# Duplicate Observations Trailing Mean & IQR Outlier Flags

> Duplicate Observations Trailing Mean & 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 2026-10-20).

Computes a trailing mean time series and flags IQR-based outliers for duplicate_rows or total_rows observations across up to 200 records in two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-04-149?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-20
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/duplicate-observations-trailing-mean-iqr-outlier-flags-5a527ddf
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_7rKNMqJavz6JnsnisLqbL

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-trailing-mean-iqr-outlier-flags-5a527ddf -d '<json body>'
```

Example prompt: Analyze my duplicate observation records for the 'orders' dataset group — I have 10 rows with dates from 2024-01-01 to 2024-01-10 and duplicate_rows counts ranging from 5 to 120. Use a window of 3 to compute the trailing mean series and flag any IQR outliers in the duplicate_rows field.

## When to prefer this

Choose this endpoint when you need fast, local statistical analysis of duplicate observation records — specifically trailing mean time series and IQR outlier detection — without requiring any external data sources, live lookups, or predictions. It is ideal for data quality monitoring workflows where you supply pre-collected duplicate_rows/total_rows metrics and want two complementary statistical views in a single low-cost call. Prefer it over general-purpose analytics tools when your dataset fits within 200 rows and you want deterministic, reproducible outlier flags based on IQR methodology.

## Known failure modes

- Input array exceeds 200 rows — request will be rejected or truncated
- Window size larger than number of input rows — trailing mean cannot be computed for early rows
- Missing required fields (row_id, date, dataset_group) — validation error returned
- Date strings not matching YYYY-MM-DD pattern — schema validation failure
- Numeric fields outside allowed range (±1 trillion) — rejected by schema validation
- Empty rows array — minimum 1 item required

## How this service works

Duplicate observations — Trailing mean series + IQR outlier flags: Trailing mean series + 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 per call: (1) a trailing mean time series computed over the specified window for the chosen field (duplicate_rows or total_rows), and (2) IQR-based outlier flags marking which observations fall beyond 1.5× the interquartile range — all derived from the supplied input rows without any 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"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/duplicate-observations-trailing-mean-iqr-outlier-flags-5a527ddf/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)