煤矿安全监控预警数据集合

1、基础数据处理：采用Excel工具完成监控点数据的录入、字段核对（名称、值、数据类型）与初步查看，统一数据格式（确保“文本变量16位字符集”类型适配所有监控点），排查明显格式错误；2、深度数据优化：使用Python（集成pandas库）开展核心数据处理 ——一是空白值标记（如识别WS_Point_S_50 的空白值并标注，避免误判为0值）；二是重复数据剔除（删除因设备重复采集产生的冗余记录）；三是数值分类统计（按“0值”“非零值”“空白值”分类统计各监控点占比，为后续分析提供基础）。1. Basic Data Processing: Utilize Excel to complete data entry for monitoring points, verify data fields (including field names, field values and data types), conduct preliminary inspections, unify data formats (ensure that the 16-bit character set type for text variables is compatible with all monitoring points), and identify obvious format errors; 2. In-depth Data Optimization: Conduct core data processing using Python integrated with the pandas library, which includes three tasks: first, blank value labeling: identify the blank values of WS_Point_S_50 and mark them to avoid misjudging them as 0 values; second, duplicate data removal: delete redundant records generated by repeated device data collection; third, numerical classification statistics: calculate the proportion of each monitoring point categorized into "0 values", "non-zero values" and "blank values", providing a basis for subsequent analysis.

搜集汇总

背景与挑战

背景概述

该数据集是针对煤矿安全生产的监控预警数据集合，规模1G且每日更新，涵盖实时监控、风险识别和应急决策等应用场景。数据处理采用Excel和Python工具，重点处理空白值标记和重复数据剔除，为煤矿安全提供精准数据支撑。