# Duplicate Observations Analytics: Trailing Mean Series + Date by Category Pivot

> Duplicate Observations Analytics: Trailing Mean Series + Date by Category Pivot 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 a date-by-category pivot table for duplicate-observation metrics (duplicate_rows, total_rows) across up to 200 supplied data rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-04-152?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-analytics-trailing-mean-series-date-by-374d5034
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_l_yy8a8dqwC41rS6WY9W8

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-analytics-trailing-mean-series-date-by-374d5034 -d '<json body>'
```

Example prompt: I have duplicate observation records for two dataset groups over the past week — can you run a trailing mean series and a date-by-category pivot on the duplicate_rows field using a window of 3, for these rows: row-1 on 2026-10-01 group-a with 10 duplicates out of 100 total, row-2 on 2026-10-02 group-b with 20 duplicates out of 200 total, row-3 on 2026-10-03 group-a with 15 duplicates out of 150 total?

## When to prefer this

Choose this endpoint when you have up to 200 rows of duplicate observation records and need both a trailing moving average time series AND a date-by-category pivot in a single cost-efficient call ($0.01 USDC for both reports). It is ideal for data quality monitoring, ETL auditing, and governance dashboards where offline computation on supplied data is sufficient and no live lookup or external data is needed.

## Known failure modes

- Fewer than 1 row supplied — minimum 1 row required
- More than 200 rows supplied — exceeds maximum item limit
- Window size larger than number of rows — trailing mean may produce insufficient data points
- Invalid date format (not YYYY-MM-DD) — fails pattern validation
- Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) — schema validation error
- Numeric values outside allowed range (-1T to +1T) — rejected
- Invalid field enum value — must be 'duplicate_rows' or 'total_rows'
- Payment failure — 0.01 USDC required per call via x402 protocol

## How this service works

Duplicate observations — Trailing mean series + Date by category pivot: Trailing mean series + Date by category pivot 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 computed from the supplied rows: (1) a trailing mean series over the chosen field (duplicate_rows or total_rows) using the specified window size, and (2) a date-by-category pivot table showing the field values broken down by date and dataset_group. Both reports are computed locally on the provided data 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-analytics-trailing-mean-series-date-by-374d5034/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)