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Predict antimicrobial resistance
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Conduct principal component analysis for AMR
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<img src="../logo.svg" class="logo" alt=""><h1>Check Availability of Columns</h1>
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<small class="dont-index">Source: <a href="https://github.com/msberends/AMR/blob/HEAD/R/availability.R" class="external-link"><code>R/availability.R</code></a></small>
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<div class="d-none name"><code>availability.Rd</code></div>
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</div>
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<div class="ref-description section level2">
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<p>Easy check for data availability of all columns in a data set. This makes it easy to get an idea of which antimicrobial combinations can be used for calculation with e.g. <code><a href="proportion.html">susceptibility()</a></code> and <code><a href="proportion.html">resistance()</a></code>.</p>
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<div class="section level2">
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<h2 id="ref-usage">Usage<a class="anchor" aria-label="anchor" href="#ref-usage"></a></h2>
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<div class="sourceCode"><pre class="sourceCode r"><code><span><span class="fu">availability</span><span class="op">(</span><span class="va">tbl</span>, width <span class="op">=</span> <span class="cn">NULL</span><span class="op">)</span></span></code></pre></div>
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<div class="section level2">
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<h2 id="arguments">Arguments<a class="anchor" aria-label="anchor" href="#arguments"></a></h2>
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<dl><dt>tbl</dt>
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<dd><p>a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> or <a href="https://rdrr.io/r/base/list.html" class="external-link">list</a></p></dd>
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<dt>width</dt>
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<dd><p>number of characters to present the visual availability, defaults to filling the width of the console</p></dd>
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</dl></div>
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<div class="section level2">
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<h2 id="value">Value<a class="anchor" aria-label="anchor" href="#value"></a></h2>
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<p><a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with column names of <code>tbl</code> as row names</p>
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</div>
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<div class="section level2">
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<h2 id="details">Details<a class="anchor" aria-label="anchor" href="#details"></a></h2>
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<p>The function returns a <a href="https://rdrr.io/r/base/data.frame.html" class="external-link">data.frame</a> with columns <code>"resistant"</code> and <code>"visual_resistance"</code>. The values in that columns are calculated with <code><a href="proportion.html">resistance()</a></code>.</p>
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</div>
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<div class="section level2">
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<h2 id="ref-examples">Examples<a class="anchor" aria-label="anchor" href="#ref-examples"></a></h2>
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<div class="sourceCode"><pre class="sourceCode r"><code><span class="r-in"><span><span class="fu">availability</span><span class="op">(</span><span class="va">example_isolates</span><span class="op">)</span></span></span>
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<span class="r-out co"><span class="r-pr">#></span> count available visual_availabilty resistant visual_resistance</span>
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<span class="r-out co"><span class="r-pr">#></span> date 2000 100.0% |################| </span>
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<span class="r-out co"><span class="r-pr">#></span> hospital_id 2000 100.0% |################| </span>
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<span class="r-out co"><span class="r-pr">#></span> ward_icu 2000 100.0% |################| </span>
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<span class="r-out co"><span class="r-pr">#></span> ward_clinical 2000 100.0% |################| </span>
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<span class="r-out co"><span class="r-pr">#></span> ward_outpatient 2000 100.0% |################| </span>
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<span class="r-out co"><span class="r-pr">#></span> age 2000 100.0% |################| </span>
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<span class="r-out co"><span class="r-pr">#></span> gender 2000 100.0% |################| </span>
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<span class="r-out co"><span class="r-pr">#></span> patient_id 2000 100.0% |################| </span>
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<span class="r-out co"><span class="r-pr">#></span> mo 2000 100.0% |################| </span>
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<span class="r-out co"><span class="r-pr">#></span> PEN 1629 81.5% |############----| 73.7% |###########-----|</span>
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<span class="r-out co"><span class="r-pr">#></span> OXA 365 18.3% |##--------------| 31.2% |#####-----------|</span>
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<span class="r-out co"><span class="r-pr">#></span> FLC 943 47.2% |#######---------| 29.5% |####------------|</span>
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<span class="r-out co"><span class="r-pr">#></span> AMX 1350 67.5% |##########------| 59.6% |#########-------|</span>
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<span class="r-out co"><span class="r-pr">#></span> AMC 1879 94.0% |###############-| 23.7% |###-------------|</span>
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<span class="r-out co"><span class="r-pr">#></span> AMP 1350 67.5% |##########------| 59.6% |#########-------|</span>
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<span class="r-out co"><span class="r-pr">#></span> TZP 1001 50.0% |########--------| 12.6% |##--------------|</span>
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<span class="r-out co"><span class="r-pr">#></span> CZO 446 22.3% |###-------------| 44.6% |#######---------|</span>
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<span class="r-out co"><span class="r-pr">#></span> FEP 724 36.2% |#####-----------| 14.2% |##--------------|</span>
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<span class="r-out co"><span class="r-pr">#></span> CXM 1789 89.5% |##############--| 26.3% |####------------|</span>
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<span class="r-out co"><span class="r-pr">#></span> FOX 818 40.9% |######----------| 27.4% |####------------|</span>
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<span class="r-out co"><span class="r-pr">#></span> CTX 943 47.2% |#######---------| 15.5% |##--------------|</span>
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<span class="r-out co"><span class="r-pr">#></span> CAZ 1811 90.6% |##############--| 66.5% |##########------|</span>
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<span class="r-out co"><span class="r-pr">#></span> CRO 943 47.2% |#######---------| 15.5% |##--------------|</span>
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<span class="r-out co"><span class="r-pr">#></span> GEN 1855 92.8% |##############--| 24.6% |###-------------|</span>
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<span class="r-out co"><span class="r-pr">#></span> TOB 1351 67.6% |##########------| 34.4% |#####-----------|</span>
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<span class="r-out co"><span class="r-pr">#></span> AMK 692 34.6% |#####-----------| 63.7% |##########------|</span>
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<span class="r-out co"><span class="r-pr">#></span> KAN 471 23.6% |###-------------| 100.0% |################|</span>
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<span class="r-out co"><span class="r-pr">#></span> TMP 1499 75.0% |############----| 38.1% |######----------|</span>
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<span class="r-out co"><span class="r-pr">#></span> SXT 1759 88.0% |##############--| 20.5% |###-------------|</span>
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<span class="r-out co"><span class="r-pr">#></span> NIT 743 37.2% |#####-----------| 17.1% |##--------------|</span>
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<span class="r-out co"><span class="r-pr">#></span> FOS 351 17.6% |##--------------| 42.2% |######----------|</span>
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<span class="r-out co"><span class="r-pr">#></span> LNZ 1023 51.2% |########--------| 69.3% |###########-----|</span>
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<span class="r-out co"><span class="r-pr">#></span> CIP 1409 70.5% |###########-----| 16.2% |##--------------|</span>
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<span class="r-out co"><span class="r-pr">#></span> MFX 211 10.6% |#---------------| 33.6% |#####-----------|</span>
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<span class="r-out co"><span class="r-pr">#></span> VAN 1861 93.1% |##############--| 38.3% |######----------|</span>
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<span class="r-out co"><span class="r-pr">#></span> TEC 976 48.8% |#######---------| 75.7% |############----|</span>
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<span class="r-out co"><span class="r-pr">#></span> TCY 1200 60.0% |#########-------| 29.8% |####------------|</span>
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<span class="r-out co"><span class="r-pr">#></span> TGC 798 39.9% |######----------| 12.7% |##--------------|</span>
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<span class="r-out co"><span class="r-pr">#></span> DOX 1136 56.8% |#########-------| 27.7% |####------------|</span>
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<span class="r-out co"><span class="r-pr">#></span> ERY 1894 94.7% |###############-| 57.2% |#########-------|</span>
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<span class="r-out co"><span class="r-pr">#></span> CLI 1520 76.0% |############----| 61.2% |#########-------|</span>
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<span class="r-out co"><span class="r-pr">#></span> AZM 1894 94.7% |###############-| 57.2% |#########-------|</span>
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<span class="r-out co"><span class="r-pr">#></span> IPM 889 44.5% |#######---------| 6.2% |----------------|</span>
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<span class="r-out co"><span class="r-pr">#></span> MEM 829 41.5% |######----------| 5.9% |----------------|</span>
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<span class="r-out co"><span class="r-pr">#></span> MTR 34 1.7% |----------------| 14.7% |##--------------|</span>
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<span class="r-out co"><span class="r-pr">#></span> CHL 154 7.7% |#---------------| 21.4% |###-------------|</span>
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<span class="r-out co"><span class="r-pr">#></span> COL 1640 82.0% |#############---| 81.2% |############----|</span>
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<span class="r-out co"><span class="r-pr">#></span> MUP 270 13.5% |##--------------| 5.9% |----------------|</span>
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<span class="r-out co"><span class="r-pr">#></span> RIF 1003 50.2% |########--------| 69.6% |###########-----|</span>
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<span class="r-in"><span><span class="co"># \donttest{</span></span></span>
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<span class="r-in"><span><span class="kw">if</span> <span class="op">(</span><span class="kw"><a href="https://rdrr.io/r/base/library.html" class="external-link">require</a></span><span class="op">(</span><span class="st"><a href="https://dplyr.tidyverse.org" class="external-link">"dplyr"</a></span><span class="op">)</span><span class="op">)</span> <span class="op">{</span></span></span>
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<span class="r-in"><span> <span class="va">example_isolates</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
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<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/filter.html" class="external-link">filter</a></span><span class="op">(</span><span class="va">mo</span> <span class="op">==</span> <span class="fu"><a href="as.mo.html">as.mo</a></span><span class="op">(</span><span class="st">"E. coli"</span><span class="op">)</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
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<span class="r-in"><span> <span class="fu"><a href="https://dplyr.tidyverse.org/reference/select_all.html" class="external-link">select_if</a></span><span class="op">(</span><span class="va">is.rsi</span><span class="op">)</span> <span class="op"><a href="https://magrittr.tidyverse.org/reference/pipe.html" class="external-link">%>%</a></span></span></span>
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<span class="r-in"><span> <span class="fu">availability</span><span class="op">(</span><span class="op">)</span></span></span>
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<span class="r-in"><span><span class="op">}</span></span></span>
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<span class="r-msg co"><span class="r-pr">#></span> ℹ Function `as.mo()` is uncertain about "E. coli" (assuming Escherichia</span>
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<span class="r-msg co"><span class="r-pr">#></span> coli). Run `mo_uncertainties()` to review this.</span>
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<span class="r-out co"><span class="r-pr">#></span> count available visual_availabilty resistant visual_resistance</span>
|
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<span class="r-out co"><span class="r-pr">#></span> PEN 467 100.0% |######################| 100.0% |######################|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> OXA 0 0.0% |----------------------| </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> FLC 0 0.0% |----------------------| </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> AMX 392 83.9% |##################----| 50.0% |###########-----------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> AMC 467 100.0% |######################| 13.1% |##--------------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> AMP 392 83.9% |##################----| 50.0% |###########-----------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> TZP 416 89.1% |###################---| 5.5% |#---------------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> CZO 82 17.6% |###-------------------| 2.4% |----------------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> FEP 317 67.9% |##############--------| 2.8% |----------------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> CXM 465 99.6% |######################| 5.4% |#---------------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> FOX 377 80.7% |#################-----| 6.9% |#---------------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> CTX 459 98.3% |#####################-| 2.4% |----------------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> CAZ 460 98.5% |#####################-| 2.4% |----------------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> CRO 459 98.3% |#####################-| 2.4% |----------------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> GEN 460 98.5% |#####################-| 2.0% |----------------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> TOB 462 98.9% |#####################-| 2.6% |----------------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> AMK 171 36.6% |########--------------| 0.0% |----------------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> KAN 0 0.0% |----------------------| </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> TMP 396 84.8% |##################----| 39.1% |########--------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> SXT 465 99.6% |######################| 31.6% |######----------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> NIT 458 98.1% |#####################-| 2.8% |----------------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> FOS 61 13.1% |##--------------------| 0.0% |----------------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> LNZ 467 100.0% |######################| 100.0% |######################|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> CIP 456 97.6% |#####################-| 12.5% |##--------------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> MFX 57 12.2% |##--------------------| 100.0% |######################|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> VAN 467 100.0% |######################| 100.0% |######################|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> TEC 467 100.0% |######################| 100.0% |######################|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> TCY 3 0.6% |----------------------| 66.7% |##############--------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> TGC 68 14.6% |###-------------------| 0.0% |----------------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> DOX 0 0.0% |----------------------| </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> ERY 467 100.0% |######################| 100.0% |######################|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> CLI 467 100.0% |######################| 100.0% |######################|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> AZM 467 100.0% |######################| 100.0% |######################|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> IPM 422 90.4% |###################---| 0.0% |----------------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> MEM 418 89.5% |###################---| 0.0% |----------------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> MTR 2 0.4% |----------------------| 0.0% |----------------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> CHL 0 0.0% |----------------------| </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> COL 240 51.4% |###########-----------| 0.0% |----------------------|</span>
|
||
<span class="r-out co"><span class="r-pr">#></span> MUP 0 0.0% |----------------------| </span>
|
||
<span class="r-out co"><span class="r-pr">#></span> RIF 467 100.0% |######################| 100.0% |######################|</span>
|
||
<span class="r-in"><span><span class="co"># }</span></span></span>
|
||
</code></pre></div>
|
||
</div>
|
||
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|
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|
||
<p></p><p><code>AMR</code> (for R). Developed at the <a target="_blank" href="https://www.rug.nl" class="external-link">University of Groningen</a> in collaboration with non-profit organisations<br><a target="_blank" href="https://www.certe.nl" class="external-link">Certe Medical Diagnostics and Advice Foundation</a> and <a target="_blank" href="https://www.umcg.nl" class="external-link">University Medical Center Groningen</a>.</p>
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