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add_miss_cluster.html
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add_miss_cluster.html
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For example, if you use vis_miss(airquality, cluster = TRUE), you can
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<h1>Add a column that tells us which "missingness cluster" a row belongs to</h1>
<small class="dont-index">Source: <a href='https://github.com/njtierney/naniar/blob/master/R/add-cols.R'><code>R/add-cols.R</code></a></small>
<div class="hidden name"><code>add_miss_cluster.Rd</code></div>
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<div class="ref-description">
<p>A way to extract the cluster of missingness that a group belongs to.
For example, if you use <code><a href='http://visdat.njtierney.com//reference/vis_miss.html'>vis_miss(airquality, cluster = TRUE)</a></code>, you can
see some clustering in the data, but you do not have a way to identify
the cluster. Future work will incorporate the <code>seriation</code> package to
allow for better control over the clustering from the user.</p>
</div>
<pre class="usage"><span class='fu'>add_miss_cluster</span>(<span class='no'>data</span>, <span class='kw'>cluster_method</span> <span class='kw'>=</span> <span class='st'>"mcquitty"</span>, <span class='kw'>n_clusters</span> <span class='kw'>=</span> <span class='fl'>2</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 dataframe</p></td>
</tr>
<tr>
<th>cluster_method</th>
<td><p>character vector of the agglomeration method to use,
the default is "mcquitty". Options are taken from <code><a href='https://rdrr.io/r/stats/hclust.html'>stats::hclust</a></code>
helpfile, and options include: "ward.D", "ward.D2", "single", "complete",
"average" (= UPGMA), "mcquitty" (= WPGMA), "median" (= WPGMC) or
"centroid" (= UPGMC).</p></td>
</tr>
<tr>
<th>n_clusters</th>
<td><p>numeric the number of clusters you expect. Defaults to 2.</p></td>
</tr>
</table>
<h2 class="hasAnchor" id="see-also"><a class="anchor" href="#see-also"></a>See also</h2>
<div class='dont-index'><p><code><a href='bind_shadow.html'>bind_shadow()</a></code> <code><a href='add_any_miss.html'>add_any_miss()</a></code> <code><a href='add_label_missings.html'>add_label_missings()</a></code> <code><a href='add_label_shadow.html'>add_label_shadow()</a></code> <code>add_miss_cluster()</code> <code><a href='add_n_miss.html'>add_n_miss()</a></code> <code><a href='add_prop_miss.html'>add_prop_miss()</a></code> <code><a href='add_shadow_shift.html'>add_shadow_shift()</a></code> <code><a href='cast_shadow.html'>cast_shadow()</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'>add_miss_cluster</span>(<span class='no'>airquality</span>)</div><div class='output co'>#> <span style='color: #555555;'># A tibble: 153 x 7</span><span>
#> Ozone Solar.R Wind Temp Month Day miss_cluster
#> </span><span style='color: #555555;font-style: italic;'><int></span><span> </span><span style='color: #555555;font-style: italic;'><int></span><span> </span><span style='color: #555555;font-style: italic;'><dbl></span><span> </span><span style='color: #555555;font-style: italic;'><int></span><span> </span><span style='color: #555555;font-style: italic;'><int></span><span> </span><span style='color: #555555;font-style: italic;'><int></span><span> </span><span style='color: #555555;font-style: italic;'><int></span><span>
#> </span><span style='color: #555555;'> 1</span><span> 41 190 7.4 67 5 1 1
#> </span><span style='color: #555555;'> 2</span><span> 36 118 8 72 5 2 1
#> </span><span style='color: #555555;'> 3</span><span> 12 149 12.6 74 5 3 1
#> </span><span style='color: #555555;'> 4</span><span> 18 313 11.5 62 5 4 1
#> </span><span style='color: #555555;'> 5</span><span> </span><span style='color: #BB0000;'>NA</span><span> </span><span style='color: #BB0000;'>NA</span><span> 14.3 56 5 5 2
#> </span><span style='color: #555555;'> 6</span><span> 28 </span><span style='color: #BB0000;'>NA</span><span> 14.9 66 5 6 1
#> </span><span style='color: #555555;'> 7</span><span> 23 299 8.6 65 5 7 1
#> </span><span style='color: #555555;'> 8</span><span> 19 99 13.8 59 5 8 1
#> </span><span style='color: #555555;'> 9</span><span> 8 19 20.1 61 5 9 1
#> </span><span style='color: #555555;'>10</span><span> </span><span style='color: #BB0000;'>NA</span><span> 194 8.6 69 5 10 2
#> </span><span style='color: #555555;'># … with 143 more rows</span><span></div><div class='input'><span class='fu'>add_miss_cluster</span>(<span class='no'>airquality</span>, <span class='kw'>cluster_method</span> <span class='kw'>=</span> <span class='st'>"ward.D"</span>)</div><div class='output co'>#> </span><span style='color: #555555;'># A tibble: 153 x 7</span><span>
#> Ozone Solar.R Wind Temp Month Day miss_cluster
#> </span><span style='color: #555555;font-style: italic;'><int></span><span> </span><span style='color: #555555;font-style: italic;'><int></span><span> </span><span style='color: #555555;font-style: italic;'><dbl></span><span> </span><span style='color: #555555;font-style: italic;'><int></span><span> </span><span style='color: #555555;font-style: italic;'><int></span><span> </span><span style='color: #555555;font-style: italic;'><int></span><span> </span><span style='color: #555555;font-style: italic;'><int></span><span>
#> </span><span style='color: #555555;'> 1</span><span> 41 190 7.4 67 5 1 1
#> </span><span style='color: #555555;'> 2</span><span> 36 118 8 72 5 2 1
#> </span><span style='color: #555555;'> 3</span><span> 12 149 12.6 74 5 3 1
#> </span><span style='color: #555555;'> 4</span><span> 18 313 11.5 62 5 4 1
#> </span><span style='color: #555555;'> 5</span><span> </span><span style='color: #BB0000;'>NA</span><span> </span><span style='color: #BB0000;'>NA</span><span> 14.3 56 5 5 1
#> </span><span style='color: #555555;'> 6</span><span> 28 </span><span style='color: #BB0000;'>NA</span><span> 14.9 66 5 6 1
#> </span><span style='color: #555555;'> 7</span><span> 23 299 8.6 65 5 7 1
#> </span><span style='color: #555555;'> 8</span><span> 19 99 13.8 59 5 8 1
#> </span><span style='color: #555555;'> 9</span><span> 8 19 20.1 61 5 9 1
#> </span><span style='color: #555555;'>10</span><span> </span><span style='color: #BB0000;'>NA</span><span> 194 8.6 69 5 10 2
#> </span><span style='color: #555555;'># … with 143 more rows</span><span></div><div class='input'><span class='fu'>add_miss_cluster</span>(<span class='no'>airquality</span>, <span class='kw'>cluster_method</span> <span class='kw'>=</span> <span class='st'>"ward.D"</span>, <span class='kw'>n_clusters</span> <span class='kw'>=</span> <span class='fl'>3</span>)</div><div class='output co'>#> </span><span style='color: #555555;'># A tibble: 153 x 7</span><span>
#> Ozone Solar.R Wind Temp Month Day miss_cluster
#> </span><span style='color: #555555;font-style: italic;'><int></span><span> </span><span style='color: #555555;font-style: italic;'><int></span><span> </span><span style='color: #555555;font-style: italic;'><dbl></span><span> </span><span style='color: #555555;font-style: italic;'><int></span><span> </span><span style='color: #555555;font-style: italic;'><int></span><span> </span><span style='color: #555555;font-style: italic;'><int></span><span> </span><span style='color: #555555;font-style: italic;'><int></span><span>
#> </span><span style='color: #555555;'> 1</span><span> 41 190 7.4 67 5 1 1
#> </span><span style='color: #555555;'> 2</span><span> 36 118 8 72 5 2 1
#> </span><span style='color: #555555;'> 3</span><span> 12 149 12.6 74 5 3 1
#> </span><span style='color: #555555;'> 4</span><span> 18 313 11.5 62 5 4 1
#> </span><span style='color: #555555;'> 5</span><span> </span><span style='color: #BB0000;'>NA</span><span> </span><span style='color: #BB0000;'>NA</span><span> 14.3 56 5 5 2
#> </span><span style='color: #555555;'> 6</span><span> 28 </span><span style='color: #BB0000;'>NA</span><span> 14.9 66 5 6 2
#> </span><span style='color: #555555;'> 7</span><span> 23 299 8.6 65 5 7 1
#> </span><span style='color: #555555;'> 8</span><span> 19 99 13.8 59 5 8 1
#> </span><span style='color: #555555;'> 9</span><span> 8 19 20.1 61 5 9 1
#> </span><span style='color: #555555;'>10</span><span> </span><span style='color: #BB0000;'>NA</span><span> 194 8.6 69 5 10 3
#> </span><span style='color: #555555;'># … with 143 more rows</span><span></div><div class='input'><span class='fu'>add_miss_cluster</span>(<span class='no'>airquality</span>, <span class='kw'>n_clusters</span> <span class='kw'>=</span> <span class='fl'>3</span>)</div><div class='output co'>#> </span><span style='color: #555555;'># A tibble: 153 x 7</span><span>
#> Ozone Solar.R Wind Temp Month Day miss_cluster
#> </span><span style='color: #555555;font-style: italic;'><int></span><span> </span><span style='color: #555555;font-style: italic;'><int></span><span> </span><span style='color: #555555;font-style: italic;'><dbl></span><span> </span><span style='color: #555555;font-style: italic;'><int></span><span> </span><span style='color: #555555;font-style: italic;'><int></span><span> </span><span style='color: #555555;font-style: italic;'><int></span><span> </span><span style='color: #555555;font-style: italic;'><int></span><span>
#> </span><span style='color: #555555;'> 1</span><span> 41 190 7.4 67 5 1 1
#> </span><span style='color: #555555;'> 2</span><span> 36 118 8 72 5 2 1
#> </span><span style='color: #555555;'> 3</span><span> 12 149 12.6 74 5 3 1
#> </span><span style='color: #555555;'> 4</span><span> 18 313 11.5 62 5 4 1
#> </span><span style='color: #555555;'> 5</span><span> </span><span style='color: #BB0000;'>NA</span><span> </span><span style='color: #BB0000;'>NA</span><span> 14.3 56 5 5 2
#> </span><span style='color: #555555;'> 6</span><span> 28 </span><span style='color: #BB0000;'>NA</span><span> 14.9 66 5 6 1
#> </span><span style='color: #555555;'> 7</span><span> 23 299 8.6 65 5 7 1
#> </span><span style='color: #555555;'> 8</span><span> 19 99 13.8 59 5 8 1
#> </span><span style='color: #555555;'> 9</span><span> 8 19 20.1 61 5 9 1
#> </span><span style='color: #555555;'>10</span><span> </span><span style='color: #BB0000;'>NA</span><span> 194 8.6 69 5 10 3
#> </span><span style='color: #555555;'># … with 143 more rows</span><span></div></span></pre>
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