# Transformation Throughput Analytics — Record Quality Audit, String Normalisation & Missing-Value Fill

> Transformation Throughput Analytics — Record Quality Audit, String Normalisation & Missing-Value Fill 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).

Audits data quality, normalises strings, and fills missing values for transformation throughput records (processed_rows, duration_seconds) across up to 200 rows, returning 3 independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-13-208?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-record-quality-audit-string-3c0de002
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_NSUt9jk7QgO6whLUxEjQz

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-record-quality-audit-string-3c0de002 -d '<json body>'
```

Example prompt: Can you audit the data quality, normalise the strings, and fill in any missing processed_rows values using median imputation for these transformation throughput records — I have 4 rows covering group-a and group-b from October 2026?

## When to prefer this

Choose this endpoint when you need a combined, low-cost ($0.01 USDC) pass of quality auditing, string normalisation, and missing-value imputation specifically on transformation throughput data (processed_rows, duration_seconds) for up to 200 rows. It is ideal for pre-processing ETL logs or pipeline run records before downstream analytics, when no external data lookup or prediction is needed and all analysis can be done locally against the supplied data.

## Known failure modes

- Rows array exceeds 200 items — request rejected
- Missing required fields (row_id, date, processed_rows, duration_seconds) — validation error
- date field does not match YYYY-MM-DD pattern — schema validation failure
- Invalid enum value for field or method parameter — request rejected
- All values already present — missing-value fill report returns no imputations
- Payment not included or insufficient USDC — 402 payment required error

## How this service works

Transformation throughput — Record quality audit + String normalisation + Explicit missing-value fill: Record quality audit + String normalisation + Explicit missing-value fill for supplied transformation throughput records (processed_rows, duration_seconds). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.

## Output

Returns 3 independent analytical reports: (1) a record quality audit identifying issues such as nulls, out-of-range values, and malformed fields; (2) a string normalisation report showing standardised versions of string fields like dataset_group; and (3) a missing-value fill report showing imputed values for the selected numeric field (processed_rows or duration_seconds) using the chosen method (zero, mean, or median). All processing is local 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"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/transformation-throughput-analytics-record-quality-audit-string-3c0de002/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)