Authors: Alla Hale, Adam Yang, Armand Kok
In recent years, ride sharing services, lead by Uber, have been rapidly growing in popularity. A big part of the rising popularity of these services is the convenience that allows users to travel on their own timelines, without the hassles of using their own vehicles. They also have an advantage over taxi services because they allow users to plan their trips more accurately by providing estimated arrival times and cost before commitment.
Data describing the use of these services can shed light on how people get around in a city. Analysis of when, where, and how people use these services can be used by rideshare providers to help optimize their operation, or by city administrators (e.g. city planners, transport authorities) to help minimize traffic or even improve public transportation systems.
Uber usage is quite high in New York City. This analysis will focus on Uber data from NYC in 2014. This data will be used to understand the effect of weather and other factors on Uber usage. Additionally, the variation in Uber usage will be analyzed by day, month, and time of day. The effects of special case variations, such as severe weather events or key holidays will also be identified.