# Duplicate Observations Analytics — Exact Row Deduplication + Category Frequencies

> Duplicate Observations Analytics — Exact Row Deduplication + Category Frequencies 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 category-frequency breakdowns across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-04-041?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-analytics-exact-row-deduplication-category-760d7551
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Ds-DjloKQx6eiNH0HZD7S

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-exact-row-deduplication-category-760d7551 -d '<json body>'
```

Example prompt: I have 4 observation records across two dataset groups — group-a and group-b — with dates from 2026-10-01 to 2026-10-04 and duplicate row counts of 10, 20, 15, and 30 out of totals of 1, 2, 3, and 4 rows respectively. Can you run an exact row deduplication report and a category frequency breakdown on this data?

## When to prefer this

Choose this endpoint when you have pre-collected duplicate-observation records (with row IDs, group labels, dates, and duplicate/total row counts) and need two fast, local analytical outputs — exact deduplication stats plus category frequency distributions — without any external data lookup or prediction. It is ideal for data quality pipelines processing up to 200 records per call at very low cost.

## Known failure modes

- Submitting more than 200 rows will be rejected (maxItems constraint)
- Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) will cause validation errors
- Invalid date format (non-YYYY-MM-DD) will fail pattern validation
- Null or out-of-range numeric values for duplicate_rows or total_rows may produce incomplete results
- Payment of 0.01 USDC must be included; missing payment will block the request

## How this service works

Duplicate observations — Exact row deduplication + Category frequencies: Exact row deduplication + Category frequencies 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) an exact row deduplication report identifying duplicate rows and deduplication statistics from the supplied records, and (2) a category frequency report showing how often each dataset_group appears across the input rows — all computed locally 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
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/duplicate-observations-analytics-exact-row-deduplication-category-760d7551/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)