PDF to Excel
Pull PDF tables into XLSX spreadsheets.
or click to browse — supports PDF files up to 100MB
How to use
- 1 Drop or click to upload your file
- 2 Adjust options if shown
- 3 Click Run Tool
- 4 Download your result instantly
- ✓ Files up to 1GB
- ✓ Unlimited jobs/hour
- ✓ Batch processing
- ✓ Priority support
Files are processed securely and permanently deleted within 1 hour. We never store, read, or share your documents.
Why this works
Pull tables out of a PDF into an editable Excel spreadsheet (.xlsx). Works on both born-digital PDFs (clean tables) and scanned PDFs (auto-OCR\u2019d into structured cells).
PDFs are where data goes to die. Every bank statement, every utility bill, every research dataset arrives as a PDF whose tables you can see but can\u2019t actually use \u2014 you can\u2019t total a column, sort by date, or pivot by category until the numbers are in a real spreadsheet.
PDF to Excel extracts tabular data from your PDF and rebuilds it as a real Excel spreadsheet. Each detected table becomes a worksheet in the output .xlsx file. Numbers come through as numbers (not text); dates come through as dates; column headers carry over; rows preserve their grouping. For multi-table PDFs (bank statement with multiple sections, financial report with summary + detail tables), each table becomes its own sheet, named for the table\u2019s position in the source document.
The converter handles two distinct cases. Born-digital PDFs (anything exported from Excel, accounting software, or a database) extract cleanly because the table structure was encoded into the PDF when it was created. Expect near-perfect column alignment and zero text errors. Scanned PDFs (bank statements that arrive as image-only PDFs, photographed receipts) run through OCR first, then table detection. Accuracy is high for clean modern scans but may need a manual touch-up in Excel for rows where column boundaries weren\u2019t crisp in the source.
What extracts well: simple grid tables, multi-column financial statements, transaction lists, contact lists, schedules, price lists. What needs a touch-up: heavily merged-cell layouts (org charts in table form), tables with nested sub-tables, free-flowing text formatted to look like a table.
Numbers and dates are typed appropriately in the output \u2014 a column of dollar amounts comes through as proper numbers you can SUM(), not as text strings. Date columns are recognised and formatted as Excel dates so they sort correctly. Currency symbols are preserved as cell formatting, not as part of the cell value.
The reverse direction (combining Excel data back into a PDF) is Excel to PDF.
How it works
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1Upload your PDFDrop your PDF into the upload box. Born-digital PDFs (exported from accounting software, etc.) extract cleanest; scanned PDFs work via OCR but may need touch-ups.
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2Run the conversionPress Convert. Born-digital PDFs finish in 3\u20135 seconds; scanned PDFs take 2\u20134 seconds per page because each page is OCR\u2019d.
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3Open in ExcelYou\u2019ll get an .xlsx with each detected table as its own worksheet. Open in Excel, Google Sheets, Numbers, or LibreOffice.
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4Touch up if neededFor scanned sources or complex layouts, scan the output for any rows where columns shifted; manual fix in Excel takes seconds per row.
Real-world uses
Accountants
Bank statements arrive as PDF; extract into Excel for reconciliation in seconds rather than retyping every line.
Financial analysts
Earnings reports published as PDF extract into spreadsheets for modelling without manual data entry.
Researchers
Datasets published in research papers (as PDF tables) extract into Excel for re-analysis.
Bookkeepers
Vendor invoices in PDF format extract into Excel for monthly expense aggregation.
Common questions
How accurate is the extraction?
For born-digital PDFs with clean tables: near-perfect, including correct numeric typing. For scanned PDFs: typically 95\u201399% on modern, clean scans \u2014 the bottleneck is OCR accuracy on the underlying image. Expect to spend a minute reviewing the output spreadsheet for any rows where columns shifted, especially on heavily-formatted source tables.
Do numbers come through as numbers, not text?
Yes. Dollar amounts, percentages, integers, and dates are detected and typed appropriately in the output spreadsheet \u2014 you can immediately SUM() columns, sort by date, and use formulas. Currency symbols carry over as cell formatting, not as part of the cell value.
What happens to multi-table PDFs?
Each detected table becomes its own worksheet in the output .xlsx, named by position in the source document. A bank statement with summary + transaction sections produces a workbook with at least those two sheets.
Does it work on scanned PDFs?
Yes. Scanned PDFs are routed through OCR first, then table detection. Accuracy depends on scan quality \u2014 phone photos in good light produce near-as-clean output as digital sources; heavily skewed or low-contrast scans need more touch-up.
Can I extract one specific table instead of all of them?
Not in one step \u2014 PDF to Excel extracts all detected tables. Workaround: use Extract Pages to pull only the pages containing the table you want, then run that smaller PDF through PDF to Excel.
Is there a page limit?
No hard cap \u2014 only the upload-size cap (25 MB free, 500 MB Pro). Long documents take longer to process: budget 1\u20132 seconds per page for born-digital, 2\u20134 for scanned.