The Wikipedia Scraper by No Code Web Scraper turns Wikipedia pages into clean spreadsheets. Open any article table, list page or category, click the list once, and every row — with table columns, links, images and more — lands in Excel or CSV. No code, no API keys, and your data never leaves the browser.
Add to Chrome — FreeGo to any article table — or any Wikipedia page with a list of tables and lists — in Chrome.
Open No Code Web Scraper from the side panel, hover the list and click — every row on the page is detected with all its fields automatically.
Run the extraction (current page, auto-scroll or pagination) and download every row as a clean spreadsheet.
Turn any wiki table into a clean dataset.
Extract rankings and statistics instantly.
Collect structured data for projects.
Grab country and company lists without retyping.
Prototype with real-world datasets.
Scraping publicly visible data for personal analysis is generally lawful in the US and EU. The extension only reads what your own browser already displays — nothing is bypassed and no data leaves your machine.
Install the free Chrome extension, open Wikipedia, and click the list you want. Fields are detected automatically and you export to Excel or CSV — no code, no selectors, no API.
Excel (.xlsx), CSV and JSON — ready for spreadsheets, CRMs or scripts.
No API keys and no signup. The extension works on the pages your browser can open, exactly as you see them.
The scraper reads rendered table rows — including links and images inside cells — and exports them as columns.
Yes. The same extension scrapes any site — Wikipedia today, Amazon, Zillow or your niche directory tomorrow. One tool for every list on the web.
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Learn more →Deep dives on web scraping without code.
Step-by-step 2026 guide with screenshots and a real example.
Tutorial3 methods compared — Power Query, IMPORTHTML and a Chrome extension.
RoundupHonest comparison of features, free-tier limits, and which to pick.
Stop copying tables and lists by hand. Install No Code Web Scraper free and export Wikipedia data in seconds.