Analyze Pasted Data

Get findings from a pasted table or CSV with magnitudes, caveats, and a clear line between what the data shows and what it can't answer.

Data:
"""
[PASTE CSV, TABLE, OR EXPORTED NUMBERS]
"""

Analyze the data above. The question I'm trying to answer: [YOUR QUESTION]
Context on where this data comes from: [SOURCE, TIME PERIOD, KNOWN QUIRKS: e.g. "Stripe export, Q2, refunds excluded"]

Work in this order:
1. **Describe before analyzing**: what the columns are, row count, time range, and anything odd you notice (gaps, duplicates, outliers, suspicious zeros). If a column's meaning is ambiguous, state the assumption you're making about it in a line starting "ASSUMING:".
2. **Findings**: 3-6 findings ranked by relevance to my question. Each finding: the claim, the numbers behind it (with magnitude; "up 34%, from 1,200 to 1,610", never just "increased"), and its biggest caveat.
3. **Correlation vs. cause**: for any relationship you found, say explicitly whether the data can support a causal claim (it usually can't) and what would be needed to test one.
4. **What this data cannot answer**: the parts of my question that need data I didn't provide, and exactly what to pull.
5. **Next queries**: 2-3 specific follow-up cuts of this data worth running, and what each would confirm or kill.

Rules: compute from the pasted data only; if the data is too small or noisy for a finding to be trustworthy, say "not enough data" for that finding instead of extrapolating. Show your arithmetic for the key numbers so I can spot-check it.

How to use

Spot-check the arithmetic on at least the headline finding: models occasionally miscompute even when the reasoning is sound, which is why the prompt forces the math to be shown. For files over a few hundred rows, use a tool with code execution and this same structure.

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