# Texture Baking Analytics — Trailing Mean Series + Explicit Missing-Value Fill

> Texture Baking Analytics — Trailing Mean 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 trailing mean time series and fills missing values (zero/mean/median) for texture baking records (bake_seconds, texture_pixels) across up to 200 rows, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-10-154?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/texture-baking-analytics-trailing-mean-series-explicit-missing-value-03c7b5fc
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_VTtpXJy8f5OKcd41ZArzC

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 texture-baking-analytics-trailing-mean-series-explicit-missing-value-03c7b5fc -d '<json body>'
```

Example prompt: For my texture baking dataset of 50 rows with bake_seconds and texture_pixels fields, can you compute a trailing mean series using a window of 5 and fill any missing bake_seconds values using median imputation?

## When to prefer this

Choose this endpoint when you have up to 200 rows of texture baking records (bake_seconds or texture_pixels) and need both a trailing moving average series and explicit missing-value imputation in a single low-cost call ($0.01 USDC for 2 reports). Prefer this over generic analytics services when your data is specifically about 3D texture baking pipelines and you want offline, deterministic statistical smoothing without external data lookups or predictions.

## Known failure modes

- Fewer than 1 row provided — minimum input requirement not met
- More than 200 rows supplied — exceeds maxItems limit
- Invalid date format (not YYYY-MM-DD) — pattern validation failure
- Window size outside 2–200 range — integer constraint violation
- Unknown method value outside zero/mean/median enum — validation error
- Unknown field value outside bake_seconds/texture_pixels enum — validation error
- Numeric values outside ±1,000,000,000,000 — schema bound exceeded
- Payment not included or insufficient — x402 payment required

## How this service works

Texture baking — Trailing mean series + Explicit missing-value fill: Trailing mean series + Explicit missing-value fill for supplied texture baking records (bake_seconds, texture_pixels). 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 trailing mean series showing rolling window averages over the selected field (bake_seconds or texture_pixels) across the supplied rows, and (2) an explicit missing-value fill report replacing nulls in the selected field using the chosen method (zero, mean, or median). Both reports are computed locally against the 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",
     "bake_seconds",
     "texture_pixels"
    ],
    "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
     },
     "bake_seconds": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "texture_pixels": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "asset_group": "group-a",
     "bake_seconds": 10,
     "texture_pixels": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "asset_group": "group-b",
     "bake_seconds": 20,
     "texture_pixels": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "asset_group": "group-a",
     "bake_seconds": 15,
     "texture_pixels": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "asset_group": "group-b",
     "bake_seconds": 30,
     "texture_pixels": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "bake_seconds",
    "texture_pixels"
   ],
   "type": "string",
   "default": "bake_seconds"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/texture-baking-analytics-trailing-mean-series-explicit-missing-value-03c7b5fc/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)