This data set includes information about individual rides made in a bike-sharing system covering the greater San Francisco Bay area.
The goal of this presentation is to analyse which features can be used to predict bikeshare trip duration. The elements to be examined are: days of week, period of day, user types, age and member genders.
People tend to ride most in the afternoon in all week days. In weekend, the average trip duration is higher than week days because people have more time to enjoy the trip.
Higher duration has been done by young members aged between 25-40yo. There is no significant difference between two user types as people who ride longer are younger people.