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Monday, April 28, 2025

 

Pyhton code here..share your commetns



import requests
from bs4 import BeautifulSoup
import pandas as pd

# Define the URL you want to scrape
url = 'https://COMPXXXX.COM'  # Replace with the target website

# Send a GET request to fetch the webpage
response = requests.get(url)

# Check if the request was successful (status code 200)
if response.status_code == 200:
    soup = BeautifulSoup(response.content, 'html.parser')

    # Find the relevant HTML elements containing the data
    attendees = []

    # Example: Let's assume attendees are stored in <div class="attendee">
    for attendee in soup.find_all('div', class_='attendee'):
        name = attendee.find('span', class_='name').text.strip()
        job_title = attendee.find('span', class_='job-title').text.strip()
        company_name = attendee.find('span', class_='company-name').text.strip()
        company_activity = attendee.find('span', class_='company-activity').text.strip()

        attendees.append({
            'Name': name,
            'Job Title': job_title,
            'Company Name': company_name,
            'Company Activity': company_activity
        })

    # Convert the list of dictionaries to a DataFrame for easy manipulation
    df = pd.DataFrame(attendees)

    # Save the data to a CSV file
    df.to_csv('attendees.csv', index=False)

    print("Scraping successful! Data saved to 'attendees.csv'")
else:
    print("Failed to retrieve the webpage. Status code:", response.status_code)

{ 1 comments... read them below or add one }

  1. Really enjoyed reading your article! It’s informative, engaging, and very well written. I appreciate the clarity and detail you’ve shared. Looking forward to reading more from you soon.

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