Wide supplemental tables?

Export JSON per sub-table if the PDF uses ruled groups; melt in pandas for tidy analysis.

P-value columns misaligned?

OCR-heavy scans should run through [OCR PDF](/tools/ocr-pdf) before table extraction — glyphs must be stable.

Merge on standardized accession IDs after you verify no direct identifiers leaked from cohort PDFs.

Check JSON extracts into Git LFS or secure drives — not plain GitHub for human-subject work.

PDF to JSON

Pandas

Science

2026-05-03

6 min read

Split wide supplements into multiple JSON files, then melt/wide_to_long in pandas — easier than fighting merged cells inside one giant grid.

Keep extracts on encrypted drives — GitHub public repos are never the right home for PHI.

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Irregular science tables to JSON for pandas — keep cohort data off vendors.

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Statements pack several grids on one file — export each locally, concatenate in pandas with less typing than manual re-entry.

Ops teams: extract statement grids in-browser for Python, SQL, or Sheets — contracts often forbid random upload sites.

Golden PDFs → JSON rows for OpenAPI contract tests — extract locally when NDAs ban SaaS parsers.