# Duplicate Observations Analyzer — Numeric Row Ordering + Explicit Missing-Value Fill

> Duplicate Observations Analyzer — Numeric Row Ordering + Explicit Missing-Value Fill is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-11).

Analyzes up to 200 records of duplicate-observation data, applying numeric row ordering and explicit missing-value fill (zero, mean, or median) to either the duplicate_rows or total_rows field, returning 2 analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-04-124?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-11
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/duplicate-observations-analyzer-numeric-row-ordering-explicit-missing-6fd97e91
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_PmCPP-XhsRMEzJpOUHSnc

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-analyzer-numeric-row-ordering-explicit-missing-6fd97e91 -d '<json body>'
```

Example prompt: I have 4 rows of duplicate observation data for groups A and B dated 2026-10-01 through 2026-10-04 — can you analyze the duplicate_rows field using median fill to handle any missing values and give me the numeric row ordering plus fill reports?

## When to prefer this

Choose this endpoint when you have tabular duplicate-observation records (up to 200 rows) and need both numeric ordering of rows and explicit missing-value imputation applied to duplicate_rows or total_rows fields in a single call. Ideal for data quality workflows where you want offline, deterministic analytics without any external data lookups or live predictions.

## Known failure modes

- More than 200 rows submitted — exceeds maxItems limit
- Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) cause validation errors
- Invalid date format (not YYYY-MM-DD) rejected by pattern validation
- Invalid method enum value (not zero, mean, or median) causes error
- Invalid field enum value (not duplicate_rows or total_rows) causes error
- Numeric values outside ±1,000,000,000,000 range rejected

## How this service works

Duplicate observations — Numeric row ordering + Explicit missing-value fill: Numeric row ordering + Explicit missing-value fill 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 2 independent analytical reports: one applying numeric row ordering to the supplied rows, and one applying explicit missing-value fill (zero, mean, or median) to the selected field (duplicate_rows or total_rows). Reports are computed locally from 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"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/duplicate-observations-analyzer-numeric-row-ordering-explicit-missing-6fd97e91/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)