# Join Coverage Analytics: Exact Row Deduplication + Category Frequencies

> Join Coverage 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 2026-10-23).

Performs exact row deduplication and category frequency analysis on up to 200 join coverage records (matched_rows, source_rows) for $0.01 USDC, returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-09-041?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-23
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/join-coverage-analytics-exact-row-deduplication-category-frequencies-26faf64e
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_IxWVcauDV-U16HPFUq2uw

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 join-coverage-analytics-exact-row-deduplication-category-frequencies-26faf64e -d '<json body>'
```

Example prompt: Can you deduplicate these join coverage rows and give me category frequencies by dataset_group? I have 4 records: row-1 on 2026-10-01 with source_rows=1 and matched_rows=10 in group-a, row-2 on 2026-10-02 with source_rows=2 and matched_rows=20 in group-b, row-3 on 2026-10-03 source_rows=3 matched_rows=15 group-a, and row-4 on 2026-10-04 source_rows=4 matched_rows=30 group-b.

## When to prefer this

Choose this endpoint when you have up to 200 join coverage records and need both exact row deduplication and category frequency analysis in a single low-cost call ($0.01 USDC). It is ideal for data engineers or analysts who want a quick, offline analytical pass on join result datasets without spinning up a database or analytics pipeline. Prefer this over generic analytics services when your data specifically involves matched_rows and source_rows join coverage metrics grouped by dataset_group.

## Known failure modes

- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) — validation error
- Date field does not match YYYY-MM-DD pattern — validation error
- Numeric fields (matched_rows, source_rows) outside allowed range — validation error
- Empty rows array (minItems:1 not met) — validation error
- Payment of 0.01 USDC not completed via x402 protocol — unauthorized

## How this service works

Join coverage — Exact row deduplication + Category frequencies: Exact row deduplication + Category frequencies for supplied join coverage records (matched_rows, source_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 and removing identical rows from the supplied join coverage records, and (2) a category frequency report showing how many times each unique dataset_group value appears across the input rows. Both reports operate on the up to 200 supplied rows with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "matched_rows",
     "source_rows"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "source_rows": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "matched_rows": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "source_rows": 1,
     "matched_rows": 10,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "source_rows": 2,
     "matched_rows": 20,
     "dataset_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "source_rows": 3,
     "matched_rows": 15,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "source_rows": 4,
     "matched_rows": 30,
     "dataset_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/join-coverage-analytics-exact-row-deduplication-category-frequencies-26faf64e/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)