← All IntelClip / AI ToolsPulling tables out of a PDF as dataframes
From Structuring the Unstructured - Cedric Clyburn, Red Hat · ≈11:21
Shows the concrete deliverable that distinguishes structured extraction from text dumping: tables preserved as queryable objects rather than linearized prose.
What’s in it
- Shows the concrete deliverable that distinguishes structured extraction from text dumping: tables preserved as queryable objects rather than linearized prose.
Clip transcript
formats like markdown, HTML, dictionary, and much more. But the real value here is not just with basic text and columns, but working with tables. So, this PDF here has a variety of different tables that we want to be able to extract. And so, by doing a converter for this specific document, we can then extract these tables here and be able to export this to a data frame so we can render this out in our Jupiter notebook here. So as I run this cell, you can see that we've exported eight different tables from that source PDF and we can list these but also be able to get these in a format ready to use in a rag application or just to query with our LLM. So we've
Comments
Checking sign-in…
Loading comments…