码头集装箱业务分析数据

对码头内空箱、重箱运行状态记录分析，掌握码头集装箱库存信息，分析码头集装箱库存周转率，对码头进行分级，分为集装箱库存利用效率高码头、集装箱库存利用率中等和集装箱库存利用效率低码头，有助于同行企业感知不同码头的集装箱利用效率，为管理码头提供建议。1、数据采集：通过四港联动码头集装箱数据库输出码头中文名称、集装箱状态、装船港名称、卸船港名称等字段；
2、数据处理：对采集到的数据进行清洗、分类汇总，对箱主等进行匿名化处理。
3、数据加工：使用SUMIFS和COUNTIFS函数计算出码头箱子一个月总堆存量A，码头箱子提重一个月总提重出箱数B，码头集装箱最大堆存量C，计算一个月内码头箱子日平均存量At=A/T（T为一个月天数），一个月内码头提重出箱日平均数Bt=B/T，计算码头库存周转率Y=Bt/At*100%，计算码头堆场利用率：X=At/C*100%，计算码头集装箱业务活跃度W=Y+X，排名前30%的码头为集装箱业务活跃码头，排名后30%的码头为集装箱业务不活跃码头，其余为中等。
4、数据应用：有利于港口公司更好感知码头集装箱作业，为集装箱作业提供建议。

This dataset analyzes the operational status records of empty and loaded containers within terminals, aiming to grasp terminal container inventory information, calculate container inventory turnover rates, and classify terminals into three tiers: terminals with high container inventory utilization efficiency, those with medium efficiency, and those with low efficiency. This classification helps peer enterprises perceive the container utilization efficiency of different terminals and provides references for terminal management.
1. Data Collection: Extract fields including Chinese names of terminals, container status, port of loading, port of discharge, and others from the four-port linked terminal container database.
2. Data Preprocessing: Clean, classify and aggregate the collected data, and anonymize information such as container owners.
3. Data Processing and Calculation: Use the SUMIFS and COUNTIFS functions to calculate the total monthly stock volume of containers at the terminal (denoted as A), the total number of loaded containers lifted out of the terminal per month (denoted as B), and the maximum stock volume of containers at the terminal (denoted as C). Then compute the daily average stock volume At = A/T (where T is the number of days in a month) and the daily average number of lifted loaded containers Bt = B/T. Calculate the inventory turnover rate Y = Bt/At * 100%, the yard utilization rate X = At/C * 100%, and the container business activity index W = Y + X. Terminals ranking in the top 30% are categorized as active container business terminals, those in the bottom 30% as inactive ones, and the remaining as medium-level terminals.
4. Data Application: This dataset enables port companies to better perceive container operations at terminals and provides actionable suggestions for container operation management.

搜集汇总

背景与挑战

背景概述

该数据集包含1000条码头集装箱业务数据，每日更新，涵盖20个字段如码头代码、堆存量、集装箱状态等，用于分析码头集装箱库存周转率和利用率，并提供码头分级和管理建议。