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Scrape text, parse it with BeautifulSoup and save it as Pandas data frame

We want to share with you how to scrape text and store it as Pandas data frame using BeautifulSoup (Python). The code below works to store html li items in the ‘engine, ‘trans’, ‘colour’ and ‘interior’ columns.

from bs4 import BeautifulSoup
import pandas as pd
import requests

main_url = "https://www.example.com/"

def getAndParseURL(url):
    result = requests.get(url)
    soup = BeautifulSoup(result.text, 'html.parser')
    return(soup)

soup = getAndParseURL(main_url) 
ul = soup.select('ul[class="list-inline lot-breakdown-list"] li', recursive=True)
lis_e = []
for li in ul:
    lis = []
    lis.append(li.contents[1])
    lis_e.extend(lis)

engine.append(lis_e[0])
trans.append(lis_e[1])
colour.append(lis_e[2])
interior.append(lis_e[3])

scraped_data = pd.DataFrame({'engine': engine, 
'transmission': trans, 'colour': colour,
'interior': interior})
By default, Beautiful Soup searches through all of the child elements. So, setting recursive = False (line 13) will restrict the search to the first found element and its child only.

The code was provided by Ahmed Soliman.

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