Shared Bike Usage Analysis

Abstract

This essay delves into the realm of data analytics to examine patterns and trends in shared bike usage. Leveraging large-scale datasets from shared bike platforms, the analysis encompasses factors influencing usage, including geographical patterns, temporal variations, and user demographics. The essay employs advanced data analytics techniques, such as machine learning algorithms, to uncover hidden insights and predict future usage trends. By scrutinizing the data, the essay aims to contribute valuable insights for optimizing shared bike systems, enhancing urban mobility, and informing sustainable transportation policies.