You’ve spent some time learning protovis only to find that its development is halted as authors have switched to work on d3. Have your efforts all been in vain? Fear not! This series of posts will help you adapt to d3 with a protovis background.
Before we go anywhere further, let me say that these posts won’t make you awesome at d3 (yet). We won’t be talking about how to do all amazing things you could never do in protovis. Rather, we’ll focus on enabling you to be as comfortable with d3 than you could have been with protovis. And once that’s done, nothing will prevent you from learning the more powerful aspects of d3.
Anyway, if you’re reading this, you are already awesome.
Why should I make the switch to d3?
Frankly, you don’t have to. Protovis is a fine framework and works well. Now you may want to switch to d3 for several reasons.
- d3 is fast. d3 is better at handling scenes with hundreds or thousands of elements. So if you like scatterplots or network graphs, and who doesn’t, d3 has much stronger performance.
- d3 does animation. There were workarounds to get animation in protovis but there were that. Workarounds. Animation and transitions are built in d3 and are a snap to implement.
- More features. Just because development has stopped on protovis doesn’t mean that it has stopped elsewhere… for instance, d3 has more ready-to-use layouts, like voronoi tesselation or chords, and it has more methods and functions to make your life easier, to access and manipulate data for example.
- Styling. In d3 it is possible to apply style sheets in CSS to graphical elements. This helps keeping the code and the format separate.
Yes but doesn’t everything change?
Short answer: no.
Less short answer: some things do change substantially. Most things stay the same. And then, some things look the same but have changed.
Things that stay the same
- The general principle.Protovis is about transforming an array of data into the same number of graphical elements, with characteristics derived from that data. d3 does exactly this as well.
- pv.Nest, which in my personal protovis experience has been the hardest to understand. Only, it’s called d3.nest now.
Things that look different, but which are largely the same
Protovis had a number of native graphical objects, or marks, that could be manipulated at will with methods.
var vis=new pv.Panel() .height(400) .width(400) .fillStyle("aliceblue") .lineWidth(1) .strokeStyle("steelblue"); vis.render();
In protovis, it is inherently different to set the height, the width or just any property of an object. This uses different methods.
var vis=d3.select("body").append("svg:svg"); vis.append("svg:rect") .attr("height",400) .attr("width",400) .attr("fill","aliceblue") .attr("stroke","steelblue") .attr("stroke-width",1);
This produces essentially the same thing. We add a rectangle of a specified height, width, and colors. There are a few differences though. Here, controlling height, width or fill is essentially the same thing and uses the same method, .attr(). Notice also that we first created an svg document, then a shape within that document. And also, that we don’t need to use vis.render(); anymore.
The d3 approach looks longer. But if we define all the style information first we could make it much shorter, shorter than in protovis in fact!
var vis=d3.select("body").append("svg:svg").append("svg:rect").attr("class", "myRect");
Much of the apparent differences between d3 and protovis come from using explicitly svg shapes (paths, polygons, ellipses, etc.) as opposed to native objects (pv.Panel, pv.Bar, pv.Dot, etc.), although – it’s essentially the same thing. Yes, you have to learn your SVG but it’s really on a need-to-know basis. In fact, if you’ve worked with protovis, or even if you’ve worked with HTML and CSS, you probably know more SVG than you thought.
SVG is more flexible than protovis objects. The flipside is that constructs which were once simple in protovis become less obvious in SVG. But for those cases, d3 has recreated some native objects, even if not as many as in protovis.
Things that look the same, but which are different
There have been some changes in methods that have kept the same name since protovis – some minor, some more substantial. In any case, the basic ways of using these methods (like scale, color, data…) doesn’t change much. It’s only their more exotic uses who do change.