# Duplicate Observations Deduplication and Trailing Mean Analytics

> Duplicate Observations Deduplication and Trailing Mean Analytics 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).

Analyzes supplied duplicate-observation records to produce exact row deduplication stats and a trailing mean time series for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-04-045?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-deduplication-and-trailing-mean-analytics-924324f0
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_fVHkdTmtU4EM92m0psEQi

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-deduplication-and-trailing-mean-analytics-924324f0 -d '<json body>'
```

Example prompt: I have 4 rows of duplicate-observation data for groups A and B from October 2026 — can you run the exact row deduplication report and compute a trailing mean with a window of 2 for the duplicate_rows field?

## When to prefer this

Choose this endpoint when you need both exact row deduplication statistics and a trailing mean time series computed from supplied duplicate-observation records in a single call. It is well-suited for offline or batch data quality audits where you already have the data locally and need structured analytical output without live lookup or external data sources. Use it when your dataset is 200 rows or fewer and you want two independent reports (deduplication + rolling mean) from a single low-cost API call.

## Known failure modes

- Input array empty or missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows)
- More than 200 rows submitted — exceeds maxItems limit
- Window size outside valid range (must be 2–200)
- Invalid date format — must match YYYY-MM-DD pattern
- Payment not provided or insufficient — x402 protocol requires 0.01 USDC per call

## How this service works

Duplicate observations — Exact row deduplication + Trailing mean series: Exact row deduplication + Trailing mean series 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 analytical reports: (1) an exact row deduplication summary identifying duplicate records within the supplied data, and (2) a trailing mean time series computed over the specified window for the chosen field (duplicate_rows or total_rows), covering up to 200 input rows.

## 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-deduplication-and-trailing-mean-analytics-924324f0/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)