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, 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></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>

</dl>

train_discrete: Train (update) a discrete scale

Description

Usage

Arguments