GV

GeezerVison

The World Wide Web, restored to 800 pixels of glory.

Home|About|Gaming cabinet|Archives|How it works|Starter sites

On this site

  • Sign in
  • ActionsCI/CD and automation
  • CodespacesCloud development environments
  • All Features
  • Documentation
  • Training
  • Certifications
  • Build with Copilot
  • Customize Copilot
  • Integrations
  • Trending repos
  • GitHub Sponsors
  • Developer articles
  • Enterprises

This view

  • Original page
  • New address

GeezerVison is showing github.com — interesting-python/BSGS_Rent at master · Alfred1984/interesting-python

Expand file tree

/

BSGS_Rent

/
Copy path

Directory actions

More options

More options

Directory actions

More options

More options

Latest commit

 

History

History
History
/

BSGS_Rent

/
Copy path

Folders and files

NameName
Last commit message
Last commit date

parent directory

..
data_sample.csv
data_sample.csv
 
 
house_data_crawler.py
house_data_crawler.py
 
 
info.py
info.py
 
 
readme.md
readme.md
 
 
北上广深租房图鉴.ipynb
北上广深租房图鉴.ipynb
 
 

readme.md

Outline

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

You are visitor 01402520 — GeezerVison does not store the pages you look up.
Best viewed with Netscape Navigator 4.7 or Internet Explorer 6 at 800×600. No cookies required.