# Market Survey Observations — String Normalisation + Numeric Row Ordering

> Market Survey 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 sorts rows numerically for market survey observation records containing respondent_count and sample_weight fields, producing two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-06-025?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/market-survey-observations-string-normalisation-numeric-row-ordering-ab73613d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_0lzSyVrkzTm9ndRGrSrc_

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 market-survey-observations-string-normalisation-numeric-row-ordering-ab73613d -d '<json body>'
```

Example prompt: Can you run string normalisation and numeric row ordering on my market survey data? I have 4 rows with company groups 'group-a' and 'group-b', dates from 2026-10-01 to 2026-10-04, and I want the analysis on the respondent_count field — give me the two reports.

## When to prefer this

Choose this endpoint when you need lightweight, local string normalisation and numeric row ordering on market survey data (respondent_count or sample_weight fields) without requiring any external data lookups, predictions, or live integrations. It is ideal for pre-processing up to 200 survey observation rows cheaply ($0.01 USDC for two reports). Prefer alternatives if you need pivot tables, histogram generation, weighted means, or other analytical transformations offered by sibling endpoints.

## Known failure modes

- Rows array empty or missing — returns validation error
- More than 200 rows supplied — rejected with maxItems error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- field value not in enum ['respondent_count','sample_weight'] — rejected
- Numeric fields out of allowed range (±1,000,000,000,000) — validation error
- Payment not included or insufficient USDC — x402 payment required error

## How this service works

Market survey observations — String normalisation + Numeric row ordering: String normalisation + Numeric row ordering for supplied market survey observations records (respondent_count, 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 covering the supplied market survey observation rows: one applying string normalisation to text fields (such as company_group) and one ordering rows numerically by the selected field (respondent_count or sample_weight). No external lookups or predictions are made; analysis is performed locally on the provided data.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/market-survey-observations-string-normalisation-numeric-row-ordering-ab73613d/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)