# Transformation Throughput — String Normalisation + Trailing Mean Series

> Transformation Throughput — String Normalisation + Trailing Mean Series 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).

Performs string normalisation and trailing mean series analysis on transformation throughput records (processed_rows, duration_seconds) for up to 200 rows, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-13-028?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-string-normalisation-trailing-mean-series-a2df391b
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_u6MkFUiZwyTJTbszIPj50

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-string-normalisation-trailing-mean-series-a2df391b -d '<json body>'
```

Example prompt: Can you run a string normalisation and trailing mean series analysis on my transformation throughput data — I have 50 rows with processed_rows and duration_seconds fields, I want the trailing mean on processed_rows with a window of 7?

## When to prefer this

Choose this endpoint when you need both string normalisation and trailing mean series computed together on transformation throughput records (processed_rows and/or duration_seconds) in a single paid call. It is ideal for data engineering teams cleaning and smoothing ETL pipeline metrics in batch, covering up to 200 rows. Prefer alternatives if you need only one of the two reports, need more than 200 rows, or require real-time lookups, predictions, or external data enrichment.

## Known failure modes

- Fewer than 1 row supplied — minimum row count not met
- More than 200 rows supplied — exceeds maximum row limit
- Window size larger than number of rows — trailing mean undefined for early rows
- Invalid date format (must match YYYY-MM-DD pattern)
- Missing required fields (row_id, dataset_group, date, processed_rows, duration_seconds)
- Null numeric values reducing effective window coverage
- row_id exceeds 80-character limit
- Payment not processed — x402 payment required before response

## How this service works

Transformation throughput — String normalisation + Trailing mean series: String normalisation + Trailing mean series 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 dataset_group and other string fields, and (2) a trailing mean series for the selected numeric field (processed_rows or duration_seconds) computed over the specified rolling window — all derived from the supplied input rows 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"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/transformation-throughput-string-normalisation-trailing-mean-series-a2df391b/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)