Bike Sharing Datasets

The dataset used in this analysis comprehends internal data (directly collected from the firm itself) from 01/01/2022 to 31/12/2022. The starting datasets are organized in 12 differents datasets (one for each month of the year). Each dataset contains several columns: * ride_id: primary key of the dataset which contains a specific number associated with a given ride * rideable_type: specifies the type of bike which has been used in a given ride * start_station_id: contains the id of the station where a given trip has started * end_station_id: contains the id of the station where a given trip has ended * start_station_name: contains the name of the station where a given trip has started * end_station_name: contains the name of the station where a given trip has ended * start_lat, end_lat, start_lng, end_lng: contain the geolocation of the starting and ending station * member_casual: contains information about the type of rider. It can be either member (has an annual membership) or casual (uses only single or daily passes)

Regarding the data Reliability, Originality, Comprehensiveness, Currency and Context (ROCCC) it is assumed that all these qualities are satisfied. As a fact, we are dealing with primary data directly collected from the firm itself(reliable and original). The data is comprehensive and current since it covers an entire year with more than 5 million of data rows.