Collect data 70k Greek Apartment Listings

@imraz2016

Hi There, I have strong experience with large-scale property data extraction, deduplication, CSV structuring, and high-volume scraping workflows. For this project, I would use your curated area URLs to systematically crawl each market, collect all requested fields, normalize the data, remove duplicates, validate required fields, and export everything into one master CSV matching your header exactly. I can also build the workflow to handle the target pricing dates and capture six image URLs per listing where available. I’m comfortable working with datasets at the 70,000-listing scale and can first provide a small sample to confirm field mapping and data quality before the full run.

@sohandas

I can scrape and deduplicate 70,000+ property listings into your CSV format, including prices and images. Ready to provide a quick sample.

@sujonmax2

Hello, I’m interested in this project and have experience with large-scale web scraping, property data collection, CSV formatting, and data cleaning. I can collect all required listing details, pricing, amenities, descriptions, and six image URLs while removing duplicates and checking missing data. I’ll follow your CSV format exactly and use a reliable, efficient workflow. Estimated turnaround is 5 days, depending on the source and pricing availability. Regards sujon

@asifdwan

Hi, I can handle this high-volume Greek property scraping project using Python/Playwright with reliable pagination, retries, deduplication, and checkpointing. I’ll extract all requested fields, including date-specific pricing and 6 image URLs, and deliver a clean UTF-8 CSV matching your format. I suggest starting with a 100–500 listing test batch to verify the structure and pricing before scaling to ~70,000 listings. Estimated full turnaround: 5–10 days after approval of the test batch.

@brashel

Hello, I can scrape 70K listings into a clean CSV with pricing, amenities, descriptions, and images, using automated extraction, deduplication, validation, and error tracking.

@tusharhossen123

Hi, can you send me the URL list then I will provide a few samples data now. Thank you

@imahedi

I'm an experienced web scraping specialist. Here is my workflow. I will use Python with BeautifulSoup or Scrapy to scrape all listings from the area URLs you provide. For each property I will collect apartment name, area and town, full description, facilities, sleep details, max guests, bedrooms, bathrooms, price per night for your specified dates and 6 image URLs. Final output will be a clean CSV matching your sample header exactly with no missing rows and no duplicates. Please share the area URL list, target date range and sample CSV header when we start so I can set everything up correctly from the beginning. Estimated turnaround time depends on the number of URLs and site load speed but I will give you a more accurate timeline once I review the list. Regards, Mahedi H

@abhaysony20

Dear Client, As per your description, I am able to collect all records for your apartment listing and did similar for apartment.com. I have lots of experience in similar field so requesting you to please reach me and discuss this in details. Thanks Rakhi

@sagarwal3005

To effectively compile the inventory of 70,000 Greek apartment listings into a single CSV file, I will utilize a web scraping approach that combines automated tools for data extraction with careful attention to data accuracy and platform compliance. My workflow will involve first developing a tailored script to scrape property details using libraries like Puppeteer or BeautifulSoup, ensuring all required fields are accurately captured. I will also incorporate methods to check for duplicates and enforce consistent formatting. I specialize in web scraping and data processing using technologies such as Python and relevant libraries, allowing for precise and efficient data collection. I have a 4.9-star rating across 200 client reviews and have completed 220 projects. To better understand your needs, could you specify the target date range for the pricing data?

@zafarfarooq612

Hello, I can collect and organize the 70,000+ Greek property listings into a clean, duplicate-free CSV matching your required format. I’ll capture all requested property details, date-specific pricing, and 6 image URLs using an efficient automated/hybrid workflow with quality checks. I can provide a sample first for approval. Regards, Zafar

@AgnarConsulting

I can collect and deliver the Greek apartment listings in the required CSV format, including property details, amenities, sleeping information, guest capacity, bedrooms, baths, date-specific nightly pricing, and 6 image URLs per listing. The workflow will use Python with requests/BeautifulSoup and Selenium where required, with pandas for consistent formatting, deduplication, validation, and final CSV generation. I can first produce a representative sample from your supplied area URLs so the fields and pricing results can be verified before processing the full inventory. After approval, I can proceed with the full collection and final verification to identify missing or duplicate records and deliver the completed dataset in your specified column order. I can start as soon as you contact me with more information. Best Regards, Rish

@suganyav12

Hi there, Myself suganya, hope you are doing good. I have gone through the project description and ready to collect the details of For every property, capture: • Apartment name • Area and town • Full description • Facilities/amenities offered • “Where you’ll sleep” details • Max guests • Number of bedrooms and baths • Price per night for the specific dates I will provide • 6 images urls from 70,000 url listings to csv perfectly. waiting for your message. kindly consider this straightforward project for me. Thanks

@muneeb6767

I can build a scalable Python/Playwright scraping pipeline to process the ~70,000 listings, normalize all requested fields, capture six image URLs, apply date-specific pricing, and deduplicate records against stable property identifiers. I’d use controlled concurrency, retries, checkpointing, validation and incremental CSV output so interruptions don’t lose progress, while respecting the target platform’s access rules and terms.

@ganeshrasekar

With over a decade's worth of experience in the tech industry, my data-oriented skill set is exceptionally suited for your project. My prowess in languages such as Python, C#.Net and Html will enable me to automate the process, ensuring speed and accuracy throughout the data extraction phase. I am well-versed in data mining principles, proficiently extracting whole directories of data while upholding host platform's terms and conditions. I assure you that your CSV file will be immaculate, complete and devoid of any duplicates. To give an ETA on this project, I propose a turnaround time of three weeks. However, please note that extracting 70k Greek apartment listings is a task that requires meticulous attention to detail; hence, speed will not be prioritized over quality. Having successfully handled similarly high-volume property data projects in the past with great delivery, rest assured that I am well-equipped and competent to breathe life into your dataset.

@prosenjit9970

Hi, I’m interested in your project and can help collect and organize the ~70,000 Greek tourist-apartment listings into a clean, structured CSV matching your required header. I have experience with large-scale web research, data extraction, scraping, data cleaning, and CSV/Excel processing. I can follow your area URL list and capture all required fields, including property name, location, description, amenities, sleeping details, guest capacity, bedrooms/baths, date-specific nightly pricing, and 6 image URLs. My workflow will be: Process the provided area URLs systematically Use automated extraction with manual validation where necessary Capture pricing for your exact target dates Standardize all fields and remove duplicates Run completeness and quality checks before final delivery Deliver the data in your exact CSV column order For a dataset of approximately 70,000 listings, I would first test a small sample to confirm that all required fields can be reliably extracted from the source platform. After reviewing the URLs and target dates, I can provide an accurate turnaround estimate. I’m ready to start with a sample immediately. Thank you.

@gitachowdory1

Hello, I can efficiently collect and organize the ~70,000 Greek apartment listings into a single, clean, deduplicated CSV matching your exact template. I’ll capture all required property details, amenities, sleeping arrangements, capacity, bedrooms/baths, date-specific pricing, and 6 image URLs per listing, with consistent formatting and quality checks throughout. Turnaround: 7–10 days, depending on source accessibility and pricing complexity. I’m experienced in high-volume web research, data extraction, and structured CSV/Excel data management. Please send me the area URLs, target dates, and CSV header so I can review the scope and get started. Best regards, Gita

@ImranAli01

Hi, I got that you are looking for a freelancer to collect data from 70,000 Greek apartment listings into a single CSV file, including specific details for each property. This is what I can help you with, let's chat. My approach is to utilize automated scraping tools to efficiently gather the required information from each listing. By leveraging advanced data extraction techniques, I will ensure that all details are accurately captured and organized in a structured format. The outcome will be a comprehensive CSV file with no missing rows or duplicates, meeting your exact specifications. I have extensive experience in handling high-volume property data and have successfully completed similar projects in the past. As final deliverables, you will receive a fully populated CSV file containing all the requested information for each apartment listing. One thing I'd like to confirm before we start: Are there any specific platforms or websites that you prefer to prioritize for data collection? Let's discuss further to align on the details and ensure a successful outcome. Regards, Imran

@juanpablomacf

At 70,000 listings, the main challenge isn’t extracting fields once; it’s maintaining completeness, deduplication and date-specific pricing across a large property set without silently losing records. I’d start by validating a representative sample of your area URLs and mapping the listing structure into a fixed schema matching your CSV header. The collector would then paginate systematically, extract the requested property data and six image URLs, normalize text and numeric fields, and maintain a unique property key to prevent duplicates. For pricing, I’d treat the supplied dates separately from static listing data and validate that the returned nightly price actually corresponds to the requested date range. I’d also build checkpoints and retry handling so temporary failures don’t become missing rows. A final reconciliation against the source URL/listing counts would help identify gaps before delivery. I’m comfortable with Python-based scraping/data-processing workflows and large structured datasets. For a collection of this size, I’d also design the workflow to respect applicable platform terms and avoid unnecessary load. Could you confirm which platform(s) the area URLs point to? Are the 70,000 listings expected to be captured from those pages directly, or are there additional search/result pages behind them? Also, should the CSV contain one row per property regardless of availability for the requested dates, with pricing left blank when unavailable? Juan Pablo

@mahads31

As an experienced tech professional, I have the perfect toolset to deliver on this project. My extensive background in big data management, specifically in highly complex and voluminous databases coupled with my proficiency in data entry and processing mean I can ensure you get a comprehensive CSV file without any missing rows, duplicates or format inconsistencies. In past projects, I’ve successfully handled property datasets with over 100k entries. For your Greek apartment listings project, I propose a three-stage workflow that begins first with web scraping using Python to collect the necessary data which will be cleaned and harmonized to prevent any duplicates. Then results will be thoroughly checked manually against the curated list of area URLs you will provide. Finally, we’ll make use of my Excel expertise to put everything into a well-structured CSV file that mirrors your sample header provided. Given the scale, I anticipate approximately two weeks for the turnaround time as this allows for adequate data collection and validation. Rest assured, even within this timeframe, accuracy is never compromised. I am well versed in respectful scraping and automation practices to adhere to platform terms and am excited about possible adaptations between myself and your platform that maximizes efficiency and ensures lasting success in our relationship.

@dattapreti

Greetings, Hope you are doing very well. I can handle the high-volume collection of approximately 70,000 Greek tourist-apartment listings and deliver a clean, structured, duplicate-free CSV matching your required format. My workflow will include automated collection, data validation, duplicate detection, consistent formatting, extraction of amenities, descriptions, sleeping details, capacity, bedrooms, bathrooms, date-specific pricing, and 6 image URLs per property. I have experience with large-scale web research, scraping, data extraction, and CSV preparation. I’ll prioritize accuracy, completeness, and compliance with the relevant platform terms. Estimated turnaround: 7–14 days, depending on site structure and access. I’m ready to review your URLs and sample CSV header and begin with a test batch. Best regards, Preti