Through this short visualization project, I was interested in studying Pittsburgh depression rate because I believe depression is one of the most common disease in today’s alienated society where individuals often have to deal with complex problems alone without support from others. In particular, I was interested in the extent and severity of the mental state across the various demographics of Pittsburgh. Moreover, I wanted to understand the role gender plays in depression, and how a sincere companionship helps people recover from depression. All data visualization is based on data from data.gov and pittsburgh alleghaney blah blah. [ add links ]
During the process of visualization and working with the data, I discovered that women and singles are more vulnerable to mental illness–or at least the data says that. Whether this data actually means women are more vulnerable to depression or they are more open to seek for help is still unknown. Percentage of married household was definitely lower in higher depression areas. This may means that individuals with mental illness could recover from depression faster if there is someone who sincerely cares about them and listen to their concerns.
For future revision, I would like to add toggle feature between grid view and map view in order to provide more clear comparison between neighborhoods. Map view was effective to communicate the context, however I believe grid view will help users make easier comparison in amount and density.
Sneak picks of process
Please refer to my Medium Post [add link] for detailed process documentation about this project.