# Compositing Graphs Two-Measure Correlation and Missing-Value Fill

> Compositing Graphs Two-Measure Correlation 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 2026-10-22).

Computes Pearson/rank correlation between node_count and render_seconds, and fills missing values using zero, mean, or median imputation, across up to 200 compositing graph records.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-09-184?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-22
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/compositing-graphs-two-measure-correlation-and-missing-value-fill-884fec4a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_qwqOK5axO2BbgMku8JOSP

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 compositing-graphs-two-measure-correlation-and-missing-value-fill-884fec4a -d '<json body>'
```

Example prompt: I have up to 200 rows of compositing graph data with node_count and render_seconds fields — can you run a two-measure correlation between those two metrics and also fill any missing node_count values using median imputation?

## When to prefer this

Choose this endpoint when you have compositing graph records (node_count, render_seconds) and need both a two-measure correlation analysis and explicit missing-value imputation in a single $0.01 call. Prefer it over general-purpose analytics when your data fits the compositing-graph domain schema and you need both reports bundled together with no external lookups or live data.

## Known failure modes

- Fewer than 1 row submitted — validation error
- More than 200 rows submitted — rejected with maxItems violation
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Field or method enum value not in allowed set — schema rejection
- All values for a field are null — correlation undefined, report may be empty or return NaN
- Payment not confirmed — endpoint returns 402 or no response

## How this service works

Compositing graphs — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + Explicit missing-value fill for supplied compositing graphs records (node_count, render_seconds). 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: (1) a correlation report quantifying the statistical relationship between node_count and render_seconds across the submitted rows, and (2) a missing-value fill report showing imputed values for the chosen field using the specified method (zero, mean, or median). Both reports are computed locally from supplied data.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/compositing-graphs-two-measure-correlation-and-missing-value-fill-884fec4a/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)