This was my first ever project done in python, using numpy and pandas.
The code is available in .py and .ipynb both.
The project loads the US Bikeshare data of three cities, 
New York City,
Chicago,
Washington DC(data not complete here, have compensated for possible errors in code)
It asks the user for:
--City to look into
--Month (from January to June). User can select all as well.
--Day of the week. User can select all as well.
The output is as follows:
- The most frequent times of travel, 
  The most common month, 
  The most common Weekday of travel,
  The most common starting hour
        
-The most common starting and ending stations, 
	and the most common trip
        
-The total travel time and the mean travel time of all bikes

-The user statistics[ types of users, with their count,
			Earliest year of birth,
			Most recent year of birth,
			Most common year of birth]  
       
-Raw data (5 rows at a time, more if the user wishes)

Finally, it asks the user if the user wants to start over. If the answer is no, the program stops.
Hope you like it!