[1]王荩梓,赖雯洁. 基于房产交易网站的数据获取与在线工具开发[J].计算机技术与发展,2017,27(05):154-159.
 WANG Jin-zi,LAI Wen-jie. Data Acquisition and Development of Online Analysis Tools Based on Real Estate Transaction Websites[J].,2017,27(05):154-159.
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 基于房产交易网站的数据获取与在线工具开发()
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《计算机技术与发展》[ISSN:1006-6977/CN:61-1281/TN]

卷:
27
期数:
2017年05期
页码:
154-159
栏目:
应用开发研究
出版日期:
2017-05-10

文章信息/Info

Title:
 Data Acquisition and Development of Online Analysis Tools Based on Real Estate Transaction Websites
文章编号:
1673-629X(2017)05-0154-06
作者:
 王荩梓赖雯洁
 华东师范大学 地理科学学院
Author(s):
 WANG Jin-ziLAI Wen-jie
关键词:
 房屋交易网站网络爬虫地理编码ArcPy
Keywords:
 real estate transaction websiteswebsite spidersgeocodingArcPy
分类号:
TP39
文献标志码:
A
摘要:
 房屋交易网站提供了每个交易房产的详细信息,自动获取这些数据并进行在线分析可以帮助人们更好地分析一个地区房产情况,更有利于决策.开发网页分析工具是分析大数据发展的趋势,其具有更少的代码,同时拥有不亚于应用程序的功能实现数据采集与数据分析的实时对接,使得其成为工具开发的新宠.房产交易网站在线工具利用Python语言结合Scrapy、ArcPy等第三方模块开发,可自动提取房产数据,并针对不同数据类型,对某一地区的房产进行空间分布分析和规律监测等.以链家网、安居客两个房产交易网站为例,从中获取上海市的新房、二手房等房产数据,通过统计图表的形式显示上海市房产的空间分布情况,房价涨幅,各地区房产数量分布比例等,实现用户对大数据的进一步分析认识.
Abstract:
 Real estate transaction websites provide every detail about the real estate data.It would be helpful for people to know better about real estate,which is helpful for final decision.Development of online analysis tools meets the trend to analyze big data on real estate with less code to expect the integration of data mining with data analysis in real time owning the function no less than practical programs as new favorite in tool development.This analysis tool online has been developed with Python language as well as third party modules including Scrapy,ArcPy etc.to acquire information on real estate and to monitor and analyze spatial distributions and variations of real estate information from various types of data.Taking two trade websites of real estate,Network for Linking Family and Dwelling Guest,as examples,real estate data in Shanghai has been acquired to display spatial distributions and variations of housing prices as well as percents of real estates in diverse districts for convenience to analysis.

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更新日期/Last Update: 2017-07-07