# Fancy Cut

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About a year ago I was working on an analysis that required me to take about 20 continuous variables and turn each into a factor based on some banding rule. The rules were complicated enough that using `cut()`

was painful.

`cut()`

works great when the banding you want to do is simple. For example,

```
<span class="n">vals</span><span class="w"> </span><span class="o"><-</span><span class="w"> </span><span class="nf">c</span><span class="p">(</span><span class="m">22</span><span class="p">,</span><span class="w"> </span><span class="m">69</span><span class="p">,</span><span class="w"> </span><span class="m">89</span><span class="p">,</span><span class="w"> </span><span class="m">56</span><span class="p">,</span><span class="w"> </span><span class="m">33</span><span class="p">,</span><span class="w"> </span><span class="m">57</span><span class="p">,</span><span class="w"> </span><span class="m">10</span><span class="p">,</span><span class="w"> </span><span class="m">38</span><span class="p">,</span><span class="w"> </span><span class="m">50</span><span class="p">,</span><span class="w"> </span><span class="m">25</span><span class="p">)</span><span class="w">
</span><span class="n">cut</span><span class="p">(</span><span class="w">
</span><span class="n">vals</span><span class="p">,</span><span class="w">
</span><span class="n">breaks</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nf">c</span><span class="p">(</span><span class="m">0</span><span class="p">,</span><span class="w"> </span><span class="m">50</span><span class="p">,</span><span class="w"> </span><span class="m">65</span><span class="p">,</span><span class="w"> </span><span class="m">100</span><span class="p">),</span><span class="w">
</span><span class="n">labels</span><span class="w"> </span><span class="o">=</span><span class="w"> </span><span class="nf">c</span><span class="p">(</span><span class="s1">'Low'</span><span class="p">,</span><span class="w"> </span><span class="s1">'Med'</span><span class="p">,</span><span class="w"> </span><span class="s1">'High'</span><span class="p">)</span><span class="w">
</span><span class="p">)</span><span class="w">
</span>
```

```
## [1] Low High High Med Low Med Low Low Low Low
## Levels: Low Med High
```

To

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