About PDF to Excel
Tables locked in PDFs are a regular frustration. The bank sent your monthly statement as a PDF, but you want to total a column. The vendor's price list is a PDF with 300 line items, and you need it in a spreadsheet to filter. The research paper has a useful table in it, and you want to put the numbers into your own analysis.
PDF to Excel extracts the tabular data into a spreadsheet. The output is an XLSX file you can open in Excel, Google Sheets, or Numbers, with the rows and columns roughly where they were in the PDF.
What works well
Clean tables with consistent rows and columns. Bank statements, invoices, price lists, research data tables. The extraction reads the column boundaries from the layout and gets the rows right most of the time.
Multi-page tables with repeating headers. The converter recognises the header pattern and stitches the data into a single sheet instead of breaking at each page.
Numeric data. Numbers come across as numbers in the spreadsheet, not as text-formatted numbers, which means you can immediately use them in formulas without a Find and Replace pass.
Where you'll need to clean up
Tables without visible borders. The extractor uses whitespace and alignment to guess at column boundaries when there are no lines to follow. For well-aligned data this works; for messy data the column splits sometimes drift, and you'll need to redo a couple by hand.
Merged cells. The PDF doesn't store the concept of a merged cell, only the visual layout. The extractor either splits the merged cell across multiple rows or repeats the value, depending on the case. Quick to fix in Excel after.
Scanned PDFs. Treat them like the Word conversion: run OCR first, then extract. Without OCR you get a worksheet with images instead of editable cells.
Tables with footnote markers or unit symbols in cells. The extractor pulls the whole cell text, including the markers. You might want to clean those out before doing math.
Real uses
Pulling expenses from a bank statement PDF into a spreadsheet you can categorise and chart.
Building a price comparison sheet from several vendor catalogues. Convert each catalogue, copy the relevant rows into a master sheet.
Importing financial data from a quarterly report's appendix tables into your own analysis model.
Cleaning data from a government open-data PDF report when the original CSV isn't published.
Limits
Formulas are not reconstructed. The extracted values are the values; if the original PDF was generated from a spreadsheet, the formulas that produced those values are gone. You can rebuild them on your end.
Charts in the PDF don't come across as chart objects. They appear as static images if they appear at all. The data underneath those charts is what you want to extract; the chart itself can be rebuilt in Excel from the data once it's in the sheet.
When the output needs cleanup
Open the extracted XLSX and skim it once before sharing. Look for empty rows or columns inserted by the layout detection; delete them. Watch for header rows that ended up in the middle of the data because the PDF had per-section headers; merge or move them to keep your data block clean.
If numbers are showing as text (you can tell because they don't right-align by default and don't sum), select the column, click Data, click Text to Columns, and step through with the Finish button. That forces Excel to re-parse the column and treat the numeric cells as numbers. A handful of seconds and the data becomes computable.