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<meta property="og:description" content="Create a frequency table of a vector with items or a data frame. Supports quasiquotation and markdown for reports. The best practice is: data %&amp;gt;% freq(var).
top_freq can be used to get the top/bottom n items of a frequency table, with counts as names." />
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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. The best practice is: <code>data %&gt;% freq(var)</code>.<br />
<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='fu'>header</span>(<span class='no'>f</span>, <span class='kw'>property</span> <span class='kw'>=</span> <span class='kw'>NULL</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 (except when <code>nmax</code> is defined) 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 that 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>
<tr>
<th>property</th>
<td><p>property in header to return this value directly</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;
#&gt; (omitted 11 entries, n = 1,251 [62.6%])
#&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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<p>Developed by <a href='https://www.rug.nl/staff/m.s.berends/'>Matthijs S. Berends</a>, <a href='https://www.rug.nl/staff/c.f.luz/'>Christian F. Luz</a>, <a href='https://www.rug.nl/staff/c.glasner/'>Corinna Glasner</a>, <a href='https://www.rug.nl/staff/a.w.friedrich/'>Alex W. Friedrich</a>, <a href='https://www.rug.nl/staff/b.sinha/'>Bhanu N. M. Sinha</a>.</p>
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