Introduction

A “play area” is a place designated for children by the City of New York. This term is used because while we may know them as “playgrounds,” this term is applies to spaces that may contain more than just a “play area.” Therefore, the space may not be designated for children alone. This distinction is important to make in the case of this visualization. The relationship between spaces designated for children, play areas, and another place designated for children, schools, will likely have a relationship. However, other factors may influence this distribution.

Inspiration

I chose this map as inspiration as it relates directly to the content of my visualization, play areas and green spaces. However, I chose it as a negative example.

While the side bar is full of information, it is not clear how that legend relates to the map. Here you can navigate more closely, but even then it still remains unclear to me how the legend relates to the map. Because of its chaotic nature, I chose to take a much more minimal approach measuring less attributes and in an attempt at making a more clear statement.

Materials

This visualization layers two shapefiles that reference the IDs of shapes. First, I chose two shapefiles from NYC Open Data to compare. I found one shapefile that represents the NYC School districts. That serves as the first layer in my visualization. Then, I found another shapefile representing play areas within NYC.

Since I am layering two shapefiles, I chose to work with Carto Builder, a new extension of Carto. I was eager to use a new visualization platform. And based on the files I analyzed, this choice seems like a good fit.

Methods

The first step in my process was to create a polygon and a point layer in the visualization. This image represents the default settings after importing the two shapefiles into two separtate layers.

Then I made adjustments to color to clarify the distinction between districts and also to emphasize the points.

I realized that since the districts are not being analyzed, rather, they are creating a new boundary in the map, that they do not really need a fill color. I removed the fill color, and I changed the point color to create more emphasis on count. Then, I removed all other distracting labels in the base map. I chose neutral colors for the boarder and the points to coordinate with the color scheme of the basemap.

Then I added titles and renamed the layers in the visualization. I also added a map description.

This completed my process below are images of the results and discussions of the findings.

Results

This map shows the NYC school districts as polygons and play areas as points. Upon closer inspection, I notice that some of the larger districts, like Staten Island, have very few play areas; however, there are also small school districts in the Rockaways that also have very few play areas. This map can be interpreted with a third factor, population. While the polygons help us see the school districts clearly, it takes a viewer familiar with NYC and its population distribution to make interpretations.

Reflection

Carto Builder is a trial base platform. I had thirteen days to work on my visualization. After the thirteen days, I no longer have access to this platform. In order to create visualizations that remain live, I may have to register for a paid account. Also, I found that Carto Builder does not have many of the same capabilities as Carto I have seen in demos. In those constraints, I feel confident that I did my best to accomplish the task. However, I would prefer to have some direct labeling, titles and some map identifiers, by borough specifically, if a live version of the visualization is not available.