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.

本分析所采用的数据集涵盖了自2022年1月1日至2022年12月31日期间的内部数据（直接由该公司自行收集）。起始数据集被组织为12个不同的数据集（每年每月各一个）。每个数据集包含多个列：
* ride_id：数据集的主键，其中包含与特定行程关联的唯一编号
* rideable_type：指定了在给定行程中所使用的自行车型号
* start_station_id：包含起始站点的ID
* end_station_id：包含结束站点的ID
* start_station_name：包含起始站点的名称
* end_station_name：包含结束站点的名称
* start_lat, end_lat, start_lng, end_lng：包含起始和结束站点的地理坐标
* member_casual：包含关于骑行者类型的详细信息。它可以是会员（拥有年度会员资格）或临时（仅使用单次或每日通行证）。

关于数据的可靠性、原创性、全面性、时效性和上下文（ROCCC）方面，我们假设所有这些品质均得到满足。事实上，我们处理的是直接从公司收集的原始数据（可靠且原创）。数据全面且时效，因为它覆盖了整整一年，数据行数超过500万行。