Squirrels in Central Park: The Nuttiest Question — Writeup
After some initial discussion in the beginning stages of the project, we knew that we wanted to focus on an analysis of a lighthearted, but still intriguing data set. Thus, we scoured the internet for “out there” datasets until landing upon the Central Park squirrel data set which we ended up using. As there is not a real “squirrel problem” that could be answered or discussed with the data set, we instead decided to take an exploratory approach to our final visualization. Thus, we sought to create multiple visualizations that could answer a variety of questions regarding the park’s squirrel population such as their appearance, location, activities and behaviors.
Our main inspiration arose from a group of visually appealing projects/visualizations which worked with the same datasets. The first was a Tableau visualization created by Sarah Bartlett which created three heat-maps based on Hectare data for squirrel color, and included a map of Central Park on the side for reference. The second was a map on Central Park created by Nicolas Mieszaly overlaid with different color circles representing each individual squirrel found in the data set as well as pie charts for squirrel activities. Finally, the third was this global map of squirrel sightings mapped by The Squirrel Census.
Our data was obtained from the raw 2018 Central Park Squirrel Census — Squirrel Data found in the NYC OpenData portal. We included all squirrels in the data set but decided to forego including all the data points and instead focused on location data as well as appearance (gray, cinnamon, black), activities (chasing, running, foraging, climbing, eating) and behaviors (running away, indifference, approaching). We carried out a count of each of the different characteristics separately and used that to inform the visualizations we sought to create.
Regarding the design of our final project, feedback from our initial presentation made it apparent that many people were interested particularly in location data for the final visualization: Where would I go if I want to see a particular type of squirrel in Central Park? Do squirrels tend to conglomerate in areas with a lot of food sources? Do they gravitate or stay away from areas with many humans? For that reason, we focused on two main facets when designing the multiple visualizations in the final deliverable: using maps of the park in order to give users visual clarity, as well as heat maps which allowed us to show amounts of squirrels per region without overloading the map and allowing for ease of comparison between different squirrel concentrations (as seen in our multiple “squirrel activity” heat maps. Our main interactive element was allowing element to pick and choose which elements to filter for, and have the visualizations dynamically change based on user input.
For our project we stuck with d3 for creating our visualizations as well as HTML, CSS and Javascript for the creation of the page itself. We used the inbuilt d3 csv parser to load the data into the program and then adapted the heat map templates from the d3 graph gallery to suit what we wished to visualize. The visualizations for depicting activity and behavior ratios were made from scratch and through d3, while the interactive map of squirrels was created using mapbox. While we managed to implement most of what we wished to include in the final deliverable, if possible, it would’ve been ideal to add more detail and information to the heat maps.
Overall, the response to the final deliverable was positive and we believe that we managed to make an effective exploratory tool for the data set. Instead of focusing on answering a particular question or hypothesis, we feel that our final deliverable allows for the user to interact with a rather unwieldy data set in a fun and interactive way, while also including some information about our own experience for both context and to serve as a fun framing device.
Regarding future work, we believe it would be both prudent and extremely interesting to combine this data set with datasets describing central park geography, human foot traffic and maybe even weather to add richer context to the data set and grant the user more information to delve through as they seek to explore the magnificent world of Central Park’s furry inhabitants.
We would like to thank the members of COMSW4995 as well as critics Hannah Fresques, Christian Swinehart, Erica Greene and Eugene Wu for their invaluable feedback in the beginning of the project, as well as Prof. Agnes Chang for her role in teaching the class and giving us the resources necessary for the development of the final project.
