# Transformation Throughput Analytics — Category Frequencies + Adjacent Row Changes

> Transformation Throughput Analytics — Category Frequencies + 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 to produce category frequency distributions and adjacent row change reports for processed_rows or duration_seconds fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-13-104?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-category-frequencies-adjacent-row-0a8dfb81
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_1GZvW5MPIkeE8_q5e8vht

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-category-frequencies-adjacent-row-0a8dfb81 -d '<json body>'
```

Example prompt: Can you analyze my ETL throughput records — here are up to 200 rows with row_id, dataset_group, date, processed_rows, and duration_seconds — and give me both the category frequency breakdown by dataset_group and the adjacent row changes for processed_rows?

## When to prefer this

Choose this endpoint when you need both a categorical frequency distribution and a consecutive-row delta analysis on transformation throughput data (processed_rows, duration_seconds) in a single $0.01 call covering up to 200 rows. Prefer it over general analytics APIs when working specifically with ETL or data pipeline logs segmented by dataset_group, and when you need two complementary reports (frequency + change detection) without external data lookups or live connections.

## Known failure modes

- Fewer than 1 row submitted — minimum row count not met
- More than 200 rows submitted — exceeds maximum row limit
- Missing required fields (row_id, dataset_group, date, processed_rows, duration_seconds) on any row
- Invalid date format (must be YYYY-MM-DD)
- Field selector not one of 'processed_rows' or 'duration_seconds'
- Numeric values outside allowed range (±1,000,000,000,000)

## How this service works

Transformation throughput — Category frequencies + Adjacent row changes: Category frequencies + 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 analytical reports: (1) category frequency counts showing how often each dataset_group value appears across the submitted rows, and (2) adjacent row changes showing the delta in the selected field (processed_rows or duration_seconds) between each consecutive row. Both reports are 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-category-frequencies-adjacent-row-0a8dfb81/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)