# Duplicate Observations Analytics: Category Frequencies + Two-Measure Correlation

> Duplicate Observations Analytics: Category Frequencies + Two-Measure Correlation 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).

Analyzes duplicate observation records to produce category frequency distributions and a two-measure correlation report for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-04-108?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-category-frequencies-two-measure-7c5f21b2
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_HikP6Hc7YL08KiRIbNMt0

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-category-frequencies-two-measure-7c5f21b2 -d '<json body>'
```

Example prompt: I have some duplicate observation records across dataset groups and I want two reports: one showing the frequency breakdown by category group and another showing the correlation between duplicate_rows and total_rows — here are the rows: [{"row_id":"r1","dataset_group":"group-a","date":"2024-01-01","duplicate_rows":50,"total_rows":500},{"row_id":"r2","dataset_group":"group-b","date":"2024-01-02","duplicate_rows":20,"total_rows":200}].

## When to prefer this

Choose this endpoint when you have up to 200 pre-collected duplicate observation records keyed by dataset group and date, and you need both a categorical frequency breakdown and a two-measure correlation between duplicate_rows and total_rows in a single low-cost call. It is ideal for lightweight data quality analytics workflows where you already hold the data locally and do not need external enrichment, predictions, or live lookups.

## Known failure modes

- Fewer than 1 row or more than 200 rows submitted — request rejected
- Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) on any row — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Null values in both numeric measures may degrade or prevent correlation computation
- Payment of 0.01 USDC not satisfied — x402 payment required error

## How this service works

Duplicate observations — Category frequencies + Two-measure correlation: Category frequencies + Two-measure correlation 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 based on the supplied rows: (1) a category frequency breakdown showing how often each dataset_group value appears in the records, and (2) a two-measure correlation report quantifying the statistical relationship between the duplicate_rows and total_rows fields across all supplied observations. No external data is fetched; all computation is local.

## 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-category-frequencies-two-measure-7c5f21b2/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)