My research question for this project was how I move around the city. Over the course of one week (March 28-April 3), I wanted to explore when, where, how long, how far, and how (mode) of my travel. I also collected data on outside factors that may influence my transportation choices, such as temperature and precipitation.

This question interests me because, as a New York City resident, I have a variety of transportation options available to me, such as trains, Citibikes, buses, and walking that are not available to people who live in most parts of the country, who are generally restricted to car travel. Because I have so many options, I was curious about exploring which modes of transportation I tend to gravitate towards, as well as how long and far I tend to travel. Living in a densely populated location such as Manhattan, I would hypothesize that I don’t have to travel very far to go to work, run errands, and see my friends in comparison to someone living in a less densely populated area.

The sole audience of this visualization is myself. I don’t think anyone else would be interested in knowing this information, but I am personally curious about learning more about my habits, so this was a fun exercise to complete.

How far do I travel each day?

This visualization shows the total distance I traveled each day, broken down by transportation type. I chose to use a stacked bar chart because it visualizes the data by day as well as by transportation type. This chart shows that I travel farthest on Tuesdays, Wednesdays, and Thursdays, which are days that I travel uptown for school and work. On other days of the week, I stay closer to home and prefer walking or biking to get around.

How long do I spend traveling each day?

This visualization shows the total time spent traveling each day, broken down by transportation type. Similar to the previous visualization, I chose to use a stacked bar chart because it visualizes the data by day as well as by transportation type. I chose to visualizes these variables because it acts as a contrast to the previous distance traveled graph. While the previous graph showed that I traveled the most distance by the train by a wide margin, I spent a larger proportional amount of time using slower modes of transportation like walking and biking. While I didn’t cover as much ground, this graph shows I spent a large amount of time biking and walking.

How far did I travel using each mode of transportation in total this week?

This visualization shows how far I traveled by each mode of transportation in total throughout the entire week of data collection. I used a bubble chart because I wanted a simple, overall view of the total distance traveled by each type of transportation. I covered the most ground using a train, which comes across in the scale of this bubble compared to the other transportation types. In contrast to the bar charts, the simplicity of this graph conveys that I chose trains, rather than walking, biking, or cars, for longer trips.

Next Steps

There are so many options to further explore this topic! I think the visualizations would tell a much more interesting story if I were able to collect data over a longer period of time (1) to have more data, and (2) to have data that spans across the many seasonal fluctuations New York experiences in a year. I would be very interested to visualize this data by season.

For this project, I collected data on temperature and precipitation to see if it would correlate with my transportation habits, but it ultimately did not, so I didn’t end up using these data in my visualizations. Again, if I had more data to work with, I think these variables could tell a more interesting story. For a larger scale project, I would also like to use my start and end points to explore my most visited locations throughout the city on a map. A variable I might add to tell this story would be the coordinates of my start and end points of my travels.

Lastly, I would be interested in comparing my travel habits to someone living in a vastly different area. For example, I’d love to compare my data to someone living in a very hot or cold climate, or a rural area.