Bulk Phone Data Cleanup

@bktk

Hello there! I will do right now with 100% accuracy. I am offering a free sample before awarding the project. Can you please open a chat box to discuss the project in detail? I am 24/7 available for discussing the project. Sir, please check my profile link for your satisfaction and of my client reviews: https://www.freelancer.com/u/bktk Regards: Muhammad Bilal KTK

@SamirBanna

Hello, I’m a Senior Software Engineer with extensive experience in Python automation and web scraping & C# WindowFormApp and WFP. I’ve carefully reviewed your requirements and I can deliver a reliable, production-ready solution — not a quick workaround. ✅ Clean and maintainable code ✅ Clear communication ✅ On-time delivery I’d be happy to discuss your project details and propose the best technical approach. Best regards, Samir

@divibj

understand you need to consolidate 10,000 messy records into a professional, verified dataset. I can automate this entire workflow using Python (Pandas & Phonenumbers library) to ensure 100% formatting accuracy and use specialized APIs for the verification requirements. I aim for a 0% error rate on formatting and will provide a duplicate-free list. I will provide the log/script used so you can run this process again in the future. Deliverables: A clean, 3-column Excel file (Number, WhatsApp, Name). A summary report of valid vs. invalid entries. The Python script/logic log for your records. I am ready to start immediately. Could you please share the country code I should use for the missing entries?

@DataScraperNirod

Hi, I have read your job description & have understood your all requirements. I am an experienced person to do this kind of job. And also I have a big team to complete it earlier. So, you can hire me at a low price. After seeing my previous records, You will decide that I will be the right person for you. Now you can justify me and give me a chance to serve you. Best regards Nirod Biswas

@Kishoreindia

Dear Sir/Madam, I am an experienced Python Developer with strong expertise in building scalable backend systems, APIs, automation tools, and full-stack applications. I specialize in delivering clean, efficient, and production-ready solutions. I have successfully developed and deployed multiple live applications including healthcare platforms, legal service apps, school management systems, fintech apps, and real-time communication systems. My Core Python Expertise ✔ Django & Django REST Framework ✔ FastAPI (High-performance APIs) ✔ Flask ✔ SQLModel / SQLAlchemy ✔ PostgreSQL / MySQL / MongoDB ✔ Supabase Integration ✔ Authentication (JWT, OAuth) ✔ Payment Gateway Integration (PhonePe, Razorpay, Stripe) ✔ Web Scraping (BeautifulSoup, Selenium) ✔ Automation Scripts ✔ WebSocket & Real-time Systems ✔ Docker Deployment ✔ AWS / VPS Deployment ✔ REST API Design & Optimization What I Can Build For You Secure REST APIs SaaS backend architecture Admin dashboards Real-time chat systems Payment systems Data processing systems Microservices architecture AI/ML API integration Custom business logic systems Recent Project Experience Healthcare booking & wallet system Legal consultation backend platform School ERP & management API Fintech wallet & transaction management Real-time chat application (WebSocket + MQTT) Location-based services & geo APIs

@sstock935

Hello! I can consolidate all phone numbers from every column in your 10,000-row Excel file into one clean mobile-only list, remove duplicates/landlines, and normalize everything into a single international format by appending your country code where missing. I’ll use a reliable VBA or Python (pandas/openpyxl) workflow with strict validation rules so malformed entries are discarded and the final error rate stays under 1%. For each cleaned number, I’ll populate Column B with WhatsApp availability (Yes/No) and Column C with the Truecaller display name, clearly marking “Unavailable” wherever lookup data can’t be returned. You’ll receive the final self-contained Excel workbook plus a short reproducible log of the rules/scripts used so you can rerun the same process anytime.

@maharf061

Hello! As an experienced digital marketer with a strong background in data analysis, I’m confident that I can efficiently handle your Bulk Phone Data Cleanup project. My skills with Excel, Python (including pandas and openpyxl), and PHP make me well-versed in handling datasets of various sizes, cleaning them, and applying specific formatting requirements – exactly what you are looking for. My proficiency will ensure all phone numbers are accurately extracted from your dataset while filtering out any non-mobile numbers or errors, resulting in a clean, verified list that you can confidently use for your outreach and analytics purposes. Being a detail-oriented professional, the accuracy of my work aligns with your project's payment structure; I understand that every cell counts. I am also comfortable documenting any rules or scripts used as requested so you can reproduce the process later if the need arises. Trust me to not only produce the required deliverables but exceed your expectations as well. Let's get started on creating a clean, unified dataset that meets your defined criteria!

@sudhir0112

Hi, I have recently worked on Excel data-cleaning projects involving large datasets, duplicate removal, formatting standardization, and structured data organization. I can help clean and organize your phone records into a consistent and reliable format with proper country codes and validation checks. I’m comfortable handling large Excel datasets and ensuring accuracy through careful review and structured processing. I can also organize the final workbook with clearly separated columns for cleaned numbers, statuses, and additional lookup information where available. My focus is on delivering a clean, well-structured dataset with minimal errors and clear documentation of the process used. I’m available to start immediately and can discuss the best approach for handling the verification requirements efficiently.

@Danzy262

Hi, I’ll clean and standardize your 10,000 phone records into a reliable, outreach-ready dataset with WhatsApp and Truecaller verification. What you’ll get: * All phone numbers extracted into one clean column * Invalid numbers, landlines, and duplicates removed * Uniform international formatting with your supplied country code * WhatsApp availability marked Yes/No * Truecaller display names added in a separate column * Reproducible workflow using Python/Excel automation I’ll use automation for speed and consistency while manually spot-checking results to keep the error rate below 1%. I’ve completed similar large-scale data cleaning projects with 5⭐ feedback for accuracy and delivery. Timeline: 2–4 days Rate: ₹250 INR/hour Please send me a message so we can get started immediately!

@himanshubisht001

Dear Client, I can help you clean and organize the 10,000 phone records accurately according to your requirements. I will extract valid mobile numbers from all columns, format them with the correct country code, remove duplicates and invalid entries, and properly organize the final data in Excel. I will also check WhatsApp availability and add Truecaller names where available. I understand that accuracy is very important for this project, and I will carefully process the data to ensure a clean and reliable final sheet. Please give me one opportunity to work on this project. I will complete the work with full dedication and attention to detail. Regards, Himanshu Bisht

@ummekalsoom25

Hello, I am a highly skilled Data Specialist with extensive experience in cleaning, structuring, and standardizing large datasets with precision. I can efficiently process your 10,000 phone records by extracting all numbers into a single column, removing invalid entries, and ensuring a consistent international format with accurate country code application. I work with Python (pandas, openpyxl) and Excel automation techniques to ensure high accuracy, deduplication, and scalable processing. I can also structure the workflow to verify WhatsApp availability and enrich records where required, while clearly marking unavailable or invalid data. I am committed to delivering a clean, analysis-ready dataset with a strict focus on accuracy, consistency, and reproducibility of the process. You are welcome to review my profile and message me to discuss the workflow in detail. Best Regards, Umm E Kalsoom

@AsifTech21

Clean data is valuable—verified, outreach-ready data is what drives results. Which country code will be applied to numbers missing one, and do you already have access to a Truecaller API/account for lookups? I can build a reliable processing pipeline using Python (pandas + openpyxl) to extract phone numbers from all columns, normalize them into a single international format, remove duplicates/invalid entries, and filter out landlines through pattern validation. I’ll then automate WhatsApp availability checks and integrate Truecaller (or an equivalent lookup source) to enrich each record with display names, while maintaining a detailed processing log for reproducibility. My approach focuses heavily on validation and accuracy checks to keep the error rate below 1% across all ~10,000 records. The final result will be a clean, structured Excel workbook ready for outreach, analytics, or CRM import—saving significant manual effort while ensuring high-quality contact data.

@angelito16

Hi there, I can help you clean and organize your bulk phone data quickly and accurately. I’ll standardize formats, remove duplicates, fix inconsistencies, and make sure all numbers are valid and ready to use. I’m comfortable working with large datasets using Excel or Google Sheets, and I pay close attention to detail to avoid errors. My goal is to deliver clean, reliable data that saves you time and effort. Happy to start right away and handle this efficiently for you. Best Regards, Angelito T.