Introduction + Visualization Inspirations + Research Questions
When growing up, I had a regular habit of going to the library. In elementary school, this was through school trips and my parents taking me. In middle school, this was me going to a library near my school to borrow books on my own. Then a pause, and now as a graduate student who knows how expensive books have gotten, the library has once again become a reliable place to find almost any book I want to read. Knowing how vital it was to have such a valuable resource while growing up, I figured a fun map visualization could be to answer the research question: Within the school districts in the boroughs of NYC, how is the library system distributed?
Aside from my childhood nostalgia of going to the libraries near my schools, I was also inspired by this visualization by a previous Pratt student, in which they visualized the distribution of libraries in NYC. My goal is to take that a step further.
Datasets + Methodology
I collected my datasets through NYC Open Data. Both were titled “School Districts” and “Libraries”, and when accessing them, I could see a Google Maps visualization of both to ensure that they were within the boroughs of NYC. Both were downloadable as shape files. I used the QGIS tool, which is an open-source geographic information application that will allow me to visualize my shape files. Once in GCIS, I imported the files and edited the properties so that the boroughs are visually present, alongside the location of all the libraries in each borough and within each district.
Results and Findings
To answer my research question: (Within the school districts in the boroughs of NYC, how is the library system distributed?), I’ve been able to notice a few insights. Staten Island is noticeably the borough with the least amount of libraries, but as a district has more than most districts, except for one. In doing some research however, I saw that the largest populated district is Staten Island’s district, but that district is noticeably less dense in library locations than Manhattan’s downtown to midtown district (District 2).
Manhattan is the smaller of the boroughs, but is the most dense overall within its districts for having library locations. This is most likely due to it being the main borough for NYPL locations alongside Staten Island and the Bronx; the difference is Manhattan is also more populated as a borough than Staten Island, causing it to appear more dense while Staten Island’s locations are more spread apart. Even the Bronx has slightly more locations than Staten Island, though the further up one goes in the borough, the more spread out it appears.
Also notable is the distribution of Queens and Brooklyn libraries. These two boroughs being the bigger boroughs with more districts would naturally mean having a lot of library locations, but it’s also much more evenly distributed. I’d say out of all the boroughs, Brooklyn appears to have the best distribution within districts, as there are noticeable gaps in other borough districts with a lack of library locations. It’s important to note that Brooklyn and Queens having just as much as Manhattan, Bronx, and Staten Island combined is largely due to the fact that they each have their own respective library institutions, thus that may play a factor into how well it is distributed since they’re functioning under different systems than NYPL.
Reflections
This lab felt much easier to do than the last lab with RStudio, which made the whole lab more approachable. If I had time, I would have looked more thoroughly into other kinds of datasets that could help further the visualization (i.e. individual school locations in relation to library locations). I also think the “School District” may have not been the best to work with because I had to manually input the borough colors (which wasn’t too bad since there are very few districts, but would have allowed for making the legend to be easier too). I think because I had a very hectic time trying to get this done that I do wish I could have given more of my mind and time to working on this, but with what I had, I think visually I made it work.
Sources
Image: Bowman, E. (2019, November 30). “We Wanted Our Patrons Back” — Public Libraries Scrap Late Fines To Alleviate Inequity. NPR. https://www.npr.org/2019/11/30/781374759/we-wanted-our-patrons-back-public-libraries-scrap-late-fines-to-alleviate-inequi
S. (2022, April 21). Libraries in New York Neighborhood. Libraries in New York Neighborhood – Information Visualization. https://studentwork.prattsi.org/infovis/visualization/libraries-in-new-york-neighbourhood/
Welcome to the QGIS project! (n.d.). Welcome to the QGIS Project! https://www.qgis.org/en/site/
School Districts | NYC Open Data. (2013, January 29). NYC Open Data. https://data.cityofnewyork.us/Education/School-Districts/r8nu-ymqj
Library | NYC Open Data. (2014, November 18). NYC Open Data. https://data.cityofnewyork.us/Business/Library/p4pf-fyc4
2023 largest school districts in the New York City area. Niche. (n.d.). Retrieved April 16, 2023, from https://www.niche.com/k12/search/largest-school-districts/m/new-york-city-metro-area/