# Join Coverage Analytics: Numeric Row Ordering + Two-Measure Correlation

> Join Coverage Analytics: Numeric Row Ordering + Two-Measure Correlation 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).

Analyzes join coverage records by computing numeric row ordering and Pearson/rank correlation between matched_rows and source_rows for up to 200 supplied data rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-09-120?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-analytics-numeric-row-ordering-two-measure-correlation-496a48b5
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_RjdPV2zqPDriJvq3niDBK

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-analytics-numeric-row-ordering-two-measure-correlation-496a48b5 -d '<json body>'
```

Example prompt: Can you analyze my join coverage data and give me both a numeric row ordering and a two-measure correlation between matched_rows and source_rows? Here are my records: row-1 on 2026-10-01 in group-a had 10 matched and 1 source, row-2 on 2026-10-02 in group-b had 20 matched and 2 source, row-3 on 2026-10-03 in group-a had 15 matched and 3 source — focus the analysis on matched_rows.

## When to prefer this

Choose this endpoint when you have pre-collected join coverage data (matched_rows, source_rows) and need both a numeric ordering of records and a statistical correlation between the two measures in a single paid call. It is best suited for data engineers and analysts validating ETL pipeline join quality across dataset groups and dates, where no external data lookup or live prediction is needed.

## Known failure modes

- Fewer than 1 row supplied — validation error
- More than 200 rows supplied — request rejected
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Null values in both matched_rows and source_rows — correlation computation may be undefined
- Missing required fields (row_id, dataset_group, date) — schema rejection
- Non-numeric values in matched_rows or source_rows — type error

## How this service works

Join coverage — Numeric row ordering + Two-measure correlation: Numeric row ordering + Two-measure correlation 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

Returns two independent analytical reports for the supplied join coverage rows: (1) a numeric row ordering of the records, and (2) a two-measure correlation analysis between matched_rows and source_rows. Reports are computed locally on the supplied data with no external lookup.

## 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"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/join-coverage-analytics-numeric-row-ordering-two-measure-correlation-496a48b5/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
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