Malleable Musings

March 27, 2010

So how many is that. Where, what and who…

Filed under: Data Visualisations, simple hacks — Brendan @ 12:03 am

I often have fairly complex sets of data that I need people to understand.  Often what I need to represent is geographical market information, i.e. country related data.

The sort of common questions I get include things like who and where are our students, how are courses growing in certain markets etc.

I’ve found that this sort of data is often best represented in some graphical format.

So I’m always interested  when I see a new way of laying the data in new ways that can be easily understood.  The latest I’ve discovered is producing kml output that uses the Google Chart api and opens in Google Earth to produce images like this.

It’s a shame that the kml doesn’t quite work the same way in Google Maps as it does in Google Earth.  Maps is more accessible in that it doesn’t require a plugin to work on the web. However the pie charts are icons and in Google Maps the icons are apparently automatically scaled to 32×32 pixels.

Because of wordpress limitations I can’t easily show the Google Earth version above and have opted for a screenshot instead. Although if you have Google Earth installed you just use the spreadsheet to produce a kml file and simply open it to get the full effect.

To enable me to generate these sort of images quickly I’ve made a spreadsheet in to which I can quickly enter data and then when I flip to the KML tab I can just copy and paste the text that’s produced into notepad.

Then it’s just a simple case of saving the file and double clicking on it in to open it up in Google Earth.

What I love about this method is how flexible it is.  I may well alter the spreadsheet so the output can be customised more easily.  e.g. at the moment on the settings tab I just allow the name, description and something that helps manage the scale of the charts to be customised.  I could easily see how I could customise the chart further (e.g. include the dataset labels, choosing colours, choosing the type of chart etc) or maybe even customising the numbers of data series used.


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