Basics of JavaScript and D3 for R Users

October 21, 2012
By

(This article was first published on Civil Statistician » R, and kindly contributed to R-bloggers)

Hadley Wickham, creator of the ggplot2 R package, has been learning JavaScript and its D3 library for the next iteration of ggplot2 (tentatively titled r2d3?)… so I suspect it’s only a matter of time before he pulls the rest of the R community along.

Below are a few things that weren’t obvious when I first tried reading JavaScript code and the D3 library in particular. (Please comment if you notice any errors.) Then there’s also a quick walkthrough for getting D3 examples running locally on your computer, and finally a list of other tutorials & resources. In a future post, we’ll explore one of the D3 examples and practice tweaking it.

Perhaps these short notes will help other R users get started more quickly than I did. Even if you’re a ways away from writing complex JavaScript from scratch, it can still be useful to take one of the plentiful D3 examples and modify it for your own purposes.

A few initial comments:

  • Despite the unfortunate name, JavaScript is really no relation to Java. They are two completely separate languages, not subsets or extensions for one another.
  • R is sort of a language and a tool: you can’t run R code without having the R software installed. But JavaScript is a scripting language that runs in the web browser, so you don’t need to install anything extra. (Though you do need a layer of HTML around the JavaScript, telling the browser how to call it.) So you typically type your JavaScript code in any text editor and save it as a .JS file; call that script from within a .HTML file; and open the HTML file in any modern browser (Firefox, Chrome, Internet Explorer, etc.) However, be aware that your code might not run the same way on each browser — there are standards, but not all browsers follow them fully.
  • To extend R beyond its base functionality, you can install packages written by other users; and generally the R software manages packages for you. To add JavaScript functionality with new libraries, you don’t have to install anything — just make sure that your HTML file calls the text files containing those libraries. We’ll see what that means below.
  • Speaking of libraries, D3 (“Data-Driven Documents”) is a great JavaScript library written by Mike Bostock. It is not a collection of datavis tools, but more generally meant for “efficient manipulation of documents based on data” … which in practice helps make it easier, faster, and cleaner to do datavis in JavaScript. However, D3 graphics use the SVG (Scalable Vector Graphics) format which is not fully implemented in earlier versions of Internet Explorer (version 8 and older), so you may run into compatibility issues.
  • In R, the dot (.) is just another character that can be part of object names. But in JavaScript, the dot is a special operator, similar to R’s dollar sign ($) operator. Also, something.contents in JavaScript or something$contents in R are equivalent to something['contents'] (in both languages).
  • R makes it super easy to provide default arguments for your functions; JavaScript does not seem to have this built in.
  • There are plenty of other JavaScript aspects (the Math object; “this”; cascading; arrays starting at 0 rather than 1…) that may trip up R users. We’ll cover them in detail in a later post.

Now, if you want to create anything yourself with D3, it’s useful to start by editing the examples and seeing how your changes affect the results. Let’s try running the example I started with, trying to read and understand and tweak a D3 choropleth map.

If you don’t have it yet, download D3 from its github site. (Near the top, there’s a  ZIP button to download everything in one zip file.) Unzip the files into a handy directory and let’s first see whether the examples work for you. Go into the .../examples/choropleth/ folder and open up choropleth.html in your web browser. Chances are, it won’t load the nice map, because as the D3 wiki says:

When running the examples locally, note that your browser may enforce strict permissions for reading files out of the local file system. Some examples use AJAX which works differently via HTTP instead of local files. To view the examples locally, you must have a local web server. Any web server will work; for example you can run Python’s built-in server:

python -m SimpleHTTPServer 8888 &

If it’s not obvious to you what that means (it wasn’t for me!), here’s what worked for me on both Windows XP and Windows 7. I’ll assume you have Python installed… (I know I said you don’t have to install anything extra, and that’s true if you put your JavaScript code online on a web server before you access it — but you’ll want to try things out on your local machine first, and having Python seems the simplest way to make that possible. Let me know if you have a simpler solution!) [Edit: we found a way to use R as the local server, so you can avoid Python entirely.]

  • Go to the Start menu, then to Run, and type “cmd” to open a command line window.
  • At the prompt, type in
    set path=%path%;C:\python27
    so Windows knows where to search for Python. (Adjust as needed if you have Python elsewhere or another version; for example, if you have version 2.5 instead of 2.7, you’d type
    set path=%path%;C:\python25
    instead.)
  • Navigate to wherever you unzipped and saved the D3 files, for example
    cd C:\d3
  • Start a local server from this directory by typing in
    python -m SimpleHTTPServer 8888
  • Open your browser and go to http://localhost:8888/
  • Finally! You can see the files in the D3 directory. Click through to the .../examples/choropleth/ subdirectory, open up choropleth.html, and it ought to work.
    (If it doesn’t work… leave a comment and we’ll try some other approaches!)

Once you get it running, try opening the HTML file in a text editor such as Notepad. (You know some basic HTML, right? If not, head over to w3schools.com (edit: or better yet, Mozilla Developer Network) for a quick overview.) Okay. In the HTML file, see how the head section calls a script with <script type="text/javascript" src="../../d3.v2.js"></script>? That says to load up the general D3 library — it’s just like using library(ggplot2) or whatever at the start of your R scripts. You’ll need to do that whenever you create a new tool that uses D3 functionality.

Further down, in the HTML body, it calls another script with <script type="text/javascript" src="choropleth.js"></script> and this script is no longer a general library but specific code for the choropleth example. Open up that choropleth.js file in your text editor, and you should see the same JavaScript code that’s at the bottom of the online example page. In a future post we’ll walk through this code, understand how it works, and tweak it to add some interactivity.

Some other resources to tide you over:

  • w3schools has a set of basic HTML and JavaScript tutorials. [Edit: see commenter Stelios below, who links to concerns about w3schools and suggests better resources.]
  • Once you have the basics down and want more details, I recommend JavaScript: The Good Parts. It’ll give you a good framework for the best parts of JavaScript… and useful warnings about the parts that are more trouble than they’re worth.
  • Christophe Porteneuve’s Pragmatic Guide to JavaScript has an excellent 2-page cheat sheet in the back. I wish the publishers would make it available for download. Meanwhile, here are two other cheat sheets from Dave Child and Addison-Wesley.
  • Luke Francl’s D3 for Mere Mortals seems to be a useful introduction for D3 newbies, including some basics of the underlying technology of SVG. There are more good D3 tutorials linked at the bottom.

See also part 2 for how to run the local server in R instead of using Python.

To leave a comment for the author, please follow the link and comment on his blog: Civil Statistician » R.

R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...



If you got this far, why not subscribe for updates from the site? Choose your flavor: e-mail, twitter, RSS, or facebook...

Comments are closed.