EVOLUTION-MANAGER

Edit File: vars.html

<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN" "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd"><html xmlns="http://www.w3.org/1999/xhtml"><head><title>R: Quote faceting variables</title>
<meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
<link rel="stylesheet" type="text/css" href="R.css" />
</head><body>

<table width="100%" summary="page for vars {ggplot2}"><tr><td>vars {ggplot2}</td><td style="text-align: right;">R Documentation</td></tr></table>

<h2>Quote faceting variables</h2>

<h3>Description</h3>

<p>Just like <code><a href="aes.html">aes()</a></code>, <code>vars()</code> is a <a href="../../rlang/html/nse-defuse.html">quoting function</a>
that takes inputs to be evaluated in the context of a dataset.
These inputs can be:
</p>

<ul>
<li><p> variable names
</p>
</li>
<li><p> complex expressions
</p>
</li></ul>

<p>In both cases, the results (the vectors that the variable
represents or the results of the expressions) are used to form
faceting groups.
</p>

<h3>Usage</h3>

<h3>Arguments</h3>

<table summary="R argblock">
<tr valign="top"><td><code>...</code></td>
<td>
<p>Variables or expressions automatically quoted. These are
evaluated in the context of the data to form faceting groups. Can
be named (the names are passed to a <a href="labellers.html">labeller</a>).</p>
</td></tr>
</table>

<p><code><a href="aes.html">aes()</a></code>, <code><a href="facet_wrap.html">facet_wrap()</a></code>, <code><a href="facet_grid.html">facet_grid()</a></code>
</p>

<h3>Examples</h3>

<pre>
p &lt;- ggplot(mtcars, aes(wt, disp)) + geom_point()
p + facet_wrap(vars(vs, am))

# vars() makes it easy to pass variables from wrapper functions:
wrap_by &lt;- function(...) {
  facet_wrap(vars(...), labeller = label_both)
}
p + wrap_by(vs)
p + wrap_by(vs, am)

# You can also supply expressions to vars(). In this case it's often a
# good idea to supply a name as well:
p + wrap_by(drat = cut_number(drat, 3))

# Let's create another function for cutting and wrapping a
# variable. This time it will take a named argument instead of dots,
# so we'll have to use the "enquote and unquote" pattern:
wrap_cut &lt;- function(var, n = 3) {
  # Let's enquote the named argument `var` to make it auto-quoting:
  var &lt;- enquo(var)

# `quo_name()` will create a nice default name:
  nm &lt;- quo_name(var)

# Now let's unquote everything at the right place. Note that we also
  # unquote `n` just in case the data frame has a column named
  # `n`. The latter would have precedence over our local variable
  # because the data is always masking the environment.
  wrap_by(!!nm := cut_number(!!var, !!n))
}

# Thanks to tidy eval idioms we now have another useful wrapper:
p + wrap_cut(drat)
</pre>

<hr /><div style="text-align: center;">[Package <em>ggplot2</em> version 3.3.2 <a href="00Index.html">Index</a>]</div>
</body></html>