摘 要:以关键部位维修周期分析为例,详细阐述了基于Pandas 对Excel 表格进行数据导入、清洗无效行、清洗无效列、数据透视、数据合并重塑、排序与排名、分组运算的实现过程。该方法解决了关键部位维修周期分析中的存在数据量大、基础数据不规范、计算过程复杂等难点,实现了关键部位维修周期分析的自动化。该方法也适用于人事数据、财务数据的年度汇总,具有良好的实用性与推广价值。
关键词:Pandas;运维记录;关键部位;数据分析
中图分类号:TP391 文献标识码:A 文章编号:2096-4706(2020)09-0148-03
Maintenance Cycle Analysis of Key Parts Based on Pandas
MA Xiaozong,WANG Xueshan,WEI Jingchun
(Cigarette Rolling Department of Zhumadian Cigarette Factory of Henan Zhongyan Industry Co.,Ltd.,Zhumadian 463000,China)
Abstract:Taking the maintenance cycle analysis of key parts as an example,the realization process of data import,invalid row cleaning,invalid column cleaning,data perspective,data consolidation and reconstruction,sorting and ranking,grouping operation of Excel tables based on Pandas is described in detail. This method solves the problems of large amount of data,nonstandard basic data and complex calculation process in the analysis of key parts’maintenance cycle,and realizes the automation of the analysis of key parts’maintenance cycle. This method is also applicable to the annual summary of personnel data and financial data,and has good practicability and promotion value.
Keywords:Pandas;operation and maintenance records;key parts;data analysis
参考文献:
[1] 马孝宗. 基于Pandas 定位信息系统中的异常数据 [J]. 电脑编程技巧与维护,2019(12):95-96+108.
[2] 张若愚.Python 科学计算 [M]. 北京:清华大学出版社,2012:469-471.
[3] 韦斯• 麦金尼. 利用Python 进行数据分析:第2 版 [M].徐敬一,译. 北京:机械工业出版社,2018:10-11.
[4] 托比• 西格兰. 集体智慧编程 [M]. 莫映,王开福,译. 北京:电子工业出版社,2009:156-157.
作者简介:马孝宗(1989—),男,汉族,河南驻马店人,信息管理员,硕士,研究方向:数据分析、机器视觉。