/bikesharing

Utilizing Pandas to extract and transform NYC CitiBike data along with Tableau to visualize findings.

Primary LanguageJupyter Notebook

CitiBike - NYC Bike Share Analysis

Our goal was to review bike share data in order to determine if a similar program could be established in Des Moines, IA (Pop. 215,408)

Results:

Tableau CitiBike Dashboard - Full results can be found on Tableau Public.

bike_use

By creating a heatmap for each hour of each day we can easily view the peak use times. For example, we can see Monday through Friday morning's and evening's have an identifiable increase, likely due to those who utilize the CitiBike system for commuting. Overall we can see the highest level of use was Thursday evenings at 6pm. trip_heatmap

trip_breakdown

use_repair

Summary:

The majority of bikes are used for 40 minutes or less, often on a weekday during traditional commuting times of 6-9am and 4-7pm. The reported gender of subscribers is largely male.

Additional suggestions on further visualizations:

  • Further visualization as to where the most frequently used bike share stations are in New York City along with their relation to landmarks and tourist attractions would surely help Des Moines determine the best locations to being an initial layout for their bike share system.
  • With repair and maintenace being a significant cost in a bike share program, it may be beneficial to locate a repair shop near the most utilized stations.