The challenge: PDFs don't "know" they have tables
A table in a PDF is just a grid of text positioned at specific coordinates. There's no tag saying "this is a table with 5 columns and 12 rows." Extracting it into Excel requires the converter to guess the table structure from text positions — which works well for clean PDFs and can struggle with complex layouts.
When PDF-to-Excel works great
- Financial reports with clean, bordered tables
- Price lists with aligned columns
- Data exports from accounting software
- Bank statements and invoices
When it's trickier
- Tables without visible borders (the converter may not detect columns)
- Merged cells spanning multiple rows or columns
- Tables that span multiple pages
- Scanned PDFs (need OCR first)
- PDFs with multiple tables per page at different column widths
How to convert PDF to Excel with PDFCraft
- Open the PDF to Excel tool.
- Upload your PDF.
- Click Convert to Excel.
- Download your .xlsx file and open it in Microsoft Excel or Google Sheets.
Post-conversion cleanup in Excel
Most conversions require a bit of cleanup:
1. Check column alignment
The converter may split a single column into two, or combine two columns into one. Sort the data and compare with the original to catch misalignments.
2. Fix number formats
Numbers in PDFs are sometimes read as text (you'll see left-aligned numbers). Select the column, click Format Cells → Number to fix this.
3. Remove header/footer rows
Page numbers, headers, and footers often appear in the spreadsheet. Delete those rows manually.
4. Handle merged cells
If the original had merged cells, the converter may have placed the data in the wrong column. Use Find (Ctrl+F) to locate misplaced values.
Alternative: copy-paste from PDF
For simple tables, you can sometimes just:
- Open the PDF in a browser
- Select and copy the table text (Ctrl+A, then Ctrl+C)
- Paste into Excel (Ctrl+V)
- Use Data → Text to Columns to split the pasted text into proper columns
This works surprisingly well for clean, text-based PDFs and requires no tool at all.
When to use dedicated data extraction software
If you routinely extract data from PDFs — say, processing 50 supplier invoices a month — consider dedicated tools like Tabula (free, open source), Camelot (Python library), or Adobe Acrobat's data extraction. They offer more control over table detection.