LLM Application Development
Intermediate
4.5
Extract Tables from PDFs for RAG
Tables break naive text extraction — handle them properly.
0h 25m
1 lesson
1.2K students
What You'll Learn
Learning objectives will be added soon.
Tutorial Content
Why tables are hard
Copying a PDF table as plain text scrambles rows and columns, and RAG then retrieves nonsense. Tables need structure-aware parsing.
Tools that help
- Unstructured / LlamaParse — detect and preserve table structure.
- Camelot / pdfplumber — extract tables to DataFrames.
A good pattern
Convert each table to Markdown or CSV, keep it as its own chunk with a caption, and store which page it came from. Clean tables in, accurate answers out — messy tables are a top cause of bad RAG results on real documents.
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Tags
RAG
Python
Data Science