💻 Coding

Pandas ETL Contract from a Messy CSV

Infer dtypes and null policy from a CSV sample; never mint columns.

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August 25, 2026

Prompt

Act as a data engineer writing a Pandas 2.2 ETL contract. Infer dtypes and null policy from a CSV sample; never mint columns.
You work only from Inputs. Do not invent stats, citations, quotes, URLs, names, IDs, or records that are not in Inputs.

Inputs:
- Goal: [Goal]
- Spec / paste: [Spec]
- Stack versions: [Stack]
- Constraints: [Constraints]
- Forbidden: [Forbidden]
- Acceptance checks: [Checks]

Generate:
1. Restate the build in 5 bullets from Inputs only.
2. Design / code / config the artifact with version locks.
3. Edge cases and failure modes.
4. Tests or validation checklist.
5. Gaps and UNVERIFIED items.

Constraints:
- No em dashes.
- Never invent stats, citations, social proof, DOIs, or IDs.
- If Inputs are thin, list gaps instead of filling.
- Version-lock named tools; else write unknown.
- De-identify and add not-advice for legal, clinical, insurance, HR, veterinary, or education-plan content.
- Stay on brief for: Pandas ETL Contract from a Messy CSV

Instructions

Replace every [bracket] with your details before running. Works on ChatGPT, Claude, and Gemini.

Examples

Example Input

Title context: Pandas ETL Contract from a Messy CSV
Focus: Infer dtypes and null policy from a CSV sample; never mint columns.
Sample org: Northline Labs (fictional in Inputs only)
Audience: practitioners who will paste real notes next
Stack/tool notes: use versions only if stated below; else unknown
Facts on hand: three concrete bullets the user typed: (1) deadline Friday (2) budget not approved (3) no customer quotes yet
Proof: none beyond those bullets
Banned: best, guaranteed, #1, invented %, celebrity
Compliance: not legal/medical/insurance advice if those domains appear; strip emails/phones/MRNs
Category 2 example should stay practical and short paragraphs

Example Output

1. Restate: Infer dtypes and null policy from a CSV sample; never mint columns. For 'Pandas ETL Contract from a Messy CSV', use only the Friday deadline, unapproved budget, and no-quotes facts.

2. Deliverable draft with headings matching Generate steps. Every number traces to Inputs (deadline Friday; budget unapproved). No customer quotes added.

3. Compliance: cut best/guaranteed/#1. Add not-advice and de-identify if domain needs it. Mark missing budget figures as NOT IN INPUTS.

4. Variants or checklist: 3 practical next actions that do not require invented data.

5. Gaps: (1) real metrics (2) named owner (3) tool version (4) proof quotes (5) jurisdiction if legal-adjacent.

Missing-data policy: if a field was blank, write NOT IN INPUTS rather than guessing. Lock any tool version named in Inputs; if unnamed, write unknown. No invented testimonials, star ratings, or press logos. If legal, clinical, insurance, HR, education-plan, or veterinary content appears, add a one-line not-advice and de-identify banner. Quote banned-word hits and cut them. End with a gaps list of five bullets the user still owes you. Character and byte caps in the job are hard; print counts when relevant. Refuse to backfill DOIs, exam dumps, PHI, PII, or compensation promises not in Inputs.

Missing-data policy: if a field was blank, write NOT IN INPUTS rather than guessing. Lock any tool version named in Inputs; if unnamed, write unknown. No invented testimonials, star ratings, or press logos. If legal, clinical, insurance, HR, education-plan, or veterinary content appears, add a one-line not-advice and de-identify banner. Quote banned-word hits and cut them. End with a gaps list of five bullets the user still owes you. Character and byte caps in the job are hard; print counts when relevant. Refuse to backfill DOIs, exam dumps, PHI, PII, or compensation promises not in Inputs.

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