challenge-collecting-data's Introduction

WEB SCRAPING

Get ready to collecting data from ImmoWeb which is the most popular real estate website in Belgium? 🇧🇪

The main mission of the project is creating a dataset for a machine learning model to make a price predictions on real estatse sales in Belgium. Our dataset holds the following columns:

Locality
Type of property (House/apartment)
Subtype of property (Bungalow, Chalet, Mansion, ...)
Price
Type of sale (Exclusion of life sales)
Number of rooms
Area
Fully equipped kitchen (Yes/No)
Furnished (Yes/No)
Open fire (Yes/No)
Terrace (Yes/No)
- If yes: Area
Garden (Yes/No)
- If yes: Area
Surface of the land
Surface area of the plot of land
Number of facades
Swimming pool (Yes/No)
State of the building (New, to be renovated, ...)

All these datasets are saved in property_data.csv file.

While saving the datasets, we used python libraries ;

python from bs4 import BeautifulSoup
from selenium import webdriver
import time
import json
import pandas as pd

Collaborators

Design and construction phase of the project was made by 4 collaborators.(Ujjwal Kandel, Reena Koshta, Nichelle Pinto Machado, Yusuf Akcakaya)

Installation

Pull requests are welcome.
or git clone https://github.com/UjjwalKandel2000/challenge-collecting-data.git

Repo Architecture

challenge-collecting-data
│
│   README.md           :explains the project
│   property_data.csv   :keeps all data for properties
│   
│__   
│   driver              :directory contains chromedriver
│   │
│   │ chromedriver      :is a standalone server or a separate executable that is used by Selenium WebDriver to control Chrome.
│__ 
│   immo_scraping       :directory contains web_scraping.py
│   │
│   │ web_scraping.py   :Python script file for web scraping
│   
│