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HTML Table Extractor

Pull structured table data from any web page and export it as clean JSON or CSV. No custom scraper needed — just provide URLs containing HTML tables and get rows and columns as structured data. Process multiple pages in a single run.

Features

• Automatic table detection — finds all <table> elements on each page
• Header recognition — detects <th> headers or uses the first row as column names
• Bulk processing — extract tables from multiple URLs in one run
• Clean JSON output — each table row becomes a structured object with named fields
• Configurable concurrency — process 1 to 50 URLs in parallel

Input

Input Example

{
"urls":[
"https://en.wikipedia.org/wiki/List_of_countries_by_population_(United_Nations)"
]
}

Output

Each URL produces one dataset item containing all tables found on the page.

Key output fields:

• inputUrl (string) — the original URL provided
• finalUrl (string) — the URL after following redirects
• status (number) — HTTP status code
• tableCount (number) — number of tables found on the page
• tables (array) — array of table objects, each containing headers and rows
• error (string) — error message if extraction failed, otherwise null
• checkedAt (string) — ISO 8601 timestamp

Output Example

{
"inputUrl":"https://en.wikipedia.org/wiki/List_of_countries_by_population_(United_Nations)",
"finalUrl":"https://en.wikipedia.org/wiki/List_of_countries_by_population_(United_Nations)",
"status":200,
"tableCount":2,
"tables":[
{
"headers":["Rank","Country","Population"],
"rows":[
["1","India","1,450,935,791"],
["2","China","1,419,321,278"]
]
}
],
"error":null,
"checkedAt":"2025-01-15T10:30:00.000Z"
}

Pricing

Use Cases

• Data collection — grab financial data, sports stats, or product specs from web pages without writing a scraper
• Spreadsheet import — convert HTML tables to CSV or JSON for import into Excel or Google Sheets
• Research automation — extract tabular data from Wikipedia, government sites, or academic pages
• Price monitoring — pull pricing tables from competitor websites

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