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: Excel is utilized to complete the entry of monitoring point data, field verification (including name, value and data type), preliminary inspection, unified data formatting (ensuring that the "16-bit character set text variable" type is compatible with all monitoring points), and removal of obvious format errors. 2. In-depth Data Optimization: Core data processing is conducted using Python integrated with the pandas library, which encompasses three aspects: a. Missing value marking: Identify and label the missing values of WS_Point_S_50, for example, to avoid misjudging them as 0 values; b. Duplicate data elimination: Delete redundant records generated by repeated data collection from devices; c. Numerical classification statistics: Calculate the proportion of each monitoring point classified into "0 values", "non-zero values" and "missing values", providing a basis for subsequent analysis.

搜集汇总

背景与挑战

背景概述

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