.. _l-challenges-city-bike: City Bike ========= Many cities offer bicycles people can rent for short trips and many people use it every day. As a result, by knowing when and where people use them, we may infer... Data preparation ++++++++++++++++ The following notebook describes how the data was obtained and preprocessed to build the examples introduced above. .. toctree:: :maxdepth: 2 ../notebooks/bike_seattle ../notebooks/bike_chicago The challenge +++++++++++++ We know how people use bicycles. People, people... it is us. What do I know about myself I could use to explore the data and determines living and working areas of Chicago? .. toctree:: :maxdepth: 2 ../notebooks/city_bike_challenge The data can be seen in many ways. .. toctree:: :maxdepth: 2 ../notebooks/city_bike_views ../notebooks/business_chicago A solution ++++++++++ .. toctree:: :maxdepth: 2 ../notebooks/city_bike_solution A solution including clustering +++++++++++++++++++++++++++++++ The first notebook only clusters on arrival time. The second one clusters on bith arrival and starting time. .. toctree:: :maxdepth: 2 ../notebooks/city_bike_solution_cluster ../notebooks/city_bike_solution_cluster_start Other sources of data +++++++++++++++++++++ Chicago has one of the richest open data portal. Here are some others sources of data: * `Taxi Trips - Dashboard `_ * `Current Employee Names, Salaries, and Position Titles `_ * `Building Permits `_ * `Libraries - Locations, Hours and Contact Information `_ * `Crimes - One year prior to present `_ * `Fire Stations - Map `_ * `Average Daily Traffic Counts `_ * `Divvy Bicycle Stations - Historical - Dashboard `_ * `Divvy Trips - Dashboard `_ * `Business Licenses - Current Active `_