ahmadyasser1 / udacity-us-bikeshare

The Udacity US Bikeshare Data Analysis project is a hands-on project that involves using Python to explore and analyze bike share data from three major cities in the United States: Chicago, New York City, and Washington DC. You will gain insights into trends in bike share usage in different demographics, locations, and times of the year.

Udacity-US-Bikeshare

In this project, I explored data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington. I wrote the code to import the data and answer interesting questions about it by computing descriptive statistics. Also, I wrote a script that takes in raw input to create an interactive experience in the terminal to present these statistics.

In this project, data is provided by Motivate, a bike share system provider for many major cities in the United States, to uncover bike share usage patterns. The system usage is compared among the three cities.

Randomly selected data for the first six months of 2017 are provided for all three cities. All three of the data files contain the same core six (6) columns:

-Start Time (e.g., 2017-01-01 00:07:57)

-End Time (e.g., 2017-01-01 00:20:53)

-Trip Duration (in seconds - e.g., 776)

-Start Station (e.g., Broadway & Barry Ave)

-End Station (e.g., Sedgwick St & North Ave)

-User Type (Subscriber or Customer)

The Chicago and New York City files also have the following two columns:

-Gender

-Birth Year

Statistics Computed

-Popular Times of Travel

-Popular stations and trips

-Trip Duration

-User Info

-Sample of Raw Data (Optional)