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Aggregating the data found in the Citi Bike Trip History Logs to identify and visualize new phenomena regarding city bike use.

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Interactive Dashboard

Module 18 - Tableau

Highlights

  • When examining station data and maps, we notice that popular stations have larger circles. These circles represent frequent starting and ending points for riders.
  • Many of these popular stations are consistent for both ride starts and ride ends.
  • Stations located in the outer areas of the city tend to have larger circles, possibly due to population distribution and limited alternative transportation options.

Spotlights

  • Rider behavior varies based on the time of the month: in the first half of the month, both customers and subscribers take longer trips on average, in the second half of the month, the number of rides increases, especially for subscribers.
  • Subscribers may be motivated to maximize their subscription value.
  • Gender influences bike usage: women, on average, take longer rides than men.
  • Although there are more male subscribers, women’s ride lengths stand out. This gender difference impacts the overall dataset.

Recommendations

To boost membership and ride usage, city can:

  • Promote deals for becoming a subscriber, focusing on popular stations.
  • Tailor marketing efforts based on target audience and gender.
  • Highlight leisure benefits for female riders and accessibility advantages for men.

Future work

  • Investigate how gender affects ride frequency at the start and end of the month.
  • Explore age-related impacts on dataset trends.
  • Examine bike utilization further, especially the bike with ID 15259, which stands out in terms of usage.

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Aggregating the data found in the Citi Bike Trip History Logs to identify and visualize new phenomena regarding city bike use.

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