train_discrete

Graphical scales map data to aesthetics, and provide methods
for automatically determining breaks and labels for axes and legends.

Thomas Lin Pedersen

scales

Scale Functions for Visualization

Hadley Wickham

Dana Seidel

Posit Software, PBC 

train_discrete function

<dl><dt>new</dt>
<dd>New data to add to scale</dd>
<dt>existing</dt>
<dd>Optional existing scale to update</dd>
<dt>drop</dt>
<dd><code>TRUE</code>, will drop factor levels not associated with data</dd>
<dt>na.rm</dt>
<dd>If <code>TRUE</code>, will remove missing values</dd>
<dt>fct</dt>
<dd>Treat <code>existing</code> as if it came from a factor (ie. don't sort the range)</dd>
<dt>call</dt>
<dd>A call to display in error messages</dd></dl>

Arguments

Train (update) a discrete scale — train_discrete

<dl>

<dt>new</dt>
<dd>New data to add to scale</dd>


<dt>existing</dt>
<dd>Optional existing scale to update</dd>


<dt>drop</dt>
<dd><code>TRUE</code>, will drop factor levels not associated with data</dd>


<dt>na.rm</dt>
<dd>If <code>TRUE</code>, will remove missing values</dd>


<dt>fct</dt>
<dd>Treat <code>existing</code> as if it came from a factor (ie. don't sort the range)</dd>


<dt>call</dt>
<dd>A call to display in error messages</dd>

</dl>

train_discrete: Train (update) a discrete scale

Description

Usage

Arguments