Using the Area Breakdown Chart to view the timing of crime in Chicago

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It is possible with minimal effort in InstantAtlas to throw a set of statistical indicators into an interactive dashboard and view them using the default maps, tables and charts. While that approach is fine in many cases, my interest lies more in how you can delve into the toolbox of design options to create visualisations that are highly tailored to the data they show.

There are many chart types available in InstantAtlas to help you with your data visualisation, from bar charts and line charts to radar charts and bubble plots. In this post I’d like to feature the Area Breakdown chart. This is a bar chart that shows a breakdown of indicators (or associates) for the area (or areas) that the user selects in the map or table. It has a unique characteristic that sets it apart from the other bar charts in InstantAtlas: it is possible to assign a different colour to each bar. You could therefore shade each bar according to political party for example, if the bar chart is showing election results.

Colour can be used in all sorts of ways to help data interpretation. I liked the idea of using the colour of the bars in the chart to represent the time of day, one possible scenario being display of how different crime types vary over a 24 hour period. Visualisation of the timing of crime has been done before for US cities, and even in some detail for Chicago. However the City of Chicago data portal provides access to such a fabulous crime dataset that it is too good to pass up. Downloading the over 6 million reported incidents of crime going back to 2001 did seem overkill for this experiment so I decided to limit my dashboard to incidents reported in 2015.

Rather than burden the dashboard with numbers I kept this to just three key stats to leave plenty of space for the area breakdown chart. For the chart itself I used a black-to-yellow gradient to simulate the change in light intensity throughout the day.

To cover myself I will say that this example does contain some somewhat gratuitous use of graphical elements that are superfluous for interpretation of the raw data. But every data viz geek likes to break the rules from time to time!

Click HERE to view the report.

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