# Document Approvals Two-Measure Correlation and Missing-Value Fill

> Document Approvals 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 2026-11-02).

Computes Pearson correlation between submitted_documents and approved_documents, and fills missing values using zero, mean, or median imputation — delivering two statistical reports for up to 200 document approval records.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-operations-17-184?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-02
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/document-approvals-two-measure-correlation-and-missing-value-fill-a8862c5c
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_hlCGGGdPhLLlJoWK-5g4K

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 document-approvals-two-measure-correlation-and-missing-value-fill-a8862c5c -d '<json body>'
```

Example prompt: I have up to 200 rows of document approval data with submitted_documents and approved_documents counts per team group — can you run a two-measure correlation between those fields and fill any missing approved_documents values using median imputation?

## When to prefer this

Choose this endpoint when you have tabular document approval data (submitted vs approved counts per team/date) and need both a correlation analysis and missing-value imputation in a single call for up to 200 rows. It is especially useful when you want two distinct analytical outputs from shared input data without building your own statistical pipeline. Not suitable for live document system queries, approval predictions, or datasets exceeding 200 rows.

## Known failure modes

- Fewer than 1 row provided — minimum item count not met
- More than 200 rows submitted — exceeds maxItems limit
- Missing required fields (row_id, date, submitted_documents, approved_documents) on any row
- Invalid date format not matching YYYY-MM-DD pattern
- Invalid enum value for method or field parameters
- Payment not completed — x402 payment required before response
- All values null in target field — imputation has no non-null reference for mean/median

## How this service works

Document approvals — Two-measure correlation + Explicit missing-value fill: Two-measure correlation + Explicit missing-value fill for supplied document approvals records (submitted_documents, approved_documents). 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 Pearson or equivalent two-measure correlation result between submitted_documents and approved_documents across the supplied rows, and (2) a dataset with missing values in the specified field filled using the chosen method (zero, mean, or median). Results are computed locally with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/document-approvals-two-measure-correlation-and-missing-value-fill-a8862c5c/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)