This map is intended to give the user an idea of which Manhattan libraries are busiest. It visualizes the location of each library as well as the total attendance and reference transactions. The library’s neighborhood population is also visualized to give the user a sense of what percentage of the community each library serves.

To make this map, I used 4 datasets found on OpenData NYC, including Library Location, Library Branch Services – Manhattan, Neighborhood Tabulation Areas and NYC Population by Neighborhood Tabulation Areas. I cleaned the data in OpenRefine, making sure relevant column headings in the different datasets matched so analysis could be run in Carto.

I created a map with each dataset as a layer. I then ran an analysis to add columns from the Branch Services data into the Library Location data layer. This allowed me to add the Total Attendance and Reference Transaction data and style the points on the map based on this data. Attendance numbers were tightly grouped with a few outliers so it was hard to visually differentiate but with some trial and error the best way to communicate both was to use color to represent Attendance and Reference Transactions for size.

I ran the same type of analysis, adding the population data to the Neighborhood Tabulation Area dataset. This allowed me to style the map, using color to visualize the neighborhood populations where the libraries are located. I decided to include this because without it, there seemed to be a missing piece of the overall picture when the map only included the branch service numbers. It seemed important to contextualize larger and smaller attendance numbers by also showing how many people the libraries are potentially regularly serving.

I also had to add widgets so the library and neighborhood areas would only include Manhattan. I included pop ups so users can see the actual numbers but while I did experiment with legends and other background options, they did not serve any benefit so I excluded them.

As is, it’s not the most useful map. It’s hard to take away any real information just by quickly looking it over but with a little more customization it could become so much better. I toyed with them as much as possible in Carto but being able to further customize the buckets for color and size based on the attendance and reference data would make the visual information, and goal of the map much more clear.