# Source Attribution Data Cleaner — Numeric Row Ordering + Missing-Value Fill

> Source Attribution Data Cleaner — Numeric Row Ordering + 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).

Sorts source attribution records (cited_sources, verified_links) by numeric row order and fills missing values using zero, mean, or median imputation, producing two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-news-02-124?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/source-attribution-data-cleaner-numeric-row-ordering-missing-value-fill-1c8b578d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_UJk1gLhqgYNyyyHFVFudQ

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 source-attribution-data-cleaner-numeric-row-ordering-missing-value-fill-1c8b578d -d '<json body>'
```

Example prompt: I have up to 200 rows of source attribution data with cited_sources and verified_links fields — some values are missing. Can you sort them by numeric row order and fill in the nulls using median imputation on the cited_sources field, then give me two reports?

## When to prefer this

Choose this endpoint when you have source attribution datasets (cited_sources, verified_links) up to 200 rows that need numeric sorting and missing-value imputation using standard statistical methods (zero, mean, or median), and you want two bundled reports for a flat $0.01 USDC. It is a local, offline computation — no live lookups or external data sources are involved, making it deterministic and auditable.

## Known failure modes

- More than 200 rows submitted — request rejected with validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Missing required fields (row_id, channel_group, date, cited_sources, verified_links) — request rejected
- Invalid method enum value (not zero/mean/median) — validation error
- Invalid field enum value (not cited_sources/verified_links) — validation error
- Empty rows array — minItems:1 constraint violation

## How this service works

Source attribution — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + Explicit missing-value fill for supplied source attribution records (cited_sources, verified_links). 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

Two analytical reports covering the submitted source attribution rows: one showing numerically ordered row data and one showing the dataset after explicit missing-value fill (using the chosen method — zero, mean, or median) applied to the specified field (cited_sources or verified_links). Up to 200 rows processed per call.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/source-attribution-data-cleaner-numeric-row-ordering-missing-value-fill-1c8b578d/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)