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          <h1 id="post-title">R Learning</h1>

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<h1 id="matrices">Matrices</h1>
<pre><code>matrix(data_vector, byrow = TRUE, nrow = 3)</code></pre>
<p>This fills the matrix with elements from <code>data_vector</code>.</p>
<pre><code>rownames(m) &lt;- foo
colnames(m) &lt;- bar</code></pre>
<p>This gives you neat row and column titles when you print the matrix.</p>
<p>Other stuff I learnt:</p>
<pre><code>matrix[,2] # select second column</code></pre>
<h1 id="factors">Factors</h1>
<p>nominal (like C++ enum) or ordinal (like movie ratings).</p>
<p>ordinal:</p>
<pre><code>factor(foo, ordered = TRUE, levels = c(&quot;bronze&quot;, &quot;silver&quot;, &quot;gold&quot;))</code></pre>
<h1 id="data-frame">Data Frame</h1>
<p>data frame = table</p>
<pre><code>str(foo) gives you
number of observations (rows), number of variables (columns)
variable: type and first few observations

foo_frame[,&quot;col_name&quot;]
foo_frame$col_name

foo_frame[foo_frame$rings, &quot;names&quot;]
# The first part selects rows, the second part selects columns.

# Get column &quot;bar&quot;
foo_frame$bar</code></pre>
<h1 id="table">Table</h1>
<pre><code># To get count ratios
table(foo_frame$sex)

# To get column-wise ratios
table(foo_frame$sex, foo_frame$Survived)

# To get proportions
prop.table(table(foo_frame$sex, foo_frame$Survived), margin = 1)</code></pre>
<h1 id="workspace">Workspace</h1>
<p>contents:</p>
<pre><code>ls()</code></pre>
<h1 id="reference">Reference</h1>
<p><a href="https://www.datacamp.com/courses/free-introduction-to-r">Datacamp Introduction to R</a></p>

<div class="info">Created: May  9, 2016</div>
<div class="info">Last modified: September 28, 2019</div>
<div class="info">Status: in-progress notes</div>
<div class="info"><b>Tags</b>: notes, R</div>

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