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@ramnathv
Created May 9, 2014 20:53
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Test Presentation
<!DOCTYPE html>
<html>
<head>
<title>Test</title>
<meta charset="utf-8">
<meta name="description" content="Test">
<meta name="author" content="RV">
<meta name="generator" content="slidify" />
<meta name="apple-mobile-web-app-capable" content="yes">
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<script data-main="http://slidifylibraries2.googlecode.com/git/inst/libraries/frameworks/io2012/js/slides"
src="http://slidifylibraries2.googlecode.com/git/inst/libraries/frameworks/io2012/js/require-1.0.8.min.js">
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</head>
<body style="opacity: 0">
<slides class="layout-widescreen">
<!-- LOGO SLIDE -->
<slide class="title-slide segue nobackground">
<hgroup class="auto-fadein">
<h1>Test</h1>
<h2></h2>
<p>RV<br/></p>
</hgroup>
<article></article>
</slide>
<!-- SLIDES -->
<slide class="" id="slide-1" style="background:;">
<hgroup>
<h2>Read-And-Delete</h2>
</hgroup>
<article data-timings="">
<ol>
<li>Edit YAML front matter</li>
<li>Write using R Markdown</li>
<li>Use an empty line followed by three dashes to separate slides!</li>
</ol>
</article>
<!-- Presenter Notes -->
</slide>
<slide class="class" id="id" style="background:;">
<hgroup>
<h2>Slide 2</h2>
</hgroup>
<article data-timings="">
<pre><code class="r">library(ggplot2)
qplot(wt, mpg, data = mtcars)
</code></pre>
<p><img src="data:image/png;base64,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" alt="plot of chunk unnamed-chunk-1"> </p>
</article>
<!-- Presenter Notes -->
</slide>
<slide class="" id="slide-3" style="background:;">
<article data-timings="">
<pre><code class="r">library(rCharts)
options(rcharts.mode = &#39;iframesrc&#39;, cdn = TRUE)
rPlot(mpg ~ wt | gear, data = mtcars, type = &#39;point&#39;)
</code></pre>
<p>&lt;iframe srcdoc=&#39; &lt;!doctype HTML&gt;
&lt;meta charset = &#039;utf-8&#039;&gt;
&lt;html&gt;
&lt;head&gt;</p>
<pre><code>&amp;lt;script src=&amp;#039;/Library/Frameworks/R.framework/Versions/3.1/Resources/library/rCharts/libraries/polycharts/js/polychart2.standalone.js&amp;#039; type=&amp;#039;text/javascript&amp;#039;&amp;gt;&amp;lt;/script&amp;gt;
&amp;lt;style&amp;gt;
.rChart {
display: block;
margin-left: auto;
margin-right: auto;
width: 800px;
height: 400px;
}
&amp;lt;/style&amp;gt;
</code></pre>
<p>&lt;/head&gt;
&lt;body &gt;</p>
<pre><code>&amp;lt;div id = &amp;#039;chartc65020b6da83&amp;#039; class = &amp;#039;rChart polycharts&amp;#039;&amp;gt;&amp;lt;/div&amp;gt;
&amp;lt;script type=&amp;#039;text/javascript&amp;#039;&amp;gt;
var chartParams = {
</code></pre>
<p>&quot;dom&quot;: &quot;chartc65020b6da83&quot;,
&quot;width&quot;: 800,
&quot;height&quot;: 400,
&quot;layers&quot;: [
{
&quot;x&quot;: &quot;wt&quot;,
&quot;y&quot;: &quot;mpg&quot;,
&quot;data&quot;: {
&quot;mpg&quot;: [ 21, 21, 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, 10.4, 14.7, 32.4, 30.4, 33.9, 21.5, 15.5, 15.2, 13.3, 19.2, 27.3, 26, 30.4, 15.8, 19.7, 15, 21.4 ],
&quot;cyl&quot;: [ 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 ],
&quot;disp&quot;: [ 160, 160, 108, 258, 360, 225, 360, 146.7, 140.8, 167.6, 167.6, 275.8, 275.8, 275.8, 472, 460, 440, 78.7, 75.7, 71.1, 120.1, 318, 304, 350, 400, 79, 120.3, 95.1, 351, 145, 301, 121 ],
&quot;hp&quot;: [ 110, 110, 93, 110, 175, 105, 245, 62, 95, 123, 123, 180, 180, 180, 205, 215, 230, 66, 52, 65, 97, 150, 150, 245, 175, 66, 91, 113, 264, 175, 335, 109 ],
&quot;drat&quot;: [ 3.9, 3.9, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3.92, 3.92, 3.07, 3.07, 3.07, 2.93, 3, 3.23, 4.08, 4.93, 4.22, 3.7, 2.76, 3.15, 3.73, 3.08, 4.08, 4.43, 3.77, 4.22, 3.62, 3.54, 4.11 ],
&quot;wt&quot;: [ 2.62, 2.875, 2.32, 3.215, 3.44, 3.46, 3.57, 3.19, 3.15, 3.44, 3.44, 4.07, 3.73, 3.78, 5.25, 5.424, 5.345, 2.2, 1.615, 1.835, 2.465, 3.52, 3.435, 3.84, 3.845, 1.935, 2.14, 1.513, 3.17, 2.77, 3.57, 2.78 ],
&quot;qsec&quot;: [ 16.46, 17.02, 18.61, 19.44, 17.02, 20.22, 15.84, 20, 22.9, 18.3, 18.9, 17.4, 17.6, 18, 17.98, 17.82, 17.42, 19.47, 18.52, 19.9, 20.01, 16.87, 17.3, 15.41, 17.05, 18.9, 16.7, 16.9, 14.5, 15.5, 14.6, 18.6 ],
&quot;vs&quot;: [ 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1 ],
&quot;am&quot;: [ 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1 ],
&quot;gear&quot;: [ 4, 4, 4, 3, 3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 3, 3, 3, 3, 4, 5, 5, 5, 5, 5, 4 ],
&quot;carb&quot;: [ 4, 4, 1, 1, 2, 1, 4, 2, 2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2, 1, 1, 2, 2, 4, 2, 1, 2, 2, 4, 6, 8, 2 ]
},
&quot;facet&quot;: &quot;gear&quot;,
&quot;type&quot;: &quot;point&quot;
}
],
&quot;facet&quot;: {
&quot;type&quot;: &quot;wrap&quot;,
&quot;var&quot;: &quot;gear&quot;
},
&quot;guides&quot;: [],
&quot;coord&quot;: [],
&quot;id&quot;: &quot;chartc65020b6da83&quot;
}
_.each(chartParams.layers, function(el){
el.data = polyjs.data(el.data)
})
var graph_chartc65020b6da83 = polyjs.chart(chartParams);
&lt;/script&gt;</p>
<pre><code>&amp;lt;script&amp;gt;&amp;lt;/script&amp;gt;
</code></pre>
<p>&lt;/body&gt;
&lt;script&gt;
function getURLParameter(name) {
return decodeURIComponent((new RegExp(&#039;[?|&amp;]&#039; + name + &#039;=&#039; + &#039;([<sup>&amp;;]+?)(&amp;|#|;|$)&#039;).exec(location.search)||[,&quot;&quot;])[1].replace(/+/g,</sup> &#039;%20&#039;))||null
}
console.log(getURLParameter(&quot;viewer_pane&quot;))
if (getURLParameter(&quot;viewer_pane&quot;) === &quot;1&quot;){
document.write(&quot;&lt;style&gt;.rChart { width: 100% }&lt;/style&gt;&quot;);
}
&lt;/script&gt;
&lt;/html&gt; &#39; scrolling=&#39;no&#39; frameBorder=&#39;0&#39; seamless class=&#39;rChart polycharts &#39; id=&#39;iframe-chartc65020b6da83&#39;&gt; </iframe> <style>iframe.rChart{ width: 100%; height: 400px;}</style></p>
</article>
<!-- Presenter Notes -->
</slide>
<slide class="backdrop"></slide>
</slides>
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title subtitle author job framework highlighter hitheme widgets mode
Test
RV
io2012
highlight.js
tomorrow
standalone

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--- .class #id

Slide 2

library(ggplot2)
qplot(wt, mpg, data = mtcars)

plot of chunk unnamed-chunk-1


library(rCharts)
options(rcharts.mode = 'iframesrc', cdn = TRUE)
rPlot(mpg ~ wt | gear, data = mtcars, type = 'point')
<iframe srcdoc=' <!doctype HTML> <meta charset = 'utf-8'> <html> <head>
&lt;script src=&#039;/Library/Frameworks/R.framework/Versions/3.1/Resources/library/rCharts/libraries/polycharts/js/polychart2.standalone.js&#039; type=&#039;text/javascript&#039;&gt;&lt;/script&gt;

&lt;style&gt;
.rChart {
  display: block;
  margin-left: auto; 
  margin-right: auto;
  width: 800px;
  height: 400px;
}  
&lt;/style&gt;

</head> <body >

&lt;div id = &#039;chartc65020b6da83&#039; class = &#039;rChart polycharts&#039;&gt;&lt;/div&gt;    
&lt;script type=&#039;text/javascript&#039;&gt;
var chartParams = {

"dom": "chartc65020b6da83", "width": 800, "height": 400, "layers": [ { "x": "wt", "y": "mpg", "data": { "mpg": [ 21, 21, 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, 10.4, 14.7, 32.4, 30.4, 33.9, 21.5, 15.5, 15.2, 13.3, 19.2, 27.3, 26, 30.4, 15.8, 19.7, 15, 21.4 ], "cyl": [ 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 ], "disp": [ 160, 160, 108, 258, 360, 225, 360, 146.7, 140.8, 167.6, 167.6, 275.8, 275.8, 275.8, 472, 460, 440, 78.7, 75.7, 71.1, 120.1, 318, 304, 350, 400, 79, 120.3, 95.1, 351, 145, 301, 121 ], "hp": [ 110, 110, 93, 110, 175, 105, 245, 62, 95, 123, 123, 180, 180, 180, 205, 215, 230, 66, 52, 65, 97, 150, 150, 245, 175, 66, 91, 113, 264, 175, 335, 109 ], "drat": [ 3.9, 3.9, 3.85, 3.08, 3.15, 2.76, 3.21, 3.69, 3.92, 3.92, 3.92, 3.07, 3.07, 3.07, 2.93, 3, 3.23, 4.08, 4.93, 4.22, 3.7, 2.76, 3.15, 3.73, 3.08, 4.08, 4.43, 3.77, 4.22, 3.62, 3.54, 4.11 ], "wt": [ 2.62, 2.875, 2.32, 3.215, 3.44, 3.46, 3.57, 3.19, 3.15, 3.44, 3.44, 4.07, 3.73, 3.78, 5.25, 5.424, 5.345, 2.2, 1.615, 1.835, 2.465, 3.52, 3.435, 3.84, 3.845, 1.935, 2.14, 1.513, 3.17, 2.77, 3.57, 2.78 ], "qsec": [ 16.46, 17.02, 18.61, 19.44, 17.02, 20.22, 15.84, 20, 22.9, 18.3, 18.9, 17.4, 17.6, 18, 17.98, 17.82, 17.42, 19.47, 18.52, 19.9, 20.01, 16.87, 17.3, 15.41, 17.05, 18.9, 16.7, 16.9, 14.5, 15.5, 14.6, 18.6 ], "vs": [ 0, 0, 1, 1, 0, 1, 0, 1, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 1, 0, 0, 0, 0, 1, 0, 1, 0, 0, 0, 1 ], "am": [ 1, 1, 1, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1 ], "gear": [ 4, 4, 4, 3, 3, 3, 3, 4, 4, 4, 4, 3, 3, 3, 3, 3, 3, 4, 4, 4, 3, 3, 3, 3, 3, 4, 5, 5, 5, 5, 5, 4 ], "carb": [ 4, 4, 1, 1, 2, 1, 4, 2, 2, 4, 4, 3, 3, 3, 4, 4, 4, 1, 2, 1, 1, 2, 2, 4, 2, 1, 2, 2, 4, 6, 8, 2 ] }, "facet": "gear", "type": "point" } ], "facet": { "type": "wrap", "var": "gear" }, "guides": [], "coord": [], "id": "chartc65020b6da83" } _.each(chartParams.layers, function(el){ el.data = polyjs.data(el.data) }) var graph_chartc65020b6da83 = polyjs.chart(chartParams); </script>

&lt;script&gt;&lt;/script&gt;    

</body> <script> function getURLParameter(name) { return decodeURIComponent((new RegExp('[?|&]' + name + '=' + '([^&amp;;]+?)(&|#|;|$)').exec(location.search)||[,""])[1].replace(/+/g, '%20'))||null } console.log(getURLParameter("viewer_pane")) if (getURLParameter("viewer_pane") === "1"){ document.write("<style>.rChart { width: 100% }</style>"); } </script> </html> ' scrolling='no' frameBorder='0' seamless class='rChart polycharts ' id='iframe-chartc65020b6da83'> </iframe> <style>iframe.rChart{ width: 100%; height: 400px;}</style>

---
title : Test
subtitle :
author : RV
job :
framework : io2012 # {io2012, html5slides, shower, dzslides, ...}
highlighter : highlight.js # {highlight.js, prettify, highlight}
hitheme : tomorrow #
widgets : [] # {mathjax, quiz, bootstrap}
mode : standalone # {standalone, draft}
---
## Read-And-Delete
1. Edit YAML front matter
2. Write using R Markdown
3. Use an empty line followed by three dashes to separate slides!
--- .class #id
## Slide 2
```{r}
library(ggplot2)
qplot(wt, mpg, data = mtcars)
```
---
```{r results = 'asis', comment = NA}
library(rCharts)
options(rcharts.mode = 'iframesrc', cdn = TRUE)
rPlot(mpg ~ wt | gear, data = mtcars, type = 'point')
```
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