PDF to CSV
Extract tables from PDFs into spreadsheets.
How to use PDF to CSV
- 01
Upload the PDF
Add the PDF that contains tables — bank statements, invoices, reports, or data exports.
- 02
Review detected tables
The tool scans each page, detects rows and columns from text positions, and shows you the tables it found.
- 03
Download as CSV
Export the extracted tables as CSV files you can open directly in Excel, Google Sheets, or any spreadsheet app.
Tested and last verified on
About PDF to CSV
Detect and pull tabular data from PDFs straight into clean CSV files. Table rows and columns are auto-detected from text positions — perfect for invoices, reports and data exports. Runs entirely in your browser.
Getting usable data out of PDF tables
PDFs lock data into a visual layout: columns, rows, and borders look perfect on screen, but try to copy-paste a table and you get a jumble of text with no structure. Financial statements, product catalogues, lab results, and government data releases all ship as PDFs, and anyone who needs to analyse, sort, or chart that data has to get it into a spreadsheet first.
This tool automates the extraction. It reads the text layer of each page, identifies tabular regions by the alignment of text elements, and reconstructs rows and columns into a clean CSV. You can open the CSV in Excel, Google Sheets, or any data tool and start working with real cells immediately — no manual retyping, no reformatting.
How the table detection works
Rather than looking for drawn grid lines — which many PDFs omit — the tool clusters text elements by their coordinates. Items at the same vertical position are grouped into a row; consistent horizontal positions define columns. This positional approach works on borderless tables, shaded-row tables, and minimalist layouts where there are no visible lines at all.
The detection is heuristic: it handles standard tabular layouts well, but highly irregular tables — merged cells spanning many columns, nested sub-tables, or tables that wrap mid-cell — may need light cleanup in the spreadsheet after export. For most real-world documents like bank statements, invoices, and data reports, the output is usable straight away.
Practical tips and common scenarios
Accountants extract transaction tables from bank statement PDFs to reconcile in Excel. Procurement teams pull line-item data from vendor invoices into a tracking spreadsheet. Researchers grab data tables from published papers to run their own analysis. Students extract exam schedules or grade tables to sort and filter in Google Sheets.
For the cleanest results, use PDFs with a real text layer — digitally generated documents rather than scans. If you have a scanned table, run it through the OCR tool first to create a text layer. And remember that this tool focuses on tabular data; if you need the document's running text instead, the PDF-to-Text or PDF-to-Markdown tools are a better fit.
Questions
Everything runs in your browser. How we keep files private
How does it detect table rows and columns?
The tool reads the positions of every text element on the page and clusters them by horizontal and vertical alignment. Elements that share a row position become cells in the same row; consistent vertical alignment defines columns. It works without relying on visible grid lines.
Will it work on scanned PDFs?
Only if the PDF has a text layer. A scanned image with no embedded text will produce empty results. Run OCR on the document first, then try the CSV extraction again.
Can it handle multi-page tables?
Each page is processed independently. If a table spans multiple pages, you will get one CSV per page. You can then combine them in your spreadsheet editor by pasting them together — the columns will match.
Is the data processed privately?
Yes. Table detection and CSV generation happen entirely inside your browser. No data is sent to any server.