WhatsApp Chat Analytics Summary

@tangramua

Hello,   We carefully studied the description of your project and we can confirm that we understand your needs and are also interested in your project. Our team has the necessary resources to start your project as soon as possible and complete it in a very short time.   We are 25 years in this business and our technical specialists have strong experience in PHP, JavaScript, Python, Data Processing, Software Architecture, Data Visualization, Data Analysis, Pandas and other technologies relevant to your project.   Please, review our profile https://www.freelancer.com/u/tangramua where you can find detailed information about our company, our portfolio, and the client's recent reviews.   Please contact us via Freelancer Chat to discuss your project in details.    Best regards, Sales department Tangram Canada Inc.     

@onkarkulkarni8

Hi, I can help you with "WhatsApp Chat Analytics Summary" as per your given project description. We can discuss more in detail during a chat conversation when you are available. I've worked on many PHP projects in recent times. So I am confident on achieving your expected Goals. Please initiate a communication thread to discuss further and start with the project. ⭐ 5.0/5 from a recent client: "A more professional version: “Excellent work! The job was completed within the committed timeline. Great quality, professionalism, and timely delivery. Highly appreciated and recommended.”" Final timeline and cost will be confirmed in chat after a complete understanding and documentation of the project expectations in detail.

@C0RETECHIES

Hello, System understanding: The tool reads a WhatsApp .txt export, extracts timestamp, sender, and message, then calculates daily/weekly message frequencies and ranks users by message share. Output is a single‑page PDF or HTML report with clear tables. Technical approach: Python + pandas for parsing and aggregation. Regex handles WhatsApp’s date‑time format. Report built with pandas‑to‑HTML; optional PDF via weasyprint. One‑command CLI processes new files in a folder. Core modules: 1) Ingestion & parsing - loads .txt, normalizes timestamps into a DataFrame. 2) Metrics - daily/weekly resample, user activity totals and percentage. 3) Report builder - creates HTML table + summary, converts to PDF if needed. 4) CLI - argparse entry, error logging. Relevant systems: Social Media Content Generator (n8n AI pipeline) - shows automated text parsing and structured output; AI‑Powered Slack Clarification Assistant - extracts messages and timestamps for summary generation; AI‑Driven Sales Call Automation System - parses transcripts and produces CSV/reports, similar data flow. Implementation strategy: Begin with parser tests on a sample export, then implement frequency calculations, validate counts. Build report module, output HTML first, add PDF export. Add README with setup and one‑liner run command. MVP achievable in 2‑3 days. Questions: 1) Which timestamp format does your export use - bracketed [DD/MM/YYYY, HH:MM:SS] or the alternative without brackets? 2) Should the report show both raw counts and percentages for each user, or just the ranked list with share of total? 3) Where should the generated report be saved - alongside the input file or a separate output folder? Regards, Rohit

@PINESCRIPTERR

Hi, I can build a lightweight Python tool that parses WhatsApp group-chat exports with pandas and generates a clear PDF or HTML report showing daily/weekly message frequency and ranked user activity with message-share percentages. I’ll structure the parser and reporting logic into clean, modular components so future features such as keyword analysis can be added easily, with a simple one-command workflow, validation for export variations, and a concise README. 1. Will the WhatsApp exports always use the same date/time format and export language, or should the parser support multiple common formats? 2. Should deleted messages, system notifications, media placeholders, and messages from unknown/removed users be excluded from the metrics? 3. Would you prefer the generated report to be HTML for easier regeneration and portability, or PDF for a fixed presentation format? Regards, Houssame

@jayantkumar314

With my extensive experience as a software engineer since 2015, I assure you that building a reliable tool, like the one you’re asking for, is right within my wheelhouse. Proficient in multiple backend and frontend frameworks, using Python as the language and situations like this are where I shine. My expertise in building well-commented code means not only will it be accessible should future modifications be needed, but others can easily understand the code and build upon any features they may need in the future (like keyword analysis). Lastly, over the years I have refined my approach to web development projects where it moves seamlessly from inception to hosting and beyond. This means that apart from delivering clean code along with clear instructions on setup and use (as specified by you), I can also ensure its reliable hosting solution on AWS, VPS, GCP or any other preferred you prefer. Your project requires a freelancer who understands your needs beyond just coding – someone who invests in developing long-lasting professional relationships. Choose me for just that!

@Sv3nie

Hi, The part that breaks accuracy in WhatsApp exports is the parsing, not the counting: the timestamp format changes with phone locale (12h vs 24h, dd/mm vs mm/dd, the invisible U+202F before AM/PM on iOS), and multi-line messages have no prefix, so a naive line-by-line regex silently drops or misattributes rows. I'd write a parser that detects the format from the first few lines, folds continuation lines into the previous message, and loads everything into a pandas DataFrame; the report is then a single command producing daily/weekly counts plus a ranked user table with share of total, rendered to HTML (or PDF) from a template. Parser, metrics, and renderer would be separate modules so keyword analysis later is just one more metrics function. Is the export from Android or iOS, and does it include system lines like joins and deleted messages you'd want excluded from the counts?

@sumitsthakur

I can build a reliable Python tool that parses your WhatsApp group-chat export and generates a clean, easy-to-read summary report covering message frequency and active user rankings. My approach will be to use pandas to accurately parse the text file, compute daily and weekly message counts, and calculate individual user shares. I will structure the code cleanly so that adding future features like keyword analysis will be straightforward. You will be able to drop a fresh text file into the folder and run a single command to regenerate the report. I bring over five years of software development experience with a strong command of Python and data handling using pandas. I focus on writing well-commented, maintainable code and will include a brief README detailing the setup and usage steps. Let us chat about your preferred output format for the report and get this started.

@arslanshahid386

Hi, I understand you need a tool to analyze WhatsApp group-chat exports, focusing on message frequency and active user rankings. This project requires parsing and processing text files to extract meaningful insights, which demands careful handling of data formats and potential inconsistencies in chat exports. The main challenge here will be accurately parsing and structuring the exported chat data, especially considering variations in message formatting and potential anomalies like missing timestamps. My approach would involve developing a robust parser to handle these variations and ensure data integrity. Prioritizing stability and scope, I would start with a thorough assessment of the export format to tailor the parsing logic accordingly. I have experience in developing similar analytics tools using Python for data parsing and PHP/

@farrukhdeveloper

Hi, This is a practical project and a very good fit for my Python/data-processing background. I’m a Software Architect with 17+ years of experience building backend systems, automation tools, data pipelines, reporting utilities, and production-grade Python applications. I’ve also worked with WhatsApp-export style data extraction and structured reporting workflows. For your tool, I can build a simple one-command workflow: • Drop the exported WhatsApp .txt file into a folder • Run the script • Receive a clean PDF or HTML summary report The report will include: • Daily and weekly message frequency • Peak and low-activity periods • Ranked list of active users • Each user’s percentage share of total messages • Total messages and participation summary • Clean tables and concise narrative insights I’d use Python + pandas for parsing and analysis, with the code structured into separate parsing, analytics, and reporting modules so keyword analysis, sentiment, or topic detection can be added later without rewriting the core. I’ll also handle common WhatsApp export variations, malformed lines, multiline messages, and system messages carefully so the counts remain accurate. You’ll receive clean source code, comments, sample output, and a short README with setup and usage instructions. Regards, Farrukh Naveed Anjum Software Architect | Python, Data & Automation

@mayankinnovative

I understand you need a simple, accurate, repeatable WhatsApp analytics tool where a fresh exported .txt file can be dropped into a folder and one command generates a clear PDF/HTML report. I’ll build it in Python using pandas for robust parsing, with a modular pipeline that handles WhatsApp date/time formats, sender names, multiline messages and common export variations. The report will clearly show daily/weekly message frequency, peak/lull periods, and a ranked active-user table with each participant’s message count and percentage share. Accuracy will take priority over visual complexity, with validation checks for parsing anomalies and totals. I’ll keep parsing, analytics and report generation separated so future keyword analysis can be added without restructuring the core. Clean commented code, a concise README, sample usage and reproducible output will complete the handoff. Questions: 1. Will exports include media/system messages such as “<Media omitted>”? 2. Do you need both PDF and HTML, or is one preferred? 3. Should weekly reporting use Monday–Sunday weeks? 4. Do you have sample exports for testing multiple WhatsApp formats? I’m confident I can deliver a reliable, maintainable reporting tool.

@billybryan98

Hello there. I hope you are donig well. I have a strong background in data processing and analysis using Python and pandas, which equips me to create the reliable tool you need for WhatsApp chat analytics. My experience includes developing efficient data parsing solutions and generating insightful reports, ensuring clarity and accuracy. I understand that you require a tool to summarize WhatsApp group chat data, focusing on message frequency and active users. I will develop a straightforward script that processes the exported .txt file and generates a clear PDF/HTML report with the specified metrics, allowing easy identification of trends. I will provide high-quality, clean, and well-commented code, along with a brief README for setup and usage. My approach emphasizes accuracy and ease of use, laying a solid foundation for potential future enhancements like keyword analysis. Please feel free to reach out to me. I look forward to working with you. Best regards, Billy Bryan

@Jennycreation

Hello Sir, I have already worked on similar types of website and software development projects and I am confident that I can successfully handle your project. I am a full-time freelancer with **17+ years of experience** in web development, software development, automation, and API integrations. My expertise includes: * ASP.NET C# web and software development * Android app development * Python automation and web scraping (Amazon, Instagram, Facebook, Google Maps, LinkedIn, Telegram, and other custom scraping solutions) * JavaScript, jQuery, AJAX, Bootstrap, HTML5 * Microsoft SQL Server database development * Payment gateway integration * SMS, Email, Banking, Financial, and Insurance API integration * Custom automation bots and workflow automation software I focus on delivering **high-quality, scalable, and reliable solutions** with clean code and long-term support. Please contact me in private chat so we can discuss your requirements in detail. I can also show you a **demo of similar projects** I have completed. Looking forward to working with you. Thanks & Regards

@dataspro

Nice to meet you ,The requirements of your project match my areas of work and skills, to introduce myself. My name is Anthony Muñoz and i am the lead engineer for DS Pro IT agency. I have worked for over 10 years as a Full-Stack and software development engineer and have successfully done multiple jobs. It will be a pleasure to work together to make your project. Feel free to discuss about the project with me, greetings.

@kajal1992

Hello, I can build this lightweight WhatsApp chat analytics tool in Python with a clean, modular structure so it can easily be extended with keyword analysis and additional metrics later. The tool will: • Parse exported WhatsApp .txt chat files accurately • Generate daily and weekly message-frequency statistics • Rank active users by message count and percentage share • Produce a clean, easy-to-read PDF/HTML summary report • Allow a fresh .txt file to be dropped into a folder and processed with a single command • Use pandas for reliable data processing and a lightweight reporting library • Include error handling for common WhatsApp export formats • Provide clean, commented source code and a concise README Estimated timeline: 3–5 days I’ll focus on accuracy, maintainability, and a structure that makes future features such as keyword analysis, media statistics, and activity trends easy to add. I can start immediately.

@albertc1996

Hi, Straightforward Python task: parse WhatsApp .txt export with pandas, calculate daily/weekly message counts and per-user share, output a clean table-rich report. Structured for easy extension — adding keyword analysis later is a one-function addition. Deliverables: Python script: drop .txt → run one command → report generated Daily/weekly frequency + ranked active users with share percentages Clean PDF or HTML output, well-commented code + README Timeline: 1-2 days. Can you share a sample export (anonymized is fine) so I can confirm the format before starting?

@XRProConnect

Hi, Aashiq here from Cape Town, South Africa. This project instantly caught my eye, so I had to reach out. I see you’re looking for a reliable tool to analyze WhatsApp group chat data and generate a clear summary report. The focus on message frequency and active user metrics is spot on for understanding engagement. I’ve developed similar tools that help businesses analyze conversations and extract actionable insights. My experience with Python and libraries like pandas allows me to create efficient, clean code that meets your requirements. I’d be happy to share samples of my work if you’d like. Based on what you mentioned, here is how we would approach the project: - Parse the exported chat file using pandas. - Calculate daily and weekly message counts. - Generate a ranked list of active users. - Create a straightforward PDF/HTML report. You can count on clear communication throughout the process. I will ensure a seamless, user-focused solution optimized for performance. Best Regards, Aashiq

@wixdek

The task is to develop a reliable tool that reads an exported WhatsApp group-chat file and generates a summary report covering message frequency and active users. The goal is to streamline the analysis of chat data for better insights into user engagement and posting patterns. To achieve this, I recommend leveraging Python and the Pandas library for data manipulation, ensuring the code is clean and well-commented for easy maintenance and future enhancements. The implementation plan would be as follows: 1. Analyze the chat export format and identify key data points. 2. Develop the parsing function using Pandas to handle the text file. 3. Calculate daily and weekly message counts and identify active users. 4. Generate the summary report in the desired PDF/HTML format. 5. Create a README file for easy setup and usage instructions. What specific file format should the tool support for processing the chat exports? If this aligns with your vision, we can discuss the next steps.

@bohdan38

Hi there, The export format varies (timestamps, multi-line messages) which can misclassify messages, skewing daily/weekly counts and active-user shares. I’ll implement a robust Python parser (pandas) that uses regex to reliably extract dates, authors, and messages, then compute daily and weekly counts and a ranked active-user list. Output will be a clean HTML/PDF report with a simple template, ready to drop a new .txt export into a folder and run one command to regenerate. I’ve built a similar tool for a client, delivering a one-file script with README and accurate summaries from WhatsApp exports. Optional improvement: structures the code for easy extension to keyword analysis. Looking forward to delivering a ready-to-run, well-commented solution that you can extend later. Thank you, - Bohdan

@jeanpatrickr8

Hello, I appreciate the opportunity to work on your project for a WhatsApp group-chat summary tool. I understand your need for a reliable solution that generates clear insights on message frequency and active users, allowing you to easily analyze engagement within the group. With extensive experience in Python programming and data manipulation using pandas, I can develop a tool that meets your specifications. I have successfully created similar data analysis applications that emphasize accuracy and user-friendliness. To ensure your project is completed effectively, my approach will include: - Developing a script that reads the exported WhatsApp chat file and extracts the required metrics. - Implementing functions to calculate daily and weekly message counts, as well as ranking active users based on their contributions. - Generating a concise summary report in PDF/HTML format that highlights key insights clearly. - Writing clean, well-commented code alongside a README file for easy setup and usage, ensuring future modifications are straightforward. I am eager to begin this project and confident in delivering a high-quality, reliable tool. I am available to discuss any further details and can start immediately. Thank you for considering my bid!