# Price Basket Observations — String Normalisation + Date by Category Pivot

> Price Basket Observations — String Normalisation + Date by Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-27).

Runs two local analytical reports on price basket observation data: string normalisation and a date-by-category pivot, for up to 200 rows of item_price or quantity_weight records.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-economics-07-035?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-27
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/price-basket-observations-string-normalisation-date-by-category-pivot-51fd4901
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_ZDjN37HA2kieDhAwKnQik

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability price-basket-observations-string-normalisation-date-by-category-pivot-51fd4901 -d '<json body>'
```

Example prompt: Can you run string normalisation and a date-by-category pivot on my price basket observations? I have rows with item_price values across regions like group-a and group-b, dated from 2026-10-01 to 2026-10-04, and I want both reports for the item_price field.

## When to prefer this

Choose this endpoint when you have up to 200 rows of price basket observation data (with item_price and quantity_weight fields) and need both string normalisation and a date-by-category pivot in a single low-cost call ($0.01 USDC). It is ideal for offline, local analytical processing of economics or retail basket data without any live lookups or predictions. Prefer it over general-purpose analytics tools when you need these two specific report types bundled together cheaply.

## Known failure modes

- Rows array is empty or exceeds 200 items — validation error returned
- Invalid date format (not YYYY-MM-DD) in any row — schema validation failure
- item_price or quantity_weight values outside allowed numeric range — rejection
- Missing required fields (row_id, region, date) on any row — schema error
- Invalid field selector (not 'item_price' or 'quantity_weight') — enum validation error
- Payment not provided or insufficient USDC — 402 Payment Required

## How this service works

Price basket observations — String normalisation + Date by category pivot: String normalisation + Date by category pivot for supplied price basket observations records (item_price, quantity_weight). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.

## Output

Returns two analytical reports for the supplied price basket observation rows: (1) a string normalisation report cleaning and standardising text fields, and (2) a date-by-category pivot table grouping either item_price or quantity_weight values by date and region/category. No external data is fetched; all analysis runs locally on the supplied rows.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "region",
     "date",
     "item_price",
     "quantity_weight"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "region": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "item_price": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "quantity_weight": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "region": "group-a",
     "row_id": "row-1",
     "item_price": 10,
     "quantity_weight": 1
    },
    {
     "date": "2026-10-02",
     "region": "group-b",
     "row_id": "row-2",
     "item_price": 20,
     "quantity_weight": 2
    },
    {
     "date": "2026-10-03",
     "region": "group-a",
     "row_id": "row-3",
     "item_price": 15,
     "quantity_weight": 3
    },
    {
     "date": "2026-10-04",
     "region": "group-b",
     "row_id": "row-4",
     "item_price": 30,
     "quantity_weight": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "item_price",
    "quantity_weight"
   ],
   "type": "string",
   "default": "item_price"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/price-basket-observations-string-normalisation-date-by-category-pivot-51fd4901/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)