17/06/2020
US Bike share
key findings:
1.Popular travel time
most common month , most common week ,most common time (i.e,at what period)
2.Popular stations and trip
most common start and end station ,most common combination of travel(i.e,start and end of the trip )
3.Trip duration
Total travel time,average travel time
4.Raw data
you can also view the raw data of random trip by filtering by month ,week ,destination,start point ,end point
bikeshare.py code for all mention above findings