Analysis and prediction of bike sharing usage in New York City

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Starting Point

  • CitiBike is a large bike sharing provider in New York City
  • With over 7,000 bicycles and more than 328 stations in the urban area, around eight million trips were made in 2015
  • The team had a wealth of CitiBike data sources to predict future use

Objectives

  • Predict user numbers for specific stations to plan marketing measures
  • Predict the demand for bikes at specific stations
  • Identify areas with a lack of rental stations
  • Examine how the proximity of bike stations to subway stations affects the user numbers

Course of Action

  • Preparation and unification of existing data
  • Execution of a time series analysis in Tableau
  • Visualization and clustering of the rental locations
  • Calculation of the distance between rental stations and metro stations based on geospatial data

Results and benefits

  • Successful proof of concept: visualization of the data and prediction of the use of the CitiBike service
  • First ideas for expanding the bicycle network based on actual usage data
  • Possibility of forecasting user behaviors for specific bike stations

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