This project is part of Udacity course of Data Analysis Nano Degree program.
In this project, I used Python to explore data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington. I wrote code to import the data and answer the questions about it by computing descriptive statistics, I also wrote a script that takes in raw input to create an interactive experience in the terminal.
- Python 3
- Numpy and Pandas
- A text editor, like Sublime or Atom.
- A terminal application
- most common month
- most common day of week
- most common hour of day
- most common start station
- most common end station
- most common trip from start to end
- total travel time
- average travel time
- counts of each user type
- counts of each gender (only available for New York City and Chicago)
- earliest, most recent, most common year of birth (only available for New York City and Chicago)