Brandon LeBeau

7 minute read

My last post I talked about using rCharts to create interactive graphics for my presentation. They seemed to go over pretty well in my interviews and helped me greatly as I did not need to remember or write down specific numbers to talk about. I use slidy to create my HTML slideshows and there was some interest to see exactly how I had these charts into a slidy html presentation.

First off, I did not use rCharts and knitr in tandem, but that would make the workflow a bit easier. The major thing you’d want to remember is to make sure to add the following chunk option: results = 'asis'. This will ensure that the raw html printed from rCharts will be included in the markdown file as is.

I personally just copy and pasted the javascript into my markdown presentation. This was easier for me as I edited many specific options in the raw Javascript to come to my final version. It would be possible to make all the edits directly through the rCharts framework, but it was easier for me to just look at the highcharts.js documentation to get the figure I was looking for.

For those who did not see my last post, here is the R code I used to create my graphic:

library(rCharts)

h1 <- hPlot(x = "GenSerCor", y = "percent", group = "FitSerCor", data = converge)
h1$yAxis(title = list(text = "Convergence Rate"), min = 0, max = 100, tickInterval = 10)
h1$xAxis(title = list(text = "Generated Serial Correlation Structure"),
         categories = c("Ind", "AR1", "MA1", "MA2", "ARMA"))
h1$legend(verticalAlign = "top", align = "right", layout = "vertical", title = list(text = "Fitted SC"))
h1$plotOptions(series = list(lineWidth = 4))
h1$print('chart1', include_assets = TRUE, cdn = TRUE)

After I ran this command in R, I edited the resulting Javascript code that was printed from the last line of the R code above. My final Javascript code can be seen below.

Once you have that in markdown format, you can turn it into a slidy html presentation with the following command in pandoc:

pandoc -s --mathjax -i -t slidy inputfile.md -o outfile.html

This gives you a file that looks something like this:

<?xml version="1.0" encoding="utf-8"?>
<!DOCTYPE html PUBLIC "-//W3C//DTD XHTML 1.0 Strict//EN"
 "http://www.w3.org/TR/xhtml1/DTD/xhtml1-strict.dtd">
<html xmlns="http://www.w3.org/1999/xhtml">
<head>
  <meta http-equiv="Content-Type" content="text/html; charset=utf-8" />
  <meta http-equiv="Content-Style-Type" content="text/css" />
  <meta name="generator" content="pandoc" />
  <meta name="author" content="Brandon LeBeau" />
  <title>Impact of serial correlation structures on random effect misspecification with the linear mixed model.</title>
  <style type="text/css">code{white-space: pre;}</style>
  <link rel="stylesheet" type="text/css" media="screen, projection, print"
    href="stylesheets/slidy.css" />
<script src="stylesheets/slidy.js" charset="utf-8" type="text/javascript"></script>
<script type='text/javascript' src=stylesheets/jquery-1.9.1.min.js></script>
<script type='text/javascript' src=stylesheets/highcharts.js></script>
<script type='text/javascript' src=stylesheets/highcharts-more.js></script>
<script type='text/javascript' src=stylesheets/exporting.js></script> 
 <style>
  .rChart {
    display: block;
    margin-left: auto; 
    margin-right: auto;
    width: 1000px;
    height: 800px;
    font-size: 200%;
  }  
  </style>
<script src="http://cdn.mathjax.org/mathjax/latest/MathJax.js?config=TeX-AMS-MML_HTMLorMML" type="text/javascript">MathJax.Hub.Queue(["Typeset",MathJax.Hub]);</script>
 <!--   <script src="http://www.w3.org/Talks/Tools/Slidy2/scripts/slidy.js"
    charset="utf-8" type="text/javascript"></script> -->
</head>
<body>
<div id = 'chart1' class = 'rChart'></div>
<script type='text/javascript'>
    (function($){
        $(function () {
            var chart = new Highcharts.Chart({
 "dom": "chart1",
"width":            1000,
"height":            600,
"credits": {
 "href": null,
"text": null 
},
"exporting": {
 "enabled": false 
},
"title": {
 "text": null 
},
"yAxis": [
 {
 title: {
 text: "Convergence Rate",
  style: {
   fontWeight: 'bold',
   fontSize: '20px'
   }
 },
 labels: {
  formatter: function() {
   return this.value + '%';
  },
  style: {
   fontSize: '18px'
  }
 },
"min":              0,
"max":            100,
"tickInterval":             10 ,
minRange: 10
} 
],
"series": [
 {
 "data": [
 [
 "Ind",
         68.38 
],
[
 "AR1",
         64.88 
],
[
 "MA1",
         55.12 
],
[
 "MA2",
         61.98 
],
[
 "ARMA",
         42.17 
] 
],
events: {
            mouseOver: function () {
                this.update({
                    color: 'black'
                });                
            },
            mouseOut: function () {
                this.update({
                    color: '#e41a1c'
                }); 
            }
        },
"color": "#e41a1c",
"name": "AR1",
"type": null,
dashStyle: 'Solid',
"marker": {
 "radius":              6
} 
},
{
 "data": [
 [
 "Ind",
          65.1 
],
[
 "AR1",
         60.45 
],
[
 "MA1",
         63.68 
],
[
 "MA2",
         54.88 
],
[
 "ARMA",
          63.6 
] 
],
events: {
            mouseOver: function () {
                this.update({
                    color: 'black'
                });                
            },
            mouseOut: function () {
                this.update({
                    color: '#377eb8'
                }); 
            }
        },
"color": "#377eb8",
"name": "ARMA",
"type": null,
dashStyle: 'ShortDash',
"marker": {
 "radius":              6 
} 
},
{
 "data": [
 [
 "Ind",
         72.48 
],
[
 "AR1",
         93.88 
],
[
 "MA1",
         92.23 
],
[
 "MA2",
         95.62 
],
[
 "ARMA",
         98.37 
] 
],
events: {
            mouseOver: function () {
                this.update({
                    color: 'black'
                });                
            },
            mouseOut: function () {
                this.update({
                    color: '#4daf4a'
                }); 
            }
        },
"color": "#4daf4a",
"name": "Ind",
"type": null,
dashStyle: 'Dash',
"marker": {
 "radius":              6 
} 
},
{
 "data": [
 [
 "Ind",
         71.02 
],
[
 "AR1",
         81.37 
],
[
 "MA1",
         69.15 
],
[
 "MA2",
          84.5 
],
[
 "ARMA",
         88.02 
] 
],
events: {
            mouseOver: function () {
                this.update({
                    color: 'black'
                });                
            },
            mouseOut: function () {
                this.update({
                    color: '#984ea3'
                }); 
            }
        },
"color": "#984ea3",
"name": "MA1",
"type": null,
dashStyle: 'ShortDot',
"marker": {
 "radius":              6
} 
},
{
 "data": [
 [
 "Ind",
         67.23 
],
[
 "AR1",
         70.78 
],
[
 "MA1",
         65.93 
],
[
 "MA2",
         68.83 
],
[
 "ARMA",
          72.9 
] 
],
events: {
            mouseOver: function () {
                this.update({
                    color: 'black'
                });                
            },
            mouseOut: function () {
                this.update({
                    color: '#ff7f00'
                }); 
            }
        },
"color": "#ff7f00",
"name": "MA2",
"type": null,
dashStyle: 'DashDot',
"marker": {
 "radius":              6 
} 
} 
],
"xAxis": [
 {
 title: {
 text: "Generated Serial Correlation Structure",
  style:{
   fontWeight: 'bold',
   fontSize: '20px'
 }
},
labels: {
 style: {
  fontSize: '18px',
  fontWeight: 'bold'
 }
},
"categories": [ "Ind", "AR1", "MA1", "MA2", "ARMA" ] 
} 
],
"subtitle": {
 "text": null 
},
"legend": {
 "verticalAlign": "top",
"align": "right",
"layout": "vertical",
symbolWidth: 40,
"title": {
 "text": "Fitted SC" 
} 
},
"plotOptions": {
 "series": {
 "lineWidth":              4 
} 
},
"id": "chart1",
"chart": {
 "renderTo": "chart1", 
 zoomType: "y",
 "style": {
 fontSize: "24px"
 },
 resetZoomButton: {
  position: {
   align: 'left'
  }
 }
} 
});
        });
    })(jQuery);
</script>
</div>
</body>
</html>

That should give you a html presentation with an interactive Javascript based figure.

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