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<!DOCTYPE html>
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<title>Research Platforms: R for reproducible scientific analysis</title>
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<a href="index.html"><h1 class="title">R for reproducible scientific analysis</h1></a>
<h2 class="subtitle">Why Use R?</h2>
<h2 id="why-r">Why R?</h2>
<ul>
<li>Powerful statistical analysis</li>
<li>and powerful visualisation</li>
<li>integrated elegantly</li>
</ul>
<h2 id="what-well-accomplish">What We’ll Accomplish</h2>
<ul>
<li>Get to know R and RStudio</li>
<li>Analyze a meaningful data set</li>
<li>Extract insights and deliver them visually</li>
<li>Leave ready to learn more R independently</li>
</ul>
<h2 id="r-loves-ingesting-data">R loves ingesting data</h2>
<pre><code>gapminder <- read.csv(
"data/gapminder-FiveYearData.csv",
header=TRUE,
sep=',')</code></pre>
<h2 id="data-w-column-names">Data w/ column names</h2>
<p>head(gapminder, 1) # Show me the first row</p>
<p>country year pop continent lifeExp gdpPercap 1 Afghanistan 1952 8425333 Asia 28.801 779.4453</p>
<h2 id="quickly-graph">Quickly graph …</h2>
<pre><code>ggplot(
data=gapminder,
aes(x=lifeExp, y=gdpPercap)
) + geom_point()</code></pre>
<h2 id="to-see-what-we-have">… to see what we have</h2>
<div class="figure">
<img src="img/first_plot.png" alt="First plot" /><p class="caption">First plot</p>
</div>
<h2 id="lets-graph-more-factors">Let’s graph more factors</h2>
<pre><code>ggplot(
data=gapminder,
aes(x=year, y=lifeExp, by=country, colour=continent)
) + geom_line()
+ geom_point()</code></pre>
<h2 id="pretty">Pretty!</h2>
<div class="figure">
<img src="img/countries_and_colors.png" alt="Countries and colors" /><p class="caption">Countries and colors</p>
</div>
<h2 id="dyplr-gives-us">dyplr gives us …</h2>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">library</span>(dplyr)
cors <-<span class="st"> </span>gapminder %>%
<span class="st"> </span><span class="kw">group_by</span>(year) %>%
<span class="st"> </span><span class="kw">summarise</span>(
<span class="dt">gdpPercap.lifeExp =</span> <span class="kw">cor</span>(gdpPercap, lifeExp),
<span class="dt">gdpPercap.pop =</span> <span class="kw">cor</span>(gdpPercap, pop),
<span class="dt">pop.lifeExp =</span> <span class="kw">cor</span>(pop, lifeExp))</code></pre>
<h2 id="pairwise-correlations">… pairwise correlations</h2>
<pre><code>head(cors, 1)
Source: local data frame [1 x 4]
year gdpPercap.lifeExp gdpPercap.pop pop.lifeExp
1 1952 0.2780236 -0.02526041 -0.002724782</code></pre>
<h2 id="restructuring-the-table">Restructuring the table …</h2>
<pre class="sourceCode r"><code class="sourceCode r"><span class="kw">library</span>(tidyr)</code></pre>
<pre class="error"><code>Error in library(tidyr): there is no package called 'tidyr'
</code></pre>
<pre class="sourceCode r"><code class="sourceCode r">tidy.cors <-<span class="st"> </span>cors %>%<span class="st"> </span><span class="kw">gather</span>(
variables, correlation,
gdpPercap.lifeExp, gdpPercap.pop,
pop.lifeExp)</code></pre>
<pre class="error"><code>Error in function_list[[k]](value): could not find function "gather"
</code></pre>
<h2 id="a-subtle-art">… a subtle art …</h2>
<pre><code>head(tidy.cors, 1)
Source: local data frame [1 x 3]
year variables correlation
1 1952 gdpPercap.lifeExp 0.2780236</code></pre>
<h2 id="produces-great-results">… produces great results</h2>
<div class="figure">
<img src="img/gdp_and_life.png" alt="GDP and Life" /><p class="caption">GDP and Life</p>
</div>
</div>
</div>
</article>
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