200 product records from 10 web pages into one checked sheet

This is a self-directed demo, not client work. I wrote a Python scraper that collected 200 product records from 10 pages of a public sandbox site, a website made for scraping practice. Each record has 6 fields, and every row links back to the page it came from.

Product data on a website is spread across many pages. Copying it by hand is slow and easy to get wrong. A spreadsheet is only useful if each value can be traced back to where it came from.

A Python scraper that walks through the 10 listing pages, collects the same 6 fields for every product, checks each row and writes it to one spreadsheet with its source page.

Every row carries the URL of the page it came from, so any value can be checked in one click.

Each row was validated before it went into the sheet.

200 product records from 10 pages.

6 fields per record.

A source link on every row.

Give me a research target and the fields you need. I collect publicly available information and organise it into a clean spreadsheet, with source links so any value can be checked. You get the spreadsheet, a note on where each field came from and a separate list of anything I could not verify. I collect public information only, and I do not promise emails or phone numbers that need paid contact databases. That is my "I will research and organize public web data into a spreadsheet" service, from $30 on Contra.