This project includes data of bike share services provided in 3 Major Cities - NYC, Chicago and Washington. Using the data of respective cities an analysis is done using python and various third party libraries.
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, I will perform an exploratory analysis on data provided by Motivate, a bike-share system provider for many major cities in the United States. I will compare the system usage between three large cities:
New York City
Chicago
Washington DC.
I will also see if there are any differences within each system for those users that are registered, regular users and those users that are short-term, casual users. I will make use of Python(Pandas) to explore data and perform data wrangling to unify the format of data from the three systems and write code to compute descriptive statistics. I will also make use of a package that is not part of the standard Python library to help you visualize the data.
This project is my first exposure to the kinds of steps that a data analyst takes when they approach a dataset. For now, all you need is the general python programming skills and a desire to learn about the data analysis process!