This python project was created the 2nd of March 2019 whereas the README file was updated on the 29th of March 2019.

bikeshare_NSF is a python program that explores data related to bike share systems for three major cities in the United States—Chicago, New York City, and Washington. It allows to filter the data by month and day of week providing descriptive statistics about it. Such statistics are:

• Popular times of travel

  • most common month
  • most common day of week
  • most common hour of day

• 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)

• Trip duration

  • total travel time
  • average travel time

• 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)

In order to be able to execute this program, the following packages are required: time, statistics, sys, pandas and numpy.

This python program was part of the final project for the Udacity Nanodegree Program "Programming for Data Science".