平湖市停车场车位利用情况分析数据

本数据的面向用户及其应用场景描述如下： 1.面向停车场运营商：本数据可帮助停车场运营商通过分析停车时长的稳定性，识别停车资源管理和分配效率，优化停车策略，如动态调整停车费用、分区管理、共享停车位开发等，以鼓励车辆快速周转，提高车位利用率。 2.面向城市规划或交通管理部门：通过分析不同停车场的车位利用规律，有助于城市规划或交通管理部门了解区域内交通流量的分布和变化特征，进而优化道路设计、交通信号控制等交通管理措施，缓解交通拥堵问题。 3.面向停车场所在商圈的商户：本数据可在一定程度上反映停车场附近居民整体的出行特征，有助于辅助商家描绘客户画像，从而推出有针对性的营销策略。1.数据获取和预处理：（1）通过授权获得平湖市不同停车场每月的停车数据，具体数据字段包括停车场编号、停车场名称、统计日期、车牌号码、车辆入场时间、车辆离开时间、车位总数。（2）对获取的数据进行清洗，对“车牌号码”进行脱敏。 2.数据加工：（1）根据车辆离开和入场时间，计算每辆车的停车时长（单位为分钟）。（2）计算当月总停车时长（单位为分钟）：对统计月期内每辆车的停车时长进行累加。（3）计算当月总停车次数：对统计月期内的停车次数进行累加。（4）计算当月平均停车时长：当月总停车时长÷车位总数。（5）计算每辆车停车时长与当月平均停车时长差的平方D：（每辆车的停车时长-当月平均停车时长）²。（6）计算方差S和标准差σ：S=（当月D值的和）÷当月总停车次数；σ=SQRT（S）。（7）当月车位利用情况分析：σ＜100时，判定为当月停车时长稳定，停车场资源的管理和分配合理高效；100≤σ≤200时，判定为当月停车时长存在一定差异，停车资源的分配和管理上有优化空间；σ＞200时，判定为停车时长波动大，可能存在部分车辆长时间占用、部分车辆频繁进出的情况。

The target users and their corresponding application scenarios of this dataset are described as follows:
1. For parking lot operators: This dataset can help parking lot operators analyze the stability of parking duration, identify the efficiency of parking resource management and allocation, and optimize parking strategies such as dynamically adjusting parking fees, zoning management, and shared parking space development, so as to encourage rapid vehicle turnover and improve parking space utilization.
2. For urban planning or traffic management departments: By analyzing the parking space utilization rules of different parking lots, it helps urban planning or traffic management departments understand the distribution and change characteristics of regional traffic flow, and then optimize traffic management measures such as road design and traffic signal control to alleviate traffic congestion.
3. For merchants in the business district where the parking lot is located: This dataset can reflect the overall travel characteristics of residents near the parking lot to a certain extent, helping merchants portray customer profiles and launch targeted marketing strategies.

1. Data acquisition and preprocessing:
(1) Obtain monthly parking data of different parking lots in Pinghu City through authorization. The specific data fields include parking lot number, parking lot name, statistical date, license plate number, vehicle entry time, vehicle departure time, and total number of parking spaces.
(2) Clean the acquired data and desensitize the "license plate number" field.

2. Data processing:
(1) Calculate the parking duration (unit: minute) of each vehicle based on the vehicle's departure time and entry time.
(2) Calculate the total monthly parking duration (unit: minute): Accumulate the parking duration of each vehicle within the statistical month.
(3) Calculate the total monthly parking times: Accumulate the total number of parking occurrences within the statistical month.
(4) Calculate the average monthly parking duration: Total monthly parking duration ÷ Total number of parking spaces.
(5) Calculate the square D of the difference between each vehicle's parking duration and the monthly average parking duration: D = (Vehicle parking duration - Monthly average parking duration)².
(6) Calculate the variance S and standard deviation σ: S = (Sum of D values of the current month) ÷ Total monthly parking times; σ = SQRT(S).
(7) Monthly parking space utilization analysis: When σ < 100, it is determined that the parking duration is stable in the current month, and the management and allocation of parking resources are reasonable and efficient; When 100 ≤ σ ≤ 200, it is determined that there are certain differences in parking duration, and there is room for optimization in the allocation and management of parking resources; When σ > 200, it is determined that the parking duration fluctuates greatly, and there may be situations where some vehicles occupy parking spaces for a long time while some vehicles enter and exit frequently.

搜集汇总

背景与挑战

背景概述

该数据集记录了平湖市停车场的车位利用情况，包含停车场基本信息、车辆进出时间及停车时长统计等15个字段，规模为1000条，适用于停车场运营优化、交通管理和商业营销等场景。数据经过清洗和统计分析，如计算停车时长、方差和标准差，以评估车位利用效率。