# Table Extraction — Numeric Row Ordering + Explicit Missing-Value Fill

> Table Extraction — Numeric Row Ordering + 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 2026-10-26).

Sorts table extraction records numerically by row order and fills missing values in extracted_rows or expected_rows using zero, mean, or median imputation, producing 2 analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-web-10-124?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-26
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/table-extraction-numeric-row-ordering-explicit-missing-value-fill-cc896ac6
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_vXeuFr9yTl6gvfekyavcn

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 table-extraction-numeric-row-ordering-explicit-missing-value-fill-cc896ac6 -d '<json body>'
```

Example prompt: I have a batch of 50 table extraction records across two site groups with some missing extracted_rows values — can you sort them numerically by row order, fill the nulls using median imputation, and give me the 2 analytical reports?

## When to prefer this

Choose this endpoint when you need to programmatically sort table extraction audit records by numeric row order AND impute missing values in a single pass, producing two structured analytical reports. It is ideal for ETL auditing, scraping QA, and data pipeline validation workflows where you have up to 200 rows of extracted vs expected row count data with nulls. Prefer this over generic stats endpoints when you specifically need combined numeric ordering plus explicit missing-value fill with configurable imputation strategy.

## Known failure modes

- Submitting more than 200 rows returns an error (maxItems exceeded)
- Invalid date format (not YYYY-MM-DD) triggers schema validation failure
- Missing required fields (row_id) causes request rejection
- Values outside ±1,000,000,000,000 range are rejected
- Invalid method enum value (not zero/mean/median) causes error
- Invalid field enum value (not extracted_rows/expected_rows) causes error

## How this service works

Table extraction — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + Explicit missing-value fill for supplied table extraction records (extracted_rows, expected_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 2 analytical reports covering the submitted records (up to 200 rows) after applying numeric row ordering and explicit missing-value fill (zero, mean, or median) to the specified field (extracted_rows or expected_rows). Reports summarize ordered row sequences and imputed values based on the chosen method, using local analytical engines with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/table-extraction-numeric-row-ordering-explicit-missing-value-fill-cc896ac6/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)