Converting PDF documents to Excel format for data analysis

Extracting tabular data from PDF documents into editable Excel spreadsheets — whether financial statements, inventory reports, or survey results — enables further analysis and data manipulation.

How Nutrient helps you achieve this

Nutrient Python SDK handles PDF-to-XLSX conversion. With the SDK, you don’t need to worry about:

  • Parsing PDF table structures
  • Managing cell alignment and formatting
  • Handling complex table layouts
  • Data extraction logic

Instead, Nutrient provides an API that handles all the complexity behind the scenes, letting you focus on your business logic.

Complete implementation

Below is a complete working example that demonstrates PDF-to-XLSX conversion. These lines set up the Python application. The import statements bring in all necessary classes from the Nutrient SDK:

from nutrient_sdk import Document
from nutrient_sdk import NutrientException

This line opens the PDF file. The context manager(opens in a new tab) syntax ensures the document is automatically closed when you’re done, preventing resource leaks:

def main():
    try:
        with Document.open("input_table.pdf") as document:

This block exports the PDF content to an Excel spreadsheet and saves it as output.xlsx. The try-except block handles potential errors using NutrientException:

            document.export_as_spreadsheet("output.xlsx")
            print("Successfully converted to output.xlsx")
    except NutrientException as e:
        print(f"Error: {e}")


if __name__ == "__main__":
    main()

Conclusion

The conversion logic consists of two steps:

  1. Open the document.
  2. Export as spreadsheet.

Nutrient handles PDF table parsing and Excel formatting so you don’t need to understand PDF internals or manage cell alignment manually.

You can download this ready-to-use sample package that’s fully configured to help you get started with the Python SDK.