# Validation Rule Results — Two-Measure Correlation + Explicit Missing-Value Fill

> Validation Rule Results — Two-Measure Correlation + 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 2026-10-11).

Computes the correlation between passed_rules and total_rules, and fills missing values using a chosen strategy (zero, mean, or median), for up to 200 supplied validation rule result rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-08-184?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-11
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/validation-rule-results-two-measure-correlation-explicit-missing-cc88a040
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_DjpIS7_ick26UHLRAjsQ0

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 validation-rule-results-two-measure-correlation-explicit-missing-cc88a040 -d '<json body>'
```

Example prompt: I have up to 200 rows of validation rule results with passed_rules and total_rules columns — can you compute the correlation between those two measures and fill any missing values using median imputation, then give me both reports?

## When to prefer this

Choose this endpoint when you need both missing-value imputation and correlation analysis in a single call on validation rule result data (passed_rules, total_rules), without any external lookup or prediction. Ideal for data quality pipelines needing offline, deterministic, local-engine analytics on small batches (≤200 rows) at minimal cost ($0.01 USDC for both reports). Prefer alternatives if you need more than 200 rows, live data retrieval, or additional statistical operations beyond correlation and fill.

## Known failure modes

- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, dataset_group, date, passed_rules, total_rules) — validation error
- Invalid date format not matching YYYY-MM-DD pattern — schema rejection
- Invalid enum value for method or field — schema rejection
- Fewer than the minimum 1 row supplied — rejected
- Numeric values outside allowed range (±1,000,000,000,000) — rejected

## How this service works

Validation rule results — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + Explicit missing-value fill for supplied validation rule results records (passed_rules, total_rules). 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: (1) a two-measure correlation result quantifying the statistical relationship between passed_rules and total_rules across supplied rows, and (2) a transformed dataset with missing values in the selected field filled using the specified strategy (zero, mean, or median). Up to 200 input rows are processed per call.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/validation-rule-results-two-measure-correlation-explicit-missing-cc88a040/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)