应用Python第三方库Requests 来爬取二手房网站的房源数据，并利用Pandas 库对爬取的数据进行结构化处理，运用Pyecharts 库对二手房源数据进行多维度的深入分析及可视化呈现。从大量线上数据分析出南京市二手房源分布状况、市场热点及价格走势等信息，帮助购房者、房产中介等在市场活动中高效决策，为政府干预及监管二手房市场提供参考。

This paper uses Python third-party library Requests to crawl the housing data of second-hand housing websites, uses Pandas library to structurally process the crawled data, and uses Pyechards library to conduct multi-dimensional in-depth analysis and visual presentation of second-hand housing data. From a large number of online data, this paper analyzes the distribution of secondhand houses, market hot spots and price trend in Nanjing, helps buyers and real estate agents to make efficient decisions in market activities, and provides reference for government intervention and supervision of the second-hand housing market.