# Duplicate Observations — Exact Row Deduplication + IQR Outlier Flags

> Duplicate Observations — Exact Row Deduplication + IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).

Performs exact row deduplication and IQR-based outlier flagging on up to 200 duplicate observation records containing duplicate_rows and total_rows metrics.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-04-049?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-18
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/duplicate-observations-exact-row-deduplication-iqr-outlier-flags-151bb080
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_-RM_FjPd1GZPh8crvQbJB

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 duplicate-observations-exact-row-deduplication-iqr-outlier-flags-151bb080 -d '<json body>'
```

Example prompt: Can you run exact row deduplication and IQR outlier flagging on my duplicate observation records? I have 4 rows across two groups — group-a and group-b — from 2026-10-01 to 2026-10-04, with duplicate_rows values of 10, 20, 15, and 30, and total_rows of 1 through 4. Analyze the duplicate_rows field.

## When to prefer this

Choose this endpoint when you need both exact row deduplication AND IQR-based statistical outlier detection on duplicate observation metrics in a single call. It is best suited for data quality pipelines, ETL monitoring, or pre-processing workflows where you have structured records with duplicate_rows and total_rows counts grouped by dataset and date. Prefer this over single-report endpoints when you want two complementary analyses (deduplication + outlier flagging) at once for up to 200 rows.

## Known failure modes

- More than 200 rows submitted — input exceeds maxItems limit
- Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) — validation error
- Date field not matching YYYY-MM-DD pattern — schema validation failure
- Invalid field enum value (must be 'duplicate_rows' or 'total_rows') — rejected request
- Empty rows array — minItems constraint violation
- Non-numeric values for duplicate_rows or total_rows — type validation error

## How this service works

Duplicate observations — Exact row deduplication + IQR outlier flags: Exact row deduplication + IQR outlier flags for supplied duplicate observations records (duplicate_rows, total_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 two independent analytical reports: (1) an exact row deduplication report identifying and removing identical records from the input, and (2) an IQR outlier flagging report that identifies which records have statistically anomalous values (beyond the interquartile range fences) in the selected field (duplicate_rows or total_rows). Results are computed locally without external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/duplicate-observations-exact-row-deduplication-iqr-outlier-flags-151bb080/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)