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The project was created 2018-10-13 This README file was created 2018-10-27

Bikeshare US

The project is about comparing usage in a bicycle-sharing system between three large cities: Chicago, New York City, and Washington, DC.

A python script is created that takes in raw input to create an interactive experience in the terminal that answers questions about the dataset. Following questions will be asked and answered depending on the user input:

Would you like to see data for Chicago, New York, or Washington? Would you like to filter the data by month, day, or not at all? (If month is chosen) Which month - January, February, March, April, May, or June? (If day is chosen) Which day - Monday, Tuesday, Wednesday, Thursday, Friday, Saturday, or Sunday?

Following information will be given:

1 Popular times of travel: most common month most common day of week most common hour of day

2 Popular stations and trip: most common start station most common end station most common trip from start to end (i.e., most frequent combination of start station and end station)

3 Trip duration: total travel time average travel time

4 User info: counts of each user type counts of each gender (only available for NYC and Chicago) earliest, most recent, most common year of birth (only available for NYC and Chicago)

There is also a possibility for the user to view the raw data.

Data files used: washington.csv new_york_city.csv chicago.csv

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

Credits to Udacity resources, e.g. mentors and study groups.