Extract tabular data from PDF files securely into editable Excel (.xlsx) spreadsheets locally.
Upload the PDF containing table data.
Our tool scans the layout and determines rows and columns based on text positions.
Click "Convert to Excel" to process.
Download your generated .xlsx workbook (each PDF page becomes an Excel Sheet).
No — all PDF parsing and Excel generation runs entirely in your browser. Your financial or business data is never transmitted to any server.
No — the tool requires a native-text PDF where text is embedded as selectable characters. Scanned PDFs are images of text and contain no machine-readable data. Use OCR tools to convert scanned PDFs first.
Detection is based on spatial positioning of text characters. Simple, well-structured tables extract accurately. Complex tables with merged cells, vertical text, or irregular spacing may produce imperfect results.
Yes — each page in the PDF is extracted into its own sheet in the .xlsx workbook, named by page number.
Yes — the output is a standard .xlsx file compatible with Microsoft Excel, Google Sheets, and LibreOffice Calc.
This is normal for PDFs where columns are not strictly aligned in the source document. You may need to manually adjust some columns in Excel after extraction.
You receive a quarterly report as a PDF. Twenty pages of tables. Management wants it in a pivot table by tomorrow. Do you retype it all, or is there a faster way?
There is. This tool scans every page of your PDF, detects tabular data structures, and exports them as an Excel file (.xlsx) or CSV — ready to open in Excel, Google Sheets, or any data tool. Everything runs locally in your browser. The PDF never touches any server.
Tables with clear grid structure: PDFs created from Excel, accounting software, reporting dashboards, or database exports have well-defined column and row data. These convert cleanly — the output spreadsheet will have the right data in the right cells with minimal cleanup.
Semi-structured columnar data: Invoice line items, pricing tables, and comparison charts that aren't strict HTML-style grids still convert usably. Some alignment cleanup may be needed but the data is there.
Multi-page tables: If a table spans multiple pages of the PDF, each page is extracted to its own sheet in the XLSX output, allowing you to combine them in Excel using copy-paste or formulas.
Plain text mixed with tables: Non-tabular text (headers, footers, narrative paragraphs) appears in the spreadsheet as single-cell rows between table sections — easy to identify and delete.
The conversion process uses two browser-based libraries:
PDF.js reads the PDF's text layer page by page, retrieving each text element with its exact position (x/y coordinates), font size, and content.
A spatial clustering algorithm groups text elements by their column alignment and row proximity — essentially reconstructing the table structure from positional data. Elements spatially aligned in columns become spreadsheet columns. Elements at the same vertical position become a row.
The resulting grid is outputted to either XLSX (using SheetJS) or plain CSV.
All of this runs in your browser's JavaScript engine using your machine's processing power. No file ever leaves your device.
Best results:
Requires follow-up work:
Doesn't work:
Financial analysis: An analyst receives monthly P&L statements as PDFs from each department. Converting all of them to Excel takes minutes instead of hours, enabling rapid consolidation and year-over-year comparison.
Invoice processing: Accounts payable teams converting vendor invoices to CSV can import line items directly into their ERP or accounting system without manual data entry — dramatically reducing errors.
Research data extraction: A researcher studying government statistics finds the data in a PDF report. Converting to CSV makes it immediately workable in Python, R, or any analytics environment.
Business intelligence input: When reports come from systems that only export to PDF, converting to Excel is the first step in feeding data into Power BI, Tableau, or Looker dashboards.
Audit preparation: Auditors often receive client data as PDFs. Converting financial tables to Excel allows sorting, filtering, and formula checking that's impossible in PDF format.
Check legibility first. If you can select and copy text in your PDF viewer, the PDF has a text layer and will convert cleanly. If you can't select text, it's image-based and needs OCR first.
Use CSV if you plan to import into a database or coding environment. XLSX is better for opening directly in Excel or Google Sheets.
Clean up non-table rows after conversion. Header and footer text, page numbers, and narrative paragraphs appear as single rows in the output. Select and delete these rows before analyzing your data.
For PDFs with dozens of sheets, check each tab in the Excel output — pages without tables may produce sparse or blank sheets.
Recommended schema: SoftwareApplication + FAQPage + HowTo
Your data never leaves this device. All processing is handled locally by JavaScript.
Extracts tables and data with column alignment. 100% local — no upload.
Your file is processed securely in your browser — never uploaded
