The importance of extracting information from the web is becoming increasingly loud and clear. Every few weeks, I realize myself in a situation where we need to extract information from the web to create a machine learning model. We have to pull or extract a large amount of information from websites and we would like to do it as quickly as possible. How would we do it without manually going to every web site and getting the data? Web Scraping simply makes this job easier and faster.
Web scraping is used to collect large information from websites. But why does someone have to collect such large data from websites? Let’s look at the applications of web scraping:
Web scraping is an automated method used to extract large amounts of data from websites. The data on the websites are unstructured. Web scraping helps collect these unstructured data and store it in a structured form. There are different ways to scrape websites such as online Services, APIs or writing your own code.
Features of Python which makes it more suitable for web scraping:
To extract data using web scraping with python, you need to follow these basic steps:
Example: Scraping a website to get product details
Pre-requisite:
#Let us import all the necessary libraries
from selenium import webdriver
from BeautifulSoup import BeautifulSoup
import pandas as pd
driver = webdriver.Chrome("/usr/lib/chromium-browser/chromedriver")
products=[] #List to store name of the product
prices=[] #List to store price of the product
ratings=[] #List to store rating of the product
driver.get("Product_URL")
content = driver.page_source
soup = BeautifulSoup(content)
for a in soup.findAll('a',href=True, attrs={'class':'.…'}):
name=a.find('div', attrs={'class': '….'})
price=a.find('div', attrs={'class':'….'})
rating=a.find('div', attrs={'class':'….'})
products.append(name.text)
ratings.append(rating.text)
df = pd.DataFrame({'Product Name':products,'Price':prices,'Rating':ratings})
df.to_csv('products.csv', index=False, encoding='utf-8')
To run the code, a file name “products.csv” is created and this file contains the extracted data.
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