# Data Reconciliation: Exact Row Deduplication + Two-Measure Correlation

> Data Reconciliation: Exact Row Deduplication + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).

Deduplicates rows exactly and computes two-measure correlation between source_total and target_total for up to 200 reconciliation records, returning two analytical reports per call.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-11-050?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-19
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-reconciliation-exact-row-deduplication-two-measure-correlation-16c1c876
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_840j5c9FrdPHihBIv4L6M

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 data-reconciliation-exact-row-deduplication-two-measure-correlation-16c1c876 -d '<json body>'
```

Example prompt: Can you run a deduplication and two-measure correlation analysis on my reconciliation data? I have rows with row_id, dataset_group, date, source_total, and target_total — up to 200 rows — and I need both the duplicate-removal report and the correlation between source and target figures.

## When to prefer this

Choose this endpoint when you need both exact row deduplication AND correlation analysis between two numeric measures in a single paid call, at low cost ($0.01 USDC for both reports). Ideal for ETL validation, financial reconciliation, and data quality pipelines where you want to clean duplicates and quantify source-target agreement simultaneously without calling external systems or predictive models.

## Known failure modes

- More than 200 rows submitted — exceeds maximum row limit
- Missing required fields (row_id, dataset_group, date, source_total, or target_total) on any row — validation error
- Date values not in YYYY-MM-DD format — schema validation failure
- source_total or target_total values outside the allowed range (-1,000,000,000,000 to 1,000,000,000,000) — rejection
- Insufficient variation in source_total or target_total to compute meaningful correlation — degenerate result
- Payment not processed — x402 payment required before results returned

## How this service works

Data reconciliation — Exact row deduplication + Two-measure correlation: Exact row deduplication + Two-measure correlation for supplied data reconciliation records (source_total, target_total). 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 analytical reports per call: (1) an exact row deduplication report identifying and removing duplicate rows from the submitted dataset, and (2) a two-measure correlation report quantifying the statistical relationship between source_total and target_total values across the submitted rows. Reports are computed locally with no external lookups or predictions.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-reconciliation-exact-row-deduplication-two-measure-correlation-16c1c876/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)