# Sampling Observations — String Normalisation + Numeric Row Ordering

> Sampling Observations — String Normalisation + Numeric Row Ordering is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).

Normalises string fields and applies numeric row ordering to sampling observation records (sample_value, sample_weight) for up to 200 rows, returning 2 analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-15-025?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/sampling-observations-string-normalisation-numeric-row-ordering-3ca46b30
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_I6TGvnu0dbPsxRutix_Td

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 sampling-observations-string-normalisation-numeric-row-ordering-3ca46b30 -d '<json body>'
```

Example prompt: Can you run string normalisation and numeric row ordering on my sampling observations? I have 4 rows — row-1 (group-a, 2026-10-01, sample_value=10, sample_weight=1), row-2 (group-b, 2026-10-02, sample_value=20, sample_weight=2), row-3 (group-a, 2026-10-03, sample_value=15, sample_weight=3), row-4 (group-b, 2026-10-04, sample_value=30, sample_weight=4) — and apply the reports to the sample_value field.

## When to prefer this

Choose this endpoint when you have up to 200 sampling observation records (with sample_value and sample_weight) and need both string normalisation on group/label fields and a numeric row ordering report in a single low-cost call. It is ideal for pre-processing or QA of sampling datasets without needing live data lookup, prediction, or external integrations.

## Known failure modes

- More than 200 rows submitted — request rejected due to maxItems limit
- Missing required fields (row_id, dataset_group, date, sample_value, or sample_weight) — validation error
- Date field not matching YYYY-MM-DD pattern — schema validation failure
- Numeric values outside allowed range (-1e12 to 1e12) — validation error
- Empty rows array (minItems=1 violated) — rejected
- Invalid field selector (must be 'sample_value' or 'sample_weight') — enum validation error

## How this service works

Sampling observations — String normalisation + Numeric row ordering: String normalisation + Numeric row ordering for supplied sampling observations records (sample_value, sample_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

Two analytical reports: (1) a string normalisation report covering dataset_group and related string fields, and (2) a numeric row ordering report for the selected field (sample_value or sample_weight), applied across up to 200 supplied sampling observation rows.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/sampling-observations-string-normalisation-numeric-row-ordering-3ca46b30/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)