In the Project 1 of Metis Data Science Bootcamp (Singapore Batch 5), we are tasked on exploratory data analysis (EDA) of MTA turnstile data to advise a fictitious non-profit organization, WomenTechWomenYes (WTWY) on the optimal placement of street teams (at entrances to NYC subway stations) for social engagements. WTWY wants to invite interested individuals to its annual gala to raise awareness and increase participation for women in tech, and the street teams’ agenda is to collect as many emails as possible and give out free tickets to the gala. In my analysis, I have made the following assumptions:

Assumptions

  • WTWY is constrained by time and manpower resources, hence insights from my analysis should identify top stations by traffic, as well as the peak periods in those stations.
  • Individuals who are interested in tech have a higher probability to be encountered in city center with a denser cluster of tech corporate offices.
  • The WTWY gala is imminent, and a week of MTA turnstile data is analyzed as an sample for the weeks leading to the gala.

#data-visualization #new-york-city #data-science #metis

MTA Turnstile Traffic Analysis to Optimize Street Engagements
2.15 GEEK