# Join Coverage Numeric Distribution + Explicit Missing-Value Fill

> Join Coverage Numeric Distribution + 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 2026-10-19).

Computes numeric distribution statistics and fills missing values (zero, mean, or median) for join coverage records tracking matched_rows and source_rows across dataset groups.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-09-085?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-19
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/join-coverage-numeric-distribution-explicit-missing-value-fill-87909c6e
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_zFW56dO-P_SZNhq5jGDfb

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-numeric-distribution-explicit-missing-value-fill-87909c6e -d '<json body>'
```

Example prompt: Analyze the numeric distribution of matched_rows and fill any missing values using median imputation for this join coverage dataset — I have up to 50 rows with row_id, date, dataset_group, matched_rows, and source_rows fields.

## When to prefer this

Choose this endpoint when you have up to 200 join coverage records with matched_rows and source_rows metrics and need both a statistical distribution summary and explicit null-value imputation in a single call for $0.01 USDC. It is purpose-built for join coverage data quality workflows where you want to understand numeric spread and handle missing values without any external data lookups or predictions.

## Known failure modes

- More than 200 rows submitted — endpoint rejects input exceeding maxItems limit
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) cause validation errors
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- Invalid enum value for field or method parameter returns schema error
- All values for selected field are null — mean/median imputation may produce undefined result
- Payment not completed or insufficient USDC balance blocks the request

## How this service works

Join coverage — Numeric distribution + Explicit missing-value fill: Numeric distribution + 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

Returns two analytical reports: (1) a numeric distribution report summarizing the spread, min, max, percentiles, and shape of the selected field (matched_rows or source_rows); and (2) an explicit missing-value fill report showing which rows had nulls and what values were substituted using the chosen method (zero, mean, or median). Both reports 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-numeric-distribution-explicit-missing-value-fill-87909c6e/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)