How to clean web-extracted data?

Web-extracted data requires cleaning: remove HTML artifacts, normalize formats (dates, currencies), handle missing values, and validate records. Manual cleaning is tedious; Firecrawl Agent handles most cleaning automatically—returning typed, normalized data rather than raw text.

Raw scraped data is messy. Prices include symbols and commas. Dates appear in various formats. Text contains   entities and extra whitespace.

Schema-based extraction reduces cleaning work—Firecrawl returns typed data automatically:

result = app.scrape_url(url, {
    "formats": ["extract"],
    "extract": {
        "schema": {
            "properties": {
                "price": {"type": "number"}  # Returns numeric, not "$29.99"
            }
        }
    }
})

Data cleaning normalizes formats and removes artifacts. Schema-based extraction APIs like Firecrawl handle this automatically—prices as numbers, booleans as booleans, text without HTML artifacts.