Over the past decade, bicycle-sharing systems have been growing in number and popularity in cities across the world. Bicycle-sharing systems allow users to rent bicycles for short trips, typically 30 minutes or less. Thanks to the rise in information technologies, it is easy for a user of the system to access a dock within the system to unlock or return bicycles. These technologies also provide a wealth of data that can be used to explore how these bike-sharing systems are used.
In this project, an exploratory analysis has been performed on the data provided by Motivate, a bike-share system provider for many major cities in the United States. The system usage is compared between three large cities: New York City, Chicago, and Washington, DC.
Python 3, Jupyter Notebook
import csv
from datetime import datetime
from pprint import pprint
The data has been included in data folder.
The original data was from:
(All the codes can be found in bike_share_analysis.ipynb document.)
(Some visualise results are shown here. For all the analysis, see bike_share_analysis.ipynb document.)
