# Transformation Throughput Analytics — Adjacent Row Changes + Two-Measure Correlation

> Transformation Throughput Analytics — Adjacent Row Changes + Two-Measure Correlation 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).

Computes adjacent row changes and two-measure correlation for transformation throughput records (processed_rows, duration_seconds) on up to 200 supplied rows, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-13-158?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-adjacent-row-changes-two-measure-f98b1464
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_azPaiPZP4zmpBgAqr1eVR

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-adjacent-row-changes-two-measure-f98b1464 -d '<json body>'
```

Example prompt: Can you analyze my transformation throughput records for adjacent row changes and compute the correlation between processed_rows and duration_seconds? I have 4 records: 2026-10-01 group-a 10 rows in 1s, 2026-10-02 group-b 20 rows in 2s, 2026-10-03 group-a 15 rows in 3s, 2026-10-04 group-b 30 rows in 4s — use processed_rows as the primary field.

## When to prefer this

Choose this endpoint when you need both sequential/adjacent-row change analysis and a two-measure correlation between processed_rows and duration_seconds in a single paid call, using only your supplied data (no external lookups). It is well-suited for ETL pipeline monitoring, batch processing diagnostics, and throughput scaling analysis on up to 200 records. Prefer this over single-report endpoints when you need both analytical outputs bundled at $0.01 USDC.

## Known failure modes

- Fewer than 1 row supplied — minimum row count not met
- More than 200 rows supplied — exceeds maximum row limit
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Missing required fields (row_id, processed_rows, duration_seconds) causes rejection
- Null values in both measures may produce undefined correlation result
- Invalid field enum value (not 'processed_rows' or 'duration_seconds') causes error
- Payment of 0.01 USDC not completed — request blocked by x402 paywall

## How this service works

Transformation throughput — Adjacent row changes + Two-measure correlation: Adjacent row changes + Two-measure correlation 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 analytical reports: (1) an adjacent row changes report showing sequential differences between consecutive records for the selected field (processed_rows or duration_seconds), and (2) a two-measure correlation report quantifying the statistical relationship between processed_rows and duration_seconds across all supplied rows. No external data is fetched; analysis is performed entirely on the supplied records.

## 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-adjacent-row-changes-two-measure-f98b1464/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)