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To extract text and tables from PDF documents, you can automate the process using Python libraries like pdfplumber to read content and compile structured data. This handles administrative and research tasks by converting unstructured PDFs into analysis-ready formats.

Yes, you can perform OCR on scanned PDF files to extract data using pdf2image combined with OCR techniques. This allows you to read and digitize text from image-based scanned documents, making them searchable and ready for automated data extraction workflows.

The best way to merge, split, or watermark PDF documents is to automate these operations using Python libraries like pypdf. Automating batch processing ensures consistent results across files, saving time and reducing manual errors in document management.

You can fill forms and encrypt PDF files programmatically by using Python libraries such as pypdf to apply form fields and set password protection. This automates document security and data entry tasks across administrative and data-collection workflows.

Yes, this PDF processing approach works for batch processing invoices by extracting data from multiple files and compiling it into a structured format. Automating this extraction saves significant time and reduces errors compared to handling each invoice manually.

Limitations of using pypdf and pdfplumber for PDF extraction include difficulty reading text from scanned documents without applying OCR first. Complex PDF layouts may also require additional processing to accurately extract tables and structured data for analysis.