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. With the latest 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. The data consists of BikeShare information for three large cities in the US - New York City, Chicago, and Washington, DC.
You can get the data for each of the cities from the links provided in Bike_Share_Analysis.ipynb or else you can use the below link from kaggle to get the data.
https://www.kaggle.com/samratp/bikeshare-analysis
The files have to be downloaded from the above kaggle link and the file format should be of csv format
To analyze the data using python I have used jupyter_notebook. For the data analysis I have used pandas, numpy, for visualization I have used matplotlib.
Source files should be copied to the working directory. The Bike_Share_Analysis.ipynb should be executed from the top to bottom.
Python3, and created in Jupyter_notebook
Sridhar Varanasi