# Transformation Throughput Analytics — String Normalisation + Secondary-Measure Weighted Mean

> Transformation Throughput Analytics — String Normalisation + Secondary-Measure Weighted Mean 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).

Runs string normalisation and secondary-measure weighted mean analysis on up to 200 transformation throughput records (processed_rows, duration_seconds), returning 2 bundled analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-13-034?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/transformation-throughput-analytics-string-normalisation-secondary-f56d5c3a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_QOFea4bBsKebaRr9c8BC6

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-secondary-f56d5c3a -d '<json body>'
```

Example prompt: Can you run string normalisation and a secondary-measure weighted mean on these 150 transformation throughput records — the primary field is processed_rows — and give me the two reports? Here are the rows with row_id, dataset_group, date, processed_rows, and duration_seconds.

## When to prefer this

Choose this endpoint when you need both string normalisation and a weighted mean computed together on transformation throughput records (processed_rows, duration_seconds) in a single paid call, and your dataset has up to 200 rows. It is particularly useful for ETL/pipeline analytics workflows where you want to clean categorical labels and compute weighted performance statistics simultaneously without separate API calls. Prefer alternatives if you need only one of the two analyses, live data lookups, predictions, or more than 200 rows.

## Known failure modes

- Fewer than 1 row submitted — minimum of 1 row required
- More than 200 rows submitted — exceeds maxItems limit
- Missing required fields (row_id, date, processed_rows, duration_seconds) on any row — validation error
- Date field not in YYYY-MM-DD format — pattern mismatch error
- Null values in both numeric fields may reduce weighted mean accuracy
- Invalid field enum value (must be 'processed_rows' or 'duration_seconds') — rejected input

## How this service works

Transformation throughput — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean 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 bundled analytical reports: (1) string-normalised versions of the text fields (dataset_group labels cleaned and standardised), and (2) a secondary-measure weighted mean computed over the selected primary numeric field (processed_rows or duration_seconds), covering all submitted rows (up to 200). No external lookups or live data are involved — all computation is performed locally 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-string-normalisation-secondary-f56d5c3a/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)