Identified subway stations with the highest traffic between the hours of 10 PM to 5 AM for possible food vendors to tap into the market of "late night revelers" or evening shift workers. Techniques: exploratory data analysis using Pandas, data visualization using Tableau.

1. “Late Night Revelers”
Metis Consulting Group
Jay Gondin, Anthony Kim, Rafael Ramos,
Anny Truong, Nathan Wieneke
Operation:

2. Introduction
● Target clients
○ Food trucks,
○ Food stands,
○ Other mobile food vendors
● Target end-users
○ 10:00 pm to 5:00 am,
○ “Revelers”
○ Early/late commuters
● Assumptions
○ Users are drawn to food both when entering
or exiting subway
○ Users are willing to interrupt their transit to
purchase food

3. Data
● NYC MTA Turnstile data
● 373 Stations
● From 12/26/2015 - 4/1/2016
● Problems with data:
○ Turnstiles malfunctioning or being replacement
○ Accurately categorizing late evening vs. early morning

4. Discussion
● The market is bigger on the
weekends than on the
weekdays in the evenings.
● The most useful locations may
not be the ones with the
highest traffic
● Top 5 Stations (Weekends):
○ Times Sq - 42 St
○ 34 St - Herald Sq
○ 14 St - Union Sq
○ Bedford Av
○ 50 St

5. Heatmap of Saturday night (Sunday early morning)

6. Heatmap of Sunday night (Monday early morning)

7. Bubble Histogram of Total Traffic

8. Further Development
● Compare with competition density (other food vendors,
restaurants)
● Different types of food to cater to different types of
commuters
● Breakdown by season
● Estimate revenue
● Improve anomaly detection
● Account for traffic that does not leave station