Introduction
Considering that New York is an international metropolis, it is astonished me when I first time heard about that most of the blocks have parks or green spaces in NYC because I thought there must be dense skyscrapers in NYC. Based on the curiosity of knowing the NYC parks, I tried to use data visualization skills to find some interesting.
The database of the park properties, which contains parks’ area, zip code, type, etc., is from the New York City data. What is the distribution of the NYC parks? Which area of NYC has more parks? How much the differences among each of parks? To solve these questions and better visualize the data, I found three examples and tried to imitate them.
Methods
The software I used is Tableau, which can help people quickly analyze, visualize, share information and understand the data. More than 42,000 customers get results quickly in the office or anytime, anywhere using Tableau. Tens of thousands of users use Tableau Public to share data in blogs and websites. The first step is inserting the database into Tableau, and then drag the data into the sheet screen. On the right of the interface, users can click “show me” button to select a specific image type. Also, the “Marks” panel has several icons for adding various elements on the image.
NYC parks acres
In order to clearly display the statistics which are related to location, the map is one of the effective images to show various information. For example, here is a map of New York City showing rates of pedestrian foot traffic.
Figure 1. A map of New York City showing rates of pedestrian foot traffic, with the darker the green indicating higher rates. Credit: Placemeter
From the figure 1, it is clear to find the area where people usually pass by. Similar to this foot traffic map, NYC parks are distributed different zones, so it is effective to show the NYC parks acres by applying this figure’s style.
Figure 2. NYC parks acres
Figure 3. NYC parks number in each zone
Here are two figures, and each zone on this map has different colors, which the zone are divided by their zip code. Figure 2 shows NYC parks’ area. The deeper the color is, the bigger the park area is of each zone, and the number shows the sum of the park area ( unit: acres) of each zone. Figure 3 color’s difference shows the different number of parks, and the number is the sum of park number of each zone. It is quite interesting to compare these two images. For example, in the upper Queens, the park area is huge, 898 acres; however, there are only 15 parks there.
NYC parks‘ classification
There are multiple kinds of images to present the various classification, such as these following images.
The NYC parks database contains several classifications of the parks. I imitate the upper images to create the following images:
Figure 4. NYC parks type category
Figure 4 shows the different types of the NYC parks. The garden is the maximum type of NYC park, which is 343; however, the jointly Operated playground, playground, neighborhood and triangle/plaza’s amount are similar to the garden.
Figure 5. NYC parks are waterfront or not
There are 166 parks are waterfront, and 1844 are not waterfront.
Figure 6 NYC parks classification
Also, the chart bar is another effective way to clarify the classification. it is obvious to see the neighborhood playground is the most type of the NYC parks. Each of the classifications has been listed in the image. Based on this image, the quantitive record can infer some qualitative ideas. For instance, the large park is not the most type of the NYC parks, instead, the neighborhood playground and the sitting area are more normal. Maybe the NYC people more focused on the relaxing places close to their neighbor.
The Future trend
Although data visualization is not a novice concept in current time, it still has the powerful impact when applied to many industries, especially in the era of artificial intelligence. Bunch of data fulfilled in people’s life; no matter Tableau or other software, there are infinite data need to be analyzed for finding the necessary information which requires the need for that software. I believe the skills of data visualization and the skills of using these tools are significant to adapt the future.