# Duplicate Observations — Numeric Interval Filter + IQR Outlier Flags

> Duplicate Observations — Numeric Interval Filter + 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 2026-10-16).

Filters duplicate observation records by a numeric interval and flags IQR-based outliers across the duplicate_rows and total_rows fields, producing two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-04-130?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-16
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/duplicate-observations-numeric-interval-filter-iqr-outlier-flags-9ce226ab
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_5yAeXbe2ZuHLvuSnJr9Jg

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-numeric-interval-filter-iqr-outlier-flags-9ce226ab -d '<json body>'
```

Example prompt: Analyze my duplicate observation records for the 'sales' dataset group — filter the duplicate_rows field between 0 and 100, and flag any IQR outliers. Here are my rows: row-1 on 2024-01-01 with 10 duplicate_rows out of 500 total, row-2 on 2024-01-02 with 85 duplicate_rows out of 600 total, row-3 on 2024-01-03 with 200 duplicate_rows out of 700 total.

## When to prefer this

Choose this endpoint when you need both a numeric range filter and IQR-based outlier detection on duplicate observation records in a single paid call. It is ideal for data quality workflows where you want to audit duplicate row counts across dataset groups without any external data lookup or prediction — purely statistical analysis on your supplied rows. Prefer this over generic statistics tools when you need two distinct reports (interval filter + outlier flags) computed together cost-effectively for up to 200 rows.

## Known failure modes

- Fewer than 1 row supplied — rejected by minItems constraint
- More than 200 rows supplied — rejected by maxItems constraint
- Invalid date format (not YYYY-MM-DD) — schema validation error
- Numeric values outside ±1 trillion range — rejected by schema bounds
- Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) — validation error
- Payment not fulfilled — x402 payment required error

## How this service works

Duplicate observations — Numeric interval filter + IQR outlier flags: Numeric interval filter + 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) records from the input that fall within the specified numeric interval for the chosen field (duplicate_rows or total_rows), and (2) IQR-based outlier flags identifying which records are statistically extreme. Both reports are computed locally from the supplied data with no 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"
  },
  "maximum": {
   "type": "number",
   "default": 100,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  },
  "minimum": {
   "type": "number",
   "default": 0,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/duplicate-observations-numeric-interval-filter-iqr-outlier-flags-9ce226ab/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)