Creating multi-tab reports with R and jQuery UI
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
by Matt Parker, Data Scientist at Microsoft
One of the great advantages of R's openness is its extensibility. R's abundant packages are the most conspicuous example of that extensibility, and Revolution R Enterprise is a powerful example of how far it can stretch.
But R is also part of an entire ecosystem of open tools that can be linked together. For example, Markdown, Pandoc, and knitr combine to make R an incredible tool for dynamic reporting and reproducible research. If your chosen output format is HTML, you've linked into yet another open ecosystem with countless further extensions.
One of those extensions – and the focus of this post – is jQuery UI. jQuery UI makes a set of JavaScript's most useful moves available to developers as a robust, easy-to-implement toolkit ideal for adding a bit of interactivity to your knitr reports.
Tabs
For example: it's easy to use jQuery UI's Tabs widget to split a long report across several tabs of a webpage. Tabs are great for splitting complex reports up by topic, or for providing different types of users with customized views of the results.
To get a sense of what this conversion might look like, here's a simple R-Markdown report without tabs (Rmd source):
… and the same report with tabs (source):
Here's how I added tabs to the report.
1) First, I downloaded jQuery UI. Picking the right place to store the library can be tricky, but as long as the jQuery UI files are accessible to knitr when it's building the report, you'll be okay. For this demo report, I just unzipped the files right next to the .rmd source.
2) Next, I added a few lines to the <head> element of the report. Every
webpage has a <head> element. knitr would typically build this for you, but
in this case we need to write it manually to be sure that the jQuery UI scripts
and CSS are linked in the HTML output.
<head>
<meta charset="utf-8">
<title>Reported Active Tuberculosis Cases in the United States, 1993-2013</title>
<link rel="stylesheet" href="jquery-ui/jquery-ui.min.css">
<script src="jquery-ui/external/jquery/jquery.js"></script>
<script src="jquery-ui/jquery-ui.js"></script>
<script>
$(function() {
$( "#tabs" ).tabs();
});
</script>
</head>
3) Next, I created the navigation bar by creating an HTML chunk (div) with a
list inside of it (ul). Each item in that list (li) represents one tab
that I'd like the page to have. Finally, I make each of those list items a link
with a unique tag (<a href="#nation">),
and give the link a title (Nationally, By State, Treatment Completion).
<div id="tabs"> <ul> <li><a href="#nation">Nationally</a></li> <li><a href="#states">By State</a></li> <li><a href="#treatment">Treatment Completion</a></li> </ul>
Don't worry if you don't understand the HTML syntax here – you can just copy and edit the code above.
4) Finally, I marked out which sections of R-Markdown I wanted to put on each
tab by surrounding that section with a div:
<div id="nation">
## Reported Active TB Cases in the United States, 1993-2013
```{r nation}
tbstats %>%
group_by(Year) %>%
summarise(n_cases = sum(Count)) %>%
ggplot(aes(x = Year, y = n_cases)) +
geom_line(size = 2) +
labs(x = "Year Reported",
y = "Number of Cases",
title = "Reported Active TB Cases in the United States") +
expand_limits(y = 0)
```
</div>
There are two crucial details here:
– the div has an id that corresponds to one of the tabs I've created
(href=#nation corresponds to <div id="nation">)
– the div is closed with a </div> tag. Without this, the entire report
would be included on the first tab.
5) Click the “Knit HTML” button! knitr will convert your R-Markdown into plain Markdown, and then call Pandoc to complete the conversion into gloriously-tabbed HTML.
Tabs are very handy for reporting – but the whole HTML/CSS/JavaScript ecosystem is at your disposal. If you've seen other good reporting tricks in HTML, let us know in the comments below.
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.