Data Scraping Jobs

I have a collection of Excel sheets filled only with numerical data, and they need to be cleaned so the figures are reliable for downstream reporting. Every value is already in place—there are no text fields—so the task focuses on catching and fixing issues such as inconsistent formats, hidden errors, duplicate rows, and any out-of-range or missing numbers. You are free to use Excel’s built-in tools, Power Query, or a lightweight script in Python/R if that speeds things up, as long as the end result remains in the same workbook structure I’ll provide. Deliverables • The original workbooks returned with all numerical data cleaned and validated • A concise change log (just a tab or a separate file) summarising the corrections you applied and any assump...

I have a collection of Excel sheets filled only with numerical data, and they need to be cleaned so the figures are reliable for downstream reporting. Every value is already in place—there are no text fields—so the task focuses on catching and fixing issues such as inconsistent formats, hidden errors, duplicate rows, and any out-of-range or missing numbers. You are free to use Excel’s built-in tools, Power Query, or a lightweight script in Python/R if that speeds things up, as long as the end result remains in the same workbook structure I’ll provide. Deliverables • The original workbooks returned with all numerical data cleaned and validated • A concise change log (just a tab or a separate file) summarising the corrections you applied and any assump...

I have several Excel/CSV files full of text fields that now need thorough cleaning and verification. The job is straightforward: go through every record, remove duplicates, standardise capitalization and spacing, correct obvious typos, and flag anything ambiguous for my review. Accuracy matters more than speed, so I prefer a careful, methodical approach over quick automated passes—although you’re welcome to use Excel functions, Power Query, or a light Python script if it helps you reach perfect results. Deliverables • A cleaned and fully verified version of each original file, returned in the same Excel/CSV format. • A brief change log that lists the key fixes you applied (e.g., number of duplicates removed, common corrections made). • A short summary high...

I’m working with a master Excel sheet that holds roughly 1,500 email addresses for last year’s officers of student consulting clubs worldwide. The task is to refresh that file with this academic year’s leadership details while preserving the existing column structure—club name, institution, website, officer name, email, and notes. Primary source material should come straight from each club’s own web page; if a club doesn’t publish addresses, you may cross-check LinkedIn or wider browser searches, but validated email addresses take priority because I need to avoid another high bounce rate. Where an address simply cannot be confirmed, the officer’s full name is still useful, yet please flag those rows so I can see at a glance which contacts lack ema...

### Canada Retail Product Database I am looking for a **fresh Canadian retail product database** from these retailers: * Costco Canada * Walmart Canada * Maxi Canada ### Required fields For every product, provide: | Field | Requirement | | ----------------------- | ------------------------------------- | | Retailer | Costco / Walmart / Maxi | | Product Name | English, clean product name | | Brand | Brand name | | Barcode / UPC | Product barcode — very important | | Store SKU / Item Number | Retailer's SKU/item number | | Category | Product category | | Subcategory ...

I need a clean, up-to-date spreadsheet that lists Polish companies at scale. The file must contain three columns only—Company Name, Email Address, and Sector—and total no fewer than 300 000 unique records. Automated web-scraping or API harvesting is the only collection method I will consider; manual research is out of scope. Please structure the delivery as a single XLSX (or compatible) file. In your proposal tell me: • how many records you can supply for each sector you intend to cover, • your total price for the full dataset, and • the estimated turnaround time. Data quality matters: I will sample for duplicate domains, obvious syntax errors, and bounced addresses, so plan for basic validation before hand-off. If this is within your capabilities, I look ...

I need a machine-scraped contact database for Romanian companies operating in five clearly defined sectors: design offices & architects, locksmithing & metalworking, electrical installations, stonemasons, and carpentry. Each record must contain exactly three fields—company name, phone number, and email address—delivered in a single Excel file. Feel free to pull the information from company websites, reputable business directories, and social-media business pages; those three sources together should give the breadth I’m after. A basic validation of phone numbers and email syntax is enough, as long as obvious bounces or malformed entries are removed. Volume is critical. I expect several thousand, ideally tens of thousands, of unique records overall. When you respo...

I need a simple automation tool that extracts financial data from WhaleWisdom stock pages. Example: Changing the ticker in the URL loads another page (e.g., /stock/MTH). Requirements Input: stock ticker Scrape the data of the 25 first company of the last two quarters (see picture and the columna needed) Clean numeric values (remove commas so numbers can be used in calculations) Automatically export the data to Excel in a predefined format Goal: A one-click workflow: enter a ticker → run the script → the Excel file is automatically filled with the latest two quarters of data. I don't have any API key

I need a machine-scraped contact database for Romanian companies operating in five clearly defined sectors: design offices & architects, locksmithing & metalworking, electrical installations, stonemasons, and carpentry. Each record must contain exactly three fields—company name, phone number, and email address—delivered in a single Excel file. Feel free to pull the information from company websites, reputable business directories, and social-media business pages; those three sources together should give the breadth I’m after. A basic validation of phone numbers and email syntax is enough, as long as obvious bounces or malformed entries are removed. Volume is critical. I expect several thousand, ideally tens of thousands, of unique records overall. When you respo...

I’m launching a large-scale outreach campaign and require a database of one million up-to-date leads specifically from small businesses. I’m flexible on geography and sector, but every record must be real, current, and ready for cold-email or phone contact. Please source the data ethically—LinkedIn, public directories, web scraping, or reputable data providers are all acceptable as long as the final list is freshly verified. Automation is fine; what matters is accuracy and scale. Duplicate suppression, spam-trap removal, and basic enrichment (company size, website, and primary contact role) should already be handled on your end before delivery. Deliverables (CSV or XLSX): • 1,000,000 unique small-business records • Fields: business name, contact name, role/t...

I have an up-to-date list of stores that we already supply to, but the details on my end are incomplete. I need you to go through Supplier A website and pull every location’s name, full street address, opening hours, as well as its exact longitude and latitude. Once gathered, enter everything neatly into my existing spreadsheet so the data can be dropped straight into our “Find a Store” feature. Accuracy is crucial because the coordinates will feed our map and the hours will appear on the store profile pages. Deliverables: • One spreadsheet (Excel or Google Sheets) containing:  – Store name  – Street address (with city, state, postcode)  – Opening hours in a clear format (e.g., “Mon-Fri 9 am-6 pm”)  &n...

I need an experienced web scraping developer to extract the complete public Hacker Database from SoldierX.com. Pages to scrape: Also scrape every individual profile/subpage linked from these index pages. Required fields: Handle/Name, Profile URL, IRL Name, Tags, Full Biography, Facts, Rumors, References, Images/Image Links, Picture Count. Output: Excel/CSV, fully editable. The site may have Cloudflare/ASN restrictions, so please test access before bidding. Public data only; no login/private data required. Important: I will share a sample file showing the exact required format and fields. Please follow that sample exactly. Please bid only if you can test the website and confirm you can extract the full dataset.

I’m assembling a detailed Excel database of ship-owning companies and need reliable, up-to-date information gathered either from your own network or by scraping industry sources such as Equasis and China Shipbuild. Every row in the sheet must include: • Shipowner name • Primary email and phone number • Number of vessels in fleet • Vessel size range and type • Person in Charge contact • Chartering contact • Sale & Purchase contact Accuracy is essential, especially for the three specific contacts listed above, so please cross-check each entry before delivery. If you already possess part of this data, feel free to combine it with new findings from the public databases mentioned. The finished deliverable is a clean, well-struc...

Scraping data for b2b marketing. The database must comprise Founders / Co-Founders / Managing Directors / CEOs, Strategy Managers, Strategic Management Directors and all those responsible for strategy, strategic planning and strategic visions of organisations- 60 000 contacts wanted across all industries and from South Africa, Zambia, Zimbabwe, Namibia, Ghana, Kenya, Uganda, Tanzania, and Nigeria. All contacts must be active, true corporate/work email addresses with a minimum 95%+ deliverability rate. Generic or personal emails (e.g., @, @, @) will not be accepted. Quality & Verification Requirements: Deliverability Guarantee: Minimum 95% valid, deliverable work emails. Zero Spam Traps / Hard Bounces: All emails must be dynamically validated via real-time SMTP/MX ping checks (using to...

I need a detailed, up-to-date database of every household cleaning-liquid manufacturer operating in India. My company produces detergent raw materials—specifically thickeners for liquids—and our sales team will use your list to approach the right people, so accuracy matters more than sheer volume. The file should cover each manufacturer’s registered name, plant or head-office address, phone number, general and purchasing-department emails, website (if any), and the names and titles of decision makers you can locate. If you uncover extra insights such as product lines or regional distributors, include them, but contact details remain the priority. Please gather the data from reliable sources (industry directories, trade associations, Ministry of Corporate Affairs filings...