The project and README file were created on 27th january 2019.

The project explores U.S. bikeshare data. Calculates statistics and builds an interctive environment where a user chooses the data and filter for a dataset to analyze.

Statistics Computed: #1 Popular times of travel most common month, day of week, hour of day

#2 Popular stations and trip
	most common start station, end station, trip from start to end 

#3 Trip duration
	total travel time
	average travel time

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

Python files: bikeshare.py

Sources: chicago.csv new_york_city.csv washington.csv

It's important to give proper credit. Add links to any repo that inspired you or blogposts you consulted. GitHub repo: https://github.com/Torumaus/pdsnd_github