Introduction
The aim of this analysis was to deduce insights that could help improve the operations of the Citibike, which is New York City’s most popular bike sharing program. The data collected was for the year 2017, and obtained from this website.
Analyses performed
- Total number of trips taken in the year 2017
- User distribution of Citibike
- Gender distribution of Citibike users
- Age distribution of Citibike users
- Number of operational bikes for the year 2017
- Number of trips taken per month
- Number of rides with trip duration less than two minutes.
- Average distance covered per month
- Rush hour figures of trips taken
- Number of trips taken by subscribers and customers separately
- Ride duration of all trips
- Annual membership growth
- Number of one-day and three-day passes purchased per month
- Revenue distribution
- Heatmap of all Citibike stations
Tools used
- Python
- SQL
- Pandas
- Plotly
- matplotlib
- Google Maps API
Check it out
The code can be viewed here.