Outline for Final Project

Qigao Wang
Data Mining the City
2 min readNov 29, 2017

View missed along New York City Subway

Team Member: Weijian Bi, Hui Liu, Qigao Wang, Shaochun Zhou

Background and significance:

The New York City Subway is one of the world’s oldest public transit systems, one of the world’s most used metro systems, and the metro system with the most stations. It offers service 24 hours per day on every day of the year. Thanks to the never-ending congestion of the city’s road transit, the NYC Subway, with its high capacity, congestion-free experience and flat fare, has become the first choice for most commuters of the city.

Though it may be one of the most mature underground transit in the world, traveling through NYC Subway may not be a wise decision for tourists. Here we are not going to judge its noise, delay, or trash problem, but we really feel sorry for tourists traveling beneath the earth. Just to save less than an hour in their whole lifetime, they will probably never know how much landmark they just missed!

As a group of four international students, some of us rely on 1 Train for daily commute from the campus to where we live. It’s just routine for us to kill the trip time reading books and miss everything happened along Broadway. So, we decided to create an imitation of “What you have missed traveling on 1 Train” to catch back the above grade life not only for ourselves, but also for more tourists to this city.

Goal: We plan to create an interactive google street view sequence above ground along Line 1 in order to show the missing scenes as much as possible.

Method:

1. Get the coordinates of points along Line 1 every certain distance using tools like GIS or Python

2. Download the street view images and code all the images

3. Create functions to display interactive and map along №1 train

Data:

Subway Lines Data: in Shapefile format

Google Street view API

Other supporting data

Teamwork distribution:

Collecting and cleaning the data: Weijian Bi and Hui Liu

Writing the Medium post and scripts: Qigao Wang and Shaochun Zhou

Building the classes and functions: All of the team members

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