How to Convert PDF to Excel: Extract Tables & Data Accurately

Why Convert PDF to Excel?

PDFs are designed for viewing and sharing, not for data manipulation. When someone sends you a financial report, invoice, data table, or statistical summary as a PDF, the data is locked behind a format that does not allow sorting, filtering, calculations, or analysis. You need that data in Excel (or Google Sheets) to actually work with it.

Manual retyping is slow, error-prone, and impractical for anything beyond a few rows. Copy-paste from PDF rarely works -- tables lose their structure, columns merge together, and numbers become uneditable text. The solution is automated PDF-to-Excel conversion that intelligently recognizes table structures and preserves data relationships.

This guide covers every method for extracting data from PDFs into Excel, from simple single-table documents to complex multi-page reports with merged cells, nested headers, and scanned images.

Types of PDF Data Extraction

Not all PDFs are created equal. The extraction method depends on how the PDF was generated.

Native (Digital) PDFs

These PDFs were created digitally -- exported from Word, Excel, accounting software, or generated by a web application. The text and table structure exist as actual data in the PDF file. These are the easiest to convert because the converter can read the underlying data directly.

Examples: Bank statements exported from online banking, reports generated by business software, invoices from billing platforms, government forms downloaded from websites.

Scanned PDFs

These PDFs are essentially photographs of paper documents. They contain image data, not text data. Converting these requires OCR (Optical Character Recognition) to first recognize the text in the images, then reconstruct the table structure.

Examples: Scanned invoices, photographed receipts, digitized paper records, faxed documents saved as PDF.

For detailed OCR guidance, see our tutorial on how to OCR scanned documents.

Hybrid PDFs

Some PDFs combine digital text with scanned elements. A report might have typed text with a scanned table embedded as an image, or a form with machine-readable headers but hand-written values. These require both direct extraction and OCR.

Method 1: Convert PDF to Excel Online

Our online converter provides the fastest path from PDF to Excel without installing any software.

Step-by-Step Instructions

1. Open the ConvertIntoMP4 PDF converter
2. Upload your PDF file by dragging it into the upload area or clicking to browse
3. Select XLSX (Excel) as the output format
4. Choose your conversion options:
   • Table detection mode -- Automatic (recommended), or manual grid definition
   • Page range -- All pages or specific pages containing your tables
   • OCR -- Enable for scanned PDFs (auto-detected in most cases)
5. Click Convert and download your Excel file

The converter analyzes the PDF structure, identifies table boundaries, maps columns and rows, and exports a clean spreadsheet with properly aligned data.

What Gets Preserved

• Column and row structure
• Numeric values (recognized and formatted as numbers, not text)
• Date values (converted to Excel date format)
• Currency values (with appropriate formatting)
• Merged cell structures
• Header rows (detected and optionally frozen)
• Multiple tables per page (each in a separate sheet or section)

Method 2: Use Adobe Acrobat

Adobe Acrobat Pro includes built-in PDF-to-Excel conversion:

1. Open the PDF in Acrobat Pro
2. Click Export PDF in the right panel
3. Select Spreadsheet > Microsoft Excel Workbook
4. Click Export
5. Choose a save location

Acrobat's conversion uses Adobe's proprietary table recognition engine, which handles complex layouts well but requires a paid subscription ($22.99/month for Acrobat Pro).

Method 3: Use Microsoft Excel Directly

Excel 365 and Excel 2019+ can import data from PDFs:

1. Open Excel
2. Go to Data > Get Data > From File > From PDF
3. Select your PDF file
4. Excel's Power Query shows detected tables -- select the ones you want
5. Click Load to import the data

This method works best with simple, well-structured tables. Complex layouts with merged cells or multiple tables per page may require manual cleanup.

Method 4: Python Script (Advanced)

For developers or analysts who need programmatic extraction:

import tabula

# Extract all tables from a PDF
tables = tabula.read_pdf("report.pdf", pages="all")

# Export each table to a separate Excel sheet
with pd.ExcelWriter("output.xlsx") as writer:
    for i, table in enumerate(tables):
        table.to_excel(writer, sheet_name=f"Table_{i+1}", index=False)

The tabula-py library uses Java's Tabula engine, which is one of the most accurate open-source table extractors available.

Handling Complex Table Structures

Real-world PDFs rarely contain simple, clean tables. Here are strategies for dealing with common complications.

Multi-Line Cell Content

Some PDF tables have cells where text wraps to multiple lines. During extraction, each line may be interpreted as a separate row. Solutions:

• Use a converter with "detect multi-line cells" option
• Post-conversion: in Excel, use Find & Replace to merge split rows
• For programmatic extraction, set the lattice mode (grid-line based detection) instead of stream mode (whitespace-based detection)

Merged Header Cells

Tables with merged headers (a single header spanning multiple columns) are particularly challenging. Most converters handle the top-level merge but may struggle with nested merges.

Post-conversion fix: Manually merge the header cells in Excel and adjust column alignment. This takes seconds but often cannot be automated reliably.

Tables Spanning Multiple Pages

When a table continues across page boundaries, converters may create separate tables for each page. To merge them:

1. Convert the entire PDF
2. In Excel, verify that column headers match between page-break tables
3. Cut the data rows from subsequent pages and paste below the first page's table
4. Delete the duplicate header rows

Tables Without Visible Gridlines

Some PDFs use spacing and alignment instead of visible lines to define table structure. These "borderless tables" are harder to detect because there are no grid lines to follow.

Strategy: Use a converter with "stream mode" table detection, which analyzes whitespace patterns to identify columns. Our online converter automatically tries both lattice (grid-based) and stream (space-based) detection and uses whichever produces better results.

Converting Scanned PDFs to Excel

Scanned PDFs require OCR before table extraction. The process adds complexity but is fully achievable with modern tools.

OCR Quality Factors

The accuracy of scanned PDF-to-Excel conversion depends on:

• Scan resolution -- 300 DPI minimum; 600 DPI for small text
• Contrast -- High contrast between text and background produces best results
• Skew -- Slightly rotated scans reduce accuracy; deskewing helps
• Image quality -- Compression artifacts, smudges, and shadows degrade OCR accuracy
• Font type -- Standard printed fonts convert well; handwriting is much harder
• Table structure -- Clear gridlines help both OCR and table detection

Step-by-Step for Scanned PDFs

1. Improve scan quality (if needed) -- Increase contrast, deskew, remove noise
2. Run OCR -- Use our PDF OCR tool to convert the scanned PDF into a searchable PDF with recognized text
3. Convert to Excel -- Process the OCR'd PDF through the PDF-to-Excel converter
4. Verify and correct -- Check the output against the original PDF, fixing any OCR errors

For a complete guide on making scanned documents machine-readable, see our tutorial on how to OCR scanned documents. Our tool supports 17 languages for OCR processing.

Post-Conversion Cleanup in Excel

Even the best conversion produces output that needs some cleanup. Here is a systematic approach:

1. Check Data Types

After conversion, verify that numbers are actually numbers (right-aligned in Excel), not text strings that look like numbers (left-aligned). Select a column of numbers and check the status bar -- if it shows COUNT instead of SUM, the values are text.

Fix: Select the column, go to Data > Text to Columns > Finish (this forces Excel to re-evaluate data types). Or use the VALUE() function to convert text to numbers.

2. Fix Date Formats

Dates may be converted as text strings ("01/15/2026") rather than Excel date values. Use DATEVALUE() or Text to Columns with date format specification to convert them.

3. Remove Empty Rows and Columns

Conversion often inserts blank rows between sections or creates empty columns from whitespace in the original PDF. Use Go To Special > Blanks to select and delete empty rows quickly.

4. Rebuild Formulas

PDF-to-Excel conversion extracts values, not formulas. If the original spreadsheet had SUM, AVERAGE, or other calculations, you need to recreate them manually. The converted values serve as a reference for verifying your formulas.

5. Format for Readability

Apply consistent number formatting, column widths, header styling, and borders to make the extracted data match your organization's spreadsheet standards.

Use Cases and Industry Applications

Finance and Accounting

Bank statements, financial reports, and tax documents are the most common PDF-to-Excel conversion targets. Extracting transaction data into Excel enables reconciliation, trend analysis, and audit preparation.

For financial document workflows, you may also need to convert Excel back to PDF after analysis, or password-protect sensitive PDFs containing financial data.

Research and Academia

Scientific papers, government reports, and statistical publications often include data tables in PDF format. Researchers extract these tables to build datasets, run statistical analyses, and create visualizations.

Supply Chain and Procurement

Purchase orders, packing lists, and inventory reports frequently arrive as PDFs from vendors. Converting to Excel enables data import into ERP systems, price comparison across suppliers, and inventory tracking.

Legal and Compliance

Contract tables, regulatory filings, and compliance reports need to be analyzed in spreadsheet form for auditing and comparison purposes. Our edit PDF tool can also help annotate the original PDF with review notes.

Real Estate

Property listings, rent rolls, and financial pro formas are shared as PDFs. Converting to Excel allows investors to run their own financial models and comparisons. For large document packages, our merge PDF tool can combine multiple property documents before batch processing.

Batch Converting Multiple PDFs

When you have dozens of PDFs to convert (monthly bank statements, quarterly reports, vendor invoices):

1. Upload all PDF files to our converter simultaneously
2. Select XLSX output for all files
3. Process the batch and download all converted files as a ZIP
4. In Excel, use Power Query to combine multiple workbooks into a single master spreadsheet

For programmatic batch processing, our file conversion API supports automated PDF-to-Excel conversion with webhook notifications when processing completes.

Tips for Better Conversion Results

1. Use the original digital PDF whenever possible -- avoid printing and re-scanning
2. Check the PDF source -- if the data originated in Excel, ask for the original XLSX file
3. Convert specific pages -- target only the pages with tables, not the entire document
4. Verify numbers -- spot-check converted values against the PDF, especially totals and percentages
5. Keep the original PDF -- always retain the source file for reference

PDF-to-Excel conversion transforms locked, view-only data into actionable information you can sort, filter, calculate, and visualize. Whether you are extracting financial data, research tables, or business reports, the methods in this guide ensure accurate, efficient extraction from any type of PDF.

If the converted Excel file needs to be shared as a PDF later, our PDF compressor reduces the file size for email delivery. For the reverse workflow, see our guide on how to convert Excel to PDF. And for other PDF conversion needs, explore our tutorials on converting PDF to Word and converting PDF to images.