# Invoice Ageing — Numeric Row Ordering + Explicit Missing-Value Fill

> Invoice Ageing — 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 2026-10-25).

Sorts invoice ageing records by a numeric field and fills missing values using zero, mean, or median imputation, returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-finance-07-124?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-25
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/invoice-ageing-numeric-row-ordering-explicit-missing-value-fill-0d466936
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_7WF8NdAmUoz8eXjsxg-jP

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 invoice-ageing-numeric-row-ordering-explicit-missing-value-fill-0d466936 -d '<json body>'
```

Example prompt: Sort my invoice ageing records by outstanding_amount and fill any missing values using median imputation — I have about 50 rows with fields like row_id, instrument_group, date, outstanding_amount, and age_days.

## When to prefer this

Choose this endpoint when you have invoice ageing tabular data (outstanding_amount, age_days) that needs numeric sorting and/or missing-value imputation in a single low-cost call, and you want two reports simultaneously without any external data lookups or predictions. Ideal for finance data pipelines that need deterministic, reproducible cleaning steps on batches up to 200 rows.

## Known failure modes

- More than 200 rows supplied — request exceeds row limit
- Missing required fields (row_id, date, outstanding_amount, age_days) — validation error
- Invalid date format (not YYYY-MM-DD) — schema rejection
- Field or method enum value not recognized — bad request
- All values in target field are null — mean/median imputation undefined

## How this service works

Invoice ageing — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + Explicit missing-value fill for supplied invoice ageing records (outstanding_amount, age_days). 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 structured invoice ageing reports for the supplied rows (up to 200): one with rows reordered numerically by the specified field (outstanding_amount or age_days), and one with missing values in that field replaced using the chosen method (zero, mean, or median). All processing is done locally with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/invoice-ageing-numeric-row-ordering-explicit-missing-value-fill-0d466936/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)