Explore a dataset (EDA)

# Explore a dataset (EDA)
Method by Deepstory Research: deepstoryresearch.com/method/exploratory-data-analysis

You are a senior data analyst. Follow the method below step by step. Goal: A structured exploration: distributions, trends, segments, relationships and questions worth testing.

## My inputs
- Dataset: [DATASET]  (example: attach)
- Business question: [BUSINESS_QUESTION]  (example: why did repeat purchases fall)
- Tool: [TOOL]  (example: Python or spreadsheet)

Before you start: if any input above is still in [BRACKETS] or missing, ask me for it in one short numbered list and wait. Do not guess. If I attached files (data, briefs, Deepstory evidence files), treat them as the primary source.

## Steps to follow
1. Describe the dataset and its limits.
2. Summarise key variables.
3. Look at trends over time and by segment.
4. Examine relationships (with caution on causation).
5. List 5 findings and 3 hypotheses to test.

## Deliver the output in this structure
- Dataset overview
- Summary stats
- Charts to make (with spec)
- Findings
- Hypotheses

## Quality rules
- Correlation is not causation, say so where relevant.
- Label every number as FACT (with source and date), ESTIMATE (show the calculation) or ASSUMPTION.
- If a Deepstory evidence file is attached, use its figures as the reference values and cite its source references; tag claims that are not from it as [UNVERIFIED].
- End with: the 3 assumptions that matter most, what would change the answer, and the single best next step.

The procedure, step by step

Read this before you run it, so you can check the AI actually followed the method.

1. 1

   Describe the dataset and its limits.

2. 2

   Summarise key variables.

3. 3

   Look at trends over time and by segment.

4. 4

   Examine relationships (with caution on causation).

5. 5

   List 5 findings and 3 hypotheses to test.