Web Scraping means to collect data from the Internet. As a beginner in data science, you must have seen CSV files on the Internet distributed by some popular websites like Kaggle and other govt websites. The data is prepared by either collecting and writing using standard methods or by scraping it from the Internet. In this article, I will take you through web scraping with Python using BeautifulSoup.

I will scrape data from Flipkart and create a CSV file from that data. It’s not that difficult what it seems. Let’s get our hands dirty with web scraping to create a CSV file using python. I will start by importing the necessary packages that we need for this task. So let’s get started.

Web Scraping to Create a CSV File

So we need two primary packages for this task, BeautifulSoup and urllib. We can easily install both these packages using the pip command – pip install bs4 and pip install urllib. After successfully installing these packages the next thing you need to do is importing these packages, so let’s import these and scrape the link we need to collect data from:

from bs4 import BeautifulSoup as soup
from urllib.request import urlopen as uReq

my_url="https://www.flipkart.com/search?q=samsung+mobiles&sid=tyy%2C4io&as=on&as-show=on&otracker=AS_QueryStore_HistoryAutoSuggest_0_2&otracker1=AS_QueryStore_HistoryAutoSuggest_0_2&as-pos=0&as-type=HISTORY&as-searchtext=sa"

uClient = uReq(my_url)
page_html = uClient.read()
uClient.close()
page_soup = soup(page_html, "html.parser")

#python #beautifulsoup #web-scraping #data-science #developer