robgmizzou / bikesharing Goto Github PK

In support of a business idea to emulate the model of Citibike in our hometown of Des Moines, I collected and analysed bikeshare data in support of a business plan pitch for an angel investor identified by my partner, Kate. In review of the New York City data, some key data like ridership demographics, trip timing and location data helped up begin to frame our business case.

Link to Tabeau Public Citibike Story

The majority of rides are very short, with 5 minutes being the most common ride duration.

Trips are concentrated on weekdays around traditional commuting windows.

Males account for the most quick trips, with genders converging on longer trips over 30 minutes.

Male and Female riders have the highest frequency of rides in commuting windows on Monday through Friday, weekend traffic is more evenly distributed.

Male subscribers are the highest frequency users, again primarily through the traditional work week.

Top starting locations (green heatmap) and stopping locations (red heatmap) both cluster around highest density areas in Manhattan.

Based on lessons taken from New York City, further data could be integrated to help us make a stronger pitch for our bike sharing project.
-What is the optimum number of bikes in a certain location? Is this based on nearby attractions, transit connections, residences or places of employment?
-What is the right number of bikes to depoy in our project?
-What is the average distance traveled?