Bike Sharing Analysis
Description
This project focuses on analyzing bike sharing data from Capital Bikeshare in Washington, D.C., USA, for the period between January 1, 2011, and December 31, 2012. The data is aggregated on an hourly basis. This means that no initial and final locations of the individual rides are available, but only the total number of rides per hour. Nevertheless, additional meteorological information is available in the data, which could serve as a driving factor for identifying the total number of requests for a specific time frame (bad weather conditions could have a substantial impact on bike sharing demand)
Problem Statement
This project seeks to investigate how temporal features and weather conditions affect hourly bike-sharing demand, aiming to uncover meaningful insights that can enhance operational strategies and service responsiveness
Dataset
Bike-sharing rental process is highly correlated to the environmental and seasonal settings. For instance, weather conditions, precipitation, day of week, season, hour of the day, etc. can affect the rental behaviors. The core data set is related to the two-year historical log corresponding to years 2011 and 2012 from Capital Bikeshare system, Washington D.C., USA which is publicly available in http://capitalbikeshare.com/system-data. We aggregated the data on two hourly and daily basis and then extracted and added the corresponding weather and seasonal information.
Dataset characteristics
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Analyzed Capital Bikeshare data to understand bike-sharing demand influenced by weather and temporal features.
Timeline
Dec 31, 2010 - Dec 30, 2012