51k Rediffmail.com.txt Today

import re from collections import Counter

def analyze_rediffmail_file(filename): email_regex = r'\b[A-Za-z0-9._%+-]+@rediffmail\.com\b' emails = [] with open(filename, 'r', encoding='utf-8') as file: for line in file: potential_emails = re.findall(email_regex, line) emails.extend(potential_emails) 51k rediffmail.com.txt

# Username analysis usernames = [email.split('@')[0] for email in emails] avg_username_length = sum(len(username) for username in usernames) / len(usernames) print(f"Average Username Length: {avg_username_length}") 51k rediffmail.com.txt

# Example usage filename = "51k_rediffmail.com.txt" analyze_rediffmail_file(filename) This example performs basic analysis like counting unique emails, checking for the most common email (if any), and calculating the average length of usernames. For a deeper analysis, consider integrating more sophisticated natural language processing (NLP) techniques or data visualization tools. 51k rediffmail.com.txt

# Counting unique emails and their frequency email_counts = Counter(emails) print(f"Total Unique Emails: {len(email_counts)}") print(f"Most Common Email (if any): {email_counts.most_common(1)}")