# Sampling Observations Analytics — Grouped Numeric Summary + Adjacent Row Changes

> Sampling Observations Analytics — Grouped Numeric Summary + 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).

Computes two analytical reports on supplied sampling observation rows: a grouped numeric summary (by dataset_group) and adjacent row-to-row change analysis, for up to 200 rows of sample_value/sample_weight data.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-15-091?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-analytics-grouped-numeric-summary-adjacent-row-6d9ef6e0
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_rlw-hZW28H7asnZSQKwSN

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-analytics-grouped-numeric-summary-adjacent-row-6d9ef6e0 -d '<json body>'
```

Example prompt: I have 50 sampling observation rows with row IDs, dates, group labels (like 'control' and 'treatment'), sample_value, and sample_weight — can you run a grouped numeric summary and adjacent row change analysis on the sample_value field for me?

## When to prefer this

Choose this endpoint when you have tabular sampling observation data with group labels and need two analytical outputs — grouped statistics and sequential row changes — in a single API call. It is best suited for offline/batch analytical use cases where you supply all rows at once (up to 200) and want lightweight local computation without any external data lookups, predictions, or professional assessments. Prefer this over general-purpose analytics tools when you specifically need the combination of grouped numeric summary AND adjacent row change analysis on sample_value or sample_weight fields.

## Known failure modes

- Input array has zero rows — minItems:1 violation returns validation error
- More than 200 rows supplied — maxItems:200 exceeded returns rejection
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- sample_value or sample_weight outside allowed range (-1T to +1T) causes rejection
- Missing required fields (row_id, dataset_group, date) returns validation error
- field enum value not 'sample_value' or 'sample_weight' causes rejection
- Payment not included or insufficient USDC causes 402 response

## How this service works

Sampling observations — Grouped numeric summary + Adjacent row changes: Grouped numeric summary + 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) a grouped numeric summary breaking down statistics (counts, means, sums, min/max, etc.) per dataset_group for the selected field, and (2) an adjacent row change report showing sequential differences between consecutive rows for the selected field — all computed locally with no external data lookups.

## 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-analytics-grouped-numeric-summary-adjacent-row-6d9ef6e0/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)