re run OneNum Story after merging pull request

story/OneNum.html

@@ -238,7 +238,7 @@
 
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-<p><br><br><br>This document gives a few suggestions to analyse a dataset composed by a unique numeric variable.<br> It considers the night price of about 10,000 <a href="https://www.airbnb.fr">Airbnb</a> appartements on the French Riviera in France.<br>This example dataset has been downloaded from the <a href="http://insideairbnb.com/get-the-data.html">Airbnb website</a> and is available on this <a href="https://github.com/holtzy/data_to_viz/tree/master/Example_dataset">Github repository</a>. Basically it looks like the table beside.</p>
+<p><br><br><br>This document porvides a few suggestions for analying a dataset composed of a unique numeric variable.<br> It considers the nightly price of about 10,000 <a href="https://www.airbnb.fr">Airbnb</a> apartements on the French Riviera in France.<br>This example dataset has been downloaded from the <a href="http://insideairbnb.com/get-the-data.html">Airbnb website</a> and is available on this <a href="https://github.com/holtzy/data_to_viz/tree/master/Example_dataset">Github repository</a>. Basically it looks like the table to the right.</p>
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 <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r"><span class="co"># Libraries</span>
@@ -299,8 +299,8 @@
 <div id="histogram" class="section level1">
 <h1>Histogram</h1>
 <hr />
-<p>The most common way to represent a unique numeric variable is probably to produce a histogram. Basically, the numeric variable is cut in several <code>bins</code>: between 0 and 10 euros a night, between 10 and 20 and so on. This is represented on the X axis. Then, the number of appartment per bin is counted and represented by the Y axis.</p>
-<p>Here, it appears that about 500 appartments have a price between 80 and 90 euros. A histogram is a convenient way to visualize the data: it allows to understand its <code>distribution</code>.</p>
+<p>The most common way to represent a unique numeric variable is with a histogram. Basically, the numeric variable is cut in several <code>bins</code>: between 0 and 10 euros a night, between 10 and 20 and so on. This is represented on the X axis. Then, the number of apartments per bin is counted and represented on the Y axis.</p>
+<p>Here, it appears that about 500 appartments have a price between 80 and 90 euros. A histogram is a convenient way to visualize the data: it allows us to understand its <code>distribution</code>.</p>
 <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">data <span class="op">%&gt;%</span>
 <span class="st">  </span><span class="kw">filter</span>( price<span class="op">&lt;</span><span class="dv">300</span> ) <span class="op">%&gt;%</span>
 <span class="st">  </span><span class="kw">ggplot</span>( <span class="kw">aes</span>(<span class="dt">x=</span>price)) <span class="op">+</span>
@@ -311,7 +311,7 @@ <h1>Histogram</h1>
       <span class="dt">plot.title =</span> <span class="kw">element_text</span>(<span class="dt">size=</span><span class="dv">12</span>)
     )</code></pre></div>
 <p><img src="OneNum_files/figure-html/unnamed-chunk-2-1.png" width="672" style="display: block; margin: auto;" /></p>
-<p>Note that it is really important to play with the <code>bin size</code> during your exploratory analysis. Let’s check what happens when spliting prices by bins of 2 euros instead of 10:</p>
+<p>Note that it is important to play with the <code>bin size</code> during your exploratory analysis. Let’s check what happens when spliting prices by bins of 2 euros instead of 10:</p>
 <div class="sourceCode"><pre class="sourceCode r"><code class="sourceCode r">data <span class="op">%&gt;%</span>
 <span class="st">  </span><span class="kw">filter</span>( price<span class="op">&lt;</span><span class="dv">300</span> ) <span class="op">%&gt;%</span>
 <span class="st">  </span><span class="kw">ggplot</span>( <span class="kw">aes</span>(<span class="dt">x=</span>price)) <span class="op">+</span>