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By admin, June 23, 2011 3:43 pm

The Stanford Visualization Group have been responsible for a number of fantastic tools for supporting information visualisation work. One of the inherent problems in creating data visualisations is that you usually do not get the data in a format that is particularly easy to work with. Cleaning up the data is one of the first things that you must to, so that you can take out extraneous data points, pare down to what you want to actually work with, and then format the information logically, so that it will be easy to incorporate into your visualisation software or code.

This step, data cleaning, is usually a real hassle and Excel is not very good for the task, because it’s not really made to do this sort of thing. Although you can delimit by commas, tabs or arbitrary characters, it’s a pain to write regular expressions that allow you to take out things or re-order them. You can write scripts to do this, but then you’re busy writing scripts instead of creating a visualization.

That’s why I’m very excited about Wrangler, a new tool for data wrangling that substantially reduces the pain associated with this process.

Check out their video and head on over to try it for yourself!

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By admin, July 7, 2009 4:34 pm

I’ve been honing my houghts on this for a while, because many people have been asking me why pie charts are problematic. On the surface, they seem like a good way of presenting part-to-part and part-to-whole relationships. And hey, everybody uses them, so they must be good, right? Unfortunately, they make little use of our best capabilities for visual perception and rely on comparing angles and areas – two of our weaker visual tasks, according to many perceptual studies.

Their principle faults are:

1. They force us to compare either 2-D areas or lots of angles,
2. They take a lot of time to interpret using a legend, and
3. They miss the point!

For example, take the pie chart below. Imagine that you had to determine the quantities represented by the slices or even easier, to simply rank order them from biggest to smallest. Think about how long it would take to make your best guesses and how much you’d have to rely on rough estimates by either: 1) evaluating the relative sizes of the slices or 2) comparing the angles of the slices where they converge at the centre of the pie:

It’s pretty tough going. Just how much bigger is the red slice than the orange slice, expressed as a percentage? Furthermore, adding labels actually complicates matters because your eyes have to bounce back and forth in order to know what you are making comparisons about. In this case, perhaps the number of animals adopted from a pet shelter:

It’s visual ping-pong folks, and it’s not fun. What, you say? Just add the percentages into the slices and that will help you to solve the estimation problem. Let’s take a look:

It does indeed make it easier to see that there were almost twice as many Rabbits adopted as Hamsters. It might even be easier if my version of Excel allowed me to put the labels in the slices (though it doesn’t!). However, this misses the final point: that if we have to rely on displayed numerical values to get the answers, it would be better (and easier) to just show them without all of the visual nonsense:

There is is. Simple, straightforward, and easy to read. It might not make for pretty pictures in the boardroom. But ask yourself if you are really just trying to entertain your audience or whether you are trying to communicate something effectively, precisely, and meaningfully. And in that case, it doesn’t matter if that last line is a Platypus or a Profit Margin.