杭州临平区塘栖街道公共自行车租还不均衡系数分析数据

临平区塘栖街道公共自行车租还不均衡系数帮助我们了解不同自行车站点租还是否均衡。租还不均衡系数过小可能意味着该站点的客流量过低，导致公共自行车资源的浪费。租还不均衡系数过大可能意味着该站点的客流量超出预期，不能较好的满足客户的使用需求。
公共自行车作为一种绿色出行方式，能够有效减少燃油消耗和碳排放，公共自行车租还不均衡系数为不同站点公共自行车投放数量提供依据，指导公共自行车资源的合理分配，很大程度上解决客户出行的“最后一公里”问题。在提升客户使用体验的同时，公共自行车的便捷性和环保性有助于提升城市的整体形象，增强城市的吸引力和竞争力。1、数据采集：利用智能单车调度系统导出杭州市临平区塘栖街道公共自行车站点租还车数据；
2、数据处理：对数据进行清洗，确保数据的准确性和完整性，清理数据剔除重复和错误记录，确保数据字段格式的一致性，进行分类聚合汇总。
3、数据加工：租车不均衡系数=当天租用(辆次)/周期内平均租用(辆次)，还车不均衡系数=当天还回(辆次)/周期内平均还回(辆次)
4、数据应用：利用可视化工具，直观展示不同站点的租还不均衡系数。

The rental-return imbalance coefficient of public bicycles in Tangqi Subdistrict, Linping District, Hangzhou is utilized to assess the balance of bicycle rental and return services across different stations. An excessively low coefficient may signal insufficient passenger flow at the station, leading to waste of public bicycle resources. Conversely, an excessively high coefficient indicates that the passenger flow exceeds expectations, failing to adequately meet users' travel needs.

As a green travel mode, public bicycles can effectively reduce fuel consumption and carbon emissions. The rental-return imbalance coefficient provides a scientific basis for determining the deployment quantity of public bicycles at each station, guiding the rational allocation of public bicycle resources, and largely addressing the "last-mile" problem in residents' daily travel. While enhancing users' travel experience, the convenience and environmental friendliness of public bicycles help improve the city's overall image, as well as its attractiveness and competitiveness.

The dataset development workflow is as follows:
1. Data Collection: Export the rental and return data of public bicycle stations in Tangqi Subdistrict, Linping District, Hangzhou through the intelligent bicycle scheduling system.
2. Data Processing: Clean the collected data to ensure accuracy and completeness, eliminate duplicate and erroneous records, unify the format of all data fields, and perform classification, aggregation and summarization.
3. Data Calculation: Rental imbalance coefficient = Number of same-day rentals / Average number of rentals over the statistical cycle; Return imbalance coefficient = Number of same-day returns / Average number of returns over the statistical cycle.
4. Data Application: Adopt visualization tools to intuitively display the rental-return imbalance coefficients of various public bicycle stations.

搜集汇总

数据集介绍

特点

该数据集记录了杭州临平区塘栖街道公共自行车站点的租还数据，包括租用和还回的辆次、租车和还车的不均衡系数等，共2105条数据，每日更新。主要用于分析公共自行车站点的租还均衡性，指导公共自行车资源的合理分配，解决出行“最后一公里”问题。