Southeast Asia Daily AQI Dataset

@raminde

Have over 18 years of experience in data mining/ Web scrapping/ Scraping Bots/ Chrome/Opera Extensions I have done it all. Tell us your source and we will put it in excel for you, Or we can even give you filtered results as per your requirement, In the format you want. You can also ask for data into a particular format - Excel, Json, Mysql, Databases, XMLs, you name them. Further Can help you with integrating it with ur databases, Can create json outputs. We are not only good with scraping but also with the tools that u may need after that. We can help you build you softwares round the data we have 99% Data Accuracy. We have Duplicate finder. etc., We can help with Statistics on the data We can help with creating Api's front the data We can create Softwares to manage that data We can build Sites round the data

@GameOfWords

I can gather and process the Southeast Asia daily AQI dataset to meet your exact specifications. As an experienced full-stack developer specialized in Python, I’ve been working with data scraping and processing for years - skills that align perfectly with your project requirements. Additionally, I’m adept at transforming vast amounts of raw data into clean, structured, and research-ready datasets. Having built scalable web and mobile applications, I understand the importance of reliable and consistent data. With this in mind, I can assure you of the highest level of integrity in my work. Upholding the importance of verified sources like you mentioned, I will trace every piece of data back to the relevant government site, keeping a detailed record of retrieval methods and conversion factors within the readme file. Moreover, using Python/R scripts, I’d be happy to develop scripts for you to reproduce or extend this workflow later on. My portfolio showcases my ability to bring significant support to businesses with effective technical writing and documented systems. Partnering with me will not only deliver your desired dataset but also provide valuable project documentation for référence. Let's chat about how my skills in AI automation and backend database management can enhance this project further!

@muneeb6767

I can build a government-source dataset (India, Indonesia, Philippines) with station-level AQI + pollutants + weather, ensuring ≥90% continuity, clean units, deduplication, and traceable sources. Will deliver structured CSV(s), full README, and optional reproducible Python scripts with automated scraping/cleaning.

@nareshk44

As an experienced data professional with an exceptional skill set in data analysis, mining, scraping, and collection, I am confident that I can expertly execute your project -- translating your detailed vision into a reality. Over the years, I have honed my expertise in various areas including efficiently handling large datasets in Excel and Python and organizing them meticulously. Also, my deep understanding of using Google Sheets for tasks like formatting and cleaning data aligns perfectly with your project requirements. Notably, what sets me apart is not just my technical acuity but also my commitment to delivering high-quality results within specified timelines. I understand the importance of a reliable and well-structured dataset for any research. In this context, my track record of achieving daily continuity of ≥90% across all variables per station proves vital. In addition to meeting the core deliverables listed in your project description, I would be more than happy to provide you with Python/R scripts that I develop during the scraping and cleaning processes as an added value. This way, you can easily reproduce or extend the workflow if necessary. With me on board, you’ll have a reliable partner dedicated to producing excellent outputs that perfectly reflect your needs. Let's collaborate and transform this vision into a powerful tool for your research!

@yuanzhi5

Building a clean, research-ready dataset for daily AQI across Southeast Asia requires a robust technical approach to source, validate, and structure disparate data from multiple countries like India and Indonesia. The primary challenge often lies not in data collection but in ensuring consistency and reliability for academic or analytical use, which demands a meticulous implementation plan. Based on the described scope for a structured daily tracking dataset, I’d suggest a budget of 120.0 INR, which covers the initial delivery of a validated sample dataset for one city over a one-month period, demonstrating the cleaning methodology and final format. This focused milestone ensures alignment on the data quality and structure before scaling to the full regional scope. To tailor the solution precisely, what are your primary data sources or APIs for India and Indonesia, and do you require a specific schema or integration with a particular analysis platform?

@PyMLExpert1

As a seasoned Python and Machine Learning professional, my skills and experiences align perfectly with your project description. I have extensive knowledge in data acquisition, especially in scraping and cleaning data from various sources. My expertise will enable me to retrieve the air quality index (AQI) dataset you need directly from the relevant government portals and monitoring stations for India, Indonesia, and the Philippines. My attention to detail will ensure that there are no duplicate rows, maintaining the unique key formed by the date and station, and achieving a daily continuity of at least 90% for each variable per station. Each dataset will be well-structured in a standard CSV format with consistent units of measurement—µg/m³ for pollutants, °C, %, m/s, and mm for meteorological variables—to satisfy your data integrity criteria. Lastly, a testament to my thorough approach is the comprehensive README and scripts I provide. The README will transparently document every source URL used, retrieval method applied, units used as well as any conversion factors applied or missing values flagged to ensure complete verifiability of all source references. The optional scripts I offer will allow you to easily reproduce or extend our workflow in future projects. With me on board for your Southeast Asia Daily AQI Dataset project, you're not just getting quality data but also peace of mind about its accuracy. Let's get started

@rajk271

Hi, I can build this as a clean, lightweight full-stack web app within 2 days. I have experience developing Python-based analytical tools with simple front-ends, and this fits well as a private-use application. I’ll create a clean interface (HTML/JS) where you can input lottery results, and a Python backend (Flask preferably) that processes the data and runs statistical analysis to generate predicted number sets. My approach will be to implement a structured analysis pipeline—frequency analysis, distribution checks, and pattern-based weighting—to generate 10 statistically informed number sets. The app will be simple, fast, and easy to use, with clean code so you can modify or extend the logic later if needed.

@ApexAline

Hi, I’ve worked on large data collection and cleaning projects for over 4 years, and this is exactly the kind of structured dataset I can handle. I can collect station-level daily air quality and weather data directly from official government sources for India, Indonesia, and the Philippines, keeping everything clean, consistent, and well documented. You’ll get a properly structured CSV with all required fields, no duplicates, consistent units, and a clear README with sources, methods, and handling of missing data. I can also share the scripts used so the process is fully reproducible. Happy to start and build this dataset step by step with regular updates. Thanks & Regards, Diksha