PDF to Excel

Extract tables from PDFs into Excel spreadsheets.

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About the PDF to Excel

PDF to Excel turns the tables locked inside a PDF into a real spreadsheet you can sort, filter, sum, and chart. Instead of retyping numbers cell by cell, you upload an invoice, bank statement, vendor report, or inventory list and get back rows and columns in an .xlsx or .csv file. The point is reusability: a printed table is read-only, but once values land in Excel you can run pivots, compare months, standardise headers, and feed the data into accounting or analytics systems without manual transcription errors creeping in.

Reach for this tool whenever data lives in PDF form but the work needs to happen in a spreadsheet. Accountants pull line items from supplier invoices and statements; analysts rebuild sales summaries and survey tables for dashboards; operations teams refresh weekly stock or freight reports without rekeying. It is most valuable for repetitive, structured documents where the same layout appears every period, because that is exactly the retyping that wastes the most time and introduces the most mistakes when done by hand.

Under the hood, conversion happens in two stages: table detection then cell mapping. The tool looks for column boundaries, header rows, and cell edges, then writes each value into the matching spreadsheet cell. This works cleanly on native (digitally created) PDFs that already contain a selectable text layer. Scanned PDFs are just images of pages, so they first need OCR (Optical Character Recognition) to read the characters from the pixels before any table structure can be rebuilt. Documents with ruled gridlines and consistent spacing convert far more reliably than free-flowing layouts.

Accuracy depends heavily on the source file. Native PDFs with clean tables can convert almost perfectly, while scanned or photographed pages depend on scan quality and rarely hit the same precision. Always spot-check the result against the original before trusting it, watching for OCR character swaps like 0 versus O or l versus 1. For files that contain financial figures or personal details, prefer browser-based conversion that processes the document on your own device, so the PDF never leaves your computer and is not stored on a server.

Frequently asked questions

Can it convert a scanned PDF or a photo of a table?

Yes, but scanned and photographed pages are images, so they require OCR to read the characters before the table can be rebuilt. Results are best when the scan is sharp, well-lit, straight, and at least 300 DPI. Always verify the numbers, because image-based conversion is less reliable than a native PDF with selectable text.

Will my table formatting and merged cells survive the conversion?

Plain tables with clear gridlines and one value per cell convert most faithfully. Merged cells, multi-row headers, and nested tables are the hardest cases and may be split or shifted across columns, so they often need a quick manual cleanup in Excel afterwards.

What is the difference between exporting to .xlsx and .csv?

An .xlsx file keeps multiple sheets, cell types, and basic formatting and opens directly in Excel. A .csv file is plain comma-separated text with no formatting, which is lighter and ideal for importing into databases, other tools, or scripts.

Is it safe to upload a bank statement or invoice?

Choose a converter that processes the file in your browser on your own device, so the document is never uploaded to or stored on a remote server. That keeps account numbers, totals, and personal details private throughout the conversion.

Why are some columns merged together or split in the wrong place?

Basic converters extract characters in reading order and guess where columns begin and end, so tables without ruled lines or with uneven spacing can misalign. Adding gridlines in the source document, or fixing the few affected columns in Excel, usually resolves it quickly.

From our blog

Bulk Image Compression: How to Make a Whole Site Load Faster in One Pass

By the Super Simple Digital Tools Team · Updated June 2026

If your website feels sluggish, images are the usual suspect. On a typical un-optimized page they account for somewhere between 60 and 80 percent of the total bytes a browser has to download, dwarfing the HTML, CSS, and JavaScript. That is why optimizing pictures gives a bigger speed return than almost any other single change, and why doing it in bulk, across every image at once, beats fiddling with files one at a time.

Speed is not just about user patience anymore; it is measurable and ranked. Google's Largest Contentful Paint metric clocks how long it takes for a page's biggest visible element to render, and on most pages that element is an image. When you compress your hero and content images, you are directly attacking the metric that determines a good Core Web Vitals score, which in turn influences how the page is judged in search.

The single biggest lever is format. Modern WebP packs the same visual quality into far fewer bytes than the formats it replaces: lossy WebP averages around 30 percent smaller than JPEG, and for photographs saved as PNG the savings can reach 60 to 80 percent when switched to WebP. It manages this by dividing each image into blocks, predicting each block from its neighbors, and spending more data on detailed regions than on flat ones, an approach more efficient than JPEG's older method.

Choosing between lossy and lossless comes down to what the image is. Photographs and screenshots tolerate lossy compression well, because the discarded detail hides in complex textures the eye glosses over. Graphics with crisp text, logos, or hard edges look better kept lossless, since lossy artifacts show up clearly against flat color. A good bulk workflow lets you apply the aggressive setting to photos and a gentler one to graphics rather than treating everything the same.

Finally, remember that compression and resizing are different jobs that work best together. Compression reduces the bytes per pixel; resizing reduces the number of pixels. A 4000-pixel-wide camera photo displayed in a 800-pixel column wastes enormous bandwidth no matter how well it is compressed. Scale images down to the largest size they will actually be shown at, then compress, and the combined effect on file size and load time is far greater than either step alone.

  • Always keep your original full-resolution files. Lossy compression is permanent, so treat the compressed batch as a separate web-ready copy rather than overwriting your masters.
  • Use lossy compression and WebP for photographs and screenshots, but keep logos, line art, and images with sharp text lossless to avoid visible artifacts around edges.
  • Resize before you compress. Scaling a huge photo down to the width it will actually display at removes far more weight than compression alone can.
  • Test one representative image at your chosen quality first, then run the whole batch once you are happy, so you do not redo a large set after spotting a bad setting.

Read the full guide →

Tool by the Super Simple Digital Tools Team. Reviewed by our editorial team. Free to use, no signup required.

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