Data Exploratory on Taxi Data in New York City

With increasing amounts of urban data being collected and made available, new possibilities of data-driven research emerge lead to changes in people living through scientific proof-based decision-making and strategies. In this paper, the researcher concentrates on an urban data set of particular significance which is taxi rides. Taxis are essential instruments, and taxi-related information can provide groundbreaking insight into different facets of city life, from economic activity and human behavior to mobility trends. Taxi data involves geographical components as well as several variables associated with each ride. Throughout this research, data insight is gain through data pre-processing, feature engineering and data exploratory analysis on the city transportation. The data exploration reveals the time, geo-location details, taxi fare and optimal fleet size of taxi transportation in the city. This transformation of raw data enables researcher, data scientist to have the meaningful insight into the data and understand the mobility pattern of New York City.