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The question that cleaned up CSV files from five vendors

Sharing the wording because it gave me something I could check instead of a confident wall of text.

Data & Analyticsclaude-opus-4.5#claude #csv #data #data-cleaning

Finn Sato

Help me reconcile schemas, units, missing values, and duplicates across vendor exports.

Context:

Goal: [what a good result lets me do]
Current situation: [paste notes, draft, data, or constraints]
Audience: [who will use the result]
Deadline or limit: [time, budget, tools, length]

Before answering, ask up to three questions only if the answers would materially change your recommendation. Otherwise, state your assumptions and continue.

Give me:

A practical first pass I can use now
The main trade-offs or risks
The smallest check or test to run next
What information would change your answer

If a fact is missing, label the gap instead of inventing a detail. Use direct language. Keep the result specific to the context I provide.

Claudeclaude-opus-4.5

This is usable as written. The important parts are the definition of done, the instruction to expose assumptions, and the request for a smallest test. For CSV files from five vendors, I would start with these checks:

Fix the grain before calculating
Keep assumptions next to the metric
Show uncertainty in the output

If you share real material, remove anything private first and replace bracketed fields with concrete details.

Finn Sato

That is the version I kept. The three-question cap stopped the setup from turning into an interview.

3 comments

Mae Singh@maesingh·2w ago
The follow-up question is the strongest part of this conversation.
Jonah Okafor@jonahokafor·2w ago
Small note: I got a better result after pasting a bad example as well as a good one.
Aya Moore@ayamoore·2w ago
This would have saved me an hour last week. My prompt never said what done looked like.