>(<span class='no'>cipr</span>),
<span class='kw'>genta_p</span> <span class='kw'>=</span> <span class='fu'>portion_S</span>(<span class='no'>gent</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
<span class='kw'>genta_n</span> <span class='kw'>=</span> <span class='fu'><a href='count.html'>count_all</a></span>(<span class='no'>gent</span>),
<span class='kw'>combination_p</span> <span class='kw'>=</span> <span class='fu'>portion_S</span>(<span class='no'>cipr</span>, <span class='no'>gent</span>, <span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>),
<span class='kw'>combination_n</span> <span class='kw'>=</span> <span class='fu'><a href='count.html'>count_all</a></span>(<span class='no'>cipr</span>, <span class='no'>gent</span>))</div><div class='output co'>#&gt; </span><span style='color: #949494;'># A tibble: 4 x 7</span><span>
#&gt; hospital_id cipro_p cipro_n genta_p genta_n combination_p combination_n
#&gt; </span><span style='color: #949494;font-style: italic;'>&lt;fct&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;chr&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;int&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;chr&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;int&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;chr&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;int&gt;</span><span>
#&gt; </span><span style='color: #BCBCBC;'>1</span><span> A 86.0% 207 76.0% 300 95.0% 202
#&gt; </span><span style='color: #BCBCBC;'>2</span><span> B 76.0% 499 71.5% 606 91.4% 488
#&gt; </span><span style='color: #BCBCBC;'>3</span><span> C 68.8% 202 75.8% 240 91.5% 201
#&gt; </span><span style='color: #BCBCBC;'>4</span><span> D 83.0% 501 74.6% 709 95.0% 499</div><div class='input'>
<span class='co'># Get portions S/I/R immediately of all rsi columns</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>amox</span>, <span class='no'>cipr</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>portion_df</span>(<span class='kw'>translate</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</div><div class='output co'>#&gt; Interpretation Antibiotic Value
#&gt; 1 S amox 0.414675768
#&gt; 2 I amox 0.002559727
#&gt; 3 R amox 0.582764505
#&gt; 4 S cipr 0.789212207
#&gt; 5 I cipr 0.048970901
#&gt; 6 R cipr 0.161816891</div><div class='input'>
<span class='co'># It also supports grouping variables</span>
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/select.html'>select</a></span>(<span class='no'>hospital_id</span>, <span class='no'>amox</span>, <span class='no'>cipr</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>portion_df</span>(<span class='kw'>translate</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</div><div class='output co'>#&gt; </span><span style='color: #949494;'># A tibble: 24 x 4</span><span>
#&gt; Interpretation hospital_id Antibiotic Value
#&gt; </span><span style='color: #949494;font-style: italic;'>&lt;ord&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;fct&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;chr&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;dbl&gt;</span><span>
#&gt; </span><span style='color: #BCBCBC;'> 1</span><span> S A amox 0.42
#&gt; </span><span style='color: #BCBCBC;'> 2</span><span> S B amox 0.378
#&gt; </span><span style='color: #BCBCBC;'> 3</span><span> S C amox 0.373
#&gt; </span><span style='color: #BCBCBC;'> 4</span><span> S D amox 0.454
#&gt; </span><span style='color: #BCBCBC;'> 5</span><span> I A amox 0
#&gt; </span><span style='color: #BCBCBC;'> 6</span><span> I B amox 0.002</span><span style='text-decoration: underline;'>68</span><span>
#&gt; </span><span style='color: #BCBCBC;'> 7</span><span> I C amox 0
#&gt; </span><span style='color: #BCBCBC;'> 8</span><span> I D amox 0.004</span><span style='text-decoration: underline;'>07</span><span>
#&gt; </span><span style='color: #BCBCBC;'> 9</span><span> R A amox 0.580
#&gt; </span><span style='color: #BCBCBC;'>10</span><span> R B amox 0.619
#&gt; </span><span style='color: #949494;'># ... with 14 more rows</span><span></div><div class='input'>
</div></span><span class='co'># NOT RUN {</span>
<span class='co'># calculate current empiric combination therapy of Helicobacter gastritis:</span>
<span class='no'>my_table</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>first_isolate</span> <span class='kw'>==</span> <span class='fl'>TRUE</span>,
<span class='no'>genus</span> <span class='kw'>==</span> <span class='st'>"Helicobacter"</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></span>(<span class='kw'>p</span> <span class='kw'>=</span> <span class='fu'>portion_S</span>(<span class='no'>amox</span>, <span class='no'>metr</span>), <span class='co'># amoxicillin with metronidazole</span>
<span class='kw'>n</span> <span class='kw'>=</span> <span class='fu'><a href='count.html'>count_all</a></span>(<span class='no'>amox</span>, <span class='no'>metr</span>))
<span class='co'># }</span></pre>
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<h1>Read data from 4D database</h1>
<div class="hidden name"><code>read.4D.Rd</code></div>
</div>
<div class="ref-description">
<p>This function is only useful for the MMB department of the UMCG. Use this function to <strong>import data by just defining the <code>file</code> parameter</strong>. It will automatically transform birth dates and calculate patients age, translate the column names to English, transform the MO codes with <code><a href='as.mo.html'>as.mo</a></code> and transform all antimicrobial columns with <code><a href='as.rsi.html'>as.rsi</a></code>.</p>
</div>
<pre class="usage"><span class='fu'>read.4D</span>(<span class='no'>file</span>, <span class='kw'>info</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/interactive'>interactive</a></span>(), <span class='kw'>header</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>row.names</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
<span class='kw'>sep</span> <span class='kw'>=</span> <span class='st'>"\t"</span>, <span class='kw'>quote</span> <span class='kw'>=</span> <span class='st'>"\"'"</span>, <span class='kw'>dec</span> <span class='kw'>=</span> <span class='st'>","</span>, <span class='kw'>na.strings</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='st'>"NA"</span>, <span class='st'>""</span>,
<span class='st'>"."</span>), <span class='kw'>skip</span> <span class='kw'>=</span> <span class='fl'>2</span>, <span class='kw'>check.names</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>strip.white</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
<span class='kw'>fill</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>blank.lines.skip</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>stringsAsFactors</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
<span class='kw'>fileEncoding</span> <span class='kw'>=</span> <span class='st'>"UTF-8"</span>, <span class='kw'>encoding</span> <span class='kw'>=</span> <span class='st'>"UTF-8"</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>file</th>
<td><p>the name of the file which the data are to be read from.
Each row of the table appears as one line of the file. If it does
not contain an <em>absolute</em> path, the file name is
<em>relative</em> to the current working directory,
<code><a href='https://www.rdocumentation.org/packages/base/topics/getwd'>getwd</a>()</code>. Tilde-expansion is performed where supported.
This can be a compressed file (see <code><a href='https://www.rdocumentation.org/packages/base/topics/connections'>file</a></code>).</p>
<p>Alternatively, <code>file</code> can be a readable text-mode
<a href='https://www.rdocumentation.org/packages/base/topics/connections'>connection</a> (which will be opened for reading if
necessary, and if so <code><a href='https://www.rdocumentation.org/packages/base/topics/connections'>close</a></code>d (and hence destroyed) at
the end of the function call). (If <code><a href='https://www.rdocumentation.org/packages/base/topics/showConnections'>stdin</a>()</code> is used,
the prompts for lines may be somewhat confusing. Terminate input
with a blank line or an EOF signal, <code>Ctrl-D</code> on Unix and
<code>Ctrl-Z</code> on Windows. Any pushback on <code><a href='https://www.rdocumentation.org/packages/base/topics/showConnections'>stdin()</a></code> will be
cleared before return.)</p>
<p><code>file</code> can also be a complete URL. (For the supported URL
schemes, see the &#8216;URLs&#8217; section of the help for
<code><a href='https://www.rdocumentation.org/packages/base/topics/connections'>url</a></code>.)</p></td>
</tr>
<tr>
<th>info</th>
<td><p>a logical to indicate whether info about the import should be printed, defaults to <code>TRUE</code> in interactive sessions</p></td>
</tr>
<tr>
<th>header</th>
<td><p>a logical value indicating whether the file contains the
names of the variables as its first line. If missing, the value is
determined from the file format: <code>header</code> is set to <code>TRUE</code>
if and only if the first row contains one fewer field than the
number of columns.</p></td>
</tr>
<tr>
<th>row.names</th>
<td><p>a vector of row names. This can be a vector giving
the actual row names, or a single number giving the column of the
table which contains the row names, or character string giving the
name of the table column containing the row names.</p>
<p>If there is a header and the first row contains one fewer field than
the number of columns, the first column in the input is used for the
row names. Otherwise if <code>row.names</code> is missing, the rows are
numbered.</p>
<p>Using <code>row.names = NULL</code> forces row numbering. Missing or
<code>NULL</code> <code>row.names</code> generate row names that are considered
to be &#8216;automatic&#8217; (and not preserved by <code><a href='https://www.rdocumentation.org/packages/base/topics/matrix'>as.matrix</a></code>).</p></td>
</tr>
<tr>
<th>sep</th>
<td><p>the field separator character. Values on each line of the
file are separated by this character. If <code>sep = ""</code> (the
default for <code>read.table</code>) the separator is &#8216;white space&#8217;,
that is one or more spaces, tabs, newlines or carriage returns.</p></td>
</tr>
<tr>
<th>quote</th>
<td><p>the set of quoting characters. To disable quoting
altogether, use <code>quote = ""</code>. See <code><a href='https://www.rdocumentation.org/packages/base/topics/scan'>scan</a></code> for the
behaviour on quotes embedded in quotes. Quoting is only considered
for columns read as character, which is all of them unless
<code>colClasses</code> is specified.</p></td>
</tr>
<tr>
<th>dec</th>
<td><p>the character used in the file for decimal points.</p></td>
</tr>
<tr>
<th>na.strings</th>
<td><p>a character vector of strings which are to be
interpreted as <code><a href='https://www.rdocumentation.org/packages/base/topics/NA'>NA</a></code> values. Blank fields are also
considered to be missing values in logical, integer, numeric and
complex fields. Note that the test happens <em>after</em>
white space is stripped from the input, so <code>na.strings</code>
values may need their own white space stripped in advance.</p></td>
</tr>
<tr>
<th>skip</th>
<td><p>integer: the number of lines of the data file to skip before
beginning to read data.</p></td>
</tr>
<tr>
<th>check.names</th>
<td><p>logical. If <code>TRUE</code> then the names of the
variables in the data frame are checked to ensure that they are
syntactically valid variable names. If necessary they are adjusted
(by <code><a href='https://www.rdocumentation.org/packages/base/topics/make.names'>make.names</a></code>) so that they are, and also to ensure
that there are no duplicates.</p></td>
</tr>
<tr>
<th>strip.white</th>
<td><p>logical. Used only when <code>sep</code> has
been specified, and allows the stripping of leading and trailing
white space from unquoted <code>character</code> fields (<code>numeric</code> fields
are always stripped). See <code><a href='https://www.rdocumentation.org/packages/base/topics/scan'>scan</a></code> for further details
(including the exact meaning of &#8216;white space&#8217;),
remembering that the columns may include the row names.</p></td>
</tr>
<tr>
<th>fill</th>
<td><p>logical. If <code>TRUE</code> then in case the rows have unequal
length, blank fields are implicitly added. See &#8216;Details&#8217;.</p></td>
</tr>
<tr>
<th>blank.lines.skip</th>
<td><p>logical: if <code>TRUE</code> blank lines in the
input are ignored.</p></td>
</tr>
<tr>
<th>stringsAsFactors</th>
<td><p>logical: should character vectors be converted
to factors? Note that this is overridden by <code>as.is</code> and
<code>colClasses</code>, both of which allow finer control.</p></td>
</tr>
<tr>
<th>fileEncoding</th>
<td><p>character string: if non-empty declares the
encoding used on a file (not a connection) so the character data can
be re-encoded. See the &#8216;Encoding&#8217; section of the help for
<code><a href='https://www.rdocumentation.org/packages/base/topics/connections'>file</a></code>, the &#8216;R Data Import/Export Manual&#8217; and
&#8216;Note&#8217;.</p></td>
</tr>
<tr>
<th>encoding</th>
<td><p>encoding to be assumed for input strings. It is
used to mark character strings as known to be in
Latin-1 or UTF-8 (see <code><a href='https://www.rdocumentation.org/packages/base/topics/Encoding'>Encoding</a></code>): it is not used to
re-encode the input, but allows <span style="R">R</span> to handle encoded strings in
their native encoding (if one of those two). See &#8216;Value&#8217;
and &#8216;Note&#8217;.</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="details"><a class="anchor" href="#details"></a>Details</h2>
<p>Column names will be transformed, but the original column names are set as a "label" attribute and can be seen in e.g. RStudio Viewer.</p>
</div>
<div class="col-md-3 hidden-xs hidden-sm" id="sidebar">
<h2>Contents</h2>
<ul class="nav nav-pills nav-stacked">
<li><a href="#arguments">Arguments</a></li>
<li><a href="#details">Details</a></li>
</ul>
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<h1>Predict antimicrobial resistance</h1>
<div class="hidden name"><code>resistance_predict.Rd</code></div>
</div>
<div class="ref-description">
<p>Create a prediction model to predict antimicrobial resistance for the next years on statistical solid ground. Standard errors (SE) will be returned as columns <code>se_min</code> and <code>se_max</code>. See Examples for a real live example.</p>
</div>
<pre class="usage"><span class='fu'>resistance_predict</span>(<span class='no'>tbl</span>, <span class='no'>col_ab</span>, <span class='no'>col_date</span>, <span class='kw'>year_min</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
<span class='kw'>year_max</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>year_every</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>30</span>,
<span class='kw'>model</span> <span class='kw'>=</span> <span class='st'>"binomial"</span>, <span class='kw'>I_as_R</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>preserve_measurements</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
<span class='kw'>info</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)
<span class='fu'>rsi_predict</span>(<span class='no'>tbl</span>, <span class='no'>col_ab</span>, <span class='no'>col_date</span>, <span class='kw'>year_min</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>year_max</span> <span class='kw'>=</span> <span class='kw'>NULL</span>,
<span class='kw'>year_every</span> <span class='kw'>=</span> <span class='fl'>1</span>, <span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>30</span>, <span class='kw'>model</span> <span class='kw'>=</span> <span class='st'>"binomial"</span>, <span class='kw'>I_as_R</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
<span class='kw'>preserve_measurements</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>, <span class='kw'>info</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>tbl</th>
<td><p>a <code>data.frame</code> containing isolates.</p></td>
</tr>
<tr>
<th>col_ab</th>
<td><p>column name of <code>tbl</code> with antimicrobial interpretations (<code>R</code>, <code>I</code> and <code>S</code>)</p></td>
</tr>
<tr>
<th>col_date</th>
<td><p>column name of the date, will be used to calculate years if this column doesn't consist of years already</p></td>
</tr>
<tr>
<th>year_min</th>
<td><p>lowest year to use in the prediction model, dafaults the lowest year in <code>col_date</code></p></td>
</tr>
<tr>
<th>year_max</th>
<td><p>highest year to use in the prediction model, defaults to 15 years after today</p></td>
</tr>
<tr>
<th>year_every</th>
<td><p>unit of sequence between lowest year found in the data and <code>year_max</code></p></td>
</tr>
<tr>
<th>minimum</th>
<td><p>minimal amount of available isolates per year to include. Years containing less observations will be estimated by the model.</p></td>
</tr>
<tr>
<th>model</th>
<td><p>the statistical model of choice. Valid values are <code>"binomial"</code> (or <code>"binom"</code> or <code>"logit"</code>) or <code>"loglin"</code> or <code>"linear"</code> (or <code>"lin"</code>).</p></td>
</tr>
<tr>
<th>I_as_R</th>
<td><p>treat <code>I</code> as <code>R</code></p></td>
</tr>
<tr>
<th>preserve_measurements</th>
<td><p>logical to indicate whether predictions of years that are actually available in the data should be overwritten with the original data. The standard errors of those years will be <code>NA</code>.</p></td>
</tr>
<tr>
<th>info</th>
<td><p>print textual analysis with the name and <code><a href='https://www.rdocumentation.org/packages/base/topics/summary'>summary</a></code> of the model.</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="value"><a class="anchor" href="#value"></a>Value</h2>
<p><code>data.frame</code> with columns:</p><ul>
<li><p><code>year</code></p></li>
<li><p><code>value</code>, the same as <code>estimated</code> when <code>preserve_measurements = FALSE</code>, and a combination of <code>observed</code> and <code>estimated</code> otherwise</p></li>
<li><p><code>se_min</code>, the lower bound of the standard error with a minimum of <code>0</code></p></li>
<li><p><code>se_max</code> the upper bound of the standard error with a maximum of <code>1</code></p></li>
<li><p><code>observations</code>, the total number of observations, i.e. S + I + R</p></li>
<li><p><code>observed</code>, the original observed values</p></li>
<li><p><code>estimated</code>, the estimated values, calculated by the model</p></li>
</ul>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p>The <code><a href='portion.html'>portion</a></code> function to calculate resistance, <br /> <code><a href='https://www.rdocumentation.org/packages/stats/topics/lm'>lm</a></code> <code><a href='https://www.rdocumentation.org/packages/stats/topics/glm'>glm</a></code></p></div>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><span class='co'># NOT RUN {</span>
<span class='co'># use it with base R:</span>
<span class='fu'>resistance_predict</span>(<span class='kw'>tbl</span> <span class='kw'>=</span> <span class='no'>tbl</span>[<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/which'>which</a></span>(<span class='no'>first_isolate</span> <span class='kw'>==</span> <span class='fl'>TRUE</span> <span class='kw'>&amp;</span> <span class='no'>genus</span> <span class='kw'>==</span> <span class='st'>"Haemophilus"</span>),],
<span class='kw'>col_ab</span> <span class='kw'>=</span> <span class='st'>"amcl"</span>, <span class='kw'>col_date</span> <span class='kw'>=</span> <span class='st'>"date"</span>)
<span class='co'># or use dplyr so you can actually read it:</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='no'>tbl</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>first_isolate</span> <span class='kw'>==</span> <span class='fl'>TRUE</span>,
<span class='no'>genus</span> <span class='kw'>==</span> <span class='st'>"Haemophilus"</span>) <span class='kw'>%&gt;%</span>
<span class='fu'>resistance_predict</span>(<span class='no'>amcl</span>, <span class='no'>date</span>)
<span class='co'># }</span><div class='input'>
<span class='co'># real live example:</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='co'># get bacteria properties like genus and species</span>
<span class='fu'><a href='join.html'>left_join_microorganisms</a></span>(<span class='st'>"mo"</span>) <span class='kw'>%&gt;%</span>
<span class='co'># calculate first isolates</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>first_isolate</span> <span class='kw'>=</span> <span class='fu'><a href='first_isolate.html'>first_isolate</a></span>(<span class='no'>.</span>)) <span class='kw'>%&gt;%</span>
<span class='co'># filter on first E. coli isolates</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>genus</span> <span class='kw'>==</span> <span class='st'>"Escherichia"</span>,
<span class='no'>species</span> <span class='kw'>==</span> <span class='st'>"coli"</span>,
<span class='no'>first_isolate</span> <span class='kw'>==</span> <span class='fl'>TRUE</span>) <span class='kw'>%&gt;%</span>
<span class='co'># predict resistance of cefotaxime for next years</span>
<span class='fu'>resistance_predict</span>(<span class='kw'>col_ab</span> <span class='kw'>=</span> <span class='st'>"cfot"</span>,
<span class='kw'>col_date</span> <span class='kw'>=</span> <span class='st'>"date"</span>,
<span class='kw'>year_max</span> <span class='kw'>=</span> <span class='fl'>2025</span>,
<span class='kw'>preserve_measurements</span> <span class='kw'>=</span> <span class='fl'>TRUE</span>,
<span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>0</span>)</div><div class='output co'>#&gt; <span class='message'><span style='color: #0000BB;'>NOTE: Using column `</span><span style='color: #0000BB;font-weight: bold;'>mo</span><span style='color: #0000BB;'>` as input for `col_mo`.</span><span></span></div><div class='output co'>#&gt; <span class='message'></span><span style='color: #0000BB;'>NOTE: Using column `</span><span style='color: #0000BB;font-weight: bold;'>date</span><span style='color: #0000BB;'>` as input for `col_date`.</span><span></span></div><div class='output co'>#&gt; <span class='message'></span><span style='color: #0000BB;'>NOTE: Using column `</span><span style='color: #0000BB;font-weight: bold;'>patient_id</span><span style='color: #0000BB;'>` as input for `col_patient_id`.</span><span></span></div><div class='output co'>#&gt; <span class='message'>=&gt; Found </span><span style='font-weight: bold;'>1,315 first isolates</span><span> (65.8% of total)</span></div><div class='output co'>#&gt;
#&gt; Logistic regression model (logit) with binomial distribution
#&gt; ------------------------------------------------------------
#&gt;
#&gt; Call:
#&gt; glm(formula = cbind(R, S) ~ year, family = binomial)
#&gt;
#&gt; Deviance Residuals:
#&gt; Min 1Q Median 3Q Max
#&gt; -1.0796 -0.4714 -0.2849 -0.1534 1.5711
#&gt;
#&gt; Coefficients:
#&gt; Estimate Std. Error z value Pr(&gt;|z|)
#&gt; (Intercept) -687.3844 340.9570 -2.016 0.0438 *
#&gt; year 0.3396 0.1692 2.007 0.0448 *
#&gt; ---
#&gt; Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
#&gt;
#&gt; (Dispersion parameter for binomial family taken to be 1)
#&gt;
#&gt; Null deviance: 13.8352 on 15 degrees of freedom
#&gt; Residual deviance: 7.0501 on 14 degrees of freedom
#&gt; AIC: 19.351
#&gt;
#&gt; Number of Fisher Scoring iterations: 6
#&gt; </div><div class='output co'>#&gt; year value se_min se_max observations observed estimated
#&gt; 1 2002 0.00000000 NA NA 12 0.00000000 0.0005290038
#&gt; 2 2003 0.00000000 NA NA 13 0.00000000 0.0007427521
#&gt; 3 2004 0.00000000 NA NA 12 0.00000000 0.0010427770
#&gt; 4 2005 0.00000000 NA NA 15 0.00000000 0.0014638156
#&gt; 5 2006 0.00000000 NA NA 16 0.00000000 0.0020545058
#&gt; 6 2007 0.00000000 NA NA 17 0.00000000 0.0028828678
#&gt; 7 2008 0.00000000 NA NA 17 0.00000000 0.0040438659
#&gt; 8 2009 0.00000000 NA NA 18 0.00000000 0.0056697665
#&gt; 9 2010 0.00000000 NA NA 13 0.00000000 0.0079441719
#&gt; 10 2011 0.04761905 NA NA 21 0.04761905 0.0111207424
#&gt; 11 2012 0.00000000 NA NA 10 0.00000000 0.0155475955
#&gt; 12 2013 0.00000000 NA NA 13 0.00000000 0.0216979872
#&gt; 13 2014 0.00000000 NA NA 19 0.00000000 0.0302067265
#&gt; 14 2015 0.15384615 NA NA 13 0.15384615 0.0419091804
#&gt; 15 2016 0.04761905 NA NA 21 0.04761905 0.0578747498
#&gt; 16 2017 0.05000000 NA NA 20 0.05000000 0.0794183382
#&gt; 17 2018 0.10806159 0.03882360 0.1772996 NA NA 0.1080615861
#&gt; 18 2019 0.14540370 0.03910717 0.2517002 NA NA 0.1454037037
#&gt; 19 2020 0.19285970 0.03682518 0.3488942 NA NA 0.1928597004
#&gt; 20 2021 0.25125053 0.03388540 0.4686157 NA NA 0.2512505261
#&gt; 21 2022 0.32030440 0.03456588 0.6060429 NA NA 0.3203043985
#&gt; 22 2023 0.39824269 0.04543193 0.7510534 NA NA 0.3982426891
#&gt; 23 2024 0.48170517 0.07378334 0.8896270 NA NA 0.4817051695
#&gt; 24 2025 0.56620119 0.12484502 1.0000000 NA NA 0.5662011910</div><div class='input'>
<span class='co'># create nice plots with ggplot</span>
<span class='kw'>if</span> (!<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>require</a></span>(<span class='no'>ggplot2</span>)) {
<span class='no'>data</span> <span class='kw'>&lt;-</span> <span class='no'>septic_patients</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>mo</span> <span class='kw'>==</span> <span class='fu'><a href='as.mo.html'>as.mo</a></span>(<span class='st'>"E. coli"</span>)) <span class='kw'>%&gt;%</span>
<span class='fu'>resistance_predict</span>(<span class='kw'>col_ab</span> <span class='kw'>=</span> <span class='st'>"amox"</span>,
<span class='kw'>col_date</span> <span class='kw'>=</span> <span class='st'>"date"</span>,
<span class='kw'>info</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>,
<span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>15</span>)
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/ggplot.html'>ggplot</a></span>(<span class='no'>data</span>,
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/aes.html'>aes</a></span>(<span class='kw'>x</span> <span class='kw'>=</span> <span class='no'>year</span>)) +
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/geom_bar.html'>geom_col</a></span>(<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/aes.html'>aes</a></span>(<span class='kw'>y</span> <span class='kw'>=</span> <span class='no'>value</span>),
<span class='kw'>fill</span> <span class='kw'>=</span> <span class='st'>"grey75"</span>) +
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/geom_linerange.html'>geom_errorbar</a></span>(<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/aes.html'>aes</a></span>(<span class='kw'>ymin</span> <span class='kw'>=</span> <span class='no'>se_min</span>,
<span class='kw'>ymax</span> <span class='kw'>=</span> <span class='no'>se_max</span>),
<span class='kw'>colour</span> <span class='kw'>=</span> <span class='st'>"grey50"</span>) +
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/scale_continuous.html'>scale_y_continuous</a></span>(<span class='kw'>limits</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/c'>c</a></span>(<span class='fl'>0</span>, <span class='fl'>1</span>),
<span class='kw'>breaks</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/seq'>seq</a></span>(<span class='fl'>0</span>, <span class='fl'>1</span>, <span class='fl'>0.1</span>),
<span class='kw'>labels</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/paste'>paste0</a></span>(<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/seq'>seq</a></span>(<span class='fl'>0</span>, <span class='fl'>100</span>, <span class='fl'>10</span>), <span class='st'>"%"</span>)) +
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/labs.html'>labs</a></span>(<span class='kw'>title</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/expression'>expression</a></span>(<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/paste'>paste</a></span>(<span class='st'>"Forecast of amoxicillin resistance in "</span>,
<span class='fu'><a href='https://www.rdocumentation.org/packages/grDevices/topics/plotmath'>italic</a></span>(<span class='st'>"E. coli"</span>))),
<span class='kw'>y</span> <span class='kw'>=</span> <span class='st'>"%IR"</span>,
<span class='kw'>x</span> <span class='kw'>=</span> <span class='st'>"Year"</span>) +
<span class='fu'><a href='https://ggplot2.tidyverse.org/reference/ggtheme.html'>theme_minimal</a></span>(<span class='kw'>base_size</span> <span class='kw'>=</span> <span class='fl'>13</span>)
}</div></span></pre>
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<h1>Calculate resistance of isolates</h1>
<div class="hidden name"><code>rsi.Rd</code></div>
</div>
<div class="ref-description">
<p>This function is deprecated. Use the <code><a href='portion.html'>portion</a></code> functions instead.</p>
</div>
<pre class="usage"><span class='fu'>rsi</span>(<span class='no'>ab1</span>, <span class='kw'>ab2</span> <span class='kw'>=</span> <span class='kw'>NULL</span>, <span class='kw'>interpretation</span> <span class='kw'>=</span> <span class='st'>"IR"</span>, <span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>30</span>,
<span class='kw'>as_percent</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>, <span class='no'>...</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
<table class="ref-arguments">
<colgroup><col class="name" /><col class="desc" /></colgroup>
<tr>
<th>ab1, ab2</th>
<td><p>vector (or column) with antibiotic interpretations. It will be transformed internally with <code><a href='as.rsi.html'>as.rsi</a></code> if needed.</p></td>
</tr>
<tr>
<th>interpretation</th>
<td><p>antimicrobial interpretation to check for</p></td>
</tr>
<tr>
<th>minimum</th>
<td><p>the minimal amount of available isolates. Any number lower than <code>minimum</code> will return <code>NA</code> with a warning. The default number of <code>30</code> isolates is advised by the Clinical and Laboratory Standards Institute (CLSI) as best practice, see Source.</p></td>
</tr>
<tr>
<th>as_percent</th>
<td><p>a logical to indicate whether the output must be returned as a hundred fold with % sign (a character). A value of <code>0.123456</code> will then be returned as <code>"12.3%"</code>.</p></td>
</tr>
<tr>
<th>...</th>
<td><p>deprecated parameters to support usage on older versions</p></td>
</tr>
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<h1>Data set with 2000 blood culture isolates of septic patients</h1>
<div class="hidden name"><code>septic_patients.Rd</code></div>
</div>
<div class="ref-description">
<p>An anonymised data set containing 2,000 microbial blood culture isolates with their full antibiograms found in septic patients in 4 different hospitals in the Netherlands, between 2001 and 2017. It is true, genuine data. This <code>data.frame</code> can be used to practice AMR analysis. For examples, press F1.</p>
</div>
<pre class="usage"><span class='no'>septic_patients</span></pre>
<h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
<p>A <code><a href='https://www.rdocumentation.org/packages/base/topics/data.frame'>data.frame</a></code> with 2,000 observations and 49 variables:</p><dl class='dl-horizontal'>
<dt><code>date</code></dt><dd><p>date of receipt at the laboratory</p></dd>
<dt><code>hospital_id</code></dt><dd><p>ID of the hospital, from A to D</p></dd>
<dt><code>ward_icu</code></dt><dd><p>logical to determine if ward is an intensive care unit</p></dd>
<dt><code>ward_clinical</code></dt><dd><p>logical to determine if ward is a regular clinical ward</p></dd>
<dt><code>ward_outpatient</code></dt><dd><p>logical to determine if ward is an outpatient clinic</p></dd>
<dt><code>age</code></dt><dd><p>age of the patient</p></dd>
<dt><code>gender</code></dt><dd><p>gender of the patient</p></dd>
<dt><code>patient_id</code></dt><dd><p>ID of the patient, first 10 characters of an SHA hash containing irretrievable information</p></dd>
<dt><code>mo</code></dt><dd><p>ID of microorganism created with <code><a href='as.mo.html'>as.mo</a></code>, see also <code><a href='microorganisms.html'>microorganisms</a></code></p></dd>
<dt><code>peni:rifa</code></dt><dd><p>40 different antibiotics with class <code>rsi</code> (see <code><a href='as.rsi.html'>as.rsi</a></code>); these column names occur in <code><a href='antibiotics.html'>antibiotics</a></code> data set and can be translated with <code><a href='abname.html'>abname</a></code></p></dd>
</dl>
<h2 class="hasAnchor" id="examples"><a class="anchor" href="#examples"></a>Examples</h2>
<pre class="examples"><div class='input'><span class='co'># ----------- #</span>
<span class='co'># PREPARATION #</span>
<span class='co'># ----------- #</span>
<span class='co'># Save this example data set to an object, so we can edit it:</span>
<span class='no'>my_data</span> <span class='kw'>&lt;-</span> <span class='no'>septic_patients</span>
<span class='co'># load the dplyr package to make data science A LOT easier</span>
<span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/library'>library</a></span>(<span class='no'>dplyr</span>)
<span class='co'># Add first isolates to our data set:</span>
<span class='no'>my_data</span> <span class='kw'>&lt;-</span> <span class='no'>my_data</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/mutate.html'>mutate</a></span>(<span class='kw'>first_isolates</span> <span class='kw'>=</span> <span class='fu'><a href='first_isolate.html'>first_isolate</a></span>(<span class='no'>my_data</span>, <span class='st'>"date"</span>, <span class='st'>"patient_id"</span>, <span class='st'>"mo"</span>))</div><div class='output co'>#&gt; <span class='message'>=&gt; Found <span style='font-weight: bold;'>1,315 first isolates</span><span> (65.8% of total)</span></div><div class='input'>
<span class='co'># -------- #</span>
<span class='co'># ANALYSIS #</span>
<span class='co'># -------- #</span>
<span class='co'># 1. Get the amoxicillin resistance percentages (p)</span>
<span class='co'># and numbers (n) of E. coli, divided by hospital:</span>
<span class='no'>my_data</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>mo</span> <span class='kw'>==</span> <span class='fu'><a href='as.mo.html'>guess_mo</a></span>(<span class='st'>"E. coli"</span>),
<span class='no'>first_isolates</span> <span class='kw'>==</span> <span class='fl'>TRUE</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='no'>hospital_id</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></span>(<span class='kw'>n</span> <span class='kw'>=</span> <span class='fu'><a href='count.html'>n_rsi</a></span>(<span class='no'>amox</span>),
<span class='kw'>p</span> <span class='kw'>=</span> <span class='fu'><a href='portion.html'>portion_IR</a></span>(<span class='no'>amox</span>))</div><div class='output co'>#&gt; <span class='warning'>Warning: Introducing NA: only 19 results available (minimum set to 30).</span></div><div class='output co'>#&gt; </span><span style='color: #949494;'># A tibble: 4 x 3</span><span>
#&gt; hospital_id n p
#&gt; </span><span style='color: #949494;font-style: italic;'>&lt;fct&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;int&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;dbl&gt;</span><span>
#&gt; </span><span style='color: #BCBCBC;'>1</span><span> A 19 </span><span style='color: #BB0000;'>NA</span><span>
#&gt; </span><span style='color: #BCBCBC;'>2</span><span> B 65 0.477
#&gt; </span><span style='color: #BCBCBC;'>3</span><span> C 35 0.543
#&gt; </span><span style='color: #BCBCBC;'>4</span><span> D 93 0.495</div><div class='input'>
<span class='co'># 2. Get the amoxicillin/clavulanic acid resistance</span>
<span class='co'># percentages of E. coli, trend over the years:</span>
<span class='no'>my_data</span> <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/filter.html'>filter</a></span>(<span class='no'>mo</span> <span class='kw'>==</span> <span class='fu'><a href='as.mo.html'>guess_mo</a></span>(<span class='st'>"E. coli"</span>),
<span class='no'>first_isolates</span> <span class='kw'>==</span> <span class='fl'>TRUE</span>) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/group_by.html'>group_by</a></span>(<span class='kw'>year</span> <span class='kw'>=</span> <span class='fu'><a href='https://www.rdocumentation.org/packages/base/topics/format'>format</a></span>(<span class='no'>date</span>, <span class='st'>"%Y"</span>)) <span class='kw'>%&gt;%</span>
<span class='fu'><a href='http://dplyr.tidyverse.org/reference/summarise.html'>summarise</a></span>(<span class='kw'>n</span> <span class='kw'>=</span> <span class='fu'><a href='count.html'>n_rsi</a></span>(<span class='no'>amcl</span>),
<span class='kw'>p</span> <span class='kw'>=</span> <span class='fu'><a href='portion.html'>portion_IR</a></span>(<span class='no'>amcl</span>, <span class='kw'>minimum</span> <span class='kw'>=</span> <span class='fl'>20</span>))</div><div class='output co'>#&gt; <span class='warning'>Warning: Introducing NA: only 13 results available (minimum set to 20).</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Introducing NA: only 14 results available (minimum set to 20).</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Introducing NA: only 13 results available (minimum set to 20).</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Introducing NA: only 15 results available (minimum set to 20).</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Introducing NA: only 16 results available (minimum set to 20).</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Introducing NA: only 17 results available (minimum set to 20).</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Introducing NA: only 17 results available (minimum set to 20).</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Introducing NA: only 18 results available (minimum set to 20).</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Introducing NA: only 13 results available (minimum set to 20).</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Introducing NA: only 10 results available (minimum set to 20).</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Introducing NA: only 13 results available (minimum set to 20).</span></div><div class='output co'>#&gt; <span class='warning'>Warning: Introducing NA: only 13 results available (minimum set to 20).</span></div><div class='output co'>#&gt; </span><span style='color: #949494;'># A tibble: 16 x 3</span><span>
#&gt; year n p
#&gt; </span><span style='color: #949494;font-style: italic;'>&lt;chr&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;int&gt;</span><span> </span><span style='color: #949494;font-style: italic;'>&lt;dbl&gt;</span><span>
#&gt; </span><span style='color: #BCBCBC;'> 1</span><span> 2002 13 </span><span style='color: #BB0000;'>NA</span><span>
#&gt; </span><span style='color: #BCBCBC;'> 2</span><span> 2003 14 </span><span style='color: #BB0000;'>NA</span><span>
#&gt; </span><span style='color: #BCBCBC;'> 3</span><span> 2004 13 </span><span style='color: #BB0000;'>NA</span><span>
#&gt; </span><span style='color: #BCBCBC;'> 4</span><span> 2005 15 </span><span style='color: #BB0000;'>NA</span><span>
#&gt; </span><span style='color: #BCBCBC;'> 5</span><span> 2006 16 </span><span style='color: #BB0000;'>NA</span><span>
#&gt; </span><span style='color: #BCBCBC;'> 6</span><span> 2007 17 </span><span style='color: #BB0000;'>NA</span><span>
#&gt; </span><span style='color: #BCBCBC;'> 7</span><span> 2008 17 </span><span style='color: #BB0000;'>NA</span><span>
#&gt; </span><span style='color: #BCBCBC;'> 8</span><span> 2009 18 </span><span style='color: #BB0000;'>NA</span><span>
#&gt; </span><span style='color: #BCBCBC;'> 9</span><span> 2010 13 </span><span style='color: #BB0000;'>NA</span><span>
#&gt; </span><span style='color: #BCBCBC;'>10</span><span> 2011 21 0.095</span><span style='text-decoration: underline;'>2</span><span>
#&gt; </span><span style='color: #BCBCBC;'>11</span><span> 2012 10 </span><span style='color: #BB0000;'>NA</span><span>
#&gt; </span><span style='color: #BCBCBC;'>12</span><span> 2013 13 </span><span style='color: #BB0000;'>NA</span><span>
#&gt; </span><span style='color: #BCBCBC;'>13</span><span> 2014 20 0.2
#&gt; </span><span style='color: #BCBCBC;'>14</span><span> 2015 13 </span><span style='color: #BB0000;'>NA</span><span>
#&gt; </span><span style='color: #BCBCBC;'>15</span><span> 2016 21 0.190
#&gt; </span><span style='color: #BCBCBC;'>16</span><span> 2017 20 0.4 </div></span></pre>
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<h1>Skewness of the sample</h1>
<div class="hidden name"><code>skewness.Rd</code></div>
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<div class="ref-description">
<p>Skewness is a measure of the asymmetry of the probability distribution of a real-valued random variable about its mean.</p>
<p>When negative: the left tail is longer; the mass of the distribution is concentrated on the right of the figure. When positive: the right tail is longer; the mass of the distribution is concentrated on the left of the figure.</p>
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<pre class="usage"><span class='fu'>skewness</span>(<span class='no'>x</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='co'># S3 method for default</span>
<span class='fu'>skewness</span>(<span class='no'>x</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='co'># S3 method for matrix</span>
<span class='fu'>skewness</span>(<span class='no'>x</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)
<span class='co'># S3 method for data.frame</span>
<span class='fu'>skewness</span>(<span class='no'>x</span>, <span class='kw'>na.rm</span> <span class='kw'>=</span> <span class='fl'>FALSE</span>)</pre>
<h2 class="hasAnchor" id="arguments"><a class="anchor" href="#arguments"></a>Arguments</h2>
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<colgroup><col class="name" /><col class="desc" /></colgroup>
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<th>x</th>
<td><p>a vector of values, a <code>matrix</code> or a <code>data frame</code></p></td>
</tr>
<tr>
<th>na.rm</th>
<td><p>a logical value indicating whether <code>NA</code> values should be stripped before the computation proceeds.</p></td>
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<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='kurtosis.html'>kurtosis</a></code></p></div>
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<h1>Supplementary Data</h1>
<div class="hidden name"><code>supplementary_data.Rd</code></div>
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<p>These <code>data.tables</code> are transformed from the <code><a href='microorganisms.html'>microorganisms</a></code> and <code><a href='microorganisms.html'>microorganisms</a></code> data sets to improve speed of <code><a href='as.mo.html'>as.mo</a></code>. They are meant for internal use only, and are only mentioned here for reference.</p>
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<pre class="usage"><span class='no'>microorganismsDT</span>
<span class='no'>microorganisms.prevDT</span>
<span class='no'>microorganisms.unprevDT</span>
<span class='no'>microorganisms.oldDT</span></pre>
<h2 class="hasAnchor" id="format"><a class="anchor" href="#format"></a>Format</h2>
<p>An object of class <code>data.table</code> (inherits from <code>data.frame</code>) with 18833 rows and 15 columns.</p>
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