摘要
基于互联网时代电子商务成为农产品销售重要渠道的背景,探讨利用网络爬虫从电子商务网站爬取农产品销售数据,并使用Python技术进行数据分析和挖掘的方法及技术。通过解析电子商务网站的HTML内容,提取农产品销售数据,并对其进行深入分析,以揭示市场需求变化、消费者行为模式、价格波动趋势和竞争对手动向,从而制定有效的市场策略,优化产品组合和提升品牌影响力。
Based on the background that e-commerce has become an important channel for agricultural product sales in the Internet era,this paper discusses the methods and technologies of crawling agricultural product sales data from e-commerce websites using web crawlers,and using Python technology for data analysis and mining.By parsing the HTML content of e-commerce websites,extracting agricultural product sales data,and conducting in-depth analysis to reveal changes in market demand,consumer behavior patterns,price fluctuations,and competitor trends,effective market strategies can be developed to optimize product combinations and enhance brand influence.
作者
于海英
Yu Haiying(School of Computer Information Management,Inner Mongolia University of Finance and Economics,Hohhot 010070,China)
出处
《现代计算机》
2024年第19期32-36,共5页
Modern Computer
基金
内蒙古自治区高等学校科学研究项目(NJZY20160)
内蒙古财经大学大数据协同创新中心项目(DSJY18008)。
关键词
网络爬虫
数据挖掘
电子商务
农产品销售
市场策略
Web crawlers
data mining
e-commerce
agricultural product sales
market strategy
