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爬取并分析北上广深链家网租房房源全部数据，得出租房建议（北上广深租房图鉴）

项目主要爬取北上广深链家网全部租房房源数据，并且得出租金分布、租房考虑因素等建议

主要的文件为：

  • house_data_crawler.py：爬取北上广深租房房源数据的代码（带说明和注释, 需要安装mongodb）
  • info.py：租房类型和各城市各区域的信息，供house_data_crawler.py调用
  • 北上广深租房图鉴.ipynb: Jupyter notebook代码，对北上广深租房数据进行分析
  • data_sample.csv: 租房数据，这里只随机选择了12000条，每城市3000条

运行环境：

  • python3.6

需要安装的包：

  • requests
  • pyecharts
  • pandas
  • numpy
  • pymongo

注：具体分析说明可以关注微信公众号：Alfred数据室，阅读对应文章《北上广深租房图鉴》

Crawling and analysing Bei-Shang-Guang-Shen rent data from Lianjia.

This project Crawls Bei-Shang-Guang-Shen renting data from Lianjia, and analyses the distribution of the rent, and provides renting advices in those cities. The main files are listed below:

  • house_data_crawler.py：codes for crawling Bei-Shang-Guang-Shen rent data from Lianjia（with annotation, MongoDB needs to be installed.）
  • info.py：infos about renting type and districts of Bei-Shang-Guang-Shen，for house_data_crawler.py
  • 北上广深租房图鉴.ipynb: Jupyter notebook codes，analysing Bei-Shang-Guang-Shen renting data
  • data_sample.csv: 12000 renting data by random choices

Python environment

  • Python3.6

Packages need to be installed

  • requests
  • pyecharts
  • pandas
  • numpy
  • pymongo

Notice: you can find the detailed document by following Alfred's wechat official account: Alfred_Lab