# Join Coverage Two-Measure Correlation and Missing-Value Fill

> Join Coverage 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 2026-10-23).

Computes Pearson correlation between matched_rows and source_rows join coverage metrics, and fills missing values using zero, mean, or median imputation — returning two analytical reports for up to 200 supplied rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-09-184?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-23
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/join-coverage-two-measure-correlation-and-missing-value-fill-2c39e7b3
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_9tAd_eH3SRCzUmDrdfX6q

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 join-coverage-two-measure-correlation-and-missing-value-fill-2c39e7b3 -d '<json body>'
```

Example prompt: I have up to 200 rows of join coverage data with matched_rows and source_rows per dataset group and date — can you run a two-measure correlation on them and fill any missing matched_rows values using median imputation?

## When to prefer this

Choose this endpoint when you have tabular join coverage data with matched_rows and source_rows columns and need both a correlation analysis and missing-value imputation in a single call without external data lookups. It is purpose-built for data engineering and ETL quality workflows where you want local statistical computation on supplied data at low cost. Prefer alternatives if you need more than two measures analyzed simultaneously, more than 200 rows processed, or external data sources consulted.

## Known failure modes

- Fewer than 1 row or more than 200 rows submitted — request rejected
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) on any row — validation error
- Invalid date format (must be YYYY-MM-DD) — schema validation failure
- Unsupported imputation method value outside zero/mean/median enum — rejected
- All values in both measures are null — correlation cannot be computed, partial or error response
- Payment not included or insufficient (requires 0.01 USDC via x402) — 402 response

## How this service works

Join coverage — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + Explicit missing-value fill for supplied join coverage records (matched_rows, source_rows). 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 structured analytical reports: (1) a Pearson correlation result between matched_rows and source_rows across the supplied dataset, and (2) a version of the chosen measure field with explicit missing-value fills applied using the specified method (zero, mean, or median). Results are computed locally from the supplied data with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/join-coverage-two-measure-correlation-and-missing-value-fill-2c39e7b3/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)