Python / SQL / Processing | WINTER 2016
A 3D interactive data visualization to understand the dependency of the number of checkouts in Seattle Public Library over years and months
In this project, I wanted to look into the relationship of the number of checkouts and 24 hours of a day. In other words, I wanted to visualize the hourly activity graph of the library. This visualization gives an insight on how the timings of the library can be modified to make it more accessible and resourceful to the people of Seattle.
As a part of the curriculum, we had the access to data giving information of the number, type and other details of the checkouts from Seattle Public library over the past 9 years. This data has been collected as a part of the “Making Visible the Invisible” project by Professor George Legrady.
This was a 3D visualization and utilized three axes to depict the data. I used concentric circles lined up along the z-axis.
Every set of concentric circles corresponds to one day, and as we move along the radius, every concentric circle corresponds to the 24 hours in a day.
The smallest radius corresponds to midnight and the largest radius corresponds to 11 PM. These are color coded as well, to enhance the clarity of what time are we looking at.
The circumference of the arc corresponds to the number of checkouts at that time .
The visualization could be interacted using the mouse, to have different viewing angles. When the mouse position hovers over the index on the top left, only the data for that particular hour through the days would be visualized. The years could be interacted with using the arrow keys.
Choosing the right colors was a major challenge in this projects, as the different time durations could be very confusing and not be comprehended easily.
Colors of different hues against a black background was a good set of colors to make the data more understandable.
From this visualization, it was visible that the most active hours in the library are from 12 noon to 3 in the afternoon and these keep changing with the months. The trend can be observed over the years.