What tools can extract tables from webpages?

There are several good tools for extracting tables from webpages, depending on how the page is built.

Python libraries

• pandas — read_html() can pull HTML tables directly from a page.
• BeautifulSoup — useful for custom scraping when tables are messy or need special handling.
• lxml — fast HTML parsing; often used with BeautifulSoup or directly.
• requests + pandas/bs4 — common combo for downloading and parsing pages.

Browser/automation tools

• Selenium — handles tables loaded dynamically with JavaScript.
• Playwright — modern alternative to Selenium, also good for JS-rendered pages.
• Puppeteer — Node.js tool for browser automation.

Dedicated table extraction tools

• Tabula — mainly for PDF tables, not webpages.
• Camelot — also for PDFs.
• Octoparse — visual web scraping tool with table extraction support.
• ParseHub — point-and-click scraping tool.
• Web Scraper (Chrome extension) — can extract tables and other page data.

No-code / enterprise tools

• Apify — scraping platform with actors for table extraction.
• Import.io — structured data extraction platform.
• Zyte — scraping infrastructure and extraction services.

Quick rule of thumb

• If the table is in plain HTML: pandas.read_html()
• If it’s dynamic/JS-loaded: Playwright or Selenium
• If it’s a PDF: Camelot or Tabula
• If you want no-code: Octoparse or ParseHub

If you want, I can also show you:

1. a Python example with pandas.read_html(), or
2. the best tool for your specific webpage.