# Render Jobs Base-100 Series + Explicit Missing-Value Fill

> Render Jobs Base-100 Series + Explicit 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 2026-10-21).

Computes a base-100 indexed time series and fills missing values for render job data (render_seconds, sample_count) across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-02-169?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-21
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/render-jobs-base-100-series-explicit-missing-value-fill-6898c81e
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_cKehEhtoWUek5cOL9nHnj

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-base-100-series-explicit-missing-value-fill-6898c81e -d '<json body>'
```

Example prompt: I have 50 render job records with render_seconds and some nulls — can you index them to a base-100 series starting from row 0 and fill the missing render_seconds values using median imputation?

## When to prefer this

Choose this endpoint when you have render job tabular data with a time dimension and need both a relative-performance index (base-100 normalization) and missing-value imputation in a single call. It is ideal for creative/media pipeline analytics where render_seconds or sample_count metrics need to be compared across dates or asset groups and gaps must be handled before visualization. Prefer it over general analytics tools when you need both operations together cheaply ($0.01 USDC for up to 200 rows) and without external data dependencies.

## Known failure modes

- Fewer than 1 or more than 200 rows submitted — request rejected
- Invalid date format not matching YYYY-MM-DD pattern
- base_index out of range (0–199) or exceeding row count
- Numeric values outside allowed range (-1e12 to 1e12)
- All values in selected field are null — mean/median fill undefined
- Missing required fields (row_id, asset_group, date, render_seconds, sample_count) per row

## How this service works

Render jobs — Base-100 series + Explicit missing-value fill: Base-100 series + 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

Returns two analytical reports for the submitted render job rows: (1) a base-100 indexed series where the specified base_index row equals 100 and all other rows are expressed relative to it, and (2) the same dataset with missing values in the chosen field explicitly filled using the selected method (zero, mean, or median). Both reports cover up to 200 rows and are computed locally without 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"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/render-jobs-base-100-series-explicit-missing-value-fill-6898c81e/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)