As part of a mock business proposal for a Des Moines-based bikesharing program, Citi Bike data from New York City was analyzed to determine trends in use and user demographics. August 2019 data was retrieved from the Citi Bike website since August is a peak use period for bikeshare programs. Data was visualized using Tableau Public and is available online for viewing.
Data findings are annotated on each Tableau story slide, but are summarized below:
- Most trips by users are less than an hour and peak around 5 minutes.
- Most users are male.
- Peak use occurs Monday through Friday between 7-9 AM and 5-7 PM, which may be associated with a commuting workforce.
- As demonstrated previously, most users are male and peak use (regardless of gender) occurs Monday through Friday between 7-9 AM and 5-7 PM.
- Top users are subscribers and male.
- Top Starting Locations were located in Manhattan, possibly the result of visitors biking to tourist locations.
- Top Ending Locations largely mirror top starting locations, suggesting that individuals tend to bring backs back to starting locations.
Over all, data suggests that that most users are male subscribers. Trips tend to be under an hour, with most only being 5 minutes. Peak use occurs Monday through Friday between 7-9 AM and 5-7 PM (irrespective of gender). While the timing of peak use suggests that heaviest users are commuters, top starting and ending locations suggest that tourist destinations can expect elevated use as well.
Two additional visualizations that would be useful for the business presentation include 1) a line graph of number of subscribers versus age bracket and 2) a heat map of pairs of bike stations with color/intensity based on the count of connecting trips between the two stations. The first additional graph would help capture more details about the heaviest user group (i.e. subscribers) and how it might align with the Des Moines age demographic. The second additional graph would help understand what locations folks traveled to/from the most and thus what locations are ideal for station placement.
- Data:
- Visualizations: