# Transformation Throughput Analytics — String Normalisation + Grouped Numeric Summary

> Transformation Throughput Analytics — String Normalisation + Grouped Numeric Summary is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).

Accepts up to 200 transformation throughput records and returns two analytical reports: string normalisation of text fields and a grouped numeric summary of processed_rows or duration_seconds by dataset group.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-13-023?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-19
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/transformation-throughput-analytics-string-normalisation-grouped-2a20ca31
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_1IyfNl6kVCromHPYMeFGu

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-string-normalisation-grouped-2a20ca31 -d '<json body>'
```

Example prompt: I have 150 rows of transformation throughput data with columns row_id, dataset_group, date, processed_rows, and duration_seconds — can you normalise the string fields and give me a grouped numeric summary of processed_rows broken down by dataset group?

## When to prefer this

Choose this endpoint when you have up to 200 transformation throughput records with both text and numeric fields and need two co-produced reports — string normalisation and a grouped numeric summary — in a single low-cost call ($0.01 USDC). Ideal for ETL pipeline analysis, data engineering audits, or quick group-level aggregation of processed_rows or duration_seconds without setting up a local analytics environment.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, dataset_group, date, processed_rows, duration_seconds) causes rejection
- Invalid date format (not YYYY-MM-DD) triggers a schema validation error
- Null values in the selected numeric field may affect summary statistics
- Selecting an invalid field enum value (not processed_rows or duration_seconds) returns an error

## How this service works

Transformation throughput — String normalisation + Grouped numeric summary: String normalisation + Grouped numeric summary 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

Two analytical reports: (1) a string normalisation report cleaning and standardising text fields such as row_id and dataset_group; (2) a grouped numeric summary report aggregating the selected numeric field (processed_rows or duration_seconds) by dataset_group, including descriptive statistics per group. All computed locally 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-string-normalisation-grouped-2a20ca31/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)