# Render Farm Usage – Adjacent Row Changes + Explicit Missing-Value Fill

> Render Farm Usage – Adjacent Row Changes + 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 2026-10-24).

Computes adjacent row-over-row changes and fills missing values in render farm usage data (node_hours, job_count) for up to 200 rows, returning 2 analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-24-162?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-24
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/render-farm-usage-adjacent-row-changes-explicit-missing-value-fill-660775d2
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_zPu0-ajLLAduH1MFDggZI

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-farm-usage-adjacent-row-changes-explicit-missing-value-fill-660775d2 -d '<json body>'
```

Example prompt: I have render farm usage records for October 2026 across two asset groups, with some missing node_hours values — can you compute the adjacent row-over-row changes and fill those missing node_hours values using median imputation? I have about 4 rows with fields like date, asset_group, node_hours, and job_count.

## When to prefer this

Choose this endpoint when you have render farm usage data (node_hours, job_count) with up to 200 rows and need both adjacent row-over-row change detection and explicit missing-value imputation in a single low-cost call. It is ideal for preprocessing render farm logs before reporting or visualization, especially when data has gaps. It does not perform live lookups, forecasting, or external enrichment — prefer it for purely local analytical transformation of supplied data.

## Known failure modes

- Fewer than 1 row or more than 200 rows submitted — request rejected
- Missing required fields (row_id, asset_group, date, node_hours, job_count) on any row
- Invalid date format not matching YYYY-MM-DD pattern
- Invalid enum value for field or method parameters
- Payment not included or insufficient — x402 payment required
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000)

## How this service works

Render farm usage — Adjacent row changes + Explicit missing-value fill: Adjacent row changes + Explicit missing-value fill for supplied render farm usage records (node_hours, job_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 supplied render farm usage rows: (1) an adjacent row changes report showing differences between consecutive rows for the selected field (node_hours or job_count), and (2) an explicit missing-value fill report where null/missing values in the selected field are replaced using the chosen method (zero, mean, or median). Both reports are computed locally with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/render-farm-usage-adjacent-row-changes-explicit-missing-value-fill-660775d2/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)