# Render Jobs String Normalisation and Missing-Value Fill

> Render Jobs String Normalisation and 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 2026-10-31).

Normalises string fields and fills missing values (via zero, mean, or median) in render job records containing render_seconds and sample_count, returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-02-037?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-31
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/render-jobs-string-normalisation-and-missing-value-fill-0561cecf
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_jL8qpIQK2m4rUpnzhL2Z8

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 render-jobs-string-normalisation-and-missing-value-fill-0561cecf -d '<json body>'
```

Example prompt: I have up to 200 render job rows with asset_group, date, render_seconds, and sample_count fields — some render_seconds values are null. Can you normalise the strings and fill those missing render_seconds values using the median method, then give me the two analytical reports?

## When to prefer this

Choose this endpoint when you have render job records (with render_seconds and sample_count) that need both string normalisation and missing-value imputation in a single paid call, and you want two analytical reports delivered together at a fixed low cost. Prefer this over general-purpose data tools when your dataset is bounded at 200 rows and you specifically need the zero/mean/median fill options applied to render pipeline metrics.

## Known failure modes

- More than 200 rows submitted — request rejected or truncated
- Missing required fields (row_id, date, asset_group) cause row-level errors
- Invalid date format (not YYYY-MM-DD) may cause parsing failures
- Numeric values outside allowed range (-1e12 to 1e12) rejected
- Invalid method enum value (not zero/mean/median) causes validation error
- Invalid field enum value (not render_seconds/sample_count) causes validation error

## How this service works

Render jobs — String normalisation + Explicit missing-value fill: String normalisation + Explicit missing-value fill for supplied render jobs records (render_seconds, sample_count). 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 independent analytical reports covering string-normalised fields and explicitly imputed numeric values (render_seconds or sample_count) for up to 200 supplied render job rows, processed entirely from supplied data with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "asset_group",
     "date",
     "render_seconds",
     "sample_count"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "asset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "sample_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "render_seconds": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "asset_group": "group-a",
     "sample_count": 1,
     "render_seconds": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "asset_group": "group-b",
     "sample_count": 2,
     "render_seconds": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "asset_group": "group-a",
     "sample_count": 3,
     "render_seconds": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "asset_group": "group-b",
     "sample_count": 4,
     "render_seconds": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "render_seconds",
    "sample_count"
   ],
   "type": "string",
   "default": "render_seconds"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/render-jobs-string-normalisation-and-missing-value-fill-0561cecf/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)