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<body>
<h1 class="title toc-ignore">dplyr <-> base R</h1>
<p>This vignette compares dplyr functions to their base R equivalents.
This helps those familiar with base R understand better what dplyr does,
and shows dplyr users how you might express the same ideas in base R
code. We’ll start with a rough overview of the major differences, then
discuss the one table verbs in more detail, followed by the two table
verbs.</p>
<div id="overview" class="section level1">
<h1>Overview</h1>
<ol style="list-style-type: decimal">
<li><p>The code dplyr verbs input and output data frames. This contrasts
with base R functions which more frequently work with individual
vectors.</p></li>
<li><p>dplyr relies heavily on “non-standard evaluation” so that you
don’t need to use <code>$</code> to refer to columns in the “current”
data frame. This behaviour is inspired by the base functions
<code>subset()</code> and <code>transform()</code>.</p></li>
<li><p>dplyr solutions tend to use a variety of single purpose verbs,
while base R solutions typically tend to use <code>[</code> in a variety
of ways, depending on the task at hand.</p></li>
<li><p>Multiple dplyr verbs are often strung together into a pipeline by
<code>%>%</code>. In base R, you’ll typically save intermediate
results to a variable that you either discard, or repeatedly
overwrite.</p></li>
<li><p>All dplyr verbs handle “grouped” data frames so that the code to
perform a computation per-group looks very similar to code that works on
a whole data frame. In base R, per-group operations tend to have varied
forms.</p></li>
</ol>
</div>
<div id="one-table-verbs" class="section level1">
<h1>One table verbs</h1>
<p>The following table shows a condensed translation between dplyr verbs
and their base R equivalents. The following sections describe each
operation in more detail. You’ll learn more about the dplyr verbs in
their documentation and in <code>vignette("dplyr")</code>.</p>
<table>
<colgroup>
<col width="38%" />
<col width="61%" />
</colgroup>
<thead>
<tr class="header">
<th>dplyr</th>
<th>base</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td><code>arrange(df, x)</code></td>
<td><code>df[order(x), , drop = FALSE]</code></td>
</tr>
<tr class="even">
<td><code>distinct(df, x)</code></td>
<td><code>df[!duplicated(x), , drop = FALSE]</code>,
<code>unique()</code></td>
</tr>
<tr class="odd">
<td><code>filter(df, x)</code></td>
<td><code>df[which(x), , drop = FALSE]</code>,
<code>subset()</code></td>
</tr>
<tr class="even">
<td><code>mutate(df, z = x + y)</code></td>
<td><code>df$z <- df$x + df$y</code>, <code>transform()</code></td>
</tr>
<tr class="odd">
<td><code>pull(df, 1)</code></td>
<td><code>df[[1]]</code></td>
</tr>
<tr class="even">
<td><code>pull(df, x)</code></td>
<td><code>df$x</code></td>
</tr>
<tr class="odd">
<td><code>rename(df, y = x)</code></td>
<td><code>names(df)[names(df) == "x"] <- "y"</code></td>
</tr>
<tr class="even">
<td><code>relocate(df, y)</code></td>
<td><code>df[union("y", names(df))]</code></td>
</tr>
<tr class="odd">
<td><code>select(df, x, y)</code></td>
<td><code>df[c("x", "y")]</code>, <code>subset()</code></td>
</tr>
<tr class="even">
<td><code>select(df, starts_with("x"))</code></td>
<td><code>df[grepl("^x", names(df))]</code></td>
</tr>
<tr class="odd">
<td><code>summarise(df, mean(x))</code></td>
<td><code>mean(df$x)</code>, <code>tapply()</code>,
<code>aggregate()</code>, <code>by()</code></td>
</tr>
<tr class="even">
<td><code>slice(df, c(1, 2, 5))</code></td>
<td><code>df[c(1, 2, 5), , drop = FALSE]</code></td>
</tr>
</tbody>
</table>
<p>To begin, we’ll load dplyr and convert <code>mtcars</code> and
<code>iris</code> to tibbles so that we can easily show only abbreviated
output for each operation.</p>
<div class="sourceCode" id="cb1"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb1-1"><a href="#cb1-1" tabindex="-1"></a><span class="fu">library</span>(dplyr)</span>
<span id="cb1-2"><a href="#cb1-2" tabindex="-1"></a>mtcars <span class="ot"><-</span> <span class="fu">as_tibble</span>(mtcars)</span>
<span id="cb1-3"><a href="#cb1-3" tabindex="-1"></a>iris <span class="ot"><-</span> <span class="fu">as_tibble</span>(iris)</span></code></pre></div>
<div id="arrange-arrange-rows-by-variables" class="section level2">
<h2><code>arrange()</code>: Arrange rows by variables</h2>
<p><code>dplyr::arrange()</code> orders the rows of a data frame by the
values of one or more columns:</p>
<div class="sourceCode" id="cb2"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb2-1"><a href="#cb2-1" tabindex="-1"></a>mtcars <span class="sc">%>%</span> <span class="fu">arrange</span>(cyl, disp)</span>
<span id="cb2-2"><a href="#cb2-2" tabindex="-1"></a><span class="co">#> # A tibble: 32 × 11</span></span>
<span id="cb2-3"><a href="#cb2-3" tabindex="-1"></a><span class="co">#> mpg cyl disp hp drat wt qsec vs am gear carb</span></span>
<span id="cb2-4"><a href="#cb2-4" tabindex="-1"></a><span class="co">#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl></span></span>
<span id="cb2-5"><a href="#cb2-5" tabindex="-1"></a><span class="co">#> 1 33.9 4 71.1 65 4.22 1.84 19.9 1 1 4 1</span></span>
<span id="cb2-6"><a href="#cb2-6" tabindex="-1"></a><span class="co">#> 2 30.4 4 75.7 52 4.93 1.62 18.5 1 1 4 2</span></span>
<span id="cb2-7"><a href="#cb2-7" tabindex="-1"></a><span class="co">#> 3 32.4 4 78.7 66 4.08 2.2 19.5 1 1 4 1</span></span>
<span id="cb2-8"><a href="#cb2-8" tabindex="-1"></a><span class="co">#> 4 27.3 4 79 66 4.08 1.94 18.9 1 1 4 1</span></span>
<span id="cb2-9"><a href="#cb2-9" tabindex="-1"></a><span class="co">#> # ℹ 28 more rows</span></span></code></pre></div>
<p>The <code>desc()</code> helper allows you to order selected variables
in descending order:</p>
<div class="sourceCode" id="cb3"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb3-1"><a href="#cb3-1" tabindex="-1"></a>mtcars <span class="sc">%>%</span> <span class="fu">arrange</span>(<span class="fu">desc</span>(cyl), <span class="fu">desc</span>(disp))</span>
<span id="cb3-2"><a href="#cb3-2" tabindex="-1"></a><span class="co">#> # A tibble: 32 × 11</span></span>
<span id="cb3-3"><a href="#cb3-3" tabindex="-1"></a><span class="co">#> mpg cyl disp hp drat wt qsec vs am gear carb</span></span>
<span id="cb3-4"><a href="#cb3-4" tabindex="-1"></a><span class="co">#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl></span></span>
<span id="cb3-5"><a href="#cb3-5" tabindex="-1"></a><span class="co">#> 1 10.4 8 472 205 2.93 5.25 18.0 0 0 3 4</span></span>
<span id="cb3-6"><a href="#cb3-6" tabindex="-1"></a><span class="co">#> 2 10.4 8 460 215 3 5.42 17.8 0 0 3 4</span></span>
<span id="cb3-7"><a href="#cb3-7" tabindex="-1"></a><span class="co">#> 3 14.7 8 440 230 3.23 5.34 17.4 0 0 3 4</span></span>
<span id="cb3-8"><a href="#cb3-8" tabindex="-1"></a><span class="co">#> 4 19.2 8 400 175 3.08 3.84 17.0 0 0 3 2</span></span>
<span id="cb3-9"><a href="#cb3-9" tabindex="-1"></a><span class="co">#> # ℹ 28 more rows</span></span></code></pre></div>
<p>We can replicate in base R by using <code>[</code> with
<code>order()</code>:</p>
<div class="sourceCode" id="cb4"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb4-1"><a href="#cb4-1" tabindex="-1"></a>mtcars[<span class="fu">order</span>(mtcars<span class="sc">$</span>cyl, mtcars<span class="sc">$</span>disp), , drop <span class="ot">=</span> <span class="cn">FALSE</span>]</span>
<span id="cb4-2"><a href="#cb4-2" tabindex="-1"></a><span class="co">#> # A tibble: 32 × 11</span></span>
<span id="cb4-3"><a href="#cb4-3" tabindex="-1"></a><span class="co">#> mpg cyl disp hp drat wt qsec vs am gear carb</span></span>
<span id="cb4-4"><a href="#cb4-4" tabindex="-1"></a><span class="co">#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl></span></span>
<span id="cb4-5"><a href="#cb4-5" tabindex="-1"></a><span class="co">#> 1 33.9 4 71.1 65 4.22 1.84 19.9 1 1 4 1</span></span>
<span id="cb4-6"><a href="#cb4-6" tabindex="-1"></a><span class="co">#> 2 30.4 4 75.7 52 4.93 1.62 18.5 1 1 4 2</span></span>
<span id="cb4-7"><a href="#cb4-7" tabindex="-1"></a><span class="co">#> 3 32.4 4 78.7 66 4.08 2.2 19.5 1 1 4 1</span></span>
<span id="cb4-8"><a href="#cb4-8" tabindex="-1"></a><span class="co">#> 4 27.3 4 79 66 4.08 1.94 18.9 1 1 4 1</span></span>
<span id="cb4-9"><a href="#cb4-9" tabindex="-1"></a><span class="co">#> # ℹ 28 more rows</span></span></code></pre></div>
<p>Note the use of <code>drop = FALSE</code>. If you forget this, and
the input is a data frame with a single column, the output will be a
vector, not a data frame. This is a source of subtle bugs.</p>
<p>Base R does not provide a convenient and general way to sort
individual variables in descending order, so you have two options:</p>
<ul>
<li>For numeric variables, you can use <code>-x</code>.</li>
<li>You can request <code>order()</code> to sort all variables in
descending order.</li>
</ul>
<div class="sourceCode" id="cb5"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb5-1"><a href="#cb5-1" tabindex="-1"></a>mtcars[<span class="fu">order</span>(mtcars<span class="sc">$</span>cyl, mtcars<span class="sc">$</span>disp, <span class="at">decreasing =</span> <span class="cn">TRUE</span>), , drop <span class="ot">=</span> <span class="cn">FALSE</span>]</span>
<span id="cb5-2"><a href="#cb5-2" tabindex="-1"></a>mtcars[<span class="fu">order</span>(<span class="sc">-</span>mtcars<span class="sc">$</span>cyl, <span class="sc">-</span>mtcars<span class="sc">$</span>disp), , drop <span class="ot">=</span> <span class="cn">FALSE</span>]</span></code></pre></div>
</div>
<div id="distinct-select-distinctunique-rows" class="section level2">
<h2><code>distinct()</code>: Select distinct/unique rows</h2>
<p><code>dplyr::distinct()</code> selects unique rows:</p>
<div class="sourceCode" id="cb6"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb6-1"><a href="#cb6-1" tabindex="-1"></a>df <span class="ot"><-</span> <span class="fu">tibble</span>(</span>
<span id="cb6-2"><a href="#cb6-2" tabindex="-1"></a> <span class="at">x =</span> <span class="fu">sample</span>(<span class="dv">10</span>, <span class="dv">100</span>, <span class="at">rep =</span> <span class="cn">TRUE</span>),</span>
<span id="cb6-3"><a href="#cb6-3" tabindex="-1"></a> <span class="at">y =</span> <span class="fu">sample</span>(<span class="dv">10</span>, <span class="dv">100</span>, <span class="at">rep =</span> <span class="cn">TRUE</span>)</span>
<span id="cb6-4"><a href="#cb6-4" tabindex="-1"></a>)</span>
<span id="cb6-5"><a href="#cb6-5" tabindex="-1"></a></span>
<span id="cb6-6"><a href="#cb6-6" tabindex="-1"></a>df <span class="sc">%>%</span> <span class="fu">distinct</span>(x) <span class="co"># selected columns</span></span>
<span id="cb6-7"><a href="#cb6-7" tabindex="-1"></a><span class="co">#> # A tibble: 10 × 1</span></span>
<span id="cb6-8"><a href="#cb6-8" tabindex="-1"></a><span class="co">#> x</span></span>
<span id="cb6-9"><a href="#cb6-9" tabindex="-1"></a><span class="co">#> <int></span></span>
<span id="cb6-10"><a href="#cb6-10" tabindex="-1"></a><span class="co">#> 1 3</span></span>
<span id="cb6-11"><a href="#cb6-11" tabindex="-1"></a><span class="co">#> 2 5</span></span>
<span id="cb6-12"><a href="#cb6-12" tabindex="-1"></a><span class="co">#> 3 4</span></span>
<span id="cb6-13"><a href="#cb6-13" tabindex="-1"></a><span class="co">#> 4 7</span></span>
<span id="cb6-14"><a href="#cb6-14" tabindex="-1"></a><span class="co">#> # ℹ 6 more rows</span></span>
<span id="cb6-15"><a href="#cb6-15" tabindex="-1"></a>df <span class="sc">%>%</span> <span class="fu">distinct</span>(x, <span class="at">.keep_all =</span> <span class="cn">TRUE</span>) <span class="co"># whole data frame</span></span>
<span id="cb6-16"><a href="#cb6-16" tabindex="-1"></a><span class="co">#> # A tibble: 10 × 2</span></span>
<span id="cb6-17"><a href="#cb6-17" tabindex="-1"></a><span class="co">#> x y</span></span>
<span id="cb6-18"><a href="#cb6-18" tabindex="-1"></a><span class="co">#> <int> <int></span></span>
<span id="cb6-19"><a href="#cb6-19" tabindex="-1"></a><span class="co">#> 1 3 6</span></span>
<span id="cb6-20"><a href="#cb6-20" tabindex="-1"></a><span class="co">#> 2 5 2</span></span>
<span id="cb6-21"><a href="#cb6-21" tabindex="-1"></a><span class="co">#> 3 4 1</span></span>
<span id="cb6-22"><a href="#cb6-22" tabindex="-1"></a><span class="co">#> 4 7 1</span></span>
<span id="cb6-23"><a href="#cb6-23" tabindex="-1"></a><span class="co">#> # ℹ 6 more rows</span></span></code></pre></div>
<p>There are two equivalents in base R, depending on whether you want
the whole data frame, or just selected variables:</p>
<div class="sourceCode" id="cb7"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb7-1"><a href="#cb7-1" tabindex="-1"></a><span class="fu">unique</span>(df[<span class="st">"x"</span>]) <span class="co"># selected columns</span></span>
<span id="cb7-2"><a href="#cb7-2" tabindex="-1"></a><span class="co">#> # A tibble: 10 × 1</span></span>
<span id="cb7-3"><a href="#cb7-3" tabindex="-1"></a><span class="co">#> x</span></span>
<span id="cb7-4"><a href="#cb7-4" tabindex="-1"></a><span class="co">#> <int></span></span>
<span id="cb7-5"><a href="#cb7-5" tabindex="-1"></a><span class="co">#> 1 3</span></span>
<span id="cb7-6"><a href="#cb7-6" tabindex="-1"></a><span class="co">#> 2 5</span></span>
<span id="cb7-7"><a href="#cb7-7" tabindex="-1"></a><span class="co">#> 3 4</span></span>
<span id="cb7-8"><a href="#cb7-8" tabindex="-1"></a><span class="co">#> 4 7</span></span>
<span id="cb7-9"><a href="#cb7-9" tabindex="-1"></a><span class="co">#> # ℹ 6 more rows</span></span>
<span id="cb7-10"><a href="#cb7-10" tabindex="-1"></a>df[<span class="sc">!</span><span class="fu">duplicated</span>(df<span class="sc">$</span>x), , drop <span class="ot">=</span> <span class="cn">FALSE</span>] <span class="co"># whole data frame</span></span>
<span id="cb7-11"><a href="#cb7-11" tabindex="-1"></a><span class="co">#> # A tibble: 10 × 2</span></span>
<span id="cb7-12"><a href="#cb7-12" tabindex="-1"></a><span class="co">#> x y</span></span>
<span id="cb7-13"><a href="#cb7-13" tabindex="-1"></a><span class="co">#> <int> <int></span></span>
<span id="cb7-14"><a href="#cb7-14" tabindex="-1"></a><span class="co">#> 1 3 6</span></span>
<span id="cb7-15"><a href="#cb7-15" tabindex="-1"></a><span class="co">#> 2 5 2</span></span>
<span id="cb7-16"><a href="#cb7-16" tabindex="-1"></a><span class="co">#> 3 4 1</span></span>
<span id="cb7-17"><a href="#cb7-17" tabindex="-1"></a><span class="co">#> 4 7 1</span></span>
<span id="cb7-18"><a href="#cb7-18" tabindex="-1"></a><span class="co">#> # ℹ 6 more rows</span></span></code></pre></div>
</div>
<div id="filter-return-rows-with-matching-conditions" class="section level2">
<h2><code>filter()</code>: Return rows with matching conditions</h2>
<p><code>dplyr::filter()</code> selects rows where an expression is
<code>TRUE</code>:</p>
<div class="sourceCode" id="cb8"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb8-1"><a href="#cb8-1" tabindex="-1"></a>starwars <span class="sc">%>%</span> <span class="fu">filter</span>(species <span class="sc">==</span> <span class="st">"Human"</span>)</span>
<span id="cb8-2"><a href="#cb8-2" tabindex="-1"></a><span class="co">#> # A tibble: 35 × 14</span></span>
<span id="cb8-3"><a href="#cb8-3" tabindex="-1"></a><span class="co">#> name height mass hair_color skin_color eye_color birth_year sex gender</span></span>
<span id="cb8-4"><a href="#cb8-4" tabindex="-1"></a><span class="co">#> <chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr> </span></span>
<span id="cb8-5"><a href="#cb8-5" tabindex="-1"></a><span class="co">#> 1 Luke Sky… 172 77 blond fair blue 19 male mascu…</span></span>
<span id="cb8-6"><a href="#cb8-6" tabindex="-1"></a><span class="co">#> 2 Darth Va… 202 136 none white yellow 41.9 male mascu…</span></span>
<span id="cb8-7"><a href="#cb8-7" tabindex="-1"></a><span class="co">#> 3 Leia Org… 150 49 brown light brown 19 fema… femin…</span></span>
<span id="cb8-8"><a href="#cb8-8" tabindex="-1"></a><span class="co">#> 4 Owen Lars 178 120 brown, gr… light blue 52 male mascu…</span></span>
<span id="cb8-9"><a href="#cb8-9" tabindex="-1"></a><span class="co">#> # ℹ 31 more rows</span></span>
<span id="cb8-10"><a href="#cb8-10" tabindex="-1"></a><span class="co">#> # ℹ 5 more variables: homeworld <chr>, species <chr>, films <list>,</span></span>
<span id="cb8-11"><a href="#cb8-11" tabindex="-1"></a><span class="co">#> # vehicles <list>, starships <list></span></span>
<span id="cb8-12"><a href="#cb8-12" tabindex="-1"></a>starwars <span class="sc">%>%</span> <span class="fu">filter</span>(mass <span class="sc">></span> <span class="dv">1000</span>)</span>
<span id="cb8-13"><a href="#cb8-13" tabindex="-1"></a><span class="co">#> # A tibble: 1 × 14</span></span>
<span id="cb8-14"><a href="#cb8-14" tabindex="-1"></a><span class="co">#> name height mass hair_color skin_color eye_color birth_year sex gender</span></span>
<span id="cb8-15"><a href="#cb8-15" tabindex="-1"></a><span class="co">#> <chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr> </span></span>
<span id="cb8-16"><a href="#cb8-16" tabindex="-1"></a><span class="co">#> 1 Jabba De… 175 1358 <NA> green-tan… orange 600 herm… mascu…</span></span>
<span id="cb8-17"><a href="#cb8-17" tabindex="-1"></a><span class="co">#> # ℹ 5 more variables: homeworld <chr>, species <chr>, films <list>,</span></span>
<span id="cb8-18"><a href="#cb8-18" tabindex="-1"></a><span class="co">#> # vehicles <list>, starships <list></span></span>
<span id="cb8-19"><a href="#cb8-19" tabindex="-1"></a>starwars <span class="sc">%>%</span> <span class="fu">filter</span>(hair_color <span class="sc">==</span> <span class="st">"none"</span> <span class="sc">&</span> eye_color <span class="sc">==</span> <span class="st">"black"</span>)</span>
<span id="cb8-20"><a href="#cb8-20" tabindex="-1"></a><span class="co">#> # A tibble: 9 × 14</span></span>
<span id="cb8-21"><a href="#cb8-21" tabindex="-1"></a><span class="co">#> name height mass hair_color skin_color eye_color birth_year sex gender</span></span>
<span id="cb8-22"><a href="#cb8-22" tabindex="-1"></a><span class="co">#> <chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr> </span></span>
<span id="cb8-23"><a href="#cb8-23" tabindex="-1"></a><span class="co">#> 1 Nien Nunb 160 68 none grey black NA male mascu…</span></span>
<span id="cb8-24"><a href="#cb8-24" tabindex="-1"></a><span class="co">#> 2 Gasgano 122 NA none white, bl… black NA male mascu…</span></span>
<span id="cb8-25"><a href="#cb8-25" tabindex="-1"></a><span class="co">#> 3 Kit Fisto 196 87 none green black NA male mascu…</span></span>
<span id="cb8-26"><a href="#cb8-26" tabindex="-1"></a><span class="co">#> 4 Plo Koon 188 80 none orange black 22 male mascu…</span></span>
<span id="cb8-27"><a href="#cb8-27" tabindex="-1"></a><span class="co">#> # ℹ 5 more rows</span></span>
<span id="cb8-28"><a href="#cb8-28" tabindex="-1"></a><span class="co">#> # ℹ 5 more variables: homeworld <chr>, species <chr>, films <list>,</span></span>
<span id="cb8-29"><a href="#cb8-29" tabindex="-1"></a><span class="co">#> # vehicles <list>, starships <list></span></span></code></pre></div>
<p>The closest base equivalent (and the inspiration for
<code>filter()</code>) is <code>subset()</code>:</p>
<div class="sourceCode" id="cb9"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb9-1"><a href="#cb9-1" tabindex="-1"></a><span class="fu">subset</span>(starwars, species <span class="sc">==</span> <span class="st">"Human"</span>)</span>
<span id="cb9-2"><a href="#cb9-2" tabindex="-1"></a><span class="co">#> # A tibble: 35 × 14</span></span>
<span id="cb9-3"><a href="#cb9-3" tabindex="-1"></a><span class="co">#> name height mass hair_color skin_color eye_color birth_year sex gender</span></span>
<span id="cb9-4"><a href="#cb9-4" tabindex="-1"></a><span class="co">#> <chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr> </span></span>
<span id="cb9-5"><a href="#cb9-5" tabindex="-1"></a><span class="co">#> 1 Luke Sky… 172 77 blond fair blue 19 male mascu…</span></span>
<span id="cb9-6"><a href="#cb9-6" tabindex="-1"></a><span class="co">#> 2 Darth Va… 202 136 none white yellow 41.9 male mascu…</span></span>
<span id="cb9-7"><a href="#cb9-7" tabindex="-1"></a><span class="co">#> 3 Leia Org… 150 49 brown light brown 19 fema… femin…</span></span>
<span id="cb9-8"><a href="#cb9-8" tabindex="-1"></a><span class="co">#> 4 Owen Lars 178 120 brown, gr… light blue 52 male mascu…</span></span>
<span id="cb9-9"><a href="#cb9-9" tabindex="-1"></a><span class="co">#> # ℹ 31 more rows</span></span>
<span id="cb9-10"><a href="#cb9-10" tabindex="-1"></a><span class="co">#> # ℹ 5 more variables: homeworld <chr>, species <chr>, films <list>,</span></span>
<span id="cb9-11"><a href="#cb9-11" tabindex="-1"></a><span class="co">#> # vehicles <list>, starships <list></span></span>
<span id="cb9-12"><a href="#cb9-12" tabindex="-1"></a><span class="fu">subset</span>(starwars, mass <span class="sc">></span> <span class="dv">1000</span>)</span>
<span id="cb9-13"><a href="#cb9-13" tabindex="-1"></a><span class="co">#> # A tibble: 1 × 14</span></span>
<span id="cb9-14"><a href="#cb9-14" tabindex="-1"></a><span class="co">#> name height mass hair_color skin_color eye_color birth_year sex gender</span></span>
<span id="cb9-15"><a href="#cb9-15" tabindex="-1"></a><span class="co">#> <chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr> </span></span>
<span id="cb9-16"><a href="#cb9-16" tabindex="-1"></a><span class="co">#> 1 Jabba De… 175 1358 <NA> green-tan… orange 600 herm… mascu…</span></span>
<span id="cb9-17"><a href="#cb9-17" tabindex="-1"></a><span class="co">#> # ℹ 5 more variables: homeworld <chr>, species <chr>, films <list>,</span></span>
<span id="cb9-18"><a href="#cb9-18" tabindex="-1"></a><span class="co">#> # vehicles <list>, starships <list></span></span>
<span id="cb9-19"><a href="#cb9-19" tabindex="-1"></a><span class="fu">subset</span>(starwars, hair_color <span class="sc">==</span> <span class="st">"none"</span> <span class="sc">&</span> eye_color <span class="sc">==</span> <span class="st">"black"</span>)</span>
<span id="cb9-20"><a href="#cb9-20" tabindex="-1"></a><span class="co">#> # A tibble: 9 × 14</span></span>
<span id="cb9-21"><a href="#cb9-21" tabindex="-1"></a><span class="co">#> name height mass hair_color skin_color eye_color birth_year sex gender</span></span>
<span id="cb9-22"><a href="#cb9-22" tabindex="-1"></a><span class="co">#> <chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr> </span></span>
<span id="cb9-23"><a href="#cb9-23" tabindex="-1"></a><span class="co">#> 1 Nien Nunb 160 68 none grey black NA male mascu…</span></span>
<span id="cb9-24"><a href="#cb9-24" tabindex="-1"></a><span class="co">#> 2 Gasgano 122 NA none white, bl… black NA male mascu…</span></span>
<span id="cb9-25"><a href="#cb9-25" tabindex="-1"></a><span class="co">#> 3 Kit Fisto 196 87 none green black NA male mascu…</span></span>
<span id="cb9-26"><a href="#cb9-26" tabindex="-1"></a><span class="co">#> 4 Plo Koon 188 80 none orange black 22 male mascu…</span></span>
<span id="cb9-27"><a href="#cb9-27" tabindex="-1"></a><span class="co">#> # ℹ 5 more rows</span></span>
<span id="cb9-28"><a href="#cb9-28" tabindex="-1"></a><span class="co">#> # ℹ 5 more variables: homeworld <chr>, species <chr>, films <list>,</span></span>
<span id="cb9-29"><a href="#cb9-29" tabindex="-1"></a><span class="co">#> # vehicles <list>, starships <list></span></span></code></pre></div>
<p>You can also use <code>[</code> but this also requires the use of
<code>which()</code> to remove <code>NA</code>s:</p>
<div class="sourceCode" id="cb10"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb10-1"><a href="#cb10-1" tabindex="-1"></a>starwars[<span class="fu">which</span>(starwars<span class="sc">$</span>species <span class="sc">==</span> <span class="st">"Human"</span>), , drop <span class="ot">=</span> <span class="cn">FALSE</span>]</span>
<span id="cb10-2"><a href="#cb10-2" tabindex="-1"></a><span class="co">#> # A tibble: 35 × 14</span></span>
<span id="cb10-3"><a href="#cb10-3" tabindex="-1"></a><span class="co">#> name height mass hair_color skin_color eye_color birth_year sex gender</span></span>
<span id="cb10-4"><a href="#cb10-4" tabindex="-1"></a><span class="co">#> <chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr> </span></span>
<span id="cb10-5"><a href="#cb10-5" tabindex="-1"></a><span class="co">#> 1 Luke Sky… 172 77 blond fair blue 19 male mascu…</span></span>
<span id="cb10-6"><a href="#cb10-6" tabindex="-1"></a><span class="co">#> 2 Darth Va… 202 136 none white yellow 41.9 male mascu…</span></span>
<span id="cb10-7"><a href="#cb10-7" tabindex="-1"></a><span class="co">#> 3 Leia Org… 150 49 brown light brown 19 fema… femin…</span></span>
<span id="cb10-8"><a href="#cb10-8" tabindex="-1"></a><span class="co">#> 4 Owen Lars 178 120 brown, gr… light blue 52 male mascu…</span></span>
<span id="cb10-9"><a href="#cb10-9" tabindex="-1"></a><span class="co">#> # ℹ 31 more rows</span></span>
<span id="cb10-10"><a href="#cb10-10" tabindex="-1"></a><span class="co">#> # ℹ 5 more variables: homeworld <chr>, species <chr>, films <list>,</span></span>
<span id="cb10-11"><a href="#cb10-11" tabindex="-1"></a><span class="co">#> # vehicles <list>, starships <list></span></span>
<span id="cb10-12"><a href="#cb10-12" tabindex="-1"></a>starwars[<span class="fu">which</span>(starwars<span class="sc">$</span>mass <span class="sc">></span> <span class="dv">1000</span>), , drop <span class="ot">=</span> <span class="cn">FALSE</span>]</span>
<span id="cb10-13"><a href="#cb10-13" tabindex="-1"></a><span class="co">#> # A tibble: 1 × 14</span></span>
<span id="cb10-14"><a href="#cb10-14" tabindex="-1"></a><span class="co">#> name height mass hair_color skin_color eye_color birth_year sex gender</span></span>
<span id="cb10-15"><a href="#cb10-15" tabindex="-1"></a><span class="co">#> <chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr> </span></span>
<span id="cb10-16"><a href="#cb10-16" tabindex="-1"></a><span class="co">#> 1 Jabba De… 175 1358 <NA> green-tan… orange 600 herm… mascu…</span></span>
<span id="cb10-17"><a href="#cb10-17" tabindex="-1"></a><span class="co">#> # ℹ 5 more variables: homeworld <chr>, species <chr>, films <list>,</span></span>
<span id="cb10-18"><a href="#cb10-18" tabindex="-1"></a><span class="co">#> # vehicles <list>, starships <list></span></span>
<span id="cb10-19"><a href="#cb10-19" tabindex="-1"></a>starwars[<span class="fu">which</span>(starwars<span class="sc">$</span>hair_color <span class="sc">==</span> <span class="st">"none"</span> <span class="sc">&</span> starwars<span class="sc">$</span>eye_color <span class="sc">==</span> <span class="st">"black"</span>), , drop <span class="ot">=</span> <span class="cn">FALSE</span>]</span>
<span id="cb10-20"><a href="#cb10-20" tabindex="-1"></a><span class="co">#> # A tibble: 9 × 14</span></span>
<span id="cb10-21"><a href="#cb10-21" tabindex="-1"></a><span class="co">#> name height mass hair_color skin_color eye_color birth_year sex gender</span></span>
<span id="cb10-22"><a href="#cb10-22" tabindex="-1"></a><span class="co">#> <chr> <int> <dbl> <chr> <chr> <chr> <dbl> <chr> <chr> </span></span>
<span id="cb10-23"><a href="#cb10-23" tabindex="-1"></a><span class="co">#> 1 Nien Nunb 160 68 none grey black NA male mascu…</span></span>
<span id="cb10-24"><a href="#cb10-24" tabindex="-1"></a><span class="co">#> 2 Gasgano 122 NA none white, bl… black NA male mascu…</span></span>
<span id="cb10-25"><a href="#cb10-25" tabindex="-1"></a><span class="co">#> 3 Kit Fisto 196 87 none green black NA male mascu…</span></span>
<span id="cb10-26"><a href="#cb10-26" tabindex="-1"></a><span class="co">#> 4 Plo Koon 188 80 none orange black 22 male mascu…</span></span>
<span id="cb10-27"><a href="#cb10-27" tabindex="-1"></a><span class="co">#> # ℹ 5 more rows</span></span>
<span id="cb10-28"><a href="#cb10-28" tabindex="-1"></a><span class="co">#> # ℹ 5 more variables: homeworld <chr>, species <chr>, films <list>,</span></span>
<span id="cb10-29"><a href="#cb10-29" tabindex="-1"></a><span class="co">#> # vehicles <list>, starships <list></span></span></code></pre></div>
</div>
<div id="mutate-create-or-transform-variables" class="section level2">
<h2><code>mutate()</code>: Create or transform variables</h2>
<p><code>dplyr::mutate()</code> creates new variables from existing
variables:</p>
<div class="sourceCode" id="cb11"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb11-1"><a href="#cb11-1" tabindex="-1"></a>df <span class="sc">%>%</span> <span class="fu">mutate</span>(<span class="at">z =</span> x <span class="sc">+</span> y, <span class="at">z2 =</span> z <span class="sc">^</span> <span class="dv">2</span>)</span>
<span id="cb11-2"><a href="#cb11-2" tabindex="-1"></a><span class="co">#> # A tibble: 100 × 4</span></span>
<span id="cb11-3"><a href="#cb11-3" tabindex="-1"></a><span class="co">#> x y z z2</span></span>
<span id="cb11-4"><a href="#cb11-4" tabindex="-1"></a><span class="co">#> <int> <int> <int> <dbl></span></span>
<span id="cb11-5"><a href="#cb11-5" tabindex="-1"></a><span class="co">#> 1 3 6 9 81</span></span>
<span id="cb11-6"><a href="#cb11-6" tabindex="-1"></a><span class="co">#> 2 5 2 7 49</span></span>
<span id="cb11-7"><a href="#cb11-7" tabindex="-1"></a><span class="co">#> 3 4 1 5 25</span></span>
<span id="cb11-8"><a href="#cb11-8" tabindex="-1"></a><span class="co">#> 4 7 1 8 64</span></span>
<span id="cb11-9"><a href="#cb11-9" tabindex="-1"></a><span class="co">#> # ℹ 96 more rows</span></span></code></pre></div>
<p>The closest base equivalent is <code>transform()</code>, but note
that it cannot use freshly created variables:</p>
<div class="sourceCode" id="cb12"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb12-1"><a href="#cb12-1" tabindex="-1"></a><span class="fu">head</span>(<span class="fu">transform</span>(df, <span class="at">z =</span> x <span class="sc">+</span> y, <span class="at">z2 =</span> (x <span class="sc">+</span> y) <span class="sc">^</span> <span class="dv">2</span>))</span>
<span id="cb12-2"><a href="#cb12-2" tabindex="-1"></a><span class="co">#> x y z z2</span></span>
<span id="cb12-3"><a href="#cb12-3" tabindex="-1"></a><span class="co">#> 1 3 6 9 81</span></span>
<span id="cb12-4"><a href="#cb12-4" tabindex="-1"></a><span class="co">#> 2 5 2 7 49</span></span>
<span id="cb12-5"><a href="#cb12-5" tabindex="-1"></a><span class="co">#> 3 4 1 5 25</span></span>
<span id="cb12-6"><a href="#cb12-6" tabindex="-1"></a><span class="co">#> 4 7 1 8 64</span></span>
<span id="cb12-7"><a href="#cb12-7" tabindex="-1"></a><span class="co">#> 5 10 7 17 289</span></span>
<span id="cb12-8"><a href="#cb12-8" tabindex="-1"></a><span class="co">#> 6 7 3 10 100</span></span></code></pre></div>
<p>Alternatively, you can use <code>$<-</code>:</p>
<div class="sourceCode" id="cb13"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb13-1"><a href="#cb13-1" tabindex="-1"></a>mtcars<span class="sc">$</span>cyl2 <span class="ot"><-</span> mtcars<span class="sc">$</span>cyl <span class="sc">*</span> <span class="dv">2</span></span>
<span id="cb13-2"><a href="#cb13-2" tabindex="-1"></a>mtcars<span class="sc">$</span>cyl4 <span class="ot"><-</span> mtcars<span class="sc">$</span>cyl2 <span class="sc">*</span> <span class="dv">2</span></span></code></pre></div>
<p>When applied to a grouped data frame, <code>dplyr::mutate()</code>
computes new variable once per group:</p>
<div class="sourceCode" id="cb14"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb14-1"><a href="#cb14-1" tabindex="-1"></a>gf <span class="ot"><-</span> <span class="fu">tibble</span>(<span class="at">g =</span> <span class="fu">c</span>(<span class="dv">1</span>, <span class="dv">1</span>, <span class="dv">2</span>, <span class="dv">2</span>), <span class="at">x =</span> <span class="fu">c</span>(<span class="fl">0.5</span>, <span class="fl">1.5</span>, <span class="fl">2.5</span>, <span class="fl">3.5</span>))</span>
<span id="cb14-2"><a href="#cb14-2" tabindex="-1"></a>gf <span class="sc">%>%</span> </span>
<span id="cb14-3"><a href="#cb14-3" tabindex="-1"></a> <span class="fu">group_by</span>(g) <span class="sc">%>%</span> </span>
<span id="cb14-4"><a href="#cb14-4" tabindex="-1"></a> <span class="fu">mutate</span>(<span class="at">x_mean =</span> <span class="fu">mean</span>(x), <span class="at">x_rank =</span> <span class="fu">rank</span>(x))</span>
<span id="cb14-5"><a href="#cb14-5" tabindex="-1"></a><span class="co">#> # A tibble: 4 × 4</span></span>
<span id="cb14-6"><a href="#cb14-6" tabindex="-1"></a><span class="co">#> # Groups: g [2]</span></span>
<span id="cb14-7"><a href="#cb14-7" tabindex="-1"></a><span class="co">#> g x x_mean x_rank</span></span>
<span id="cb14-8"><a href="#cb14-8" tabindex="-1"></a><span class="co">#> <dbl> <dbl> <dbl> <dbl></span></span>
<span id="cb14-9"><a href="#cb14-9" tabindex="-1"></a><span class="co">#> 1 1 0.5 1 1</span></span>
<span id="cb14-10"><a href="#cb14-10" tabindex="-1"></a><span class="co">#> 2 1 1.5 1 2</span></span>
<span id="cb14-11"><a href="#cb14-11" tabindex="-1"></a><span class="co">#> 3 2 2.5 3 1</span></span>
<span id="cb14-12"><a href="#cb14-12" tabindex="-1"></a><span class="co">#> 4 2 3.5 3 2</span></span></code></pre></div>
<p>To replicate this in base R, you can use <code>ave()</code>:</p>
<div class="sourceCode" id="cb15"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb15-1"><a href="#cb15-1" tabindex="-1"></a><span class="fu">transform</span>(gf, </span>
<span id="cb15-2"><a href="#cb15-2" tabindex="-1"></a> <span class="at">x_mean =</span> <span class="fu">ave</span>(x, g, <span class="at">FUN =</span> mean), </span>
<span id="cb15-3"><a href="#cb15-3" tabindex="-1"></a> <span class="at">x_rank =</span> <span class="fu">ave</span>(x, g, <span class="at">FUN =</span> rank)</span>
<span id="cb15-4"><a href="#cb15-4" tabindex="-1"></a>)</span>
<span id="cb15-5"><a href="#cb15-5" tabindex="-1"></a><span class="co">#> g x x_mean x_rank</span></span>
<span id="cb15-6"><a href="#cb15-6" tabindex="-1"></a><span class="co">#> 1 1 0.5 1 1</span></span>
<span id="cb15-7"><a href="#cb15-7" tabindex="-1"></a><span class="co">#> 2 1 1.5 1 2</span></span>
<span id="cb15-8"><a href="#cb15-8" tabindex="-1"></a><span class="co">#> 3 2 2.5 3 1</span></span>
<span id="cb15-9"><a href="#cb15-9" tabindex="-1"></a><span class="co">#> 4 2 3.5 3 2</span></span></code></pre></div>
</div>
<div id="pull-pull-out-a-single-variable" class="section level2">
<h2><code>pull()</code>: Pull out a single variable</h2>
<p><code>dplyr::pull()</code> extracts a variable either by name or
position:</p>
<div class="sourceCode" id="cb16"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb16-1"><a href="#cb16-1" tabindex="-1"></a>mtcars <span class="sc">%>%</span> <span class="fu">pull</span>(<span class="dv">1</span>)</span>
<span id="cb16-2"><a href="#cb16-2" tabindex="-1"></a><span class="co">#> [1] 21.0 21.0 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 17.8 16.4 17.3 15.2 10.4</span></span>
<span id="cb16-3"><a href="#cb16-3" tabindex="-1"></a><span class="co">#> [16] 10.4 14.7 32.4 30.4 33.9 21.5 15.5 15.2 13.3 19.2 27.3 26.0 30.4 15.8 19.7</span></span>
<span id="cb16-4"><a href="#cb16-4" tabindex="-1"></a><span class="co">#> [31] 15.0 21.4</span></span>
<span id="cb16-5"><a href="#cb16-5" tabindex="-1"></a>mtcars <span class="sc">%>%</span> <span class="fu">pull</span>(cyl)</span>
<span id="cb16-6"><a href="#cb16-6" tabindex="-1"></a><span class="co">#> [1] 6 6 4 6 8 6 8 4 4 6 6 8 8 8 8 8 8 4 4 4 4 8 8 8 8 4 4 4 8 6 8 4</span></span></code></pre></div>
<p>This equivalent to <code>[[</code> for positions and <code>$</code>
for names:</p>
<div class="sourceCode" id="cb17"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb17-1"><a href="#cb17-1" tabindex="-1"></a>mtcars[[<span class="dv">1</span>]]</span>
<span id="cb17-2"><a href="#cb17-2" tabindex="-1"></a><span class="co">#> [1] 21.0 21.0 22.8 21.4 18.7 18.1 14.3 24.4 22.8 19.2 17.8 16.4 17.3 15.2 10.4</span></span>
<span id="cb17-3"><a href="#cb17-3" tabindex="-1"></a><span class="co">#> [16] 10.4 14.7 32.4 30.4 33.9 21.5 15.5 15.2 13.3 19.2 27.3 26.0 30.4 15.8 19.7</span></span>
<span id="cb17-4"><a href="#cb17-4" tabindex="-1"></a><span class="co">#> [31] 15.0 21.4</span></span>
<span id="cb17-5"><a href="#cb17-5" tabindex="-1"></a>mtcars<span class="sc">$</span>cyl</span>
<span id="cb17-6"><a href="#cb17-6" tabindex="-1"></a><span class="co">#> [1] 6 6 4 6 8 6 8 4 4 6 6 8 8 8 8 8 8 4 4 4 4 8 8 8 8 4 4 4 8 6 8 4</span></span></code></pre></div>
</div>
<div id="relocate-change-column-order" class="section level2">
<h2><code>relocate()</code>: Change column order</h2>
<p><code>dplyr::relocate()</code> makes it easy to move a set of columns
to a new position (by default, the front):</p>
<div class="sourceCode" id="cb18"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb18-1"><a href="#cb18-1" tabindex="-1"></a><span class="co"># to front</span></span>
<span id="cb18-2"><a href="#cb18-2" tabindex="-1"></a>mtcars <span class="sc">%>%</span> <span class="fu">relocate</span>(gear, carb) </span>
<span id="cb18-3"><a href="#cb18-3" tabindex="-1"></a><span class="co">#> # A tibble: 32 × 13</span></span>
<span id="cb18-4"><a href="#cb18-4" tabindex="-1"></a><span class="co">#> gear carb mpg cyl disp hp drat wt qsec vs am cyl2 cyl4</span></span>
<span id="cb18-5"><a href="#cb18-5" tabindex="-1"></a><span class="co">#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl></span></span>
<span id="cb18-6"><a href="#cb18-6" tabindex="-1"></a><span class="co">#> 1 4 4 21 6 160 110 3.9 2.62 16.5 0 1 12 24</span></span>
<span id="cb18-7"><a href="#cb18-7" tabindex="-1"></a><span class="co">#> 2 4 4 21 6 160 110 3.9 2.88 17.0 0 1 12 24</span></span>
<span id="cb18-8"><a href="#cb18-8" tabindex="-1"></a><span class="co">#> 3 4 1 22.8 4 108 93 3.85 2.32 18.6 1 1 8 16</span></span>
<span id="cb18-9"><a href="#cb18-9" tabindex="-1"></a><span class="co">#> 4 3 1 21.4 6 258 110 3.08 3.22 19.4 1 0 12 24</span></span>
<span id="cb18-10"><a href="#cb18-10" tabindex="-1"></a><span class="co">#> # ℹ 28 more rows</span></span>
<span id="cb18-11"><a href="#cb18-11" tabindex="-1"></a></span>
<span id="cb18-12"><a href="#cb18-12" tabindex="-1"></a><span class="co"># to back</span></span>
<span id="cb18-13"><a href="#cb18-13" tabindex="-1"></a>mtcars <span class="sc">%>%</span> <span class="fu">relocate</span>(mpg, cyl, <span class="at">.after =</span> <span class="fu">last_col</span>()) </span>
<span id="cb18-14"><a href="#cb18-14" tabindex="-1"></a><span class="co">#> # A tibble: 32 × 13</span></span>
<span id="cb18-15"><a href="#cb18-15" tabindex="-1"></a><span class="co">#> disp hp drat wt qsec vs am gear carb cyl2 cyl4 mpg cyl</span></span>
<span id="cb18-16"><a href="#cb18-16" tabindex="-1"></a><span class="co">#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl></span></span>
<span id="cb18-17"><a href="#cb18-17" tabindex="-1"></a><span class="co">#> 1 160 110 3.9 2.62 16.5 0 1 4 4 12 24 21 6</span></span>
<span id="cb18-18"><a href="#cb18-18" tabindex="-1"></a><span class="co">#> 2 160 110 3.9 2.88 17.0 0 1 4 4 12 24 21 6</span></span>
<span id="cb18-19"><a href="#cb18-19" tabindex="-1"></a><span class="co">#> 3 108 93 3.85 2.32 18.6 1 1 4 1 8 16 22.8 4</span></span>
<span id="cb18-20"><a href="#cb18-20" tabindex="-1"></a><span class="co">#> 4 258 110 3.08 3.22 19.4 1 0 3 1 12 24 21.4 6</span></span>
<span id="cb18-21"><a href="#cb18-21" tabindex="-1"></a><span class="co">#> # ℹ 28 more rows</span></span></code></pre></div>
<p>We can replicate this in base R with a little set manipulation:</p>
<div class="sourceCode" id="cb19"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb19-1"><a href="#cb19-1" tabindex="-1"></a>mtcars[<span class="fu">union</span>(<span class="fu">c</span>(<span class="st">"gear"</span>, <span class="st">"carb"</span>), <span class="fu">names</span>(mtcars))]</span>
<span id="cb19-2"><a href="#cb19-2" tabindex="-1"></a><span class="co">#> # A tibble: 32 × 13</span></span>
<span id="cb19-3"><a href="#cb19-3" tabindex="-1"></a><span class="co">#> gear carb mpg cyl disp hp drat wt qsec vs am cyl2 cyl4</span></span>
<span id="cb19-4"><a href="#cb19-4" tabindex="-1"></a><span class="co">#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl></span></span>
<span id="cb19-5"><a href="#cb19-5" tabindex="-1"></a><span class="co">#> 1 4 4 21 6 160 110 3.9 2.62 16.5 0 1 12 24</span></span>
<span id="cb19-6"><a href="#cb19-6" tabindex="-1"></a><span class="co">#> 2 4 4 21 6 160 110 3.9 2.88 17.0 0 1 12 24</span></span>
<span id="cb19-7"><a href="#cb19-7" tabindex="-1"></a><span class="co">#> 3 4 1 22.8 4 108 93 3.85 2.32 18.6 1 1 8 16</span></span>
<span id="cb19-8"><a href="#cb19-8" tabindex="-1"></a><span class="co">#> 4 3 1 21.4 6 258 110 3.08 3.22 19.4 1 0 12 24</span></span>
<span id="cb19-9"><a href="#cb19-9" tabindex="-1"></a><span class="co">#> # ℹ 28 more rows</span></span>
<span id="cb19-10"><a href="#cb19-10" tabindex="-1"></a></span>
<span id="cb19-11"><a href="#cb19-11" tabindex="-1"></a>to_back <span class="ot"><-</span> <span class="fu">c</span>(<span class="st">"mpg"</span>, <span class="st">"cyl"</span>)</span>
<span id="cb19-12"><a href="#cb19-12" tabindex="-1"></a>mtcars[<span class="fu">c</span>(<span class="fu">setdiff</span>(<span class="fu">names</span>(mtcars), to_back), to_back)]</span>
<span id="cb19-13"><a href="#cb19-13" tabindex="-1"></a><span class="co">#> # A tibble: 32 × 13</span></span>
<span id="cb19-14"><a href="#cb19-14" tabindex="-1"></a><span class="co">#> disp hp drat wt qsec vs am gear carb cyl2 cyl4 mpg cyl</span></span>
<span id="cb19-15"><a href="#cb19-15" tabindex="-1"></a><span class="co">#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl></span></span>
<span id="cb19-16"><a href="#cb19-16" tabindex="-1"></a><span class="co">#> 1 160 110 3.9 2.62 16.5 0 1 4 4 12 24 21 6</span></span>
<span id="cb19-17"><a href="#cb19-17" tabindex="-1"></a><span class="co">#> 2 160 110 3.9 2.88 17.0 0 1 4 4 12 24 21 6</span></span>
<span id="cb19-18"><a href="#cb19-18" tabindex="-1"></a><span class="co">#> 3 108 93 3.85 2.32 18.6 1 1 4 1 8 16 22.8 4</span></span>
<span id="cb19-19"><a href="#cb19-19" tabindex="-1"></a><span class="co">#> 4 258 110 3.08 3.22 19.4 1 0 3 1 12 24 21.4 6</span></span>
<span id="cb19-20"><a href="#cb19-20" tabindex="-1"></a><span class="co">#> # ℹ 28 more rows</span></span></code></pre></div>
<p>Moving columns to somewhere in the middle requires a little more set
twiddling.</p>
</div>
<div id="rename-rename-variables-by-name" class="section level2">
<h2><code>rename()</code>: Rename variables by name</h2>
<p><code>dplyr::rename()</code> allows you to rename variables by name
or position:</p>
<div class="sourceCode" id="cb20"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb20-1"><a href="#cb20-1" tabindex="-1"></a>iris <span class="sc">%>%</span> <span class="fu">rename</span>(<span class="at">sepal_length =</span> Sepal.Length, <span class="at">sepal_width =</span> <span class="dv">2</span>)</span>
<span id="cb20-2"><a href="#cb20-2" tabindex="-1"></a><span class="co">#> # A tibble: 150 × 5</span></span>
<span id="cb20-3"><a href="#cb20-3" tabindex="-1"></a><span class="co">#> sepal_length sepal_width Petal.Length Petal.Width Species</span></span>
<span id="cb20-4"><a href="#cb20-4" tabindex="-1"></a><span class="co">#> <dbl> <dbl> <dbl> <dbl> <fct> </span></span>
<span id="cb20-5"><a href="#cb20-5" tabindex="-1"></a><span class="co">#> 1 5.1 3.5 1.4 0.2 setosa </span></span>
<span id="cb20-6"><a href="#cb20-6" tabindex="-1"></a><span class="co">#> 2 4.9 3 1.4 0.2 setosa </span></span>
<span id="cb20-7"><a href="#cb20-7" tabindex="-1"></a><span class="co">#> 3 4.7 3.2 1.3 0.2 setosa </span></span>
<span id="cb20-8"><a href="#cb20-8" tabindex="-1"></a><span class="co">#> 4 4.6 3.1 1.5 0.2 setosa </span></span>
<span id="cb20-9"><a href="#cb20-9" tabindex="-1"></a><span class="co">#> # ℹ 146 more rows</span></span></code></pre></div>
<p>Renaming variables by position is straight forward in base R:</p>
<div class="sourceCode" id="cb21"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb21-1"><a href="#cb21-1" tabindex="-1"></a>iris2 <span class="ot"><-</span> iris</span>
<span id="cb21-2"><a href="#cb21-2" tabindex="-1"></a><span class="fu">names</span>(iris2)[<span class="dv">2</span>] <span class="ot"><-</span> <span class="st">"sepal_width"</span></span></code></pre></div>
<p>Renaming variables by name requires a bit more work:</p>
<div class="sourceCode" id="cb22"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb22-1"><a href="#cb22-1" tabindex="-1"></a><span class="fu">names</span>(iris2)[<span class="fu">names</span>(iris2) <span class="sc">==</span> <span class="st">"Sepal.Length"</span>] <span class="ot"><-</span> <span class="st">"sepal_length"</span></span></code></pre></div>
</div>
<div id="rename_with-rename-variables-with-a-function" class="section level2">
<h2><code>rename_with()</code>: Rename variables with a function</h2>
<p><code>dplyr::rename_with()</code> transform column names with a
function:</p>
<div class="sourceCode" id="cb23"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb23-1"><a href="#cb23-1" tabindex="-1"></a>iris <span class="sc">%>%</span> <span class="fu">rename_with</span>(toupper)</span>
<span id="cb23-2"><a href="#cb23-2" tabindex="-1"></a><span class="co">#> # A tibble: 150 × 5</span></span>
<span id="cb23-3"><a href="#cb23-3" tabindex="-1"></a><span class="co">#> SEPAL.LENGTH SEPAL.WIDTH PETAL.LENGTH PETAL.WIDTH SPECIES</span></span>
<span id="cb23-4"><a href="#cb23-4" tabindex="-1"></a><span class="co">#> <dbl> <dbl> <dbl> <dbl> <fct> </span></span>
<span id="cb23-5"><a href="#cb23-5" tabindex="-1"></a><span class="co">#> 1 5.1 3.5 1.4 0.2 setosa </span></span>
<span id="cb23-6"><a href="#cb23-6" tabindex="-1"></a><span class="co">#> 2 4.9 3 1.4 0.2 setosa </span></span>
<span id="cb23-7"><a href="#cb23-7" tabindex="-1"></a><span class="co">#> 3 4.7 3.2 1.3 0.2 setosa </span></span>
<span id="cb23-8"><a href="#cb23-8" tabindex="-1"></a><span class="co">#> 4 4.6 3.1 1.5 0.2 setosa </span></span>
<span id="cb23-9"><a href="#cb23-9" tabindex="-1"></a><span class="co">#> # ℹ 146 more rows</span></span></code></pre></div>
<p>A similar effect can be achieved with <code>setNames()</code> in base
R:</p>
<div class="sourceCode" id="cb24"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb24-1"><a href="#cb24-1" tabindex="-1"></a><span class="fu">setNames</span>(iris, <span class="fu">toupper</span>(<span class="fu">names</span>(iris)))</span>
<span id="cb24-2"><a href="#cb24-2" tabindex="-1"></a><span class="co">#> # A tibble: 150 × 5</span></span>
<span id="cb24-3"><a href="#cb24-3" tabindex="-1"></a><span class="co">#> SEPAL.LENGTH SEPAL.WIDTH PETAL.LENGTH PETAL.WIDTH SPECIES</span></span>
<span id="cb24-4"><a href="#cb24-4" tabindex="-1"></a><span class="co">#> <dbl> <dbl> <dbl> <dbl> <fct> </span></span>
<span id="cb24-5"><a href="#cb24-5" tabindex="-1"></a><span class="co">#> 1 5.1 3.5 1.4 0.2 setosa </span></span>
<span id="cb24-6"><a href="#cb24-6" tabindex="-1"></a><span class="co">#> 2 4.9 3 1.4 0.2 setosa </span></span>
<span id="cb24-7"><a href="#cb24-7" tabindex="-1"></a><span class="co">#> 3 4.7 3.2 1.3 0.2 setosa </span></span>
<span id="cb24-8"><a href="#cb24-8" tabindex="-1"></a><span class="co">#> 4 4.6 3.1 1.5 0.2 setosa </span></span>
<span id="cb24-9"><a href="#cb24-9" tabindex="-1"></a><span class="co">#> # ℹ 146 more rows</span></span></code></pre></div>
</div>
<div id="select-select-variables-by-name" class="section level2">
<h2><code>select()</code>: Select variables by name</h2>
<p><code>dplyr::select()</code> subsets columns by position, name,
function of name, or other property:</p>
<div class="sourceCode" id="cb25"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb25-1"><a href="#cb25-1" tabindex="-1"></a>iris <span class="sc">%>%</span> <span class="fu">select</span>(<span class="dv">1</span><span class="sc">:</span><span class="dv">3</span>)</span>
<span id="cb25-2"><a href="#cb25-2" tabindex="-1"></a><span class="co">#> # A tibble: 150 × 3</span></span>
<span id="cb25-3"><a href="#cb25-3" tabindex="-1"></a><span class="co">#> Sepal.Length Sepal.Width Petal.Length</span></span>
<span id="cb25-4"><a href="#cb25-4" tabindex="-1"></a><span class="co">#> <dbl> <dbl> <dbl></span></span>
<span id="cb25-5"><a href="#cb25-5" tabindex="-1"></a><span class="co">#> 1 5.1 3.5 1.4</span></span>
<span id="cb25-6"><a href="#cb25-6" tabindex="-1"></a><span class="co">#> 2 4.9 3 1.4</span></span>
<span id="cb25-7"><a href="#cb25-7" tabindex="-1"></a><span class="co">#> 3 4.7 3.2 1.3</span></span>
<span id="cb25-8"><a href="#cb25-8" tabindex="-1"></a><span class="co">#> 4 4.6 3.1 1.5</span></span>
<span id="cb25-9"><a href="#cb25-9" tabindex="-1"></a><span class="co">#> # ℹ 146 more rows</span></span>
<span id="cb25-10"><a href="#cb25-10" tabindex="-1"></a>iris <span class="sc">%>%</span> <span class="fu">select</span>(Species, Sepal.Length)</span>
<span id="cb25-11"><a href="#cb25-11" tabindex="-1"></a><span class="co">#> # A tibble: 150 × 2</span></span>
<span id="cb25-12"><a href="#cb25-12" tabindex="-1"></a><span class="co">#> Species Sepal.Length</span></span>
<span id="cb25-13"><a href="#cb25-13" tabindex="-1"></a><span class="co">#> <fct> <dbl></span></span>
<span id="cb25-14"><a href="#cb25-14" tabindex="-1"></a><span class="co">#> 1 setosa 5.1</span></span>
<span id="cb25-15"><a href="#cb25-15" tabindex="-1"></a><span class="co">#> 2 setosa 4.9</span></span>
<span id="cb25-16"><a href="#cb25-16" tabindex="-1"></a><span class="co">#> 3 setosa 4.7</span></span>
<span id="cb25-17"><a href="#cb25-17" tabindex="-1"></a><span class="co">#> 4 setosa 4.6</span></span>
<span id="cb25-18"><a href="#cb25-18" tabindex="-1"></a><span class="co">#> # ℹ 146 more rows</span></span>
<span id="cb25-19"><a href="#cb25-19" tabindex="-1"></a>iris <span class="sc">%>%</span> <span class="fu">select</span>(<span class="fu">starts_with</span>(<span class="st">"Petal"</span>))</span>
<span id="cb25-20"><a href="#cb25-20" tabindex="-1"></a><span class="co">#> # A tibble: 150 × 2</span></span>
<span id="cb25-21"><a href="#cb25-21" tabindex="-1"></a><span class="co">#> Petal.Length Petal.Width</span></span>
<span id="cb25-22"><a href="#cb25-22" tabindex="-1"></a><span class="co">#> <dbl> <dbl></span></span>
<span id="cb25-23"><a href="#cb25-23" tabindex="-1"></a><span class="co">#> 1 1.4 0.2</span></span>
<span id="cb25-24"><a href="#cb25-24" tabindex="-1"></a><span class="co">#> 2 1.4 0.2</span></span>
<span id="cb25-25"><a href="#cb25-25" tabindex="-1"></a><span class="co">#> 3 1.3 0.2</span></span>
<span id="cb25-26"><a href="#cb25-26" tabindex="-1"></a><span class="co">#> 4 1.5 0.2</span></span>
<span id="cb25-27"><a href="#cb25-27" tabindex="-1"></a><span class="co">#> # ℹ 146 more rows</span></span>
<span id="cb25-28"><a href="#cb25-28" tabindex="-1"></a>iris <span class="sc">%>%</span> <span class="fu">select</span>(<span class="fu">where</span>(is.factor))</span>
<span id="cb25-29"><a href="#cb25-29" tabindex="-1"></a><span class="co">#> # A tibble: 150 × 1</span></span>
<span id="cb25-30"><a href="#cb25-30" tabindex="-1"></a><span class="co">#> Species</span></span>
<span id="cb25-31"><a href="#cb25-31" tabindex="-1"></a><span class="co">#> <fct> </span></span>
<span id="cb25-32"><a href="#cb25-32" tabindex="-1"></a><span class="co">#> 1 setosa </span></span>
<span id="cb25-33"><a href="#cb25-33" tabindex="-1"></a><span class="co">#> 2 setosa </span></span>
<span id="cb25-34"><a href="#cb25-34" tabindex="-1"></a><span class="co">#> 3 setosa </span></span>
<span id="cb25-35"><a href="#cb25-35" tabindex="-1"></a><span class="co">#> 4 setosa </span></span>
<span id="cb25-36"><a href="#cb25-36" tabindex="-1"></a><span class="co">#> # ℹ 146 more rows</span></span></code></pre></div>
<p>Subsetting variables by position is straightforward in base R:</p>
<div class="sourceCode" id="cb26"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb26-1"><a href="#cb26-1" tabindex="-1"></a>iris[<span class="dv">1</span><span class="sc">:</span><span class="dv">3</span>] <span class="co"># single argument selects columns; never drops</span></span>
<span id="cb26-2"><a href="#cb26-2" tabindex="-1"></a><span class="co">#> # A tibble: 150 × 3</span></span>
<span id="cb26-3"><a href="#cb26-3" tabindex="-1"></a><span class="co">#> Sepal.Length Sepal.Width Petal.Length</span></span>
<span id="cb26-4"><a href="#cb26-4" tabindex="-1"></a><span class="co">#> <dbl> <dbl> <dbl></span></span>
<span id="cb26-5"><a href="#cb26-5" tabindex="-1"></a><span class="co">#> 1 5.1 3.5 1.4</span></span>
<span id="cb26-6"><a href="#cb26-6" tabindex="-1"></a><span class="co">#> 2 4.9 3 1.4</span></span>
<span id="cb26-7"><a href="#cb26-7" tabindex="-1"></a><span class="co">#> 3 4.7 3.2 1.3</span></span>
<span id="cb26-8"><a href="#cb26-8" tabindex="-1"></a><span class="co">#> 4 4.6 3.1 1.5</span></span>
<span id="cb26-9"><a href="#cb26-9" tabindex="-1"></a><span class="co">#> # ℹ 146 more rows</span></span>
<span id="cb26-10"><a href="#cb26-10" tabindex="-1"></a>iris[<span class="dv">1</span><span class="sc">:</span><span class="dv">3</span>, , drop <span class="ot">=</span> <span class="cn">FALSE</span>]</span>
<span id="cb26-11"><a href="#cb26-11" tabindex="-1"></a><span class="co">#> # A tibble: 3 × 5</span></span>
<span id="cb26-12"><a href="#cb26-12" tabindex="-1"></a><span class="co">#> Sepal.Length Sepal.Width Petal.Length Petal.Width Species</span></span>
<span id="cb26-13"><a href="#cb26-13" tabindex="-1"></a><span class="co">#> <dbl> <dbl> <dbl> <dbl> <fct> </span></span>
<span id="cb26-14"><a href="#cb26-14" tabindex="-1"></a><span class="co">#> 1 5.1 3.5 1.4 0.2 setosa </span></span>
<span id="cb26-15"><a href="#cb26-15" tabindex="-1"></a><span class="co">#> 2 4.9 3 1.4 0.2 setosa </span></span>
<span id="cb26-16"><a href="#cb26-16" tabindex="-1"></a><span class="co">#> 3 4.7 3.2 1.3 0.2 setosa</span></span></code></pre></div>
<p>You have two options to subset by name:</p>
<div class="sourceCode" id="cb27"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb27-1"><a href="#cb27-1" tabindex="-1"></a>iris[<span class="fu">c</span>(<span class="st">"Species"</span>, <span class="st">"Sepal.Length"</span>)]</span>
<span id="cb27-2"><a href="#cb27-2" tabindex="-1"></a><span class="co">#> # A tibble: 150 × 2</span></span>
<span id="cb27-3"><a href="#cb27-3" tabindex="-1"></a><span class="co">#> Species Sepal.Length</span></span>
<span id="cb27-4"><a href="#cb27-4" tabindex="-1"></a><span class="co">#> <fct> <dbl></span></span>
<span id="cb27-5"><a href="#cb27-5" tabindex="-1"></a><span class="co">#> 1 setosa 5.1</span></span>
<span id="cb27-6"><a href="#cb27-6" tabindex="-1"></a><span class="co">#> 2 setosa 4.9</span></span>
<span id="cb27-7"><a href="#cb27-7" tabindex="-1"></a><span class="co">#> 3 setosa 4.7</span></span>
<span id="cb27-8"><a href="#cb27-8" tabindex="-1"></a><span class="co">#> 4 setosa 4.6</span></span>
<span id="cb27-9"><a href="#cb27-9" tabindex="-1"></a><span class="co">#> # ℹ 146 more rows</span></span>
<span id="cb27-10"><a href="#cb27-10" tabindex="-1"></a><span class="fu">subset</span>(iris, <span class="at">select =</span> <span class="fu">c</span>(Species, Sepal.Length))</span>
<span id="cb27-11"><a href="#cb27-11" tabindex="-1"></a><span class="co">#> # A tibble: 150 × 2</span></span>
<span id="cb27-12"><a href="#cb27-12" tabindex="-1"></a><span class="co">#> Species Sepal.Length</span></span>
<span id="cb27-13"><a href="#cb27-13" tabindex="-1"></a><span class="co">#> <fct> <dbl></span></span>
<span id="cb27-14"><a href="#cb27-14" tabindex="-1"></a><span class="co">#> 1 setosa 5.1</span></span>
<span id="cb27-15"><a href="#cb27-15" tabindex="-1"></a><span class="co">#> 2 setosa 4.9</span></span>
<span id="cb27-16"><a href="#cb27-16" tabindex="-1"></a><span class="co">#> 3 setosa 4.7</span></span>
<span id="cb27-17"><a href="#cb27-17" tabindex="-1"></a><span class="co">#> 4 setosa 4.6</span></span>
<span id="cb27-18"><a href="#cb27-18" tabindex="-1"></a><span class="co">#> # ℹ 146 more rows</span></span></code></pre></div>
<p>Subsetting by function of name requires a bit of work with
<code>grep()</code>:</p>
<div class="sourceCode" id="cb28"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb28-1"><a href="#cb28-1" tabindex="-1"></a>iris[<span class="fu">grep</span>(<span class="st">"^Petal"</span>, <span class="fu">names</span>(iris))]</span>
<span id="cb28-2"><a href="#cb28-2" tabindex="-1"></a><span class="co">#> # A tibble: 150 × 2</span></span>
<span id="cb28-3"><a href="#cb28-3" tabindex="-1"></a><span class="co">#> Petal.Length Petal.Width</span></span>
<span id="cb28-4"><a href="#cb28-4" tabindex="-1"></a><span class="co">#> <dbl> <dbl></span></span>
<span id="cb28-5"><a href="#cb28-5" tabindex="-1"></a><span class="co">#> 1 1.4 0.2</span></span>
<span id="cb28-6"><a href="#cb28-6" tabindex="-1"></a><span class="co">#> 2 1.4 0.2</span></span>
<span id="cb28-7"><a href="#cb28-7" tabindex="-1"></a><span class="co">#> 3 1.3 0.2</span></span>
<span id="cb28-8"><a href="#cb28-8" tabindex="-1"></a><span class="co">#> 4 1.5 0.2</span></span>
<span id="cb28-9"><a href="#cb28-9" tabindex="-1"></a><span class="co">#> # ℹ 146 more rows</span></span></code></pre></div>
<p>And you can use <code>Filter()</code> to subset by type:</p>
<div class="sourceCode" id="cb29"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb29-1"><a href="#cb29-1" tabindex="-1"></a><span class="fu">Filter</span>(is.factor, iris)</span>
<span id="cb29-2"><a href="#cb29-2" tabindex="-1"></a><span class="co">#> # A tibble: 150 × 1</span></span>
<span id="cb29-3"><a href="#cb29-3" tabindex="-1"></a><span class="co">#> Species</span></span>
<span id="cb29-4"><a href="#cb29-4" tabindex="-1"></a><span class="co">#> <fct> </span></span>
<span id="cb29-5"><a href="#cb29-5" tabindex="-1"></a><span class="co">#> 1 setosa </span></span>
<span id="cb29-6"><a href="#cb29-6" tabindex="-1"></a><span class="co">#> 2 setosa </span></span>
<span id="cb29-7"><a href="#cb29-7" tabindex="-1"></a><span class="co">#> 3 setosa </span></span>
<span id="cb29-8"><a href="#cb29-8" tabindex="-1"></a><span class="co">#> 4 setosa </span></span>
<span id="cb29-9"><a href="#cb29-9" tabindex="-1"></a><span class="co">#> # ℹ 146 more rows</span></span></code></pre></div>
</div>
<div id="summarise-reduce-multiple-values-down-to-a-single-value" class="section level2">
<h2><code>summarise()</code>: Reduce multiple values down to a single
value</h2>
<p><code>dplyr::summarise()</code> computes one or more summaries for
each group:</p>
<div class="sourceCode" id="cb30"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb30-1"><a href="#cb30-1" tabindex="-1"></a>mtcars <span class="sc">%>%</span> </span>
<span id="cb30-2"><a href="#cb30-2" tabindex="-1"></a> <span class="fu">group_by</span>(cyl) <span class="sc">%>%</span> </span>
<span id="cb30-3"><a href="#cb30-3" tabindex="-1"></a> <span class="fu">summarise</span>(<span class="at">mean =</span> <span class="fu">mean</span>(disp), <span class="at">n =</span> <span class="fu">n</span>())</span>
<span id="cb30-4"><a href="#cb30-4" tabindex="-1"></a><span class="co">#> # A tibble: 3 × 3</span></span>
<span id="cb30-5"><a href="#cb30-5" tabindex="-1"></a><span class="co">#> cyl mean n</span></span>
<span id="cb30-6"><a href="#cb30-6" tabindex="-1"></a><span class="co">#> <dbl> <dbl> <int></span></span>
<span id="cb30-7"><a href="#cb30-7" tabindex="-1"></a><span class="co">#> 1 4 105. 11</span></span>
<span id="cb30-8"><a href="#cb30-8" tabindex="-1"></a><span class="co">#> 2 6 183. 7</span></span>
<span id="cb30-9"><a href="#cb30-9" tabindex="-1"></a><span class="co">#> 3 8 353. 14</span></span></code></pre></div>
<p>I think the closest base R equivalent uses <code>by()</code>.
Unfortunately <code>by()</code> returns a list of data frames, but you
can combine them back together again with <code>do.call()</code> and
<code>rbind()</code>:</p>
<div class="sourceCode" id="cb31"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb31-1"><a href="#cb31-1" tabindex="-1"></a>mtcars_by <span class="ot"><-</span> <span class="fu">by</span>(mtcars, mtcars<span class="sc">$</span>cyl, <span class="cf">function</span>(df) {</span>
<span id="cb31-2"><a href="#cb31-2" tabindex="-1"></a> <span class="fu">with</span>(df, <span class="fu">data.frame</span>(<span class="at">cyl =</span> cyl[[<span class="dv">1</span>]], <span class="at">mean =</span> <span class="fu">mean</span>(disp), <span class="at">n =</span> <span class="fu">nrow</span>(df)))</span>
<span id="cb31-3"><a href="#cb31-3" tabindex="-1"></a>})</span>
<span id="cb31-4"><a href="#cb31-4" tabindex="-1"></a><span class="fu">do.call</span>(rbind, mtcars_by)</span>
<span id="cb31-5"><a href="#cb31-5" tabindex="-1"></a><span class="co">#> cyl mean n</span></span>
<span id="cb31-6"><a href="#cb31-6" tabindex="-1"></a><span class="co">#> 4 4 105.1364 11</span></span>
<span id="cb31-7"><a href="#cb31-7" tabindex="-1"></a><span class="co">#> 6 6 183.3143 7</span></span>
<span id="cb31-8"><a href="#cb31-8" tabindex="-1"></a><span class="co">#> 8 8 353.1000 14</span></span></code></pre></div>
<p><code>aggregate()</code> comes very close to providing an elegant
answer:</p>
<div class="sourceCode" id="cb32"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb32-1"><a href="#cb32-1" tabindex="-1"></a>agg <span class="ot"><-</span> <span class="fu">aggregate</span>(disp <span class="sc">~</span> cyl, mtcars, <span class="cf">function</span>(x) <span class="fu">c</span>(<span class="at">mean =</span> <span class="fu">mean</span>(x), <span class="at">n =</span> <span class="fu">length</span>(x)))</span>
<span id="cb32-2"><a href="#cb32-2" tabindex="-1"></a>agg</span>
<span id="cb32-3"><a href="#cb32-3" tabindex="-1"></a><span class="co">#> cyl disp.mean disp.n</span></span>
<span id="cb32-4"><a href="#cb32-4" tabindex="-1"></a><span class="co">#> 1 4 105.1364 11.0000</span></span>
<span id="cb32-5"><a href="#cb32-5" tabindex="-1"></a><span class="co">#> 2 6 183.3143 7.0000</span></span>
<span id="cb32-6"><a href="#cb32-6" tabindex="-1"></a><span class="co">#> 3 8 353.1000 14.0000</span></span></code></pre></div>
<p>But unfortunately while it looks like there are
<code>disp.mean</code> and <code>disp.n</code> columns, it’s actually a
single matrix column:</p>
<div class="sourceCode" id="cb33"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb33-1"><a href="#cb33-1" tabindex="-1"></a><span class="fu">str</span>(agg)</span>
<span id="cb33-2"><a href="#cb33-2" tabindex="-1"></a><span class="co">#> 'data.frame': 3 obs. of 2 variables:</span></span>
<span id="cb33-3"><a href="#cb33-3" tabindex="-1"></a><span class="co">#> $ cyl : num 4 6 8</span></span>
<span id="cb33-4"><a href="#cb33-4" tabindex="-1"></a><span class="co">#> $ disp: num [1:3, 1:2] 105 183 353 11 7 ...</span></span>
<span id="cb33-5"><a href="#cb33-5" tabindex="-1"></a><span class="co">#> ..- attr(*, "dimnames")=List of 2</span></span>
<span id="cb33-6"><a href="#cb33-6" tabindex="-1"></a><span class="co">#> .. ..$ : NULL</span></span>
<span id="cb33-7"><a href="#cb33-7" tabindex="-1"></a><span class="co">#> .. ..$ : chr [1:2] "mean" "n"</span></span></code></pre></div>
<p>You can see a variety of other options at <a href="https://gist.github.com/hadley/c430501804349d382ce90754936ab8ec" class="uri">https://gist.github.com/hadley/c430501804349d382ce90754936ab8ec</a>.</p>
</div>
<div id="slice-choose-rows-by-position" class="section level2">
<h2><code>slice()</code>: Choose rows by position</h2>
<p><code>slice()</code> selects rows with their location:</p>
<div class="sourceCode" id="cb34"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb34-1"><a href="#cb34-1" tabindex="-1"></a><span class="fu">slice</span>(mtcars, <span class="dv">25</span><span class="sc">:</span><span class="fu">n</span>())</span>
<span id="cb34-2"><a href="#cb34-2" tabindex="-1"></a><span class="co">#> # A tibble: 8 × 13</span></span>
<span id="cb34-3"><a href="#cb34-3" tabindex="-1"></a><span class="co">#> mpg cyl disp hp drat wt qsec vs am gear carb cyl2 cyl4</span></span>
<span id="cb34-4"><a href="#cb34-4" tabindex="-1"></a><span class="co">#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl></span></span>
<span id="cb34-5"><a href="#cb34-5" tabindex="-1"></a><span class="co">#> 1 19.2 8 400 175 3.08 3.84 17.0 0 0 3 2 16 32</span></span>
<span id="cb34-6"><a href="#cb34-6" tabindex="-1"></a><span class="co">#> 2 27.3 4 79 66 4.08 1.94 18.9 1 1 4 1 8 16</span></span>
<span id="cb34-7"><a href="#cb34-7" tabindex="-1"></a><span class="co">#> 3 26 4 120. 91 4.43 2.14 16.7 0 1 5 2 8 16</span></span>
<span id="cb34-8"><a href="#cb34-8" tabindex="-1"></a><span class="co">#> 4 30.4 4 95.1 113 3.77 1.51 16.9 1 1 5 2 8 16</span></span>
<span id="cb34-9"><a href="#cb34-9" tabindex="-1"></a><span class="co">#> # ℹ 4 more rows</span></span></code></pre></div>
<p>This is straightforward to replicate with <code>[</code>:</p>
<div class="sourceCode" id="cb35"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb35-1"><a href="#cb35-1" tabindex="-1"></a>mtcars[<span class="dv">25</span><span class="sc">:</span><span class="fu">nrow</span>(mtcars), , drop <span class="ot">=</span> <span class="cn">FALSE</span>]</span>
<span id="cb35-2"><a href="#cb35-2" tabindex="-1"></a><span class="co">#> # A tibble: 8 × 13</span></span>
<span id="cb35-3"><a href="#cb35-3" tabindex="-1"></a><span class="co">#> mpg cyl disp hp drat wt qsec vs am gear carb cyl2 cyl4</span></span>
<span id="cb35-4"><a href="#cb35-4" tabindex="-1"></a><span class="co">#> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl> <dbl></span></span>
<span id="cb35-5"><a href="#cb35-5" tabindex="-1"></a><span class="co">#> 1 19.2 8 400 175 3.08 3.84 17.0 0 0 3 2 16 32</span></span>
<span id="cb35-6"><a href="#cb35-6" tabindex="-1"></a><span class="co">#> 2 27.3 4 79 66 4.08 1.94 18.9 1 1 4 1 8 16</span></span>
<span id="cb35-7"><a href="#cb35-7" tabindex="-1"></a><span class="co">#> 3 26 4 120. 91 4.43 2.14 16.7 0 1 5 2 8 16</span></span>
<span id="cb35-8"><a href="#cb35-8" tabindex="-1"></a><span class="co">#> 4 30.4 4 95.1 113 3.77 1.51 16.9 1 1 5 2 8 16</span></span>
<span id="cb35-9"><a href="#cb35-9" tabindex="-1"></a><span class="co">#> # ℹ 4 more rows</span></span></code></pre></div>
</div>
</div>
<div id="two-table-verbs" class="section level1">
<h1>Two-table verbs</h1>
<p>When we want to merge two data frames, <code>x</code> and
<code>y</code>), we have a variety of different ways to bring them
together. Various base R <code>merge()</code> calls are replaced by a
variety of dplyr <code>join()</code> functions.</p>
<table>
<thead>
<tr class="header">
<th>dplyr</th>
<th>base</th>
</tr>
</thead>
<tbody>
<tr class="odd">
<td><code>inner_join(df1, df2)</code></td>
<td><code>merge(df1, df2)</code></td>
</tr>
<tr class="even">
<td><code>left_join(df1, df2)</code></td>
<td><code>merge(df1, df2, all.x = TRUE)</code></td>
</tr>
<tr class="odd">
<td><code>right_join(df1, df2)</code></td>
<td><code>merge(df1, df2, all.y = TRUE)</code></td>
</tr>
<tr class="even">
<td><code>full_join(df1, df2)</code></td>
<td><code>merge(df1, df2, all = TRUE)</code></td>
</tr>
<tr class="odd">
<td><code>semi_join(df1, df2)</code></td>
<td><code>df1[df1$x %in% df2$x, , drop = FALSE]</code></td>
</tr>
<tr class="even">
<td><code>anti_join(df1, df2)</code></td>
<td><code>df1[!df1$x %in% df2$x, , drop = FALSE]</code></td>
</tr>
</tbody>
</table>
<p>For more information about two-table verbs, see
<code>vignette("two-table")</code>.</p>
<div id="mutating-joins" class="section level3">
<h3>Mutating joins</h3>
<p>dplyr’s <code>inner_join()</code>, <code>left_join()</code>,
<code>right_join()</code>, and <code>full_join()</code> add new columns
from <code>y</code> to <code>x</code>, matching rows based on a set of
“keys”, and differ only in how missing matches are handled. They are
equivalent to calls to <code>merge()</code> with various settings of the
<code>all</code>, <code>all.x</code>, and <code>all.y</code> arguments.
The main difference is the order of the rows:</p>
<ul>
<li>dplyr preserves the order of the <code>x</code> data frame.</li>
<li><code>merge()</code> sorts the key columns.</li>
</ul>
</div>
<div id="filtering-joins" class="section level3">
<h3>Filtering joins</h3>
<p>dplyr’s <code>semi_join()</code> and <code>anti_join()</code> affect
only the rows, not the columns:</p>
<div class="sourceCode" id="cb36"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb36-1"><a href="#cb36-1" tabindex="-1"></a>band_members <span class="sc">%>%</span> <span class="fu">semi_join</span>(band_instruments)</span>
<span id="cb36-2"><a href="#cb36-2" tabindex="-1"></a><span class="co">#> Joining with `by = join_by(name)`</span></span>
<span id="cb36-3"><a href="#cb36-3" tabindex="-1"></a><span class="co">#> # A tibble: 2 × 2</span></span>
<span id="cb36-4"><a href="#cb36-4" tabindex="-1"></a><span class="co">#> name band </span></span>
<span id="cb36-5"><a href="#cb36-5" tabindex="-1"></a><span class="co">#> <chr> <chr> </span></span>
<span id="cb36-6"><a href="#cb36-6" tabindex="-1"></a><span class="co">#> 1 John Beatles</span></span>
<span id="cb36-7"><a href="#cb36-7" tabindex="-1"></a><span class="co">#> 2 Paul Beatles</span></span>
<span id="cb36-8"><a href="#cb36-8" tabindex="-1"></a>band_members <span class="sc">%>%</span> <span class="fu">anti_join</span>(band_instruments)</span>
<span id="cb36-9"><a href="#cb36-9" tabindex="-1"></a><span class="co">#> Joining with `by = join_by(name)`</span></span>
<span id="cb36-10"><a href="#cb36-10" tabindex="-1"></a><span class="co">#> # A tibble: 1 × 2</span></span>
<span id="cb36-11"><a href="#cb36-11" tabindex="-1"></a><span class="co">#> name band </span></span>
<span id="cb36-12"><a href="#cb36-12" tabindex="-1"></a><span class="co">#> <chr> <chr> </span></span>
<span id="cb36-13"><a href="#cb36-13" tabindex="-1"></a><span class="co">#> 1 Mick Stones</span></span></code></pre></div>
<p>They can be replicated in base R with <code>[</code> and
<code>%in%</code>:</p>
<div class="sourceCode" id="cb37"><pre class="sourceCode r"><code class="sourceCode r"><span id="cb37-1"><a href="#cb37-1" tabindex="-1"></a>band_members[band_members<span class="sc">$</span>name <span class="sc">%in%</span> band_instruments<span class="sc">$</span>name, , drop <span class="ot">=</span> <span class="cn">FALSE</span>]</span>
<span id="cb37-2"><a href="#cb37-2" tabindex="-1"></a><span class="co">#> # A tibble: 2 × 2</span></span>
<span id="cb37-3"><a href="#cb37-3" tabindex="-1"></a><span class="co">#> name band </span></span>
<span id="cb37-4"><a href="#cb37-4" tabindex="-1"></a><span class="co">#> <chr> <chr> </span></span>
<span id="cb37-5"><a href="#cb37-5" tabindex="-1"></a><span class="co">#> 1 John Beatles</span></span>
<span id="cb37-6"><a href="#cb37-6" tabindex="-1"></a><span class="co">#> 2 Paul Beatles</span></span>
<span id="cb37-7"><a href="#cb37-7" tabindex="-1"></a>band_members[<span class="sc">!</span>band_members<span class="sc">$</span>name <span class="sc">%in%</span> band_instruments<span class="sc">$</span>name, , drop <span class="ot">=</span> <span class="cn">FALSE</span>]</span>
<span id="cb37-8"><a href="#cb37-8" tabindex="-1"></a><span class="co">#> # A tibble: 1 × 2</span></span>
<span id="cb37-9"><a href="#cb37-9" tabindex="-1"></a><span class="co">#> name band </span></span>
<span id="cb37-10"><a href="#cb37-10" tabindex="-1"></a><span class="co">#> <chr> <chr> </span></span>
<span id="cb37-11"><a href="#cb37-11" tabindex="-1"></a><span class="co">#> 1 Mick Stones</span></span></code></pre></div>
<p>Semi and anti joins with multiple key variables are considerably more
challenging to implement.</p>
</div>
</div>
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