After the COVID-19 pandemic, most people change their behavior and daily routine. We follow the social distance to keep safe, work remotely and spend most of our time at home. In this project, I decided to explore how many New York residents still have to go working, or they can choose from home. From the analysis of people’s mobile devices, we can track people’s location and know where they stay and how many hours they spend in a place. This map shows that the average number of full-time behavior devices is much higher than the average number of part-time behavior devices. That result proves that most New Yorkers follow the policy and work from home. I think the map is handy evidence for the research on human behavior-changing in 2020.
I am inspired by the map below (Figure 2), Social Distancing Metrics – United States of America. I found out in the spatial data catalog on the Carto website. The map shows after the COVID-19 pandemic, people are currently engaging in social distancing. The map helps us to understand what is actually occurring at a census block group level. The map is provided by SafeGraph, which is offering a temporary Social Distancing Metrics product.
Based on the inspiration from the social distancing map, I decided to use its dataset to create another map presenting the changing of people’s working behaviors after the COVID-19 outbreaking. The datasets have collected the devices from 21st January 2020 to 16th June 2020. I assumed that before the pandemic. I use the mapping tool, CartoDB, powerful software as a service cloud computing platform. Carto provides GIS, web mapping, and spatial data science for data spatial analysis and information visualization.
My Design Process
After I downloaded the dataset from the Carto website, I observed the information from the data category (Figure 3) and tried to find out if there is any useful information I can extract from the data. Then, I use the table of variables which gives a further explanation of each column (Figure 4).
I created a new project and import the “distance_traveled_from_home” as a first layer (Figure 5) to show people at the home with their devices, the data included during the time period. And I changed the color to teal tone as similar to the map’s original color. I also make a 50% transparency of the color themes since the first layer is not the main topic I want to target in this map. I add the widgets and legend to help explain the graph.
Then, I added on the data “part_time_work_behavior_devices,” which is calculated by the number of devices that spent one period of between 3 and 6 hours at one location at home. And also the devices showed during the period of 8 am – 6 pm in local time. This number does not include any device that spent 6 or more hours at a location other than home. I changed the color and style to a purple/pink square that can distinguish from the green background. Also, I generated a legend with gradient colors base on the number of the devices. (Figure 6)
Finally, I created a layer from the data “full_time_work_behavior_devices,” which represents the number of devices that spent greater than 6 hours at a location other than their home during the period of 8 am – 6 pm in local time. I changed the color to yellow and red dots that can not only make a difference from the part-time work behavior devices but also distinguish from the green background. Also, I generated a legend with gradient colors base on the number of the devices. (Figure 7)
I added the pop up on each block group to show their information as below:
- Geoid: The unique 12-digit FIPS code
- Number of Devices: device_count
- Devices at Home: distance_traveled_from_home
- Part-time Work Behavior Devices: part_time_work_behavior_devices
- Full-time Work Behavior Devices: full_time_work_behavior_devices
Based on the following design and analysis step by step, the map shows that the average number of full-time work behavior devices is over twenty than the average number of part-time work behavior devices. Therefore, we can assume that most New Yorkers chose to stay at home and work remotely during the 2020 pandemic.
I think the Carto is a powerful spatial map tool to represent data and help us to read the data from a geographic perspective. And also, it can customize the color, style, legend, even the pop-up details. I feel it is very convenient that I do not need to code and only tick and untick the checkboxes to create a widget showing bar charts or the key number. The only problem with this data visualization process is that I assume that before the COVID-19, most people are “not” work at home. The dataset was collected between January to June in 2020, so I cannot compare it with the time before, such as 2019.