# Sampling Observations — Exact Row Deduplication + Adjacent Row Changes

> Sampling Observations — Exact Row Deduplication + Adjacent Row Changes 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).

Deduplicates exact rows and detects adjacent row changes in supplied sampling observation records (sample_value, sample_weight) for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-15-046?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-exact-row-deduplication-adjacent-row-changes-2126b3a4
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_qsdA90risZItjEIX_1d5x

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-exact-row-deduplication-adjacent-row-changes-2126b3a4 -d '<json body>'
```

Example prompt: I have 50 sampling observation rows with dates, sample values, and sample weights — can you run exact row deduplication and detect adjacent row changes on the sample_value field? Here's my data: row-1 on 2026-10-01, group-a, value 10, weight 1; row-2 on 2026-10-02, group-b, value 20, weight 2 ...

## When to prefer this

Choose this endpoint when you need lightweight, local-only data quality analysis on sampling observation datasets of up to 200 rows — specifically when you want both exact duplicate detection and adjacent-row change detection in a single call. It is ideal for survey data cleaning, experimental sample QA, or time-series observation auditing where no external data enrichment or prediction is needed.

## Known failure modes

- More than 200 rows submitted — request exceeds maxItems limit
- Missing required fields (row_id, dataset_group, date, sample_value, sample_weight) — validation error
- Invalid date format not matching YYYY-MM-DD pattern — schema rejection
- Values outside allowed numeric range (-1e12 to 1e12) — validation error
- Empty rows array — minItems constraint violation

## How this service works

Sampling observations — Exact row deduplication + Adjacent row changes: Exact row deduplication + Adjacent row changes 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

Returns two analytical reports: (1) an exact row deduplication report identifying fully duplicate rows among the submitted records, and (2) an adjacent row changes report flagging consecutive rows where the selected field (sample_value or sample_weight) differs. Both reports are computed locally from the supplied data, with no external lookup or prediction.

## 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-exact-row-deduplication-adjacent-row-changes-2126b3a4/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)