For travelers, there are not many things that have a higher priority than their safety. For people who have less information about the area, they might seem the price of the stay as a combination of convenience and safety. By visualizing the NYPD Public Safety and NYC Airbnb dataset on the NYC map with a layer of MTA system, I want to see if travelers have made the correct decisions by using this quick and straightforward price strategy.
After deciding to make a map, I immediately thought of the NYC safety map project my cousin sent me last August. While I did not have any knowledge of New York City, the only thing I can rely on while I tried to remote house-finding is this safety map.
Honestly, I’m not sure what dataset support this map, and I don’t know the standard of danger evaluation in this project. Even with this level of transparency, this safety map still gave me a brief understanding of city safety and the knowledge later become one of the most critical factors of my own living decision.
Methods, Results & Reflection:
This project is mainly relying on online data visualized tool — Carto. Carto is a user-friendly platform that provides a trail for beginners to explore the world of GIS.
At first, I imported the dataset one by one until I encountered the issues of color styling. In most of the situation, adding too many colors on a graph is not a good idea. However, I want to use the MTA route color to represent each subway line because it creates an intuitive understanding of these routes. The group function does not work for some unexplainable reasons, so I split the dataset by hand to form 2 layers for the purpose. I add another dataset that describes the precise location of each station because people can only interact with the subway system by entering entrances.
Below are two maps I made on Carto. At a glance, the two maps have a high level of overlaying. It is not surprising that the color distribution seems to be following the subway route. Upper Manhattan looks more dangerous than Lower Manhattan, which can also be seen in the NYC safety map in the inspiration part of this article.
I added up the color value by adjust the transparency of layers and trying to see if the price strategy works. If ” price =convience + safety (= least complaints),” the color distribution should be an equally darker color, for that higher price (darker red) + fewer complaints and lower price + more complaints. Even though we have already known that areas that cost more to stay at do have more complaints than cheaper regions, this is the hypothesis of the price strategy.
I would elaborate to use a more considered way to measure public safety and produce more comprehensive data visualization in future projects. Carto is a friendly platform. There are many functions I haven’t fully explored, and I would like to import more datasets to know the possibility of the usage of maps.
Below is the link of the Carto map. The password of it is “Pratt”
I linked all the datasets I used in the article, and I mostly use Kaggle and NYC Open Data for searching purpose.
20191204 . The Carto link has expired.