# Transformation Throughput Analytics: Grouped Numeric Summary + Adjacent Row Changes

> Transformation Throughput 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 2026-10-28).

Analyzes transformation throughput records (processed_rows, duration_seconds) by producing a grouped numeric summary and an adjacent row change report for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-13-091?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-28
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/transformation-throughput-analytics-grouped-numeric-summary-adjacent-6d5ed7f2
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Tx_-TZ9pL_7m9wLIJctcZ

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 transformation-throughput-analytics-grouped-numeric-summary-adjacent-6d5ed7f2 -d '<json body>'
```

Example prompt: I have 4 transformation throughput records — row-1 on 2026-10-01 in group-a with 10 processed_rows and 1 second, row-2 on 2026-10-02 in group-b with 20 processed_rows and 2 seconds, row-3 on 2026-10-03 in group-a with 15 processed_rows and 3 seconds, row-4 on 2026-10-04 in group-b with 30 processed_rows and 4 seconds — can you give me a grouped numeric summary and adjacent row change report for the processed_rows field?

## When to prefer this

Choose this endpoint when you have tabular transformation throughput records and need both a grouped statistical summary and adjacent row change detection in a single paid call. It is ideal for ETL monitoring, pipeline auditing, or batch job analytics where you already have the data locally and need offline, reproducible computation without live data fetches or ML predictions.

## Known failure modes

- Input array exceeds 200 rows — request will be rejected or truncated
- Missing required fields (row_id, dataset_group, date, processed_rows, duration_seconds) cause row-level errors
- Invalid date format (not YYYY-MM-DD) triggers validation failure
- Null numeric values may affect aggregate accuracy in grouped summary
- field enum value not matching 'processed_rows' or 'duration_seconds' causes schema validation error

## How this service works

Transformation throughput — Grouped numeric summary + Adjacent row changes: Grouped numeric summary + Adjacent row changes for supplied transformation throughput records (processed_rows, duration_seconds). 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 independent analytical reports: (1) a grouped numeric summary aggregating the selected metric (processed_rows or duration_seconds) by dataset_group, and (2) an adjacent row change report showing value differences between consecutive rows — both computed locally from the supplied data with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/transformation-throughput-analytics-grouped-numeric-summary-adjacent-6d5ed7f2/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)