Copyright 2007-2012

data visualization/python/processing1.0/2012

The motivation behind this project is to uncover insights on life satisfaction, happiness, and other wellbeing-related indicators, for various demographic clusters in modern, typically urban environments.

Using UK as a case study for societal well-being in urban environments, I've designed and implemented a number of visualization elements that can assist in detecting patterns that are applicable in any urban environment.

The visualized data is a recent subset of the various demographic and wellbeing-related data aggregated by the Office of National Statistics of the UK.

The visualization is made up of three sections, or "tabs." The Categories + Indicators tab displays an interactive, dynamically constructed small-multiples view of the data. The Region + Indicators tab encodes the various indicators as the saturation values on the map of the UK. Finally, the Correlations tab displays a simplified, interactive scatterplot view to allow the data to be inspected to visualize any correlation patterns between the indicators.

Google Refine and Excel were used to clean and format the data. Processing was used as the implementation framework of the visualization. The dropdown menus and checkbox elements utilize the ControlP5 library.

http://rbknrbkn.com/files/gimgs/th-8_Screen Shot 2012-11-23 at 11_40_43 PM.png
http://rbknrbkn.com/files/gimgs/th-8_Screen Shot 2012-11-23 at 11_40_59 PM.png
http://rbknrbkn.com/files/gimgs/th-8_Screen Shot 2012-11-23 at 11_41_12 PM.png