# Personal Grocery Inflation Analysis

You are helping me analyze my own grocery purchase history to estimate how much my personal prices have changed over time.

## What I'm giving you

I will paste a CSV export from BasketIndex, a browser extension that captures my online grocery receipts. The CSV contains:

- Date of purchase
- Product name
- Quantity
- Unit price
- Total price
- Store (currently Lidl)

## What I want you to do

1. **Summarize the time range** — tell me the earliest and latest dates in the data and how many purchases are included.

2. **Find repeat purchases** — identify products I bought more than once. For each repeat product, show:
   - First purchase date and price
   - Most recent purchase date and price
   - Percentage change
   - Whether the quantity/weight changed (this matters — a "price increase" might just be a larger package)

3. **Estimate personal inflation** — using only the repeat purchases where the product and quantity are comparable, estimate the average price change across my basket. This number will be approximate. State the uncertainty clearly.

4. **Separate real price changes from basket-mix changes** — if my overall spending went up, distinguish between:
   - I'm buying the same things at higher prices (actual inflation)
   - I'm buying different or more things (changed behavior)

5. **Note what the data cannot tell us** — for example:
   - Products I buy in-store (not captured by the extension)
   - Products I stopped buying (they disappear from the data)
   - Promotional/discount pricing that skews comparisons
   - Package size changes that aren't detected as the same product

## Important caveats to include in your response

- This is an estimate based on my personal shopping behavior, not an official inflation measurement
- The data only covers online purchases from supported retailers
- Basket-mix effects can make spending look like inflation when it isn't
- Small sample sizes for specific products reduce confidence

## Format

Please structure your response as:

### Summary
[Time range, purchase count, stores included]

### Repeat purchases with price changes
[A table or list of products with before/after prices and % change]

### Estimated personal inflation
[A single estimated percentage with a clear confidence statement]

### Basket-mix vs. real price changes
[Breakdown of what's driving my spending changes]

### Data limitations
[What we can and cannot conclude from this data]

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## My CSV data

[PASTE YOUR CSV EXPORT HERE]