FWD-Professional-Data-Analysis-1st-Project

Bike Share Data

Over the past decade, bicycle-sharing systems have been growing in number and popularity in cities across the world. Bicycle-sharing systems allow users to rent ### bicycles on a very short-term basis for a price. This allows people to borrow a bike from point A and return it at point B, though they can also return it to ### the same location if they'd like to just go for a ride. Regardless, each bike can serve several users per day.

Statistics Computed

You will learn about bike share use in Chicago, New York City, and Washington by computing a variety of descriptive statistics. In this project, you'll write ### code to provide the following information:

1- Popular times of travel (i.e., occurs most often in the start time)

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)