Module # 4 assignment [Visual Analytics]





In this week's dataset analysis, I opted for a distinctive visualization approach, as illustrated above. Instead of the conventional U.S. map, I found this presentation style to be more intuitive for interpreting the data. Unlike the typical geographic map that aggregates collisions for entire states, our dataset includes data for individual state counties, making it challenging to discern specific details in a standard map view.

In the showcased visualization, each square corresponds to a distinct county within various states. This format enables us to pinpoint the exact locations of each accident, offering a granular perspective rather than a holistic view. Unlike the state-level summary presented on a traditional map, this approach allows for a more detailed examination of where each incident occurs within individual counties.


As observed in the visualization, the squares positioned towards the lower right corner indicate instances where there are either zero or only one collision involving vehicles, and no collisions involving persons.


As we navigate towards the center of the graph, a discernible trend emerges – both the number of collisions involving motor vehicles and those involving persons show an increase.

In the top-left corner of the visualization, we observe the highest frequency of collisions involving both motor vehicles and persons.

This approach enhances the granularity of our analysis, providing a comprehensive understanding of accident distribution within different counties and states.


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