毕节客运西站销售及退票率分析数据集

数据采集：定时获取各客运站的发车日期、班次、售票数量、退票数量、退票时间等数据。 数据处理加工：计算站点/线路退票率：退票率 = 退票张数 / 总售票张数 × 100%。按时间维度（日、周、月）进行趋势分析，并支持按退票原因（如旅客主动退票、站方原因退票）进行分类统计。 数据应用：设定退票率正常范围，对持续或突然超出范围的站点进行告警。结合售票数据，分析退票对营收的实际影响，并关联班次准点率等服务数据，深度诊断问题根源。Data Collection: Regularly collect data including departure dates, bus trips, ticket sales volume, refund volume, refund time and other relevant information from various passenger terminals. Data Processing and Refinement: Calculate the refund rate of stations or routes: Refund rate = (Number of refunded tickets / Total number of sold tickets) × 100%. Conduct trend analysis based on time dimensions (daily, weekly, monthly), and support classified statistics according to refund reasons, such as passengers' voluntary ticket refunds and ticket refunds caused by station-side issues. Data Application: Set the normal range of refund rates, and issue alerts for stations that continuously or suddenly exceed the set range. Combine with ticket sales data to analyze the actual impact of ticket refunds on revenue, and associate with service data such as bus on-time rate to deeply diagnose the root causes of problems.

搜集汇总

背景与挑战

背景概述

该数据集由毕节交运集团客运有限责任公司创建，专注于毕节客运西站的销售及退票率分析，数据规模为10KB并每日更新。它旨在通过计算退票率并分析趋势，帮助监控站点经营稳定性、识别服务问题，并辅助优化线路营销和运营策略。数据集支持按时间和退票原因进行分类统计，为客运站管理提供数据驱动的决策支持。