pdf-extraction

Use pdfplumber's extract_tables() method on each page to detect and extract tables based on line or text strategies. The result is a list of rows that can be loaded into a pandas DataFrame and exported to CSV or Excel.

Open the file with pdfplumber and call extract_text() on the desired page objects, such as pdf.pages[4:10] for pages 5-10. You can adjust x_tolerance, y_tolerance, and layout options to control grouping and formatting.

No, pdfplumber only works with PDFs containing a native text layer. Scanned or image-based PDFs require OCR processing first, since there are no extractable characters for the library to read.

Table detection depends on the chosen vertical and horizontal strategies and tolerance settings. Tables without visible ruling lines often need the text strategy, and adjusting snap_tolerance and join_tolerance improves detection accuracy.

Use page.to_image() to render the page, then call debug_tablefinder() and save the image to see detected cells and edges. You can also draw character, word, and line bounding boxes to inspect the page structure visually.