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<h1 id="subsetting-data.frames-and-matrices">Subsetting Data.Frames and Matrices</h1>
<p>Subsetting a 2-dimensional object in R follows the same rules as one dimension. We can use positions, negative positions, logical vectors, names, empty/missing indices for each dimension. The computation is</p>
<pre class="sourceCode r"><code class="sourceCode r">obj[i, j]</code></pre>
<p>This is essentially the same as the two step</p>
<pre class="sourceCode r"><code class="sourceCode r">obj[i, ] [, j]</code></pre>
<p>The empty/missing index means all the elements from that dimension. So for a data.frame df,</p>
<pre class="sourceCode r"><code class="sourceCode r">df[, ]</code></pre>
<p>means all of the rows and all of the columns.</p>
<pre class="sourceCode r"><code class="sourceCode r">df[ <span class="kw">c</span>(<span class="dv">1</span>, <span class="dv">3</span>, <span class="dv">6</span>), ]</code></pre>
<p>means rows 1, 3 and 6, and all of the columns. Since this is [, we get back a data frame.</p>
<h2 id="single-column-as-vector-or-data-frame">Single Column as Vector or Data Frame?</h2>
<p>Typically, if we subset a single column, e.g,</p>
<pre class="sourceCode r"><code class="sourceCode r">mtcars[, <span class="st">"mpg"</span>]</code></pre>
<p>R recognizes we want that as a vector and not as a data frame with one column.</p>
<p>However, if we do want to ensure it is a data.frame with one column, we can use the <code>drop = FALSE</code> in the [ ] operation, as we did for factors when we wanted to drop the levels that were not in the subset. So</p>
<pre class="sourceCode r"><code class="sourceCode r">mtcars[, <span class="st">'mpg'</span>, drop =<span class="st"> </span><span class="ot">FALSE</span>]
mpg
Mazda RX4 <span class="fl">21.0</span>
Mazda RX4 Wag <span class="fl">21.0</span>
Datsun <span class="dv">710</span> <span class="fl">22.8</span>
Hornet <span class="dv">4</span> Drive <span class="fl">21.4</span>
Hornet Sportabout <span class="fl">18.7</span>
......</code></pre>
<p>gives a data.frame with one column.</p>
<p>Again, like list[[x]] where x may have more than one element, it can be useful to use drop = FALSE to ensure you get a data frame in a computation such as <code>df[, x]</code> where x may have 1 or more than one element.</p>
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