台州商办及社区物业管理企业/居民画像分析评价数据

（1）数据适用范围：台州市黄岩区
（2）数据内容：对台州市黄岩区部分写字楼、居民社区物业管理过程中，业主的缴费数据进行采集分析，包括停车费、物业费、水电费、能耗费、车位管理费、电梯维护费、商铺管理费、垃圾清运费等，分析企业及居民相关缴费情况、缴费水平、资产情况、欠费信用分析等。
（3）数据应用场景：对采集归集的数据进行分析挖掘，通过物业费缴纳情况数据对商办企业、社区居民进行画像分析，用各小区月度业主人均缴费总额代表小区缴费消费水平等级，用各业主物业费及车位费等缴纳数据评估业主资产情况。通过统计分析改进物业运营管理；为商铺选址、商铺招租提供周边社区及人群画像分析及选址决策依据；为金融机构社区营销拓客提供社区缴费消费提供画像数据及评级依据。（1）数据清洗：对数据集进行清洗，包括去除异常数据、处理缺失值。
（2）数据获取：通过物业管理人员线下采集、记录核算、数据统计等，获取物业管理过程中业主信息、缴费信息等数据。
（3）计算规则：
对每月数据进行合并统计，得出每月每社区的缴费总额、每小区业主总数等。以此基础数据开展计算，户均月度缴费总额=每月每社区的缴费总额/每小区业主总数。根据户均月度缴费总额缴费情况进行社区排序，得出小区缴费消费水平等级，其中前25%评价等级为A，前25-50%评价等级为B，50%-75%评价等级为C，后25%评价等级为D。

1. Scope of Application: Taizhou Huangyan District
2. Data Content: Collected and analyzed the owners' payment data during property management of some office buildings and residential communities in Taizhou Huangyan District, including parking fees, property management fees, water and electricity fees, energy consumption fees, parking space management fees, elevator maintenance fees, shop management fees, garbage collection fees, etc. The analysis covers the payment status, payment level, asset conditions and overdue credit analysis of enterprises and residents.
3. Data Application Scenarios: Conduct analysis and mining on the collected and aggregated data. Carry out portrait analysis of commercial office enterprises and community residents based on property management fee payment data. Use the total monthly per-capita payment amount of owners in each community to represent the community's payment consumption level. Use the payment data of each owner's property management fees and parking space fees to evaluate the owner's asset status. Specific applications include: improving property operation management through statistical analysis; providing portrait analysis of surrounding communities and target groups and site selection decision-making basis for shop site selection and shop leasing; providing portrait data and rating basis based on community payment and consumption for financial institutions to carry out community marketing and customer acquisition.
(1) Data Cleaning: Clean the dataset, including removing abnormal data and handling missing values.
(2) Data Acquisition: Obtain data such as owner information and payment information during property management through offline collection, recordkeeping, accounting and data statistics by property management personnel.
(3) Calculation Rules: Merge and count the monthly data to obtain the total payment amount of each community per month and the total number of owners in each community. Based on these basic data, calculate the average monthly household payment amount = total monthly payment amount of each community / total number of owners in each community. Sort the communities according to the average monthly household payment amount to get the community payment consumption level grades, where the top 25% are rated as Grade A, 25%-50% as Grade B, 50%-75% as Grade C, and the bottom 25% as Grade D.

搜集汇总

数据集介绍

特点

该数据集包含台州市黄岩区部分写字楼和居民社区的物业管理缴费数据，共计1279条，每月更新。数据用于分析业主缴费情况、消费水平和资产情况，支持物业运营管理改进、商铺选址决策和金融机构社区营销拓客。